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The Role of a Digital Industry 4.0 in a Renewable Energy System
International Journal of Energy Research
Abstract
The transition to an intermittent energy production from renewable energy sources (RES) increases the complexity of providing reliable energy supply in Germany. Yet, the growing number of RES impede the necessary effort to control the system. The introduction of digital or smart energy systems is often proclaimed as a logical next step towards copeing with this rising complexity. It seems convenient that the manufacturing industry, as one of the major energy consumers, is currently also in a process of a digital transition, the fourth industrial revolution. This paper explores the current state of expert discourse on the role of a digitised industry as a potential enabler for the energy transition using Germany as a case study. For this purpose, we gathered qualitative data through semi-structured interviews among industry managers and energy researchers. We identified the three major areas in the expert discourse of industry's future potentials: (1) increasing transparency in the energy system, (2) providing demand flexibility and (3) increasing energy efficiency. In this paper, we address the internal barriers and explore industry’s reluctance to interact with the energy system in order to initiate a transition.
... A small set of studies provide important insights regarding I4.0 and RE relations, and the roles of economic factors in this relation is not an explored field of research in the context of I4.0. Scharl and Praktiknjo center their research on Germany as a case study to investigate the status of expert discourse on the role of a digital industry as a potential enabler for energy transition [7]. To this end, they utilize qualitative data based on semi-structured interviews with industry leaders and managers and academic researchers in the field of energy [7]. ...
... Scharl and Praktiknjo center their research on Germany as a case study to investigate the status of expert discourse on the role of a digital industry as a potential enabler for energy transition [7]. To this end, they utilize qualitative data based on semi-structured interviews with industry leaders and managers and academic researchers in the field of energy [7]. The future of the energy sector is shown to be dependent on three factors, augmenting transparency in systems of energy, achievement of more flexibility to energy demand, and augmentation of energy efficiency for I4.0 [7]. ...
... To this end, they utilize qualitative data based on semi-structured interviews with industry leaders and managers and academic researchers in the field of energy [7]. The future of the energy sector is shown to be dependent on three factors, augmenting transparency in systems of energy, achievement of more flexibility to energy demand, and augmentation of energy efficiency for I4.0 [7]. Recent studies investigated energy efficiency gains of new technologies in energy grid and smarting of energy systems and energy grid with IoT is suggested [21]. ...
In line with the fourth industrial revolution, most countries have imposed a variety of regulations or policies for the goals of energy conservation, sustainable development, and industrial transition. Renewable energy production and its production process, which is widely discussed, especially in the context of sustainable energy, has become more important with Industry 4.0. This paper tested the relation among economic growth, renewable electricity generations (% of GDP), Industry 4.0, industrial structure, trade openness, financial development, and research and development expenditure for G20 countries in 2000–2021 by employing a panel quantile regression approach and various panel cointegration tests in addition to investigation of panel Granger causality among the analyzed variables. The variables of industrial structure, trade openness, and financial development were selected as control variables. Since this study is the first study on this topic, it will contribute to the development of the literature by providing resources for future studies about I4.0, renewable energy production, and economic growth. Furthermore, this study will not only contribute to the literature by revealing the theoretical and empirical relationship between these variables but will also shed light on the policies that G20 countries will produce in this regard. According to results, all variables examined have significant causal effects: unidirectional causality from economic growth to Industry 4.0, to research and development, and to renewable energy output and, also, from research and development to renewable energy output. Bidirectional causality and feedback effects between renewable energy and Industry 4.0 are determined. Further, unidirectional causality from industrial structure, from openness to trade, and from financial development to renewable energy output are determined. Results indicate renewable-enhancing effects of Industry 4.0.
... Due to the decentralized, variable, and unpredictable nature of renewable energy sources [13], a smart system that controls and solves intermittency [14] as well as allowing a highly distributed grid [15] is needed. A smart grid is the result of digitalizing the traditional electric power system to facilitate the integration of renewable energy sources [15]. ...
... A digital twin is a virtual replica of a physical component or system that accurately depicts the status of the element empowered by data and simulation [25]. Energy suppliers can use the obtained data from digital twins for failure detection at the grid [13]. Therefore, digital twins are key enablers for the integration of renewable energy sources in smart grids, as they can predict, monitor, control, and diagnose energy supply [26]. ...
... Essentially, Industry 4.0 possesses several energy sustainability applications such as smart energy management, energy sector transformation, and new business models among others [5], which means it fosters great opportunities for renewable energy sector development. Industry 4.0 can technically contribute to the adoption of a renewable energy system by providing flexibility, improving traceability, enhancing efficiency and reducing consumption [13]. ...
The growth of the renewable energy industry is happening at a swift pace pushed, by the emergence of Industry 4.0. Smart technologies like artificial intelligence (AI), Big Data, the Internet of Things (IoT), Digital Twin (DT), etc. enable companies within the sector of renewable energies to drastically improve their operations. In this sectoral context, where upgraded sustainability standards also play a vital role, it is necessary to fulfil the human capital requirements of the imminent technological advances. This article aims to determine the current skills of the renewable energy industry workforce and to predict the upcoming skill requirements linked to a digital transition by creating a unified database that contains both types of skills. This will serve as a tool for renewable energy businesses, education centers, and policymakers to plan the training itinerary necessary to close the skills gap, as part of the sectoral strategy to achieve a competent future workforce.
... AI is a key technology of Industry 4.0 (Da Silva et al., 2019;Ivanov, 2022). Among various emerging technologies like blockchain, IoT, and cloud computing, AI stands out for its ability to enable machines to communicate and mimic human capabilities (Scharl & Praktiknjo, 2019). AI enhances problem-solving by improving accuracy, speed, and the ability to process large volumes of data (Holzinger et al., 2019). ...
... Artificial intelligence aims to understand human cognition to create intelligent systems capable of efficiently handling complex problems (Tabor et al., 2018;Zeng et al., 2024), even though replicating the intricacies of human thought remains a significant challenge. Advances in AI have eased the burden of manual computations (Abisoye et al., 2023;Scharl & Praktiknjo, 2019). While a few areas still outperform human brainpower, many have been overtaken by technological advancements, with machines capable of performing thousands of calculations per second-something impossible for the average human brain (Toorajipour et al., 2021). ...
The global transition toward renewable energy necessitates supply chains that are not only sustainable but also digitally transformed-a concept we term digitainability. In this regard, Artificial Intelligence (AI) technology has emerged as a promising tool for advancing the digitainability of the renewable energy supply chain. This study investigates the transformative role of AI in advancing the digitainability of renewable energy supply chains. Through an extensive, content-focused literature review, the researchers identified 11 distinct AI functions critical to RESC digitainability. To better understand how these functions interact and complement each other, the study applied the Interpretive Structural Modeling (ISM) method, drawing on insights from supply chain experts. By employing ISM, we uncover the interdependencies among these functions and develop a strategic roadmap for their sequential implementation. Unlike prior studies, which often adopt linear approaches, this research provides a systemic and holistic framework for integrating AI capabilities to enhance supply chain sustainability. The roadmap equips managers and stakeholders with actionable insights to prioritize investments, foster collaboration, and navigate the complexities of AI adoption in RESC. By bridging theoretical exploration with practical application, this study contributes to the global effort to achieve a sustainable and digital energy future.
... It defines ML as "a set of rules that allows systems to learn directly from examples, data and experience". This involves the development of algorithms and models that allow computer systems to learn from data, extract models, and apply those models to make decisions or make predictions without explicit programming [76] (strengths and limitations of ML in the construction field, as shown in Table 3). ...
... This includes (1) historical building reconstruction for analyzing information (geometric, radiometric, and intensity features) and semantic annotation according to task requirements [78], (2) intelligent building management for monitoring ventilation systems, daylighting, and green building features, thus improving the efficiency of decision-making and prediction [61], (3) bridge-damage detection and assessment for analyzing the structural state of bridges and detecting and assessing bridge damage [79]. ML techniques are very useful in data preprocessing, such as data cleaning, feature selection, and data transformation [76]. ...
The construction field currently suffers from low productivity, a lack of expertise among practitioners, weak innovation, and lack of predictability. The digital twin, an advanced digital technology, empowers the construction sector to advance towards intelligent construction and digital transformation. It ultimately aims for highly accurate digital simulation to achieve comprehensive optimization of all phases of a construction project. Currently, the process of digital twin applications is facing challenges such as poor data quality, the inability to harmonize types that are difficult to integrate, and insufficient data security. Further research on the application of digital twins in the construction domain is still needed to accelerate the development of digital twins and promote their practical application. This paper analyzes the commonly used architectures for digital twins in the construction domain in the literature and summarizes the commonly used technologies to implement the architectures, including artificial intelligence, machine learning, data mining, cyber–physical systems, internet of things, virtual reality, augmented reality applications, and considers their advantages and limitations. The focus of this paper is centered on the application of digital twins in the entire lifecycle of a construction project, which includes the design, construction, operation, maintenance, demolition and restoration phases. Digital twins are mainly moving towards the integration of data and information, model automation, intelligent system control, and data security and privacy. Digital twins present data management and integration challenges, privacy and security protection, technical manpower development, and transformation needs. Future research should address these challenges by improving data quality, developing robust integration methodologies, and strengthening data security measures.
... In the energy sector, issues relating to the implementation of innovative solutions and digital transformation are also quite intensively analyzed. Among other things, surveys were carried out on the use of solutions based on the Industry 4.0 paradigm in the energy sector [7], the role of Industry 4.0 in the energy sustainability [8], and the use of modern digital technologies, such as artificial intelligence (AI), big data, Internet of Things (IoT), blockchain in energy industries that facilitate the development of smarter energy grids and offer a more efficient and innovative approach to energy use [9][10][11][12]. However, given the complexity and uncertainty of digital transformation, it remains quite difficult for entrepreneurs to appreciate the consequences of digital transformation. ...
... (www.preprints.org) | NOT PEER-REVIEWED | Posted: 1 July 2024 doi:10.20944/preprints202406.2078.v19 ...
Digital transformation, organizational resilience, and agility are now becoming one of the keys to meeting the competitive challenges of modern organizations. It is no surprise that digital transformation and digital technologies have also begun to significantly impact the energy industry, moving towards improving the sector's profitability and efficiency. However, to navigate through the difficult process of digital transformation in today's turbulent environment, organizations, including those in the energy sector, need to build organizational resilience. Nevertheless, the nature of the relationship between digital transformation and organizational resilience has not yet been sufficiently clarified. Focusing on the level of digital transformation, and more precisely within the two dimensions of digital maturity, i.e. digital intensity and transformation management intensity, as well as based on the perspective of dynamic capabilities, this study developed a configurational framework and proposed a theoretical model to study the equifinal paths through which digital transformation and dynamic capabilities influence organizational resilience in energy sector companies. Based on a fuzzy set qualitative comparative analysis (fs/QCA) conducted on selected companies in the energy sector, i.e. Polish CHP plants, the relationship between digital transformation, dynamic capabilities and organizational resilience was investigated. The results show that a high level of organizational resilience can be achieved through two main paths based on the dominance of dynamic capabilities and the dominance of digital maturity. The study found that digital maturity can significantly influence CHP resilience. Moreover, the transformation management intensity is strongly related to high organizational resilience. The paper concludes by describing theoretical and practical implications, as well as research limitations and prospects for future research.
... It is of great importance for enterprises to efficiently coordinate and integrate these value chain links in order to realize the two-wheel drive of business value and social value through the digital transformation. Although the existing literature has demonstrated the positive impact of digital transformation on CSR performance [1,[20][21][22][23], digital transformation has not been anchored in specific value chain links, and the unique value for stakeholders created by combining digitalization with core value-creating activities has yet to be elucidated. Therefore, it is necessary to study the impact of the digital transformation of value chains on CSR to compensate for the shortage of existing studies. ...
... The existing studies have the viewpoint that the digital transformation of enterprises is the organic integration of digital technology and physical elements [5,14]. Related work only focuses on the positive effects of digital transformation on CSR performance [1,[20][21][22][23] and does not embed digitalization into the value creation activity. What really works is the digitalization of each business link and operation level and the effective integration of the whole value chain system in the digitalization process. ...
With the accelerated evolution of the digital transformation of economic activities, the digitalization of the different parts of the value chain, such as manufacturing, marketing, and management, has increased significantly, thereby changing the form of organizational production management while affecting how corporate social responsibility (CSR) is achieved. Therefore, in this study, we examined the relationship between the digital transformation of value chains and CSR performance and the moderating role of property ownership and market dependence. The results show that the digital transformation of value chains can improve CSR performance. When the three types of digital transformation are conducted at the same time, compared with digital manufacturing transformation and digital marketing transformation, digital management transformation has a greater impact on CSR performance. Non-state-owned enterprises and enterprises with higher market dependency show greater improvement in their CSR performance than state-owned enterprises and enterprises with lower market dependency as a result of the digital transformation of value chains. Furthermore, we found a certain degree of value mismatch between the digital transformation of the different value chain links of enterprises and the different dimensions of social responsibility. Specifically, the digital transformations of manufacturing, marketing, and management activities only exert a significant impact on shareholder responsibility, public responsibility, and shareholder and employee responsibility, respectively. This result indicates that the digital transformation of the entire value chain needs to be further optimized and integrated to achieve social responsibility values that match the value chain. This study not only helps enterprises identify the shortcomings in the digital transformation of the value chain but also provides development ideas for enterprises to realize the two-wheel drive of business value and social value through the digital transformation of the whole value chain.
... I4.0 has paved the way for the development of modernised electric energy systems able to integrate a larger number of renewable energy sources (Furstenau et al., 2020). I4.0 will contribute to the provision of additional flexibility for renewable energy sources through increased flexibility of production processes (Scharl and Praktiknjo, 2019;Stock et al., 2018). I4.0 also had an impact on the development of digital twins, which will be useful for network operators not only to obtain accurate estimations of industrial energy consumption and generation but also to perform a more effective identification of failures in power systems. ...
... I4.0 also had an impact on the development of digital twins, which will be useful for network operators not only to obtain accurate estimations of industrial energy consumption and generation but also to perform a more effective identification of failures in power systems. In fact, Scharl and Praktiknjo (2019) stated that the digitisation of the industry might provide positive impacts on future renewable energy systems, Hidayatno et al. (2019) contributed to a better understanding of how I4.0 might support the transition to a widespread use of renewable energy sources in Indonesia, and Nara et al. (2021) realised that it is possible to increase the use of renewables by integrating different I4.0 technologies, such as the IoT, sensors, and big data in the Brazilian plastics industry. ...
The aim of this paper is to provide a multi-criteria decision-making intelligent approach based on Industry 4.0 and Triple Bottom Line principles for sustainable supply chain development in the renewable energy sector. In particular, the solar photovoltaic energy supply chain is used as a case study, encompassing the entire energy production process, from supply to disposal. An exhaustive literature review is conducted to identify the main criteria affecting social, economic and environmental sustainability in the photovoltaic energy supply chain, and to explore the potential impact of Industry 4.0 on sustainability. Subsequently, three Fuzzy Inference Systems combining quantitative and qualitative data are built to calculate the supply chain's social, economic and environmental sustainability. Experts' opinions are used to identify the impact of Industry 4.0 technologies on the three pillars of sustainability for each supply chain stage. Finally, a novel sustainability index, Sustainability Index 4.0, is formulated to compute the overall sustainability of the photovoltaic energy supply chain in seven countries. The results show the applicability and usefulness of the proposed holistic model in helping policy makers, stakeholders and users to make informed decisions for the development of sustainable renewable energy supply chains, taking into account the impact of Industry 4.0 and digital technologies.
... DTs are key to the industry 4.0 transformation, hence, research has been focussed in optimising manufacturing and production. [2][3][4][5] For example, using DTs in the offshore renewable sector 6,7 can reduce operational costs and maximise energy output due to the harshness of the environment where the devices operate. However, the application of DT technology to other sectors is growing, with the use of DTs in 'smart cities' offering huge potential. ...
... This is not to be confused with information sources (see first footnote). ‡ The frameworks by Arksey and O'Malley 52 and Levac et al 53 and the JBI guidance (4,5) refer to the process of data extraction in a scoping review as data charting. § The process of systematically examining research evidence to assess its validity, results, and relevance before using it to inform a decision. ...
Background
Digital Twins (DTs), virtual copies of physical entities, are a promising tool to help manage and predict outbreaks of Covid-19. By providing a detailed model of each patient, DTs can be used to determine what method of care will be most effective for that individual. The improvement in patient experience and care delivery will help to reduce demand on healthcare services and to improve hospital management.
Objectives
The aim of this study is to address 2 research questions: (1) How effective are DTs in predicting and managing infectious diseases such as Covid-19? and (2) What are the prospects and challenges associated with the use of DTs in healthcare?
Methods
The review was structured according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR) framework. Titles and abstracts of references in PubMed, IEEE Xplore, Scopus, ScienceDirect and Google Scholar were searched using selected keywords (relating to digital twins, healthcare and Covid-19). The papers were screened in accordance with the inclusion and exclusion criteria so that all papers published in English relating to the use of digital twins in healthcare were included. A narrative synthesis was used to analyse the included papers.
Results
Eighteen papers met the inclusion criteria and were included in the review. None of the included papers examined the use of DTs in the context of Covid-19, or infectious disease outbreaks in general. Academic research about the applications, opportunities and challenges of DT technology in healthcare in general was found to be in early stages.
Conclusions
The review identifies a need for further research into the use of DTs in healthcare, particularly in the context of infectious disease outbreaks. Based on frameworks identified during the review, this paper presents a preliminary conceptual framework for the use of DTs for hospital management during the Covid-19 outbreak to address this research gap.
... This contribution mainly includes resource consumption efficiency along with energy consumption, waste, and emission reduction. Industry 4.0 is also believed to offer unique opportunities to integrate renewable energy sources into the energy distribution and transmission systems (Scharl and Praktiknjo, 2019). Finally, the environmental benefit of Industry 4.0 also involves applying underlying digital technologies for developing and producing more sustainable products and services (Bag et al., 2021). ...
... The environmental benefits of Industry 4.0 involve various eco-efficiency functions. Resource and energy consumption efficiency is the most prominent environmental implication of Industry 4.0, and scholars such asBag et al. (2021),Jena et al. (2020), andScharl and Praktiknjo (2019) have theoretically and empirically explored various resource and energy efficiency opportunities that Industry 4.0 and its underlying technologies offer. The literature also widely acknowledges the opportunities that Industry 4.0 may offer for waste reduction, management, and recycling. ...
The fourth industrial revolution, known as Industry 4.0, and the underlying digital transformation, is a cutting- edge research topic across various disciplines. Industry 4.0 literature is growing exponentially, overexpanding the current understanding of the digital industrial revolution through thousands of academic publications. This unprecedented growth calls for a systematic review of the concept, scope, definition, and functionality of Industry 4.0. Such systematic review should address the existing ambiguities and deliver a clear, comprehensive, and up-to-date overview of this phenomenon, including the possible implications for sustainability. Consistently, the present study carried out a systematic literature review of related articles, published online within the Industry 4.0 discipline until November 2020. The systematic literature review identified 745 eligible articles and applied extensive qualitative and quantitative data analysis methodically. The study provides a descriptive assessment of eligible articles' properties and offers a unified conceptualization of Industry 4.0 and the underlying building blocks. The study explains how the implications of Industry 4.0 for value creation expand beyond the manufacturing industry. The study further describes the sustainability value drivers of the fourth industrial revolution and identifies the conditions on which digital industrial transformation success lays. Overall, findings reveal that Industry 4.0 transformation could address pressing issues of sustainable development goals, particularly concerning the manufacturing-economic development. The study also draws on the findings and offers important theoretical and practical implications, highlights the existing gaps within the literature, and discusses the possible future research directions.
... Decentralized energy systems are one of the most significant changes brought about by digitalization. In a decentralized model, energy generation occurs closer to where it is consumed, most times by small-scale producers such as households and businesses that have solar panels, wind turbines, or other renewable technologies (Scharl & Praktiknjo, 2019). This is unlike the traditional, centralized systems with radial power generation systems, in which large numbers of power generation plants supply island-wide energy over long distances. ...
... Furthermore, it drives the shift in urban industrial focus towards technology-intensive industries, optimizes the urban industrial structure, and achieves improvements in energy efficiency. Finally, the digital industry, with technological upgrading as the key path, has strong penetration and multiplier effects, which can significantly drive urban economic growth [54]. ...
The digital economy (DE) is characterized by invention, low energy consumption, cross-sector integration, and open sharing. It can effectively enhance social production methods, influence consumer behavior, and provide new pathways to enhance total factor energy efficiency (TFEE). This paper studies 280 Chinese cities, employing the entropy method and data envelopment analysis (DEA) model to evaluate and analyze urban DE and TFEE. It also constructs a system generalized method of moments model (SGMM model) and a threshold regression model (TR model) to examine the impact of the DE on TFEE in China. The main study findings include the following: (1) The regression results of the SGMM model indicate that the effect of DE on TFEE in Chinese cities shows a U-shaped trend. (2) The regression results of the TR model further confirm a U-shaped association connecting DE and TFEE, with the threshold estimated at 0.304. (3) The economic factors and industrial structure have a major impact on inhibiting the improvement of TFEE, whereas technological advancements and environmental regulations significantly facilitate its improvement.
... This drives more efficient monitoring and tracking of carbon emissions, natural ecosystem status, and energy utilization throughout the supply chain [10]. According to Scharl and Praktinjo [11], the Fourth Industrial Revolution or Industry 4.0, 1 led by the digital economy, can significantly facilitate the integration of renewable energy into future smart factories based on advanced digital technologies, thereby substantially improving energy sustainability. ...
Given the threat of climate change, the renewable energy transition will play a pivotal role in reaching net-zero goals. The digital economy and institutional quality are considered key enablers of the rapid deployment of renewable energy because they can strengthen the reliability and security of energy systems. This study examines the impacts of the digital economy and institutional quality on renewable energy deployment across 85 countries from 2003 to 2021 using a Two-Step System GMM.
The selection of a dynamic panel model is motivated by the path-dependent nature of renewable energy deployment. Sub-sample analyses are conducted to account for the diversity of the dataset in terms of energy mixes, levels of economic development, digital infrastructures, and institutional qualities. A dynamic threshold regression analysis is then conducted to determine the non-linearity of fossil fuel dependence on the impact of the digital economy and institutional quality on renewable energy deployment. The estimates reveal that the digital economy promotes renewable energy deployment, whereas institutional quality has an ambiguous effect. Additionally, depending on the degree of fossil fuel dependency, the impacts of both the digital economy and institutional quality vary significantly and exhibit non-linear and asymmetric features.
... Digitalisation enhances operational efficiency, adaptability, and resilience in manufacturing processes, allowing for adjustments in energy sources and prices and developing strategies to mitigate the impact of disruptions. When compared to the industrial sector, the energy sector has adopted digital technologies early on and the integration of sustainable energy systems with digital technologies will drastically alter energy generation, distribution, and consumption [141]. As part of the Industry 4.0 era, the integration of physical and digital infrastructure in the energy sector will result in the digitisation of power plants. ...
Industrial demand response (IDR) will play a crucial role in shaping future electricity systems, as it is a key element of a just energy transition and industrial development. The aim of this work is to provide an overview of the current status of IDR in a holistic perspective. First, the main benefits and potential of IDR are reviewed, together with the motivations and challenges for the industrial sector. Most recent advances in European markets and regulations with specific focus on IDR applications are explored. Then, the different resources which are currently available to help industries participate and implement IDR programmes are reviewed. In particular: 1) the (possible) tools for defining energy-aware scheduling and planning of the manufacturing systems are analysed ; 2) The role of aggregators (i.e. intermediaries between industries and power markets) for facilitating explicit IDR is examined; 3) the importance of digitalisation to provide better IDR services from the manufacturing industry is highlighted, pointing out that digital twins, cyber-physical systems, Internet of Things sensors, robots, edge computing, artificial intelligence, and big data are promising technologies; and 4) most recent related research projects are reviewed. Finally, it is analysed and discussed how each of those resources can address the different challenges that are still preventing industries to apply IDR programmes. Abbreviations ACER
... In the energy sector, issues relating to the implementation of innovative solutions and digital transformation are also quite intensively analyzed. Among other things, surveys were carried out on the use of solutions based on the Industry 4.0 paradigm in the energy sector [7], the role of Industry 4.0 in energy sustainability [8], and the use of modern digital technologies, such as artificial intelligence (AI), big data, Internet of Things (IoT), blockchain in energy industries that facilitate the development of smarter energy grids and offer a more efficient and innovative approach to energy use [9][10][11][12]. Given the nature of digital transformation, which is uncertain and highly complex, it is invariably difficult for entrepreneurs to fully appreciate the results and implications of digital transformation. ...
Digital transformation, organizational resilience, and agility are now becoming key to meeting the competitive challenges of modern organizations. It is no surprise that digital transformation and digital technologies have also begun to significantly impact the energy industry, moving towards improving the sector’s profitability and efficiency. However, to move the difficult process of digital transformation in today’s dynamically changing environment, organizations, including those in the energy sector, need to build organizational resilience. Nevertheless, the relationship between digital transformation and organizational resilience has not yet been explained in a satisfactory and sufficient manner. Focusing on the level of digital transformation, and more precisely within the two dimensions of digital maturity, i.e., digital intensity and transformation management intensity, as well as based on the perspective of dynamic capabilities, this study developed a configurational framework and proposed a theoretical model to study the equifinal paths through which digital transformation and dynamic capabilities influence organizational resilience in energy sector companies. Based on a fuzzy set qualitative comparative analysis (fs/QCA) conducted on selected companies in the energy sector, i.e., Polish CHP plants, the relationship among digital transformation, dynamic capabilities, and organizational resilience was investigated. The results show that a high level of organizational resilience is possible to achieve through two main paths based on the dominance of dynamic capabilities and the dominance of digital maturity. The results show that a high level of organizational resilience is possible to achieve through two main paths based on the dominance of dynamic capabilities and the dominance of digital maturity. The study found that digital maturity can significantly influence CHP resilience. Moreover, the transformation management intensity is strongly related to high organizational resilience. The paper concludes by describing theoretical and practical implications, as well as research limitations and prospects for future research.
... The advanced control theories focused on by us in this paper are critical in supporting different policy goals in smart grids, as it is inherently related to new technologies and intelligent energy management through the entire value chain from the generation to the consumers [284]. It is noteworthy that, the advanced grid control methods are the heart of the power system evolution especially in industry 4.0, the main impacts of digitized renewable energy systems are addressed in [285] for a case study in Germany. Considering the rapid promotion of energy transition, the environmental concerns, fossil fuel problems, energy system security, and economic and operation cost issues all raise the requirements of suitable control schemes [286]. ...
The integration of various grid-enhancing technologies is crucial for addressing the current challenges faced in controlling transmission grids. The growing variability in energy supply necessitates innovative solutions such as advanced grid monitoring and control systems, energy storage technologies, and flexible grid infrastructure. These technologies are essential for balancing the intermittent nature of renewable energy sources (RESs) and ensuring a stable and reliable electricity supply. This paper offers a comprehensive review of grid-enhancing technologies, incorporating insights from worldwide academic papers and various existing industrial projects that address current challenges and enhance the functionality, reliability, and sustainability of transmission grids. The findings highlight that modernizing grid infrastructure and integrating cutting-edge digital technologies are vital for effectively incorporating a growing number of RESs and enhancing overall grid resilience and efficiency. In addition, the paper explores future opportunities for improving the control of transmission grids, emphasizing the need for continued innovation and investment to meet evolving energy demands and support the transition to a more sustainable energy system.
... In this context, the enhancement of energy management plays a fundamental role, not only to guarantee the quality, the reliability, and the consumption awareness of the power grids inside smart factories, but also to improve the sustainability of the plants and the deployment of renewable and low-impact energy sources [6][7][8]. The characteristics listed above are part of the definition of Smart Grids (SGs), which are self-sufficient systems capable of delivering a sustainable, reliable, and quality power supply to the end-users, by monitoring the power system's condition and, eventually, resolving the possible problems on the grid [9]. ...
In the era of Industry 4.0, achieving optimization in production and minimizing environmental impact has become vital. Energy management, particularly in the context of smart grids, plays a crucial role in ensuring sustainability and efficiency. Lithium-ion batteries have emerged as a leading technology for energy storage due to their versatility and performances. However, accurately assessing their State of Health (SOH) is essential for maintaining grid reliability. While discharge capacity and internal resistance (IR) are commonly used SOH indicators, battery impedance also offers valuable insights into aging degradation. This article explores the use of Electrochemical Impedance Spectroscopy (EIS) to define the SOH of lithium batteries. By analyzing impedance spectra at different frequencies, a comprehensive understanding of battery degradation is obtained. A life cycle analysis is conducted on cylindrical Li–Mn batteries under various discharge conditions, utilizing EIS measurements and an Equivalent Circuit Model (ECM). This study highlights the differential effects of aging on battery characteristics, emphasizing the variations at different life stages and the behavior changes on each region of the impedance spectrum. Furthermore, it demonstrates the efficacy of EIS and the advantages of this technique compared to the solely IR measurements used in tracking SOH over time. This research contributes to advancing the understanding of lithium battery degradation and underscores the importance of EIS in defining their State of Health for Smart Grids applications.
... The PRE function draws on the integrability and data interoperability features of Industry 4.0 technology to allow value partners to integrate sustainable decision-making and meaningfully scale up a circular economy (Rajput & Singh, 2020). This function also involves enabling industrial value networks to integrate green materials and renewable energy sources into value engineering and creating processes to benefit all stakeholders from the desirable economic and socio-environmental outcomes (Scharl & Praktiknjo, 2019). Industry 4.0 delivers this functionality via several mechanisms, such as facilitating green innovation capability, decentralised decision systems, smarter energy management systems, and energy supply chain digitalisation (Ghobakhloo & Fathi, 2021). ...
The present study addresses two critical controversies surrounding the emerging Industry 5.0 agenda. Firstly, it seeks to elucidate the driving forces behind the accelerated momentum of the Industry 5.0 agenda amidst the ongoing digital industrial transformation. Secondly, it explores how the agenda’s sustainability values can be effectively realised. The study conducted a comprehensive content-centric literature synthesis and identified how Industry 4.0 shortcomings adversely impacted sustainability values. Furthermore, the study implements a novel approach that determines how and in what order the sustainability functions of Industry 4.0 should be leveraged to promote the sustainability objectives of Industry 5.0. Results reveal that Industry 4.0 has benefited economic and environmental sustainability values most at the organisational and supply chain levels. Nonetheless, most micro and meso-social sustainability values have been adversely impacted by Industry 4.0. Similarly, Industry 4.0 has been worryingly detrimental to macro sustainability values like social or economic growth equality. These contradictory implications of Industry 4.0 have pulled the Industry 5.0 agenda. However, the results identified nine sustainability functions of Industry 4.0 that, when leveraged appropriately and in the correct order, can offer important implications for realising the economic and socio-environmental goals of Industry 5.0. For example, under extreme unpredictability of business world uncertainties, the business should first leverage the automation and integration capabilities of Industry 4.0 to gain the necessary cost-saving, resource efficiency, risk management capability, and business antifragility that allow them to introduce sustainable innovation into their business model without jeopardising their survival. Various scenarios for empowering Industry 5.0 sustainability values identified in the present study offer important implications for knowledge and practice.
... Last but not least, the increasing share of renewable energy sources (RES) is also associated with intermittent energy production, for example, placing greater demands on ensuring the reliability of supply, e.g., (Scharl and Praktiknjo 2019). Here, the growing number of RES hinders the effort necessary to control and control the system. ...
... For instance, CPS provides an integrated platform for all components in the system to communicate and exchange data. When combined with AI, new technologies like the IoT can turn solar and wind farms into intelligent energy systems [20]. In this context, wind farms can employ data mining and machine learning to develop the maintenance schedules for wind farms to effectively diminish risks and their consequences [21]. ...
Industry 4.0 is revolutionising all industries including Blue Economy, and transforming different aspects of the way we live, work, and learn. Industry 4.0 has redefined entire services and processes through intelligent and integrated technologies such as Cyber-Physical-Systems (CPS), the Internet of Things (IoT), and artificial intelligence (AI). The Industry 4.0 has brought many positive changes and at the same time challenges that directly or indirectly involve the human element and sustainability. While the long-term strategy of the Blue Economy is aimed at unlocking the potential of ocean resources, a qualified and intelligent workforce in a sustainable environment can increase productivity and growth opportunities. So far, Industry 4.0 application in the Blue Economy industry has mainly addressed technological innovation. However, so far, the future role of the human and sustainability were not the focus of the R&D activities and thus under-researched. Understanding such a role is important, as industry 4.0, through digitalisation and automation, is redefining jobs, work activities, and the workplace itself. This entails not only the need for training a new breed of workforce who are able to operate novel systems but also affects the design of support equipment and systems for the offshore environment. This paper aims to explore the current status of human elements and sustainability associated with the application of Industry 4.0 on the Blue Economy programs such as aquaculture and renewable energy industries by utilising a systematic literature review. The paper will focus on issues that include changing the nature of jobs and its effect on the workforce in the Blue Economy industries and the need for training and upskilling of the workforce.
... Industry 4.0 aims to create a network that addresses the interoperability issues within and across all levels of an automated factory-improving the flexibility and agility of conventional manufacturing. Industry 4.0 is the advancement and integration of digital technologies, such as the Internet of Things (IoT), artificial intelligence (AI), machine learning, big data analytics, robotics, additive manufacturing, and DTs (Tao et al. 2018b;Scharl and Praktiknjo 2019). As Industry 4.0 continues to evolve; the above key trends and technologies are shaping the future of manufacturing and production, creating more efficient, flexible, and sustainable processes. ...
As the adoption of Industry 4.0 advances and the manufacturing process becomes increasingly digital, the Digital Twin (DT) will prove invaluable for testing and simulating new parameters and design variants. DT solutions build a 3D digital replica of the physical object allowing the managers to develop better products, detect physical issues sooner, and predict outcomes more accurately. In the past few years, Digital Twins (DTs) dramatically reduced the cost of developing new manufacturing approaches, improved efficiency, reduced waste, and minimized batch-to-batch variability. This paper aims to highlight the evolution of DTs, review its enabling technologies, identify challenges and opportunities for implementing DT in Industry 4.0, and examine its range of applications in manufacturing, including smart logistics and supply chain management. The paper also highlights some real examples of the application of DT in manufacturing.
... Over the last decade, electricity consumption has increased by 73% due to the rapid population growth and it led to the power shortage faced by India, i.e., 70,000 Mega Watt (MW) [3]. Te challenge of power shortages can be handled in two ways as follows: the frst is to employ more traditional renewable energy sources to generate more electricity [4] and the second is to optimize the use of available electricity by smart appliances [5]. Technological advancements have empowered the development of smart devices not only to minimize power usage but also energy waste. ...
Currently, due to the widespread population growth, there is a widespread concern about an electricity shortage. As a result, smart devices have evolved and gained significant attention to reduce power consumption in home appliances due to electricity shortages. However, it lacks a universal remote control that can control home appliances based on environmental conditions. To overcome these challenges, this study proposed a hardware-based remote-control system that operates both in autonomous and semiautonomous modes to control home appliances based on environmental conditions. In the autonomous mode, the receiver section regulates the parameters under ambient conditions by varying the appliance’s applied voltage levels via a dimmer. The parameters in semiautonomous are monitored by the user via various levels of remote control. A 2.4 GHz RF modem is used to establish wireless personal network (WPAN) communication between the remote and the receiver. In addition, a Wi-Fi modem is built into the receiver to enable internet-based mobile applications to operate appliances. During the MATLAB analysis, a proportional integral derivative (PID) controller with a particle swarm optimization (PSO) method was found as a superior approach to control the home appliance with adequate environmental conditions. It is concluded from the MATLAB study that the PSO-PID controller delivered an energy saving of 14.88% for the heater, 36.9% for the exhaust fan, and 37.49% for the light bulb compared to the conventional appliances.
... According to them, environmental sustainability should not be sacrificed on the altar of increased production capacity. In their work, (Scharl and Praktiknjo 2019), (Hidayatno et al. 2019) and (Oláh et al. 2020) suggested the use of energy systems that meet the affordability, availability, and environmental sustainability requirements to drive the new industrial revolution. ...
Worsening environmental degradation, depletion of fossil fuels reserves, and fuel price volatility have led to increased concerns about getting adequate energy to power the rapidly growing industrial sector and other uses. The cost of energy is a major contributor to the rising cost of production and a source of worry to both the producers and consumers alike. Investigation into devising sustainable, accessible, and affordable energy sources to power the manufacturing sector and other consumers has engaged the attention of researchers and other stakeholders in recent decades. The current research, therefore, investigates techniques for ensuring sustainable energy consumption in the Industry 4.0 era. Results show that effective implementation of energy saving, cost reduction, and green manufacturing measures will lower energy costs, benefit the environment and result in a high return on invested capital. The application of novel intelligent technologies like cyber-physical systems, industrial internet of things, artificial intelligence, big data, cloud computing, smart metering, and other components of Industry 4.0 will contribute to achieving sustainable energy utilization in the manufacturing sector. Going forward, more targeted investigations are required to cultivate realistic and implementable models for achieving affordable, environmentally benign, and sustainable energy for the manufacturing sector.
... Policies and measures to promote renewables in households, linking them to the main barriers[48][49][50][51][52][53][54][55][56][57][58]. ...
Although renewable energy adoption in the residential sector has increased significantly in the EU due to the governmental policies, aiming to reduce the barriers of renewable energy penetration, the full potential of renewable energy deployment in households is still not realized due to the behavioral and other barriers. One of the most important factors in the adoption of renewable energy technologies in households is the decision-making to implement renewables; therefore, the behavioral economics insights should be taken into account during the analysis of renewable energy acceptance by households. The paper provides a systematic literature review on renewable energy use in households by analyzing policies and measures, which could increase the use of renewable energy in households by overcoming the major barriers. The dynamics of renewable energy consumption in EU households was performed by applying Eurostat data, and the empirical case study was conducted in Lithuania to understand the main reasons of renewable energy acceptance by the household. Even though the use of renewable energy sources has increased significantly in the EU member states during the recent years, the study has found the following most common barriers that the traditional policies are unable to overcome: (1) high upfront cost and long pay-back period, (2) a lack of information and knowledge, (3) low priority of environmental concern, (4) resistance to change; human habits. The case study shows that the majority of Lithuanian households would like to use renewable energy technologies in their homes, but they encounter financial difficulties and lack of infrastructure. The policy recommendations were developed based on the results of the conducted study.
... In this regard, sustainable manufacturing can be defined as a systematic approach of creating and distributing innovative products and services in a way that eliminates excessive use of resources such as water, land, and energy, produces zero waste to reduce CO2 emissions, and eradicates toxic substances [39]. Digital transition plays a critical role in availing appropriate technologies needed to manufacture products in sustainable ways that align with the globally accepted sustainable development goals that involve meeting current generations' goals and needs without compromising future generations [40]. For example, under sustainable manufacturing, companies are implementing new analysis procedures and designs to reduce environmental impacts. ...
The digital transition processes have demonstrated an enormous capacity to develop and implement sustainable solutions, which allow solving several problems such as poverty, high rates of species extinction and lack of equal opportunity. However, little attention is paid to the connection between the digital transition and sustainability. Thus, a systematic bibliometric literature review was developed to fill this knowledge gap and demonstrate the potential contributions of the digital transition to environmental, economic, and social sustainability aspects. In environmental sustainability, the digital transition involves the application of technologies such as Artificial Intelligence (AI), big data analytics, Internet of Things (IoT), and mobile technologies that are used to develop and implement sustainability solutions in areas such as sustainable urban development, sustainable production, and pollution control. In economic sustainability, emerging digital technologies can drive transformation into a more sustainable circular economy, the digital sharing economy, and establish sustainable manufacturing and infrastructure design. In the digital transition to social sustainability, the studies analyzed demonstrate the need for multidimensional policy perspectives to address the current digital divide. For effective management of the digital transition that achieves sustainability goals, the study discusses alternative approaches that include innovation through experimentation and dynamic and sustainable advantages achievable through temporary benefits.
... According to experts [91], in the context of Industry 4.0 technologies' use in renewable energy, the main emphasis should be placed on: ...
The paper is devoted to the analysis of the current and the forecast of the prospective state of introducing digital technologies into the oil and gas mining industry of the Russian Arctic. The authors of the paper analyzed the global trends that define the process of digital technologies’ introduction into the oil and gas mining industry. They also reviewed the Russian companies’ experience in this sphere. The main trends and prospects for the development of oil and gas resources extraction in the Russian Arctic in the digitalization sphere were identified. Together with this, the researchers considered prospects for digital technologies’ introduction into the oil and gas industry, observing their competition with RES. As a result, the authors have come to the following conclusions: (1) in Russian companies, digitalization is being more actively introduced into the processes of general enterprise management. (2) The main purpose of Russian oil and gas sector digitalization is to increase the efficiency of business process management, while the key constraining factors of digitalization are the lack of qualified personnel, lack of material and technical base and cyber-security threats aggravation. (3) The prospects of introducing a new package of sanctions can become both an incentive for a qualitative leap in Russian software development/implementation and an obstacle to the development of Arctic projects due to their rise in price. (4) The COVID-19 pandemic factor is one of the incentives for the widespread introduction of production and various business processes automation in the oil and gas industry, as well as the development of digital communications. (5) The leader in the digital technology development industry among Russian oil and gas companies is “Gazprom Neft” PJSC, followed by “NK Rosneft” PJSC. (6) “Gazprom” PJSC continues to lag behind in the sphere of digitalization; however, qualitative changes here should be expected in 2022. (7) The “sensitivity parameters” influencing the industry digitalization process in the Arctic region are the high dependence on foreign technological solutions and software, characteristics of the entire Russian oil and gas industry, and the problem of ensuring cybersecurity in Arctic oil and gas projects and power outages. (8) For the Arctic regions, the use of RES as the main source of electricity is the most optimal and promising solution; however, hydrocarbon energy will still dominate the market in the foreseeable future.
... In this regard, sustainable manufacturing can be defined as a systematic approach of creating and distributing innovative products and services in a way that eliminates excessive use of resources such as water, land, and energy, produces zero waste to reduce CO 2 emissions, and eradicates toxic substances [39]. Digital transition plays a critical role in availing appropriate technologies needed to manufacture products in sustainable ways that align with the globally accepted sustainable development goals that involve meeting current generations' goals and needs without compromising future generations [40]. For example, under sustainable manufacturing, companies are implementing new analysis procedures and designs to reduce environmental impacts. ...
The digital transition processes have demonstrated an enormous capacity to develop and implement sustainable solutions, which allow solving several problems such as poverty, high rates of species extinction and lack of equal opportunity. However, little attention is paid to the connection between the digital transition and sustainability. Thus, a systematic review of the bibliometric literature was developed to fill this knowledge gap and demonstrate the potential contributions of the digital transition to environmental, economic and social sustainability aspects. In environmental sustainability, the digital transition involves the application of technologies such as AI, big data analytics, IoT, and mobile technologies that are used to develop and implement sustainability solutions in areas such as sustainable urban development, sustainable production and pollution control. In economic sustainability, emerging digital technologies can drive transformation into the more sustainable circular economy, the digital sharing economy, and establish sustainable manufacturing and infrastructure design. In the digital transition to social sustainability, the studies analyzed demonstrate the need for multidimensional policy perspectives to address the current digital divide. For effective management of the digital transition that achieves sustainability goals, the study discusses alternative approaches that include innovation through experimentation, and dynamic and sustainable advantages achievable through temporary benefits.
... At the same time, in their scientific work, S. Scharl and A. Praktiknjo [13] mention such aspects in the context of research of innovative development of the environment in the conditions of Industries 4.0, 5.0. The scientists claim that a growing influence of the role of the digital Industry 4.0 on the processes of developing the «green» economy implies a total increase in the efficiency of energy development of the economy, including industry. ...
The article is devoted to topical issues of mutual influences of ecological and economic, industrial and technological development. The main purpose of the article is to study the system characteristics of the relationship between industrial and technological development and the effectiveness of the national economy. Such a relationship is based on the policy of environmental innovation, which is implemented at the junction of relations in the fields of environmental safety, industrial policy and technological development of Ukraine. The article aims to determine economic effects of the ecological component of industrial and technological development of the country. The study found that the industrial and technological growth of the national economy depends to a large extent on the ecological component. The method of taxonomy was used to carry out an integral assessment of ecological indicators of industrial and technological development in the system of ecological and economic security of Ukraine. The application of tools of multidimensional statistical analysis, the harmonization of indicators of industrial and technological development and ecological and economic security of Ukraine helped to determine the economic effects of ecological impact.
... Equally indispensable to smart manufacturing is advanced robotics, which serves as an intelligent agent appearing in every corner of production lines. With the profound research and development of Industry 4.0 and artificial intelligence (AI), digital twin (DT) has drawn growing research attention [1][2][3][4]. As a digital replica of a physical entity, the basis of DT is the infrastructure and data, the core is the algorithm and model, and the application is the software and service. ...
Digital twin (DT) and artificial intelligence (AI) technologies have grown rapidly in recent years and are considered by both academia and industry to be key enablers for Industry 4.0. As a digital replica of a physical entity, the basis of DT is the infrastructure and data, the core is the algorithm and model, and the application is the software and service. The grounding of DT and AI in industrial sectors is even more dependent on the systematic and in-depth integration of domain-specific expertise. This survey comprehensively reviews over 300 manuscripts on AI-driven DT technologies of Industry 4.0 used over the past five years and summarizes their general developments and the current state of AI-integration in the fields of smart manufacturing and advanced robotics. These cover conventional sophisticated metal machining and industrial automation as well as emerging techniques, such as 3D printing and human–robot interaction/cooperation. Furthermore, advantages of AI-driven DTs in the context of sustainable development are elaborated. Practical challenges and development prospects of AI-driven DTs are discussed with a respective focus on different levels. A route for AI-integration in multiscale/fidelity DTs with multiscale/fidelity data sources in Industry 4.0 is outlined
This study investigates the adoption of Industry 4.0 technologies in Small and Medium Enterprises (SMEs) within emerging economies, focusing on sustainability and resource efficiency. Extant research often targets larger firms or developed economies, leaving SMEs in emerging markets underexplored. This study proposes a holistic framework for SMEs to enhance Industry 4.0 adoption, addressing sustainability goals while improving competitiveness. Twenty-five enablers of Industry 4.0 adoption were identified through a systematic literature review and validated their significance through a survey of 233 Indian manufacturing SMEs. Using Exploratory Factor Analysis, the enablers were clustered into five groups: Digital and Physical Technologies, Organizational, Supply Chain, Environmental, and Social. Fuzzy-AHP prioritized the enablers, while Fuzzy-DEMATEL explored their interrelationships. Sensitivity analysis validated the results, ensuring robustness. Analyzed results highlight organizational readiness, such as dedicated R&D teams and managerial support. Inter-organizational factors, such as supply chain integration and social enablers with effective policies, were also found to be pivotal. Digital technologies and environmental strategies emerged as factors dependent on robust organizational and policy support. Practical recommendations include targeted resource allocation, skill development, and policy interventions to support digital transformation. This research bridges gaps in Industry 4.0 adoption and advances SME participation in sustainable global supply chains.
Digital technologies (DTs) offer new avenues for organisations to boost business performance, innovation and agility and play a pivotal role in sustainable development by enhancing resource efficiency, reducing adverse environmental effects and supporting the shift to renewable energy. Specifically, renewable energy communities (RECs), as a socio-technical model, underscore the significance of digital technologies in facilitating energy decentralisation and efficiency while fostering community involvement and local economic growth. Extensive research highlights DTs’ capacity to cut emissions and foster low-carbon economies, with specific studies on RECs focusing on digital tools for energy optimisation, renewable integration and community engagement. However, challenges such as costs, technical complexities and data security in RECs require further investigation to devise effective adoption strategies. This study aims to identify the key challenges and mitigated steps for DTs adoption in RECs through a literature review and dependency impact analysis, categorising the main opportunities and hurdles into their socio-cultural, economic and technological dimensions. The findings aim to guide decision-making for RECs, enhance digital resilience and efficiency and contribute to sustainable development goals. This work offers valuable insights for both academics and practitioners in understanding adoption barriers and the effects of DTs on renewable energy systems and the broader energy transition.
Background
Energy systems, as critical infrastructures (CI), constitute Cyber-Physical-Social Systems (CPSS). Due to their inherent complexity and the importance of service continuity of CIs, digitization in this context encounters significant practical challenges. Digital Twins (DT) have emerged over the recent years as a promising solution for managing CPSSs by facilitating real-time interaction, synchronization, and control of physical assets. The selection of an appropriate architectural framework is crucial in constructing a DT, to ensure integration of enabling technologies and data from diverse sources.
Objectives
This study proposes a Systematic Literature Review (SLR) to examine technological enablers, design choices, management strategies and Computational Challenges of DTs in Smart Energy Systems (SES) by also analyzing existing architectures and identifying key components.
Methods
The SLR follows a rigorous workflow exploiting a multi-database search with predefined eligibility criteria, accompanied by advanced searching techniques, such as manual screening of results and a documented search strategy, in order to ensure its comprehensiveness and reliability, More specifically, research questions are first defined and then submitted as queries to scientific digital libraries (i.e., IEEE Xplore, Scopus, and WoS) selected due to their coverage and reliability (Google Scholar was excluded for the presence of grey literature and non-peer-reviewed material). Then, inclusion and exclusion criteria are established to filter the results and shortlist the significant publications. Subsequently, relevant data are extracted, summarized, and categorized in order to identify common themes, existing gaps, and future research directions, with the aim of providing a comprehensive overview of the current state of DTs for SESs.
Results
From the proposed DT-based solutions described in the selected publications, the adopted architectures are examined and categorized depending on their logical building blocks, microservices, enabling technologies, human–machine interfaces (HMI), artificial intelligence and machine learning (AI/ML) implementations, data flow and data persistence choices, and Internet-of-Things (IoT) components involved. Additionally, the integration of edge-cloud computing and IoT technologies in literature are studied and discussed. Finally, gaps, opportunities, future study lines, and challenges of implementing DTs are thoroughly addressed. The results achieved also pave the way for a forthcoming design pattern catalog for DTs in CPSSs capable of supporting the engineering and research communities, by offering practical insights on implementation and integration aspects.
Conclusion
The proposed SLR provides a valuable resource for designing and implementing DTs of CPSSs in general and of SESs in particular. Furthermore, it highlights the potential benefits of adopting DTs to manage complex energy systems and it identifies areas for future research.
Also known as the Fourth Industrial Revolution, the concept of Industry 4.0 emerged in 2011 from a German government project, which stimulated the computerization of production lines in industries due to the increased demand for specific and personalized products using the growing evolution of new technologies that enabled the integration between machines in their production environment. Through a systematic literature review, this study seeks to understand the concepts of Industry 4.0 in the electricity sector, considering the aspects of its planning and the expected structural benefits, both in the quality of distributed energy and, consequently, in the application of this energy for the automation of industrial productive processes and smart cities. This study found twelve main dimensions most cited by the authors, of which five constructs of Industry 4.0 in the electricity sector were formed: infrastructure, technologies, smart solutions, sustainability, and energy management. Such constructs are interconnected like a gear system, on which each construct depends on the other. This study seeks to analyze the impacts, support elements, benefits, disadvantages, and the possibility of developing new procedures, products, and services that the technologies of Industry 4.0 can bring to the electrical sector and indirectly to its customers. It also aims to identify the factors that lead the top management to the right decision regarding the choice of technologies to increase efficiency and quality never previously achieved with current processes and technologies.
Citation: Afzal, M.; Li, R.Y.M.; Shoaib, M.; Ayyub, M.F.; Tagliabue, L.C.; Bilal, M.; Ghafoor, H.; Manta, O. Delving into the Digital Twin Developments and Applications in the Construction Industry: A PRISMA Approach. Sustainability 2023, 15, 16436. https://doi.
The study’s primary objective is to identify the implications of Industry 4.0 (I4.0) implementationfor renewable energy management and materials development. The study aims to establish a newperspective that promotes adopting emerging clean energy technologies. The study adopts atransdisciplinary approach and critical synthesis of existing literature. Thematic analysis andinferences from three case illustrations are used to gain insights into the value and strategies ofI4.0 implementation for achieving a sustainable and low-carbon future. The literature review on I4.0 provides a deeper understanding of its concepts and potential benefits. The study highlightsthe improved efficiency, productivity, and sustainability that I4.0 technologies, such as IoT, AI,and advanced manufacturing, can bring to various industries. The study’s findings have signifi-cant implications for the practical implementation of I4.0. By cohesively identifying andaddressing economic, regulatory, and technical obstacles, I4.0 can be effectively implemented forrenewable energy and materials development. The study is a valuable reference for students,researchers, scholars, and practitioners. It may guide the design and implementation of I4.0strategies and supports the transition toward a sustainable and low-carbon future.
This book chapter provides an overview of the digitalization process in the electricity sector, highlighting its relation and contribution to the energy transition to a low-carbon system and its current scenario in Brazil. First, we systematize the main technologies related to digitalization. From this, we identify the segments of the electricity sector in which these technologies can be applied to assist energy transition. Then, we evaluate how these elements are evolving in the Brazilian electricity system through the investigation of government initiatives and the historical (2008–2021) of Research and Development (R&D) projects. We found 263 projects related to digitalization, which represents only around 10% of the total number of projects. Digitization contributes to the energy transition by providing technologies that optimize the generation and efficient energy use, allowing greater penetration of renewables and better use of energy resources. However, for this, it is necessary to restructure market and regulatory models. Although the Brazilian government has been developing some plans and strategies for technologies such as the Internet of Things, cyber security and overall digitalization issues, few practical structural changes were identified. Thus, digitalization in the Brazilian electricity sector is still in its infancy, with a need for initiatives to speed up reforms and to make the most of the national renewable energy potential.
In the context of the booming digital economy, its underlying impact on fuel poverty alleviation needs to be accurately estimated. To this end, by applying the sample data of 30 provinces from 2006 to 2017, this chapter empirically evaluates whether the accelerated digital economy can effectively alleviate energy poverty. This chapter then tests the heterogeneous effect of digital economy on clean fuel poverty in different areas and quantiles. This chapter primarily concludes that: (1) The rapid evolution of the digital economy plays an increasingly prominent role in addressing fuel poverty; (2) only in regions with high digital economy level and low energy poverty level can digital economy influences energy poverty negatively; and (3) while contributing directly to energy alleviation, the rapid evolution of digital economy can further enhance the impact of poverty alleviation in the energy sector by optimizing energy efficiency. Based on the above three conclusions, several policy suggestions are introduced to mitigate energy poverty in China.
Purpose
With a growing demand for safe, clean and affordable energy, emerging economies (EEs) across the globe are now seeking to create and rapidly develop renewable energy (RE) businesses. The success of these businesses often hinges on their ability to translate RE into sustainable value for energy consumers and the multiple stakeholders in this industry. Such value includes low production costs due to an abundance of natural resources (e.g. wind, water and sunlight) and public health benefits from reduced environmental pollution. With that in mind, this paper aims to gauge RE’s potential for sustainable value creation and then develop an effective RE business strategy.
Design/methodology/approach
This paper develops a structural equation model, conducts an exploratory factor analysis, confirmatory factor analyses with and without common latent factors and proposes a moderated mediation analysis to identify a host of factors that influence the success of RE businesses.
Findings
This paper discovers that RE business performance is significantly affected by integrated vision, intellectual capital and social capital.
Originality/value
To the best of the authors’ knowledge, this paper is one of the first empirical studies that identify various factors influencing successful RE businesses in EEs such as Asian (e.g. China and India) and Latin American countries.
Purpose: There have been continuous developments in the production industry to meet the increasing customer demand from the past to the present. At this point, supply chain management (SCM) systems emerge as an important topic. SCM is a set of systems that manages the entire process from the production of a product to its delivery to the end user. Industry 4.0 aims to improve the production industry by increasing the quality, efficiency, and performance of the production process. Therefore, in this chapter, the authors highlight the challenges, benefits, and future trends of the combination of Industry 4.0 and SCM systems. Methodology: In this chapter, the integration of Industry 4.0 and SCM systems was investigated. For this purpose, the Industry 4.0 position of the countries and the current status of SCM systems have been examined. In addition, the key technologies in the Industry 4.0 transformation, the possible problems encountered in the transformation, the deficiencies encountered in SCM systems, and how these deficiencies can be solved with Industry 4.0 were investigated. Findings: The results of this study show that companies that use an SCM system can separate themselves from their competitors by using Industry 4.0 technologies. Significance: This can allow them to achieve their strategic goals and to ensure the maintenance of their competitive advantage.
Electric power systems are experiencing an unprecedented technological revolution that poses operational and commercial challenges for today's electric power industry. In this context, low voltage DC microgrid technology is attracting growing interest regarding its energy efficiency and local reliability. These microgrids support the innovation and implementation of new local electricity markets such as the emergent peer-to-peer energy trading paradigm which is perceived as a promising solution for tomorrow's power grid. Although, several pilot projects are under test, research is mainly concerned with the development of hardware and software infrastructure and the design of new business models. This paper deals with the prospects for synergies between low-voltage DC microgrid technology and P2P energy trading markets. After focusing on the fundamentals and the links between both concepts, the paper surveys the most innovative peer-to-peer electricity trading projects. A multi-aspect SWOT (strengths, weaknesses, opportunities and threats) analysis approach is conducted. Finally, the environmental impact is evaluated in a vision of sustainable and collaborative energy governance.
Досліджено умови забезпечення інноваційного розвитку енергетичної сфери на засадах формалізації відповідного механізму в умовах Індустрії 4.0. Визначено специфічні особливості розвитку енергетики, що впливають на теоретико-прикладні аспекти функціонування механізму інноваційного розвитку національної економіки. Визначено базові функції механізму, реалізація яких необхідна для досягнення ідентифікованих цілей. Розкрито та досліджено структурні компоненти механізму інноваційного розвитку національної економіки в енергетичній сфері. Обгрунтовано науково-методологічний підхід до формування механізму інноваційного розвитку енергетичної сфери в системі соціально-економічних трансформацій в умовах Індустрії 4.0 на засадах агрегації таких структурних елементів цього механізму, як конструкторсько-проєктний апарат, техніко-технологічний блок, ресурсно-функціональна підсистема та організаційно-управлінський інструментарій, синергічна взаємодія яких забезпечує зростання конкурентоспроможності національної економіки, оптимізацію галузево-секторальної структури останньої, зміцнення економічної безпеки держави, посилення соціальної відповідальності бізнесу, покращення рівня якості життя населення та підвищення соціальної справедливості в суспільстві.
This paper conducts strategic analysis and development plan design of energy digital transformation from a global perspective. First, this paper analyzes the reasons for the digital transformation of the energy industry, and elaborates on the current status of the digital transformation of the energy industry. Second, this paper uses the “SWOT” model to conduct a strategic analysis of the digital transformation of energy. Finally, this paper uses the “IETB” model to design the development plan. The results showed that: (1) Energy digital transformation is an effective approach to optimize the energy allocation and improve the energy scheduling. (2) The biggest barriers and uncertainties are mainly from the current weaknesses and the future threats. (3) The joint action of factors from Institution, Economy, Technology as well as Behavior achieves an effective scheme to promote the digital transformation of energy.
HIGHLIGHTS
• Reasons for the digital transformation of energy.
• The development status of the digital transformation is outlined.
• Using the “SWOT” model to conduct a strategic analysis of the digital transformation of energy.
• Using the “IETB” model to design the development plan.
The United Nations established 17 Sustainable Development Goals (SDGs), and the fulfillment of the 7th, defined as “Ensure access to affordable, reliable, sustainable, and modern energy for all”, requires energy industry transitions and digital transformations, which implies that diverse stakeholders need to move fast to allow the growth of more flexible power systems. This paper contains the case report that addresses the commercial digital transformation process developed at AES Colombia, through the implementation of a modern platform based on specialized applications that use Industry 4.0 tools. The Chivor hydropower project, a 1000-MW powerplant that covers 6% of Colombia’s demand, which is owned by AES Colombia and constitutes its primary asset, is first described. Then, a description of Colombia’s complex market (energy matrix, trading and dispatch mechanisms, and future projects) is presented. Then, the methodology followed for the digital transformation process using modern tools is described. The project, conceived as a broad framework, comprises applications for the management of hydrological, operational, and market information, commercial information systems and platforms to facilitate consultation and analysis by different users. Such an innovative project in the Latin American context has been developed in order reduce risks and to contribute to a sustainable energy supply for the future.
The European Union implemented Ecodesign and Labelling Directives to support the market diffusion of energy efficient products. Accurate signals for consumers on energy efficiency (EE) are essential, as disinformation might lead to sub-optimal market allocations. Considering complex devices such as heat pumps (HPs), a conflict between simplicity of calculation on the one hand and accuracy on the other hand arises. For this reason, main differences on EE between real working conditions and test procedures carried out according to regulations are examined within this study: Firstly, the most important deviations between the test procedure and the current state of the art are presented. Secondly, their influence on the validity of HP labels is investigated using spreadsheet calculations and a MODELICA simulation model. The results indicate that the omission of important influence factors – such as local conditions and the applied control strategy – in the regulations leads to significant differences between reality and labelling. The band of uncertainty found within this study covers high deviations of + 80% to − 24% from the label value. Therefore, we provide several recommendations to mitigate these deviations and to optimize the information content of the label. Among these are the implementation of a higher spatial resolution of climate conditions, the consideration of higher insulation standards, and the inclusion of effects caused by price-driven controls of the HP unit.
This paper analyses some possible means by which renewable power could be integrated into the steel manufacturing process, with techniques such as blast furnace gas recirculation (BF-GR), furnaces that utilize carbon capture, a higher share of electrical arc furnaces (EAFs) and the use of direct reduced iron with hydrogen as reduction agent (H-DR). It is demonstrated that these processes could lead to less dependence on—and ultimately complete independence from—coal. This opens the possibility of providing the steel industry with power and heat by coupling to renewable power generation (sector coupling). In this context, it is shown using the example of Germany that with these technologies, reductions of 47–95% of CO 2 emissions against 1990 levels and 27–95% of primary energy demand against 2008 can be achieved through the integration of 12–274 TWh of renewable electrical power into the steel industry. Thereby, a substantial contribution to reducing CO 2 emissions and fuel demand could be made (although it would fall short of realizing the German government's target of a 50% reduction in power consumption by 2050).
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Im vorliegenden Beitrag werden Überlegungen und erste Forschungsergebnisse zu den Konsequenzen für Arbeit und Qualifikation bei Industrie 4.0 zusammengefasst. Konzeptionell wird dabei Industrie 4.0 als sozio-technisches System begriffen. Davon ausgehend wird im Hinblick auf die Entwicklung von Arbeit zwischen zwei Perspektiven unterschieden, die als „Upgrading“ und als „Polarisierung“ von Qualifikationen gefasst werden. Welche konkreten Veränderungen sich tatsächlich ergeben, ist allerdings besonders von dem realisierten Automatisierungskonzept und der tatsächlichen Reichweite der Systemverbreitung abhängig. Abschließend wird verdeutlicht, dass allenfalls von einer mittelfristig begrenzten Verbreitung von Industrie-4.0-Systemen ausgegangen werden kann.
Demand response, defined as the shifting of electricity demand, is generally believed to have value both for the grid and for the market: by matching demand more closely to supply, consumers could profit from lower prices, while in a smart grid environment, more renewable electricity can be used and less grid capacity may be needed. However, the introduction of residential demand response programmes to support the development of smart grids that includes renewable generation is hampered by a number of barriers. This paper reviews these barriers and categorises them for different demand programmes and market players. The case study for the Netherlands shows that barriers can be country specific. Two types of demand response programmes have been identified as being the most promising options for households in smart grids: price-based demand response and direct load control, while they may not be beneficial for market players or distribution system operators. © 2016 The Authors. International Journal of Energy Research Published by John Wiley & Sons Ltd.
This article examines five common misunderstandings about case-study research: (1) Theoretical knowledge is more valuable than practical knowledge; (2) One cannot generalize from a single case, therefore the single case study cannot contribute to scientific development; (3) The case study is most useful for generating hypotheses, while other methods are more suitable for hypotheses testing and theory building; (4) The case study contains a bias toward verification; and (5) It is often difficult to summarize specific case studies. The article explains and corrects these misunderstandings one by one and concludes with the Kuhnian insight that a scientific discipline without a large number of thoroughly executed case studies is a discipline without systematic production of exemplars, and that a discipline without exemplars is an ineffective one. Social science may be strengthened by the execution of more good case studies.
The current globalization is faced by the challenge to meet the continuously growing worldwide demand for capital and consumer goods by simultaneously ensuring a sustainable evolvement of human existence in its social, environmental and economic dimensions. In order to cope with this challenge, industrial value creation must be geared towards sustainability. Currently, the industrial value creation in the early industrialized countries is shaped by the development towards the fourth stage of industrialization, the so-called Industry 4.0. This development provides immense opportunities for the realization of sustainable manufacturing. This paper will present a state of the art review of Industry 4.0 based on recent developments in research and practice. Subsequently, an overview of different opportunities for sustainable manufacturing in Industry 4.0 will be presented. A use case for the retrofitting of manufacturing equipment as a specific opportunity for sustainable manufacturing in Industry 4.0 will be exemplarily outlined.
The methods literature regarding sampling in qualitative research is characterized by important inconsistencies and ambiguities, which can be problematic for students and researchers seeking a clear and coherent understanding. In this article we present insights about sampling in qualitative research derived from a systematic methods overview we conducted of the literature from three research traditions: grounded theory, phenomenology, and case study. We identified and selected influential methods literature from each tradition using a purposeful and transparent procedure, abstracted textual data using structured abstraction forms, and used a multistep approach for deriving conclusions from the data. We organize the findings from this review into eight topic sections corresponding to the major domains of sampling identified in the review process: definitions of sampling, usage of the term sampling strategy, purposeful sampling, theoretical sampling, sampling units, saturation, sample size, and the timing of sampling decisions. Within each section we summarize how the topic is characterized in the corresponding literature, present our comparative analysis of important differences among research traditions, and offer analytic comments on the findings for that topic. We identify several specific issues with the available guidance on certain topics, representing opportunities for future methods authors to improve our collective understanding.
The real and the virtual worlds are growing speedily and closely to form the Internet of Things (IoT). In fact, IoT has stimulated the factories and the governments to launch an evolutionary journey toward the fourth industrial revolution called Industry 4.0. Industrial production of the new era will be highly flexible in production volume and customization, extensive integration between customers, companies, and suppliers, and above all sustainable. Reviewing and analyzing the current initiatives and related studies of the smart factories/Industry 4.0, this paper presents a reference architecture for IoT-based smart factories, defines the main characteristics of such factories with a focus on the sustainability perspectives. And then it proposes an approach for energy management in smart factories based on the IoT paradigm: a guideline and expected benefits are discussed and presented.
Recent advances in manufacturing industry has paved way for a systematical deployment of Cyber-Physical Systems (CPS), within which information from all related perspectives is closely monitored and synchronized between the physical factory floor and the cyber computational space. Moreover, by utilizing advanced information analytics, networked machines will be able to perform more efficiently, collaboratively and resiliently. Such trend is transforming manufacturing industry to the next generation, namely Industry 4.0. At this early development phase, there is an urgent need for a clear definition of CPS. In this paper, a unified 5-level architecture is proposed as a guideline for implementation of CPS.
This paper reviews and analyzes the challenges of energy transition governance towards a low-carbon society as a political achievement. The main research question is how specific “transition governance approaches” (as advocated by transition theory) can be embedded/anchored in the policy-making logics and practices. We analyze three country cases, known for their path-breaking efforts in the area: Germany (due to its pioneering role in the development and diffusion of renewable energy technologies), the Netherlands (due to its pioneering role in launching the transition management framework), and the United Kingdom (due to its pioneering role in adopting a long-term legislative commitment to a low-carbon future). The paper identifies best governance practices and remaining challenges in the following areas: (i) connecting long-term visions with short- and mid-term action; (ii) innovation (technological as well as social); (iii) integration (of multiple objectives and policy areas and levels); (iv) societal engagement; and (v) learning/reflexivity.
One of the key issues in adopting a sustainable and renewable energy system is gaining social acceptance for technological change. Many technological changes can adversely affect residents and lead to opposition. Extensive development of electricity infrastructure has been met with especially strong resistance from local stakeholders. An abundance of research has been conducted to study the process and driving factors of social acceptance in the context of these infrastructural developments. This paper develops a conceptual definition of social acceptance that is both explicit and allows for quantitative assessment. This definition will aid future literature by clearly defining the goal of social acceptance research from the outset. As examples of the problems faced in electricity system change, factors of discontent surrounding the social acceptance of wind farms, transmission lines, and pump hydro-storage facilities are identified and synthesized. Policy relevant conclusions from previous research are summarized for these three infrastructure types. It is concluded that while research has done well in understanding the causes of opposition, more work is needed to grasp the efficacy and implementation of acceptance improving strategies. Future research should be focused on devising procedures to facilitate quick and efficient negotiations between infrastructure developers and local groups.
This article examines five common misunderstandings about case-study research: (a) theoretical knowledge is more valuable than practical knowledge; (b) one cannot generalize from a single case, therefore, the single-case study cannot contribute to scientific development; (c) the case study is most useful for generating hypotheses, whereas other methods are more suitable for hypotheses testing and theory building; (d) the case study contains a bias toward verification; and (e) it is often difficult to summarize specific case studies. This article explains and corrects these misunderstandings one by one and concludes with the Kuhnian insight that a scientific discipline without a large number of thoroughly executed case studies is a discipline without systematic production of exemplars, and a discipline without exemplars is an ineffective one. Social science may be strengthened by the execution of a greater number of good case studies.
For 100 years, there has been no change in the basic structure of the electrical power grid. Experiences have shown that the hierarchical, centrally controlled grid of the 20th Century is ill-suited to the needs of the 21st Century. To address the challenges of the existing power grid, the new concept of smart grid has emerged. The smart grid can be considered as a modern electric power grid infrastructure for enhanced efficiency and reliability through automated control, high-power converters, modern communications infrastructure, sensing and metering technologies, and modern energy management techniques based on the optimization of demand, energy and network availability, and so on. While current power systems are based on a solid information and communication infrastructure, the new smart grid needs a different and much more complex one, as its dimension is much larger. This paper addresses critical issues on smart grid technologies primarily in terms of information and communication technology (ICT) issues and opportunities. The main objective of this paper is to provide a contemporary look at the current state of the art in smart grid communications as well as to discuss the still-open research issues in this field. It is expected that this paper will provide a better understanding of the technologies, potential advantages and research challenges of the smart grid and provoke interest among the research community to further explore this promising research area.
This article examines five common misunderstandings about case-study research: (a) theoretical knowledge is more valuable than practical knowledge; (b) one cannot generalize from a single case, therefore, the single-case study cannot contribute to scientific development; (c) the case study is most useful for generating hypotheses, whereas other methods are more suitable for hypotheses testing and theory building; (d) the case study contains a bias toward verification; and (e) it is often difficult to summarize specific case studies. This article explains and corrects these misunderstandings one by one and concludes with the Kuhnian insight that a scientific discipline without a large number of thoroughly executed case studies is a discipline without systematic production of exemplars, and a discipline without exemplars is an ineffective one. Social science may be strengthened by the execution of a greater number of good case studies.
In an interview, what you already know is as important as what you want to know. What you want to know determines which questions you will ask. What you already know will determine how you ask them.
A number of issues can affect sample size in qualitative research; however, the guiding principle should be the concept of saturation. This has been explored in detail by a number of authors but is still hotly debated, and some say little understood. A sample of PhD studies using qualitative approaches, and qualitative interviews as the method of data collection was taken from theses.com and contents analysed for their sample sizes. Five hundred and sixty studies were identified that fitted the inclusion criteria. Results showed that the mean sample size was 31; however, the distribution was non-random, with a statistically significant proportion of studies, presenting sample sizes that were multiples of ten. These results are discussed in relation to saturation. They suggest a pre-meditated approach that is not wholly congruent with the principles of qualitative research.
URN: urn:nbn:de:0114-fqs100387
This book discusses the transformation of firms into platforms-companies providing software and hardware products to others-that has occurred in many economic sectors. This massive transformation resulted from switching capitalism into data, considering them as a source for economic growth and resilience. Changes in digital technologies contributed much to the relationships between companies and their workers, clients, and other capitalists, who increasingly began to rely on data. Dr. Nick Srnicek critically reviews "platform capitalism", putting new forms of the business model into the context of economic history, tracing their evolution from the long downturn of the 1970s to the economic boom of the 1990s and to the consequences of the 2008 financial crisis. The author demonstrates that the global economy was re-divided among a few of the monopolistic platforms and shows how these platforms set up new internal trends for the development of capitalism. © 2019 National Research University Higher School of Economics. All Rights Reserved.
In the context of China's “Internet Plus” era, the application of big data and energy storage technology etc. plays an important role in controlling the renewables of randomness and intermittence during the generation. This paper focuses on the development of China's Energy Storage Industry, summarizes the industrial situation and policy environment, analyses China's Energy Storage Industry by the PEST‐SWOT framework, and discusses the development trends and three cases under the “Internet Plus” initiative. At last, several recommendations are offered from energy storage system, development solutions, market design and international cooperation, aiming to cope with the issues concerning the development of China's Energy Storage Industry and future challenges. It is expected that such recommendations can be a boost to China's energy storage industry in the future.
The transformation of the electricity sector towards a sustainable energy supply and use has a disruptive potential for infrastructure and utilities. The spread of digital technologies, renewable energy, and prosumers requires a swift and well-guided adaptation of the electricity distribution industry to smart grid technologies and related business models. This paper, based on the large technical systems (LTS) conceptual framework, investigates the complex evolution and company and market design adaptation needs. Challenges and opportunities are analyzed through nine multi-stakeholder workshops, held in two EU member states (Germany and Portugal) in 2016–2017, engaging distribution system operators, researchers, academics, and integrated utility companies. The results indicate considerable uncertainty for distribution system operators regarding the value of large-scale smart meter rollouts. Also, a corporate culture with resistance to change is observed, challenging the integration of novel technologies and processes. Traditional regulation is seen as a barrier to smart grid investments, and is associated with job losses and knowledge destruction. Policy-makers can benefit from these insights on the dynamics of DSOs, which can contribute to public policy design and market reform which traditionally has often been mainly concerned about operational efficiency in a steady-state, stable economy.
Timothy Kaufmann beschreibt verschiedene Geschäftsmodelle, Kundenbeispiele und geeignete Werkzeuge für die Umsetzung von Industrie 4.0 und dem Internet der Dinge, die schon heute große Chancen für neue Geschäftsmodelle und die Optimierung von bestehenden bieten. Das vorliegende Essential soll Sie ermutigen, sich jetzt auf den Weg zu begeben!
Der Inhalt
• Was ist Industrie 4.0?
• Welche Geschäftsmodelle lassen sich durch Industrie 4.0 gestalten?
• Wie finde ich das für mein Unternehmen richtige Modell?
• Wie bringe ich mein Unternehmen auf den Weg zur erfolgreichen Umsetzung?
• Welches sind realisierbare Nutzenpotentiale?
Die Zielgruppen
• Entscheider aus den Bereichen Entwicklung, Logistik, Produktion, Service und Strategie, Geschäftsführung und Interessierte für das Thema Geschäftsmodelle in Industrie 4.0 und dem Internet der Dinge.
Der Autor
Timothy Kaufmann beschäftigt sich als Unternehmensberater in einem europäischen IT-Unternehmen seit Jahren mit Geschäftsmodellen für den Anlagen- und Maschinenbau und die Fertigungs- und Automobilindustrie. Seit 2013 entwickelt er als Business Development Manager Industrie 4.0- und Internet der Dinge-Geschäftsmodelle für Kunden und ist auch an innovativen Geschäftsmodellen für das eigene Unternehmen beteiligt. Er ist Mitglied der AG2 der Plattform für Industrie 4.0.
The consumption of fossil fuel has resulted in global warming, environmental pollution, and many other crucial problems. Replacing fossil fuel with renewable energy has become an important issue over the recent decades. As a renewable clean energy, wind power is a relatively well-developed and promising energy method for current technology development in China. Under the background of growing demand for electricity and enhancing awareness for environmental, the “Internet+ wind power” concept has emerged based on both the wind power's characteristics that renewable and non-polluting, and the rapid development of the Internet in China. Through querying an amount of literature and information, this paper reveals the resource endowment and policy environment about wind power and energy Internet at first. Then, the PEST-SWOT strategy analysis model is used to analyze the internalities (strengths and weaknesses) and the externalities (opportunities and threats) of “Internet+ wind power”. According to these results, the paper puts forward some measures (development and utilization, business mode) for wind power accommodation. Then some policy recommendations have been proposed. The government should provide favorable conditions for wind power grid with the “Internet+” technology innovation.
Originally initiated in Germany, Industry 4.0, the fourth industrial revolution, has attracted much attention in recent literatures. It is closely related with the Internet of Things (IoT), Cyber Physical System (CPS), information and communications technology (ICT), Enterprise Architecture (EA), and Enterprise Integration (EI). Despite of the dynamic nature of the research on Industry 4.0, however, a systematic and extensive review of recent research on it is has been unavailable. Accordingly, this paper conducts a comprehensive review on Industry 4.0 and presents an overview of the content, scope, and findings of Industry 4.0 by examining the existing literatures in all of the databases within the Web of Science. Altogether, 88 papers related to Industry 4.0 are grouped into five research categories and reviewed. In addition, this paper outlines the critical issue of the interoperability of Industry 4.0, and proposes a conceptual framework of interoperability regarding Industry 4.0. Challenges and trends for future research on Industry 4.0 are discussed.
This book presents a domain of extreme industrial and scientific interest: the study of smart systems and structures. It presents polytope projects as comprehensive physical and cognitive architectures that support the investigation, fabrication and implementation of smart systems and structures. These systems feature multifunctional components that can perform sensing, control, and actuation.
In light of the fact that devices, tools, methodologies and organizations based on electronics and information technology for automation, specific to the third industrial revolution, are increasingly reaching their limits, it is essential that smart systems be implemented in industry. Polytope projects facilitate the utilization of smart systems and structures as key elements of the fourth industrial revolution.
The book begins by presenting polytope projects as a reference architecture for cyber-physical systems and smart systems, before addressing industrial process synthesis in Chapter 2. Flow-sheet trees, cyclic separations and smart configurations for multi-component separations are discussed here. In turn, Chapter 3 highlights periodic features for drug delivery systems and networks of chemical reactions, while Chapter 4 applies conditioned random walks to polymers and smart materials structures. Chapter 5 examines self-assembly and self-reconfiguration at different scales from molecular to micro systems. Smart devices and technologies are the focus of chapter 6. Modular micro reactor systems and timed automata are examined in selected case studies. Chapter 7 focuses on inferential engineering designs, concept-knowledge, relational concept analysis and model driven architecture, while Chapter 8 puts the spotlight on smart manufacturing, industry 4.0, reference architectures and models for new product development and testing. Lastly, Chapter 9 highlights the polytope projects methodology and the prospects for smart systems and structures.
Focusing on process engineering and mathematical modeling for the fourth industrial revolution, the book offers a unique resource for engineers, scientists and entrepreneurs working in chemical, biochemical, pharmaceutical, materials science or systems chemistry, students in various domains of production and engineering, and applied mathematicians.
The vision of the Digital Twin itself refers to a comprehensive physical and functional description of a component, product or system, which includes more or less all information which could be useful in all—the current and subsequent—lifecycle phases. In this chapter we focus on the simulation aspects of the Digital Twin. Today, modelling and simulation is a standard process in system development, e.g. to support design tasks or to validate system properties. During operation and for service first simulation-based solutions are realized for optimized operations and failure prediction. In this sense, simulation merges the physical and virtual world in all life cycle phases. Current practice already enables the users (designer, SW/HW developers, test engineers, operators, maintenance personnel, etc) to master the complexity of mechatronic systems.
The proliferation of cyber-physical systems introduces the fourth stage of industrialization, commonly known as Industry 4.0. The vertical integration of factory to implement flexible and reconfigurable manufacturing systems, i.e., smart factory, is one of the key features of Industry 4.0. In this paper, we present a smart factory framework that incorporates industrial network, cloud, and supervisory control terminals with smart shop-floor objects such as machines, conveyers, and products. Then, we give a classification of the smart objects into various types of agents and define a coordinator on cloud. The autonomous decision and distributed cooperation between agents lead the process achieving high flexibility. Moreover, this kind of self-organized system leverages on the feedback and coordination by the central coordinator in order to achieve high efficiency. Thus, the smart factory is characterized by the self-organized multi-agent system assisted with big data based feedback and coordination. Based on this model, we propose an intelligent negotiation mechanism for agents to cooperate with each other. Furthermore, the study illustrates that complementary strategies can be designed to prevent the deadlocks by improving the agents’ decision and the coordinator's behavior. The simulation results assess the effectiveness of the proposed negotiation mechanism and deadlock prevention strategies.
Load management (LM) is supposed to have a vital role in future energy management systems. This article presents overview and comparison of LM techniques along with related technologies and implementation challenges in smart grid. The article also covers consumer and utility concerns in context of LM to enhance readers' intuition about the topic. Two major categories of LM techniques, incentive based and dynamic pricing based schemes have been discussed and compared. Most commonly used incentive based direct load control (DLC) is elaborated in detail. Dynamic pricing based energy consumption scheduling (ECS) schemes, featuring peak load reduction and consumers' energy cost minimization at residential level, are also emphasized. Furthermore, the article incudes a description of dynamic pricing based home energy management and associated optimization techniques as well as comparison of the latest schemes.
Load management (LM) is supposed to have a vital role in future energy management
systems. This article presents overview and comparison of LM techniques along with related
technologies and implementation challenges in smart grid. The article also covers consumer
and utility concerns in context of LM to enhance readers’ intuition about the topic. Two major
categories of LM techniques, incentive based and dynamic pricing based schemes have
been discussed and compared. Most commonly used incentive based direct load control
(DLC) is elaborated in detail. Dynamic pricing based energy consumption scheduling (ECS)
schemes, featuring peak load reduction and consumers’ energy cost minimization at
residential level, are also emphasized. Furthermore, the article incudes a description of
dynamic pricing based home energy management and associated optimization techniques
as well as comparison of the latest schemes.
The paper reviews different approaches, technologies, and strategies to manage large-scale schemes of variable renewable electricity such as solar and wind power. We consider both supply and demand side measures. In addition to presenting energy system flexibility measures, their importance to renewable electricity is discussed. The flexibility measures available range from traditional ones such as grid extension or pumped hydro storage to more advanced strategies such as demand side management and demand side linked approaches, e.g. the use of electric vehicles for storing excess electricity, but also providing grid support services. Advanced batteries may offer new solutions in the future, though the high costs associated with batteries may restrict their use to smaller scale applications. Different “P2Y”-type of strategies, where P stands for surplus renewable power and Y for the energy form or energy service to which this excess in converted to, e.g. thermal energy, hydrogen, gas or mobility are receiving much attention as potential flexibility solutions, making use of the energy system as a whole. To “functionalize” or to assess the value of the various energy system flexibility measures, these need often be put into an electricity/energy market or utility service context. Summarizing, the outlook for managing large amounts of RE power in terms of options available seems to be promising.
This paper focuses on clean energy solutions in order to achieve better sustainability, and hence discusses opportunities and challenges from various dimensions, including social, economic, energetic and environmental aspects. It also evaluates the current and potential states and applications of possible clean-energy systems. In the first part of this study, renewable and nuclear energy sources are comparatively assessed and ranked based on their outputs. By ranking energy sources based on technical, economic, and environmental performance criteria, it is aimed to identify the improvement potential for each option considered. The results show that in power generation, nuclear has the highest (7.06/10) and solar photovoltaic (PV) has the lowest (2.30/10). When nonair pollution criteria, such as land use, water contamination, and waste issues are considered, the power generation ranking changes, and geothermal has the best (7.23/10) and biomass has the lowest performance (3.72/10). When heating and cooling modes are considered as useful outputs, geothermal and biomass have approximately the same technical, environmental, and cost performances (as 4.9/10), and solar has the lowest ranking (2/10). Among hydrogen production energy sources, nuclear gives the highest (6.5/10) and biomass provides the lowest (3.6/10) in ranking. In the second part of the present study, multigeneration systems are introduced, and their potential benefits are discussed along with the recent studies in the literature. It is shown that numerous advantages are offered by renewable energy-based integrated systems with multiple outputs, especially in reducing overall energy demand, system cost and emissions while significantly improving overall efficiencies and hence output generation rates. Copyright © 2015 John Wiley & Sons, Ltd.
Solving the energy and climate challenges ahead will require introducing massive amounts of clean energy such as renewable energy (RE) sources, in particular, in urban areas as these dominate the energy use and emissions. Variable RE sources such as solar and wind are interesting mainstream energy options in this context. However, their use may cause major problems with the power system calling for more advanced strategies to enable optimal integration and bridging of the new and old energy system. Here, we demonstrate the usefulness of electricity-to-thermal conversion and RE linked to e-mobility strategies to increase the RE share much beyond the traditional self-use limit of power. For example, the Metropolitan Helsinki (Finland) region could in this way derive up to 60% of its electricity and 30% of its heat from wind power, without any major energy storage arrangements. In sunny climates, the use of photovoltaics could be increased by a factor of 2–3 over the self-use limit of power through such strategies. Copyright © 2015 John Wiley & Sons, Ltd.
Deutschland hat im internationalen Vergleich eines der zuverlässigsten Elektrizitätssysteme. Jedoch befindet sich die Elektrizitätsversorgung in einer Transformation von fossiler zu regenerativer Erzeugung. Die Kosten der Versorgungssicherheit werden aufgrund zusätzlichen Bedarfs an Investitionen in Technologien wie Backup-Kraftwerke oder Speicher zukünftig ansteigen. Welches Sicherheitsniveau ist für die verschiedenen Kunden tatsächlich gesellschaftlich optimal? Die Antwort auf diese Frage hängt davon ab, welche Kosten Verbrauchern bei Stromunterbrechungen entstehen. Unter Umständen ist es sinnvoller, Verbraucher kurzfristig abzuschalten, anstatt diese für wenige Stunden mit teuren Kraftwerken und Speichern zu versorgen. Hierfür ist aber letztlich ein breiter gesellschaftlicher Konsens hinsichtlich der Präferenzen zwischen Versorgungssicherheit, Klimaschutz und Kernenergieausstieg notwendig. Aaron Praktiknjo befasst sich in dieser Monographie mit diesen Fragestellungen und liefert wertvolle methodische und empirische Hinweise.
How does a business firm manage its relationship with the natural environment? What are the factors that influence the choice of such strategies? Does industry type matter? The authors introduce and operationalize the concept of corporate environmentalism in an effort to answer these questions. Using stakeholder theory, the authors identify four important antecedents to corporate environmentalism, namely, public concern, regulatory forces, competitive advantage, and top management commitment. The authors then use a political - economic framework to develop testable hypotheses. To test the hypotheses, the authors perform multigroup path analysis on data gathered from more than 240 firms. They find that corporate environmentalism is related to all hypothesized antecedents and that industry type moderates several of those relationships. In the high environmental impact sector, public concern has the greatest impact on corporate environmentalism, followed by regulatory forces. In the moderate environmental impact sector, competitive advantage has the greatest impact on corporate environmentalism, followed by regulatory forces. There are strong direct and mediating influences from top management commitment, which is the antecedent with the greatest impact on both industry groups. The influences of regulatory forces, public concern, and competitive advantage are all significantly mediated by top management commitment and moderated by industry type. The empirical findings and the ensuing discussion will be of interest to managers and public policy officials.
Kurzbeschreibungnewline Viele sozialwissenschaftliche Untersuchungen beruhen auf Rekonstruktionen von Situationen oder Prozessen. Das Lehrbuch vermittelt anhand zweier Beispieluntersuchungen anwendungsbereites Wissen über alle Phasen solcher rekonstruierender Untersuchungen und stellt je eine Erhebungs- und eine Auswertungsmethode ausführlich dar. Die Interviewpartner werden als Experten aufgefasst, die über spezifisches Wissen über die zu rekonstruierenden Sachverhalte verfügen. Die qualitative Inhaltsanalyse ermöglicht eine systematische Extraktion relevanter Informationen aus den Interviews und ist zugleich offen für nicht erwartete Befunde. Mit Lernfragen nach jedem Kapitel und einer übersichtlichen Gliederung eignet sich das Buch als praxisorientierte Einführung. -- Dieser Text bezieht sich auf eine vergriffene oder nicht verfügbare Ausgabe dieses Titels.newline newline Umschlagtextnewline Viele sozialwissenschaftliche Untersuchungen beruhen auf Rekonstruktionen von Situationen oder Prozessen. Das Lehrbuch vermittelt anhand zweier Beispieluntersuchungen anwendungsbereites Wissen über alle Phasen solcher rekonstruierender Untersuchungen und stellt je eine Erhebungs- und eine Auswertungsmethode ausführlich dar. Die Interviewpartner werden als Experten aufgefasst, die über spezifisches Wissen über die zu rekonstruierenden Sachverhalte verfügen. Die qualitative Inhaltsanalyse ermöglicht eine systematische Extraktion relevanter Informationen aus den Interviews und ist zugleich offen für nicht erwartete Befunde. Mit Lernfragen nach jedem Kapitel und einer übersichtlichen Gliederung eignet sich das Buch als praxisorientierte Einführung.
[discusses] qualitative sampling strategies [in primary health care research] with a study designed to understand why particular doctors seem to attract particular patients (PsycINFO Database Record (c) 2012 APA, all rights reserved)
Industrialization and economic development have historically been associated with man's ability to harness natural energy resources to improve his condition. Based on this definition, two industrial revolutions occurred in the 18th and 19th centuries, where natural resources such as coal (first revolution) and petroleum (second revolution) were widely exploited to produce levels of energy far beyond what could be achieved by human or animal muscle power. Furthermore, modern power distribution systems made abundant energy reliably available and relatively independent from the plant location. More than two centuries of past industrialization exploited nonrenewable energy resources, however, often with undesirable side effects such as pollution and other damage to the natural environment. In the second half of the 20th century, extraction of energy from nuclear processes grew in popularity, relieving some demands on limited fossil fuel reserves, but at the same time, raising safety and political problems. Meeting the global demand for energy is now the key challenge to sustained industrialization.
The concept of energy security is widely used, yet there is no consensus on its precise interpretation. In this research, we have provided an overview of available indicators for long-term security of supply (SOS). We distinguished four dimensions of energy security that relate to the availability, accessibility, affordability and acceptability of energy and classified indicators for energy security according to this taxonomy. There is no one ideal indicator, as the notion of energy security is highly context dependent. Rather, applying multiple indicators leads to a broader understanding. Incorporating these indicators in model-based scenario analysis showed accelerated depletion of currently known fossil resources due to increasing global demand. Coupled with increasing spatial discrepancy between consumption and production, international trade in energy carriers is projected to have increased by 142% in 2050 compared to 2008. Oil production is projected to become increasingly concentrated in a few countries up to 2030, after which production from other regions diversifies the market. Under stringent climate policies, this diversification may not occur due to reduced demand for oil. Possible benefits of climate policy include increased fuel diversity and slower depletion of fossil resources.
Energy transitions to sustainability receive much interest in politics and science. Using a socio-technical and multi-level theory on transitions, this article draws important lessons from a long-term analysis of the Dutch electricity system. The article analyses technical developments, changes in rules and visions, and social networks that support and oppose renewable options. The article is multi-level because it looks at novel renewable energy technologies and structural trends in the existing electricity regime. The analysis shows that an energy transition, with roots in the 1960s and 1970s, is already occurring, but driven mainly by liberalisation and Europeanisation. Environmental aspects have become part of this ongoing transition, but do not form its main driver. Many barriers exist for a sustainability transition, but there are also some opportunities. A long-term analysis of renewable niche-innovation trajectories (wind, biomass, PV) provides lessons about socio-technical dynamics, problems and windows of opportunity.
Contrary to conventional wisdom, more efficient use of energy may actually through rebound effects lead to greater instead of less total consumption of energy—or at least to no diminution of energy consumption. If so, energy efficiency strategies may serve goals of raising economic growth and affluence, but as an environmental or energy policy strategy could backfire, leading to more resource use in absolute terms rather than less. This, in turn, could in the long run hamper economic growth, for instance if resource scarcity crowds out technical change. The hypothesis that rebound is greater than unity (‘backfire’) predicts the observed real-world correlation between rising energy consumption and rising efficiency of energy services, however difficult it may be to define a precise holistic metric for the latter. The opposing hypothesis, i.e. that rebound is less than unity and that energy efficiency increases therefore result in less energy consumption than before, requires on the other hand strong forces that do account for the empirically observed economic growth. This paper summarises some of the discussions around the rebound effect, puts it into perspective to economic growth, and provides some insights at the end that can guide future empirical research on the rebound topic.
While many corporations and Information Systems units recognize that environmental sustainability is an urgent problem to address, the IS academic community has been slow to acknowledge the problem and take action. We propose ways for the IS community to engage in the development of environmentally sustainable business practices. Specifially, as IS researchers, educators, journal editors, and association leaders, we need to demonstrate how the transformative power of IS can be leveraged to create an ecologically sustainable society. In this Issues and Opinions piece, we advocate a research agenda to establish a new subfield of energy informatics, which applies information systems thinking and skills to increase energy efficiency. We also articulate how IS scholars can incorporate environmental sustainability as an underlying foundation in their teaching, and how IS leaders can embrace environmentalsustainability in their core principles and foster changes that reduce the environmental impact of our community.
Industrial demand for energy is essentially a derived demand: the firm's demand for energy is an input is derived from demand for the firm's output. Inputs other than energy typically also enter the firm's production process. Since firms tend to choose that bundle of inputs which minimized the total cost of producing a giving level of output, the derived demand for inputs, including energy, depends on the level of output, the submitions possibilies among inputs allow by production technology, and the relative prices of all inputs.