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Reliability of Constructs Variable Item Factor Loading Cronbach's alpha Composite Reliability AVE

Reliability of Constructs Variable Item Factor Loading Cronbach's alpha Composite Reliability AVE

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The aim of this research was to explore the influence of supply chain integration (SCI) on commodity supply chain performance (SCP) with the mediating role of supply chain agility (SCA). The research methodology employed a correlational approach using structural equation modeling. 131 employees from active companies in the agricultural commodity su...

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... factor loadings above 0.60 is vital; otherwise, items should be revised or removed. This approach demonstrates the reliability and validity of the research constructs effectively (Table 1). ...

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... The microgrid including PV, FC and battery with power converter of DC to AC for meet load demand. The mathematical modeling of PV, FC and battery systems are extracted from references [31]- [35]. Also, in Fig.2. ...
Article
This paper studies the critical topic of optimal sizing of energy resources, focusing specifically on the configuration of storage system solutions within a microgrid framework. A microgrid is a localized energy system that can operate independently or in conjunction with the main power grid, and it is increasingly recognized for its potential to enhance energy resilience, efficiency, and sustainability. In this study, we examine a microgrid that integrates three key components: photovoltaic (PV) systems, battery storage, and fuel cell (FC) systems. Each of these technologies plays a vital role in the overall energy management strategy of the microgrid. In addition to installation costs, we also focus on minimizing net present costs (NPC), which encompass the total cost of ownership over the lifespan of the energy systems, including initial capital expenditures, operational and maintenance costs, and any potential revenue from energy sales or savings. By carefully analyzing the trade-offs between different system configurations, we seek to identify the most economically viable options. Another critical metric we consider is the loss of load expectation (LOLE), which quantifies the reliability of the energy supply. LOLE represents the expected number of hours per year during which the energy demand exceeds the available supply. By minimizing LOLE, we enhance the reliability and stability of the microgrid, ensuring that it can meet the energy needs of its users even during periods of high demand or low generation. Through a comprehensive analysis of these factors, this paper aims to provide valuable insights into the optimal sizing of energy resources within microgrids. By leveraging advanced modeling techniques and optimization algorithms, we seek to identify configurations that not only reduce costs but also enhance the overall performance and reliability of hybrid energy systems. Ultimately, our findings will contribute to the ongoing efforts to develop sustainable and resilient energy solutions that can meet the challenges of a rapidly changing energy landscape. The teaching-learning-based optimization (TLBO) metaheuristic algorithm is employed for configuring microgrids. Results from the algorithm demonstrate that TLBO offers a more effective resource configuration than alternative approaches.
... With the ability to detect and respond to outages or fluctuations in demand almost instantaneously, utilities can implement corrective measures swiftly, ensuring a more stable electricity supply [10]. This responsiveness is particularly crucial in the face of increasing energy demands and the growing prevalence of extreme weather events that can disrupt traditional power systems [11]. Consumers also benefit from the intelligent grid through improved Demand Response Programs (DRPs). ...
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The smart electrical grid represents a significant advancement in generating, distributing, and consuming electricity. This sophisticated system integrates modern technology and communication tools to enhance energy management efficiency and improve demand costuming within the power network. In this paper, optimal operation of the electrical network with energy management and Demand Response Program (DRP) is implemented. The implementation of the optimal operation is done via multi-stage and multi-objective functions modeling. The DRP modeling is done in first stage to optimal management of consumption in demand side. In second stage, operating cost, emission, power losses and voltage profile are optimized as multi-objective functions modeling with attention to optimal management of consumption in demand side. The solving optimal operation of the electrical network is carried out by using Elephant Herding Optimization (EHO). This problem is implemented on 33-bus test system with hybrid energy resources. Finally, DRP leads to reducing costs, emissions and losses and improving voltage profile in proposed electrical network. Hence, operation costs, emission, power losses, and voltage deviation with the participation of DRP are minimized by 39.15%, 9.94%, 33.35%, and 30.73%, respectively. On the other side, voltage stability is enhanced by 3.66% without considering DRP.
... Rising sea levels, a direct consequence of melting polar ice caps and thermal expansion of seawater, pose an existential threat to coastal communities around the world. As these areas become increasingly vulnerable to flooding and erosion, the displacement of populations and loss of livelihoods will create additional social and economic challenges [34]- [38]. The harm to ecosystems, including coral reefs and mangroves, further diminishes the natural barriers that protect coastlines and support marine biodiversity [39] [40]. ...
Article
This study is dedicated to exploring the optimal sizing and strategic placement of hybrid energy systems specifically tailored for the electronics laboratory at Manipur International University in India. The primary objective is to effectively integrate photovoltaic systems alongside energy storage solutions, ensuring that both economic and technical goals are met. These goals encompass minimizing the total net present cost, reducing the levelized cost of electricity, and decreasing the probability of power supply loss, which are critical factors in the design and implementation of sustainable energy systems. To achieve these objectives, the design and sizing of the hybrid energy systems will be meticulously optimized. The study will consider various configurations, including combinations of photovoltaic-battery systems and photovoltaic-fuel cell setups. Each configuration will be evaluated for its efficiency and effectiveness in meeting the energy demands of the laboratory while adhering to the established economic and technical criteria. A key component of this research is the development of an energy management strategy grounded in energy balance principles. This strategy will guide the operation of the hybrid systems, ensuring that energy generation and consumption are harmonized to maximize efficiency and reliability. By implementing this strategy, the study aims to create a robust framework for managing energy resources effectively. To validate the proposed configurations and strategies, three practical case studies will be conducted. These case studies will utilize metaheuristic optimization techniques, which are advanced computational methods designed to solve complex optimization problems. Through numerical simulations, the study will identify the ideal sizing and configuration of hybrid energy sources, providing valuable insights into the practical application of these systems in the context of the laboratory.
... Service providers may be the public sector, the private sector, or a combination of both. And cooperation between them to provide resources and infrastructure is based on domestic and foreign activities [86]. An example of this collaboration that businesses and IoT project developers should consider is working with mobile operators and Internet service providers. ...
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Since the emergence of the IoT and its significant benefits, various economic, social, and political groups have been deploying and implementing IoT in different sectors. The large amounts of data generated from connected devices and products can be analysed, transforming the goals and attitudes of businesses and industries, including the banking industry. However, implementing IoT on a large scale in an industry as complex as banking is challenging. While the advantages and role of IoT in banking are clear and increasing with various studies, inadequate implementation of IoT can lead to potential risks and failures. This research aims to assess the banking industry's readiness for implementing IoT, specifically focusing on their IoT implementation readiness. The study identified the factors and aspects affecting the research topic using a systematic review method and classified its enablers into dimensions, components, indicators, and sub-indicators. After validating the initial model with experts, the final model revealed that 7 dimensions, 8 components, and 63 indicators influence the readiness of the banking industry to implement IoT. To rank the main aspects of the study, the Fuzzy SWARA method was used, and the results showed the following ranking: the dimensions of hard infrastructures, soft infrastructures, supply chain infrastructures, organizational factors, environmental factors, education and users, and security and privacy ranked first to seventh, respectively. The identified dimensions, components, and indicators provide a robust model for assessing the readiness of the banking industry for IoT implementation. The findings highlight the complexity involved in implementing IoT on a large scale within the banking sector.
... The battery is modelled as follows [30][31][32][33]: ...
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This research is dedicated to exploring and identifying the most effective design for an energy source tailored specifically to meet the electricity demands of a residential community. In an era where energy efficiency and sustainability are paramount, this study emphasizes the importance of technical and economic considerations in energy sourcing. It posits that any viable solution must not only be efficient in its energy production and consumption but also reliable in its delivery and financially feasible for the residents who will depend on it. To address this multifaceted challenge, the study proposes the innovative use of a rotation-invariant coordinate convolutional neural network in conjunction with binary battle royale optimization techniques. These advanced methodologies are selected for their potential to enhance the modelling and optimization processes involved in energy source design. The primary goal of employing these methods is to minimize two critical factors: the net present cost of the energy system and the overall energy cost incurred by the residents. By focusing on these objectives, the research aims to ensure that the proposed energy solutions are not only cost-effective but also sustainable over the long term. To rigorously test the proposed model and evaluate its performance, the research is conducted using the MATLAB platform. The study employs established methodologies and performance metrics to assess the outcomes of the model, ensuring that the findings are both credible and applicable to real-world scenarios. Through comprehensive testing and detailed analysis, this research aims to provide significant insights and actionable recommendations for the optimal design of energy sources in residential areas. By contributing to the ongoing discourse on sustainable energy solutions, the study seeks to inform policymakers, energy planners, and community stakeholders about effective strategies for meeting residential energy demands while promoting environmental sustainability. Ultimately, the findings of this research could play a crucial role in shaping the future of energy sourcing in residential communities, paving the way for more resilient and sustainable energy systems.
... The rapid evolution of the Internet of Things (IoT) and its application in industrial settings, known as the Industrial Internet of Things (IIoT), has attracted significant scholarly attention in recent years. In various fields such as supply chain management [28,29], banking and financial markets [30][31][32][33], urban management [34], and educational administration [35], leveraging digital technologies like the Internet of Things (IoT) and artificial intelligence (AI) is increasingly essential for enhancing productivity and improving competitiveness. ...
... They identified and assessed 14 drivers from an extensive literature review, with results indicating that "Efficient logistics systems," "Business knowledge acumen," and "Information safety assurance" are the top three critical factors. Kumar et al. [28] conducted a study to analyze and prioritize various enablers for the adoption of blockchain-IoT in managing logistics and supply chains. To facilitate this examination, the researchers employed the Diffusion of Innovation and the Technology-Organization-Environment theories as a framework for identifying adoption enablers. ...
... Linguistic scale [28] Triangular fuzzy number Linguistic term (1, 1, 3) Very low (VL) (1, 3, 5) Low (L) (3, 5, 7) Medium (M) (5,7,9) High (H) (7,9,9) Very high (VH) ...
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The Internet of Things (IoT) technology has emerged as a vital driver across various fields, engaging businesses, platforms, and industries. IoT involves a holistic ecosystem and a value chain that necessitates the evaluation of impactful dimensions for successful implementation. This research employs the TISM method to identify driver and dependent criteria regarding IoT implementation readiness and uses the fuzzy TOPSIS method to rank these criteria. In the initial step, 15 criteria were identified through a review of previous studies. The TISM results reveal five levels reflecting the driver power and dependence of the criteria. Based on these results, “Implementation Knowledge and Expertise (C2)”, “Technical and Infrastructural Readiness (C9)” and “Financial and Investment Readiness (C12)” were placed at level 5, marking them as the most driver criteria. Additionally, “Implementation Roadmap (C8)” was identified as the most dependent criterion at level one. According to the fuzzy TOPSIS results, “Senior Management Support (C6)”, “IoT Usage Culture (C1)”, “Business Model Development Capability (C15)”, “Financial and Investment Readiness (C12)” and “Technical and Infrastructural Readiness (C9)” ranked first to fifth, respectively. The combined results provide valuable insights for decision-makers and stakeholders involved in IoT implementation. By determining driver and dependent levels and ranking the criteria, industries can effectively prepare for the successful implementation of IoT.
... Extensive research has addressed users' water consumption behavior in the world (e.g., [32,124,22,25,106,107,114]) and in Iran (e.g., [118,125]). Most of these studies have either dealt with conservation behaviors in water consumption from a logical and economic perspective, avoiding the inclusion of ethical and value variables in their studied behavior models or restricted themselves to merely including the variable of moral norms by mainly focusing on psychological variables in predicting water use behavior (e.g., [97,117,119]). ...
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To achieve sustainable development goals at the societal level, it is necessary to protect the existing water resources. The development of theories on environmental ethics, in general, and water ethics, in particular, has emphasized the normative nature of water conservation behaviors in recent decades. In this regard, various behavioral analysis models have so far been developed by including value variables of development based on descriptive and prescriptive ethical views. This research analyzed Iranian farmers’ conservation behavior in the use of water resources using the theory of planned behavior (TPB) extended by including moral norms and perceived ethical principles proposed by UNDP. This survey was conducted among farmers in the Sistan Region, for which 361 farmers were sampled by multi-stage clustering randomization. The results showed that the variable of moral norms (the feeling of internal commitment) could greatly contribute to developing water conservation attitudes among farmers. Perceived prescriptive principles and values of water ethics can also reinforce behavioral intention and develop conservation attitudes among farmers. Our results show that the use of water ethics views in managing and conserving water resources can help extend water conservation behaviors in the current water crisis and prolonged drought conditions. Pluralistic policymaking and planning for the management of water resources, considering the significance of water ethics, along with other technical and economic dimensions, can help the sustainable conservation of water for future generations.
... The programme also accounts for the fact that solar and wind power curtailment is unpredictable. A coordinated decision-making technique was used in the research [23], which included making lower-level investment decisions with operational uncertainty using a twoobjective stochastic programming formulation. Considering demand responses and daily optimal operation, the proposed model is solved on a three-bus grid that incorporates smart microgrids with Distributed Energy Resources (DERs) on each bus. ...
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Following the publication of the Retraction Notice, the article was formally retracted on 29 January 2025. The Publisher and Editors in Chief received an allegation of plagiarism for this article published recently in STET. The investigation into this allegation has confirmed a very high rate of similarity with an article currently under peer review in the journal Electrical Engineering consistent with the alleged plagiarism, and the anteriority of the submission in Electrical Engineering. Every submitted manuscript to STET is compared to published papers in order to detect similarities. However, in the present case the paper in question was still under evaluation. The authors of the article published in STET have not provided convincing answers concerning their contribution to the work and have not provided an explanation for the excessive similarity. The Publisher and Editors have concluded to the truth of the allegation and have decided to retract this article.
... This technology allows for the dynamic adjustment of electricity prices based on demand, encouraging consumers to shift their usage to off-peak times [19][20][21][22]. Additionally, smart grid systems can automatically manage loads by temporarily reducing power to non-essential devices during peak demand periods, thereby preventing grid overload and enhancing overall system stability [23][24][25][26][27][28]. ...
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This study proposes day-ahead power scheduling for electrical systems in off-grid mode, emphasizing consumer involvement. Bi-Demand Side Management (DSM) approaches like strategic conversion and demand shifting are proposed for consumer involvement. Multiple objectives are modelled to voltage profile improvement and reduce the operation energy cost. The non-dominated solutions of the voltage of buses and operation energy cost are generated by enhanced epsilon-constraint technique, simultaneously. The General Algebraic Modeling System (GAMS) software is proposed for solving optimization problems. A combination of decision-making methods like weight sum and fuzzy procedures are implemented for finding optimal solution non-dominated solutions. The proposed method’s effectiveness is confirmed through numerical simulations carried out on several case studies that utilize the 33-bus electrical system. The findings illustrate the substantial effectiveness of demand-side participation in improving power dispatch and the optimal rate of multiple objectives. By using DSM, operation cost is reduced by 21.58% and the voltage index is improved by 13.36% than the lack of implementing DSM.
... Concerns over fossil fuel usage and technical indices have grown in recent years. Their usage is not logical because of their low efficiency, shortage of fossil fuels, and environmental impacts [10]. As the globe strives to create a clean environment, the use of renewable energy resources has increased dramatically. ...
... The limit of the unmet demand is modeled by (10), and status of the unmet demand is given by (11). u UM is a binary variable that represents status of unmet demand by generation side. ...
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Renewable energy sources (RESs) have had undeniable advantages over the recent years not only to supply electrical demand but also hydrogen storage system. However, maximum use of the RES’s power has always been challenging as high penetration of the RESs as well as their intermittent nature might compromise the distribution network’s power flow constraints. In line with this challenge, this work advances the state-of-the-art in the flexibility of the distribution network to leverage RESs by employing electrical storages. This study presents technical and economic operation of the independent electrical system considering power-to-gas (PtG) technology. The PtG technology has an energy storage role as apply gas stored to reserve generators for supply demand at critical status. The main technical and economic objectives are taken into account as minimizing the fuel’s costs of the generators as economic index and maximizing the system reliability index as technical index. The particle swarm optimization algorithm (PSOA) is utilized to obtain the optimal level of the objectives. Finally, several approaches verify the effectiveness of the proposed model and method with PtG storage technology. The operation of the PtG technology leads to an improved reliability index of 4% and minimized fuel costs by 8.74% than lack of participation.