No full-text available
To read the full-text of this research,
you can request a copy directly from the authors.
Autonomous cooperative energy trading between prosumers for microgrid systems
Abstract
A method of autonomous cooperative energy trading is proposed for prosumers in microgrid systems with renewable energy generation, storage and prosumer-to-prosumer energy exchange. The trading is based on policies and protocols for sharing and matching of energy schedules, including repayment of energy. Prosumer to Prosumer (P2P) trading mode and Proxy trading mode are described. Simulation results show that the proposed energy trading can increase the utilization of renewable energy, and reduce costs of energy purchase and energy storage.
... Zhang et al. (2014) developed an algorithm for demand-side management based on social welfare maximization and using a dynamic game. 28 see Luo et al. (2014), Ghosh et al. (2018) Figure 1: Context and overall framework, where the acronym BDM refers to Bertolini et al. (2018), CMMV to the model presented in Chapter 2 and CDMV to the one of Chapter 3. ...
... In this respect, the continuous integration of Distributed Energy Resources (DERs, hereafter), (Sousa et al. (2019); Bussar et al. (2016); Zhang et al. (2018)), 5 along with the advance in Information and Communication Technology (ICT) devices (Saad al sumaiti et al., 2014), are inducing a transformation of a share of electricity consumers who produce and consume and share energy with other grid users. Such users are called "prosumers" (Luo et al. (2014); Sommerfeldt and Madani (2017); Espe et al. (2018); Zafar et al. (2018)). ...
... These two characteristics (self-consumption and possible return energy exchange with national grid) can add flexibility that, in turn, increases the value of the investment (Bertolini et al., 2018). A third important characteristic, that depends on the development of new technologies and digitalization, is the possibility to exchange energy also between agents (InterregEU (2018); Luo et al. (2014); Alam et al. (2017); Zafar et al. (2018); Zhang et al. (2018)), in a Peer-to-Peer (P2P, hereafter) energy trading or in developing energy communities (Sousa et al., 2019). ...
The purpose of this thesis is to investigate some key features of the Smart Grids topic, focusing on the agents' (i.e. prosumers) investment decisions in the photovoltaic technology, in a context characterized by uncertainty and where the investment decision is undertaken cooperatively. The effect of allowing prosumers to exchange of energy with each other (exchange P2P, hereafter) is analyzed with a special emphasis on the demand and supply matching in exchange P2P as well as the conditions assuring its economic optimality. Discussion related to Renewable Energy Communities (REC) is provided with the aim to understand how the findings of our models, can boost their diffusion.
... Prosumers are not going to bid, decide the prices, and change their energy usage pattern every hour. For the small quantity of energy sharing among the prosumers, the strategies are studied in [13][14][15][16][17][18][19]. The approaches for the sharing of energy are compared in Table 1. ...
... The load profiles and PV power generation of each prosumer is shown in Figs. 4 and 5. The adjacent prosumers storage capacity are as follows (i) prosumer 1, 2, 3, 4, 5 and 6 the adjacent storage capacity are (10,10,20,15,5), (10,20,15,5,10), (20,15,5,10,10), (15,5,10,10,10), (5,10,10,10,20), and (10,10,10,20,15) in kWh, respectively [21]. ...
... The load profiles and PV power generation of each prosumer is shown in Figs. 4 and 5. The adjacent prosumers storage capacity are as follows (i) prosumer 1, 2, 3, 4, 5 and 6 the adjacent storage capacity are (10,10,20,15,5), (10,20,15,5,10), (20,15,5,10,10), (15,5,10,10,10), (5,10,10,10,20), and (10,10,10,20,15) in kWh, respectively [21]. ...
These days electrical grid makes use of information and communication technology. Information technology is primarily used for providing intelligence in the electrical grid. Solution presented in this article is a step further in this direction. All the prosumers have photovoltaic cells and energy storage batteries. The cyber-physical energy infrastructure solves many contentious issues of traditional electrical grid. This research article addresses the issues related to energy sharing among prosumers of a microgrid. The issues are namely, (i) intermittent nature of renewable energy resources, (ii) energy loss due to physical central storage, and (iii) charging/discharging scheme of the central storage in the presence of real-time pricing. The concept of central physical energy storage system is inefficient. Therefore, it is necessary to have an efficient energy sharing mechanism to reduce energy penetration to the grid and reduce energy loss. This paper proposes a cyber-physical energy sharing structure which introduces the idea of virtual shared distributed energy storage analogous to the virtual shared memory in distributed computing systems. This concept, named as softmicrogrid, considerably reduces the subsequent charging/discharging hurdles and energy loss of microgrid. This concept is supplemented with an algorithm for charging the virtual shared distributed energy storage.
... This process has resulted in a new power system method with energy being traded on microgrids as people self-sufficiently supply their own electricity for homes, offices, and small industrial settings with renewable energy sources (RESs), which can be traded and shared in local areas [2][3][4]. This can form the basis for creating peer-to-peer (P2P) energy trading initiatives [5], involving prosumers selling excess energy generated by their own renewable energy sources to other users in the community. Up to date, P2P trading platforms have emerged in a range of sectors, allowing small suppliers to compete with traditional providers of goods and services [6]. ...
... The proliferation of innovative DERs, such as wind turbines and PV cells, has led to an increase in the number of prosumers among energy consumers. This allows for the foundation on which to create P2P energy trading initiatives [5], meaning that prosumers who create more energy from their renewable energy sources than they can consume themselves are able to sell that excess to others within their local area. Sharing energy creates a better balance of supply and demand, with the prosumers providing the supply to those with the local demand for it. ...
The emergence of distributed energy has led to a change in the role of the consumer in the traditional sense over the past decade. The proliferation of emerging generators and distributors has created opportunities for a more decentralised and open energy market. In particular, the emergence of peer-to-peer (P2P) energy trading models, challenged by the surge in demand for sustainable energy, has eliminated the need for intermediaries in energy transactions between consumers, producers, and sellers. Due to the great promise of sustainable energy, both in terms of its contribution to the environment and production costs, this paper reviews a number of well-known P2P energy trading platforms to understand what makes P2P energy trading platforms more functional. As a result, areas for consideration were identified and grouped into five themes: (1) set-up, (2) market, (3) information, (4) price, and (5) regulation.
... II. SYSTEM MODEL Distributed Energy Resources are radically changing the ways of producing and consuming energy, and traditional energy consumers are becoming prosumers [18]. At the moment, the basic option for trading electricity is a one-way process. ...
... [1]. Increasing the use of renewable energy sources at the household level requires new market approaches to price setting, decentralization of the energy market and energy infrastructure management [3], [4], [18]. It is necessary to create local energy markets where generated or stored energy can be sold locally, directly between prosumers, consumers and the network. ...
The paper discusses the issue of peer-to-peer trading between prosumers. Due to the increase in the amount of Distributed Generation in the Power Grid, it became possible to reduce power flows in the grid. This in turn will reduce power and voltage losses. Due to this, it becomes possible to prosumers to become participants in the Energy Market, and ordinary consumers to receive energy at prices lower than in the base tariffs set by electricity supplying organizations. The article is devoted to the analysis of trade in electric energy of prosumers between themselves and ordinary consumers, as well as participation in this process of Distributed System Operators. The concept of peer-to-peer trade formation and system model are considered. Investigate the role of different types of prosumers, their economic incentives, penalties for non-compliance. Prosumer model is considered in detail, including loads, renewable energy sources, battery energy storage system and switching equipment.
... In contrast, P2P energy trading encourages multi-directional trading within a local geographical area [10]. With the increasing connection of distributed energy resources (DER), traditional energy consumers are becoming prosumers who can consume and generate energy [11]. ...
... Year Type Description [8] 2020 Survey A survey on home energy management including main goals for operation and target strategies [9] 2021 Survey Comprehensive study of IoT business applications and smart energy systems [10] 2018 Technical/ Simulation P2P energy trading was designed and simulated for energy trading among prosumers and consumers in a microgrid [11] 2014 Technical/ Simulation Energy trading among prosumers in a microgrid to increase the utilization of renewable energy [12] 2019 Survey Comprehensive survey on IoT applications for smart grid and smart environments [13] 2021 Review Literature review on smart home adoption including motivations, barriers, and risks [14] 2018 Review Review on IoT-based energy system with respect to features, specifications, communication infrastructures, and privacy [15] 2019 Technical/ Implementation Design and implementation of a low-cost smart load node for monitoring and control non-smart residential load ...
The advances in the Internet of Things (IoT) and cloud computing opened new opportunities for developing various smart grid applications and services. The rapidly increasing adoption of IoT devices has enabled the development of applications and solutions to manage energy consumption efficiently. This work presents the design and implementation of a home energy management system (HEMS), which allows collecting and storing energy consumption data from appliances and the main load of the home. Two scenarios are designed and implemented: a local HEMS isolated from the Internet and relies on its processing and storage duties using an edge device and a Cloud HEMS using AWS IoT Core to manage incoming data messages and provide data-driven services and applications. A testbed was carried out in a real house in the city of Valparaiso, Chile, over a one-year period, where four appliances were used to collect energy consumption using smart plugs, as well as collecting the main energy load of the house through a data logger acting as a smart meter. To the best of our knowledge, this is the first electrical energy dataset with a 10-second sampling rate from a real household in Valparaiso, Chile. Results show that both implementations perform the baseline tasks (collecting, storing, and controlling) for a HEMS. This work contributes by providing a detailed technical implementation of HEMS that enables researchers and engineers to develop and implement HEMS solutions to support different smart home applications.
... Currently, energy trading is carried out in one direction only, between users and the electric company. With the increase in distributed generation in recent years, P2P has appeared as a new alternative for energy trading [10,11]. Previous studies have relied on P2P models to allow energy transactions between prosumers in microgrids [12,13]. ...
... With the increase in distributed energy resources, energy consumers have become prosumers [10]. There are several options when prosumers have excess energy produced. ...
Along with the exponential growth of distributed energy sources in the last decade, net-metering programs have expanded to encourage investment in renewable energy. However, several countries and some states in the United States are ending these programs. Therefore, it is needed to explore alternatives to net-metering programs to continue encouraging the adoption of renewable energies. In this paper, Peer-to-Peer (P2P) models are studied as viable options to net-metering. In particular, the evaluation and comparison of the net-metering model to two P2P models is proposed. The first P2P model uses the power grid for electricity exchange, and the other uses electric vehicles. Simulations of a 50 household microgrid with access to electric vehicles and photovoltaic generation were run to achieve this objective. Technical and economic indexes were established to measure the performance of the three models. The results indicate that the P2P model using the grid shows the best performance , followed by the P2P model using electric vehicles.
... Therefore, innovation in the energy system should see it benefit from the introduction of digitalization in the development of so-called smart grids (SG) 2 which can be defined as "robust, self-healing networks that allow bidirectional propagation of energy and information within the utility grid". 3 Such a technological transformation is exemplified by three fundamental elements: i) the continuous integration of Distributed Energy Resources (DER), (Sousa et al. (2019); Bussar et al. (2016); Zhang et al. (2018)), 4 ; ii) the massive introduction of Information and Communication Technology (ICT) devices (Saad al sumaiti et al., 2014); and iii) the central role of prosumers' 5 production and consumption choices (Luo et al. (2014); Sommerfeldt and Madani (2017); Espe et al. (2018); Zafar et al. (2018)). The SG context allows energy market players to adopt new behaviors. ...
... 11 Comprehensive review is provided by Hernández-Callejo (2019) This paper contributes to the real options literature studying investment in infrastructure for the production and exchange of energy. 12 Among contributions to these field, those closest to ours are: Bertolini et al. (2018) and Castellini et al. (2021),on the optimal plant sizing and investment decisions under uncertainty; Luo et al. (2014), focusing on the impact of cooperative energy trading on renewable energy utilization in a microgrid context; Zhang et al. (2018), who investigate the feasibility of P2P energy trading with flexible demand; Gonzalez-Romera et al. (2019), which develops a minimization problem with the aim of minimizing the energy exchange in a framework of two prosumer households; and Bellekom et al. (2016), whose agent-based model was developed in a residential community context under different prosumption scenarios. Our paper provides a theoretical framework for modeling the decision of two agents 13 to invest in a PV plant, assuming they are integrated into an intelligent network (i.e. in a SG context), where exchange P2P is possible. ...
... Therefore, innovation in the energy system should see it benefit from the introduction of digitalization in the development of so-called smart grids (SG) 2 which can be defined as "robust, self-healing networks that allow bidirectional propagation of energy and information within the utility grid". 3 Such a technological transformation is exemplified by three fundamental elements: i) the continuous integration of Distributed Energy Resources (DER), (Sousa et al. (2019); Bussar et al. (2016); Zhang et al. (2018)), 4 ; ii) the massive introduction of Information and Communication Technology (ICT) devices (Saad al sumaiti et al., 2014); and iii) the central role of prosumers' 5 production and consumption choices (Luo et al. (2014); Sommerfeldt and Madani (2017); Espe et al. (2018); Zafar et al. (2018)). The SG context allows energy market players to adopt new behaviors. ...
... 11 Comprehensive review is provided by Hernández-Callejo (2019) This paper contributes to the real options literature studying investment in infrastructure for the production and exchange of energy. 12 Among contributions to these field, those closest to ours are: Bertolini et al. (2018) and Castellini et al. (2021),on the optimal plant sizing and investment decisions under uncertainty; Luo et al. (2014), focusing on the impact of cooperative energy trading on renewable energy utilization in a microgrid context; Zhang et al. (2018), who investigate the feasibility of P2P energy trading with flexible demand; Gonzalez-Romera et al. (2019), which develops a minimization problem with the aim of minimizing the energy exchange in a framework of two prosumer households; and Bellekom et al. (2016), whose agent-based model was developed in a residential community context under different prosumption scenarios. Our paper provides a theoretical framework for modeling the decision of two agents 13 to invest in a PV plant, assuming they are integrated into an intelligent network (i.e. in a SG context), where exchange P2P is possible. ...
In this paper, we provide a real options model framing prosumers' investment in photovoltaic plants. This is presented in a Smart Grid context where the exchange of energy among prosumers is possible. We determine the optimal size of the photovoltaic installations based on the influence the self-consumption profiles on the exchange of energy among prosumers. We calibrate the model using figures relative to the Northern Italy energy market and investigate the investment decision allowing for different prosumer profiles and consider several combinations of their individual energy demand and supply. Our findings show that the shape of individual energy demand and supply curves is crucial to the exchange of energy among prosumers, and that there could be circumstances under which no exchange occurs.
... In recent years, the rapid expansion of distributed energy resources and EVs has altered the paradigm of energy production and consumption. This transformation has led to the emergence of prosumers who can actively participate in electricity generation [31]. When prosumers have excess electrical energy, they will have a spectrum of choices, such as storing this surplus energy for later use, injecting it into the electricity grid, or even offering it for sale to other energy consumers [32]. ...
Peer-to-peer (P2P) energy trading has attracted a lot of attention and the number of electric vehicles (EVs) has increased in the past couple of years. Toward sustainable mobility, EVs meet the standard development goals (SDGs) for attaining a sustainable future in the transport sector. This development and increasing number of EVs creates an opportunity for prosumers to trade electricity. Considering this opportunity, this review article aims to provide an in-depth analysis of P2P energy trading of EVs using blockchain in centralized and decentralized networks, which enables prosumers to exchange energy directly with one another. The paper is aimed to provide the reader with a state-of-the-art review on the P2P energy trading for EVs, considering different blockchain algorithms that are practically implemented or still in the research phase. Moreover, the paper presents blockchain applications, current trends, and future challenges of EVs’ energy trading. P2P energy trading for EVs using blockchain algorithms can be successfully implemented considering real-time scenarios and economically benefits smart sustainable societies.
... In telemedicine, healthcare providers can consult with patients remotely, often in real-time, using video conferencing platforms or specialized medical applications. Machine learning comes into play by aiding healthcare providers in analyzing medical images, interpreting patient data, or even flagging critical cases that require immediate attention [91]. The application of machine learning is not merely a technological advancement; it's an enhancement that can significantly affect the quality and efficiency of medical consultations. ...
The application of Machine Learning (ML) in healthcare has opened unprecedented avenues for predictive analytics, diagnostics, and personalized medicine. However, the sensitivity of healthcare data and the ethical dilemmas associated with automated decision-making necessitate a rigorous ethical framework. This review paper aims to provide a comprehensive overview of the existing ethical frameworks that guide ML in healthcare and evaluates their adequacy in ad-dressing ethical challenges. Specifically, this article offers an in-depth examination of prevailing ethical constructs that oversee healthcare ML, spotlighting pivotal concerns: data protection, in-formed assent, equity, and patient autonomy. Various analytical approaches including quantitative metrics, statistical methods for bias detection, and qualitative thematic analyses are applied to address these challenges. Insights are further enriched through case studies of Clinical Decision Support Systems, Remote Patient Monitoring, and Telemedicine Applications. Each case is evaluated against existing ethical frameworks to identify limitations and gaps. Based on our com-prehensive review and evaluation, we propose actionable recommendations for evolving ethical guidelines. The paper concludes by summarizing key findings and underscoring the urgent need for robust ethical frameworks to guide ML applications in sensitive healthcare environments. Future work should focus on the development and empirical validation of new ethical frameworks that can adapt to emerging technologies and ethical dilemmas in healthcare ML.
... The accelerated growth of renewable energy resources and the growing adoption of distributed power generation are transforming the energy sector. Peer-to-peer (P2P) energy trading has surfaced as an innovative solution, empowering prosumers and consumers to engage in energy trading in a more adaptable, efficient, and decentralized manner [19,20]. Blockchain technology, characterized by decentralization, transparency, and immutability, offers an ideal foundation for building P2P energy trading platforms [21]. ...
The widespread adoption of distributed energy resources (DERs) and the progress made in internet of things (IoT) and cloud computing technologies have enabled and facilitated the development of various smart grid applications and services. This study aims to develop and implement a peer-to-peer (P2P) energy trading platform that allows local energy trading between consumers and prosumers within a microgrid which combines IoT and blockchain technologies. The proposed platform comprises an IoT-cloud home energy management system (HEMS) responsible for gathering and storing energy consumption data and incorporates a blockchain framework that ensures secure and transparent energy trading. The proposed IoT–blockchain architecture utilizes a Chainlink oracle network and a private Ethereum blockchain. Through the use of smart contracts, consumers and prosumers can participate in an open auction to trade energy, while the settlement process involves acquiring external energy data from an API through the oracle network. The performance of the platform is evaluated through a testbed scenario using real-world energy data from a real house in Valparaiso, Chile, while storing those measurements in AWS cloud, validating the feasibility of the proposed architecture in enabling local energy trading. This work contributes to the development of energy management systems by providing a real-world implementation of an IoT–blockchain architecture for local energy trading. The integration of these technologies will allow for a more efficient and secure energy trading system that can benefit prosumers, consumers, and utilities.
... With the market for wireless devices expanding quickly, the concept has become more and more important [10]. The web (Internet) is used to connect hardware components to one another [11]. The system's connection to the internet is made possible by the ESP-8266 Wi-Fi gadget. ...
IoT-based applications are growing in popularity nowadays because they offer effective answers to numerous current problems. In this research, With the aim of decreasing human efforts for monitoring the power units and increasing users' knowledge of excessive electricity usage, an IoT-based electric metre surveillance system utilising an Android platform has been developed. With the help of an Arduino Uno and an optical sensor, the electric analyser pulse is captured. To reduce human mistake and the expense of energy usage, a low-cost wireless network of sensors for digital energy metres is implemented alongside a smartphone application that can autonomously read the metre of the unit. In this research, an intelligent power monitoring system with effective communication modules has been developed to make wise use of the electricity. The controller, NB-IoT connection module, and cloud are the three main components of an IOT-based smart energy metre system. The controller is essential for maintaining the functionality of each component. This solution reduces the need for human involvement in electricity maintenance by connecting energy metres to the cloud using an NB-IoT communication module. The IoT-based metre reading system in the proposed work is created to monitor and analyse the metre reading, and the service provider can cut off the source of electricity whenever the customer fails to pay the monthly bill. It also eliminates the need for human intervention, provides accurate metre reading, and guards against billing errors. The proposed SPM improves the overall accuracy ranges of 7.42, 27.83, and 20% better than DR, OREM, and SLN respectively.
... The installation of distributed generation (DG) systems has several benefits, including reducing dependency on the utility grid, lowering electricity costs, and promoting the use of prosumers' electricity by the utility grid, as reported by [3][4][5][6][7][8]. However, autonomous energy trading, as stated in [9], relies on policies and protocols for energy matching and sharing, but lacks a pricing mechanism, making it difficult to facilitate energy sharing and demand response. Researchers have proposed various solutions to address the pricing problem between retailers and consumers of electricity. ...
The intimidating surge in the procurement of Distributed Energy Resources (DER) has increased the number of prosumers, creating a new possibility of local energy trading across the community. This project aims to formulate the peer-to-peer energy (P2P) sharing model to encourage the DERs to share surplus energy among the consumers. An effective pricing method is developed based on the supply-demand ratio (SDR) with the importance of self-optimization, which allows the prosumers to maximize their energy sharing and profits. To implement this pricing method, a simplified dynamic matchmaking algorithm has been deployed to introduce the Outstanding Prosumer to interact with existing consumers to increase the efficiency and profitability of the trade network. Consumers also benefit from this model, as they can pick the most economical energy supplier instead of relying on the utility grid. The prosumer with high excess energy and the consumer with the highest energy demand will be prioritized to maintain the SDR ratio to one or greater than one. Here, all the above-stated features of the peer-to-peer energy trading have been demonstrated with some calculations to back up some tangible results. Finally, a case study is simulated among the residents of Dhaka, Bangladesh, to demonstrate how peers can profit from participating in trading at a given time. Comparing the results with and without P2P trading, there has been a 17.54% reduction in an electric bill on a typical day of July, and a 49.53% reduction in the interaction with the grid.
... In the existing energy market system, distributed generation resources and consumerowned generators (i.e., prosumers) are increasing continuously [11]. The surplus renewable energy produced by producers is supplied directly to the grid. ...
Rooftop solar power generation is becoming more widespread in residential microgrids. As well as new concepts of electricity markets, such as peer-to-peer (P2P) markets, where consumers and prosumers can directly exchange locally generated energy with each other without any intermediary third party for sustainable development. Data security is a big concern with energy trading; therefore, blockchain technology is being used more and more in energy markets. It has the potential to simplify P2P energy trading. In this paper, blockchain is designed to fit into the decentralized nature of the P2P market, securing the payment mechanism and transaction data store. The blockchain-enabled platform is developed using the Proof-of-Work (PoW) consensus algorithm, and is verified with the help of the Postman application programming interface (API). All transactions involving the buying and selling of energy are handled by a miner without the help of any third parties. The study of a five-user residential community, whether the strategy is recommended or not, is validated through simulation findings. An overview of the results revealed that all users benefited from the developed, secure P2P platform.
... Our project is well inspired by LO3 energy(an organization providing energy solutions), the very first peer to peer merchandising made in history of Brooklyn, NY. LO3 launched Brooklyn micro grid where proximate inhabitants were tied up over prevailing grid substructure and delimited P2P energy transactions were pioneered and archived as first execution [6]. Bitcoin is known to originated from the concept of blockchain, however beyond its usage in the transactions modifications has also change the way in which data and information are utilized [7]. ...
In this paper, we present our research, where residents purchase and sell locally produced renewable energy from each other. In this research work, we integrate block chain technology to create peer-to-peer marketplaces for distributed energy. First, we use a smart energy meter to measure various important parameters of electrical energy. In this proposed work, the initial measurements of the current are being performed with the help of hall effect sensor due to its accuracy. Second, supply voltage is calculated with the help of a transformer and DC biasing method. The apparent power is calculated by multiplying the measured current and voltage, and then the energy parameter is obtained. Using this smart energy meter, we obtain our desired parameters with sufficient accuracy of nearly 90 percent. These obtained parameters and results are directly uploaded to Amazon Web Server(AWS). We also develop an android app that connects with the AWS server. The designed system facilitates the users to perceive these electrical parameters on meter having built-in LCD display which shows all measured results including a number of units consumed, and billing information anywhere around the world. Finally, we develop a smart contract on Ethereum block chain which can transact the number of tokens according to the units sold or purchased by the users. The Consumer can set their selling rate through the app. Any user with this app is able to take their readings live to their smart phone.
... Distributed generation is an electricity generation method for supplying electricity to those with small electricity generation facilities installed near their surroundings requiring electricity, or that compensates for the shortcomings of centralized electricity generation. Distributed generation has become an alternative to centralized generation as it reduces electricity loss in the case of long-distance transmission, reducing the cost of electricity grid installation/operation/maintenance and at the same time increasing the stability of the electricity supply [1,2]. With its numerous benefits, distributed generation systems are actively installed by energy prosumers in residential areas to produce clean energy and supply it to their community. ...
This study proposed an optimal trading price of electricity by considering electricity billing system and corresponding government policies in South Korea. To this end, this study calculated the maximum and minimum trading prices of electricity by defining the profit structure from the viewpoint of the energy consumer and prosumer, based on which the optimal trading price of electricity was derived from a genetic algorithm (GA) and Pareto optimal solution.
The main results of this study can be summarized as follows. First, from the perspective of the energy prosumer, the lower the self-use rate and the higher the monthly electricity usage, the higher the optimal trading price of electricity, and the higher the number of tradable-energy consumers in the monthly electricity usage was, the greater the scope of the optimal trading price of electricity. Second, the higher the monthly electricity usage, the higher the optimal trading price of electricity, and the higher the number of tradable-energy prosumers in the monthly electricity usage, the greater the scope of the optimal trading price of electricity. The results of this study can be used to establish an energy prosumer's electricity usage strategy, improve the electricity billing system based on the optimal trading price of electricity, and establish a policy on the subsidy to be offered for the installation of solar photovoltaic (PV) panels.
... Additionally, for UCMS, the power quality or voltage regulation can be improved to reduce the daily energy cost. Another energy trading strategy is also proposed by Yuan in [102], between prosumers in an MG (microgrid). Prosumers choose either utility, purchase the electricity from the grid, or run in island mode. ...
The multiple uncertainties in a microgrid, such as limited photovoltaic generations, ups and downs in the market price, and controlling different loads, are challenging points in managing campus energy with multiple microgrid systems and are a hot topic of research in the current era. Microgrids deployed at multiple campuses can be successfully operated with an exemplary energy management system (EMS) to address these challenges, offering several solutions to minimize the greenhouse gas (GHG) emissions, maintenance costs, and peak load demands of the microgrid infrastructure. This literature survey presents a comparative analysis of multiple campus microgrids' energy management at different universities in different locations, and it also studies different approaches to managing their peak demand and achieving the maximum output power for campus microgrids. In this paper, the analysis is also focused on managing and addressing the uncertain nature of renewable energies, considering the storage technologies implemented on various campuses. A comparative analysis was also considered for the energy management of campus mi-crogrids, which were investigated with multiple optimization techniques, simulation tools, and different types of energy storage technologies. Finally, the challenges for future research are highlighted , considering campus microgrids' importance globally. Moreover, this paper is expected to open innovative paths in the future for new researchers working in the domain of campus mi-crogrids.
... Additionally, for UCMS, the power quality or voltage regulation can be improved to reduce the daily energy cost. Another energy trading strategy is also proposed by Yuan in [102], between prosumers in an MG (microgrid). Prosumers choose either utility, purchase the electricity from the grid, or run in island mode. ...
The multiple uncertainties in a microgrid, such as limited photovoltaic generations, ups and downs in the market price, and controlling different loads, are challenging points in managing campus energy with multiple microgrid systems and are a hot topic of research in the current era. Microgrids deployed at multiple campuses can be successfully operated with an exemplary energy management system (EMS) to address these challenges, offering several solutions to minimize the greenhouse gas (GHG) emissions, maintenance costs, and peak load demands of the microgrid infrastructure. This literature survey presents a comparative analysis of multiple campus microgrids’ energy management at different universities in different locations, and it also studies different approaches to managing their peak demand and achieving the maximum output power for campus microgrids. In this paper, the analysis is also focused on managing and addressing the uncertain nature of renewable energies, considering the storage technologies implemented on various campuses. A comparative analysis was also considered for the energy management of campus microgrids, which were investigated with multiple optimization techniques, simulation tools, and different types of energy storage technologies. Finally, the challenges for future research are highlighted, considering campus microgrids’ importance globally. Moreover, this paper is expected to open innovative paths in the future for new researchers working in the domain of campus microgrids.
... To design the most efficient and economic system, it is necessary to build a proper energy trading model to organise the local energy trading between the prosumers. With a growing connection within the distribution system, traditional consumers or microgrids have the capability to act as prosumers, who can generate, consume and transfer access energy [39]. The traditional peer-to-grid (P2G) scheme is a unidirectional way to undertake energy trading, where microgrids can only buy insufficient power from the grid and sell extra power to the grid [40]. ...
Energy issues and atmospheric pollution are increasing rapidly. Green energy production is a vital solution. In this research, different architectures of hybrid power system are proposed, which consist of different sequences of microgrids in grid-connected modes to meet residential load requirements. Each microgrid consists of distinct combination of wind turbines, photovoltaic panels and storage batteries. In order to improve the overall efficiency and profit of the hybrid power system, the approaches of microgrid clustering and networked microgrid are considered. Cooperative and non-cooperative game theory techniques are used to design proposed architectures for the suitable sizing of generation resources and batteries, and to achieve optimum payoff values. Game theory techniques, specifically, the Nash equilibrium, Shapley values and Nash bargaining solution, are implemented to achieve optimum outcomes. The game models are formulated based on single-object and multi-object optimisations, and different criteria such as annual profit, reliability index, loss of power supply probability, levelized cost of energy and energy index of reliability are considered to direct the objective functions.
In order to improve the overall reliability, minimise the power outage issues and increase the annual profit, the peer-to-peer energy trading scheme is considered for a networked microgrid. The power system models are formulated and analysed for peer-to-grid and peer-to-peer energy trading schemes. The outcomes of the multi-objective functions are also compared for both energy trading schemes to validate the results. Sensitivity analysis is performed for designed architectures to verify the effectiveness of multi-objective function and the stability for the price of electricity and discount rates. Simulation models are built in MATLAB software based on a different computation methods such as particle swarm optimization and imperialistic competition algorithm. Models are simulated for the maximum number of iterations to reach their global best values to find the optimum results.
In short, different architectures of hybrid power system are proposed, which consist of distinct combination of wind turbines, photovoltaic panels and storage batteries in grid-connected modes. To improve the systems’ efficiency, reliability and annual profit, the application of microgrid clustering and peer-to-peer energy trading are implemented. Game theory techniques are used for the optimization of power system models to find their correct sizing of the generation resources, and to achieve optimum payoff values.
... To design the most efficient and economic system, it is necessary to build an appropriate energy trading model to organise the local energy trading between the prosumers. With the growing connection within the distribution system, traditional consumers, or microgrids, have the capability to act as prosumers who can generate, consume and transfer access energy [20]. The traditional peer-to-grid (P2G) scheme is a unidirectional way for energy trading where microgrids can only buy sufficient power from the grid and sell extra power to the grid [21]. ...
This paper proposes a peer-to-peer energy trading system based on multi-objective game-theoretic optimisation for a clustered microgrid to find suitable sizes of distributed generations, including energy storage systems. The chosen architecture includes three different microgrids, and each microgrid can be a combination of solar panels, wind turbines and batteries, to meet the requirements of their residential loads. In the clustered microgrid, all microgrids are connected with one another, and also with the main grid, and they have the ability to perform both peer-to-peer and peer-to-grid energy trading based on load requirements and to reach the optimum value of the outlined objective function. To formulate a multi-objective function, two different criteria’ the annual profit and the loss of power supply probability are considered, and the Nash equilibrium-based game theory technique is modelled for clustered microgrids using a particle swarm optimisation algorithm to obtain suitable sizes of the players and payoff values. In the end, for each microgrid, suitable sizes of solar panels, wind turbines and batteries are proposed to meet the residential load requirements in the grid-connected mode. The outcomes of the multi-objective function are analysed and compared for two energy trading schemes, including peer-to-grid and peer-to-peer. The trends of objective functions and sizes of the players are analysed to verify the design of the proposed architecture.
... In recent decades, distributed generation (DG) units based on renewable energy sources (RES) have grown significantly at the distribution level. As these resources increases, traditional energy consumers become prosumers who can consume and produce energy [3]. Due to these energy sources' usual intermittency, the surplus of a prosumer can be stored, transferred to the power grid, cut off, or sold to other energy consumers [4]. ...
Today, the pace of development of decentralized transactive management systems has increased significantly due to growing renewable energy source technologies and communication infrastructure at the distribution system level. Such bilateral energy transactions have changed the structure of electricity markets and led to the emergence of a local energy market in electricity distribution. While examining this change of attitude, this paper analyzes the effects of local market formation on the performance and performance of distribution companies. Accordingly, the technical requirements in the three areas of operation, network control, and ICT in the new workspace are thoroughly examined. The hardware requirements will be presented in two parts for the end-user and the distribution systems. Then, the proposed local distribution market framework will be introduced, and finally, the conclusion will be presented.
... However, without intervention by the trusted third party, it is impossible or hard to guarantee trust between participants, determine the price of energy trading, or fulfill the agreement automatically or forcibly in conventional P2P energy trading systems [1]. In addition, these server-based systems are vulnerable to hacking and tampering unless costly firewalls are installed. ...
We implement a peer-to-peer (P2P) energy trading system between prosumers and consumers using a smart contract on Ethereum blockchain. The smart contract resides on a blockchain shared by participants and hence guarantees exact execution of trade and keeps immutable transaction records. It removes high cost and overheads needed against hacking or tampering in traditional server-based P2P energy trade systems. The salient features of our implementation include: 1. Dynamic pricing for automatic balancing of total supply and total demand within a microgrid, 2. prevention of double sale, 3. automatic and autonomous operation, 4. experiment on a testbed (Node.js and web3.js API to access Ethereum Virtual Machine on Raspberry Pis with MATLAB interface), and 5. simulation via personas (virtual consumers and prosumers generated from benchmark). Detailed description of our implementation is provided along with state diagrams and core procedures.
The article discusses the topic of mutual trade between prosumers at the same level. By increasing the amount of electricity distributed in the grid, it becomes possible to reduce the flow of electrical power in the grid, which in turn helps to reduce power losses and reduce voltage. This opens up an opportunity for prosumers to become participants in the Energy Market, and for ordinary consumers to receive electricity at prices that are lower than the basic tariffs set by energy supply companies. The article pays attention to the analysis of electricity trade between prosumers and ordinary consumers, as well as the role of distributed system operators in this process. The concept of peer-to-peer trading and the system model are described. The influence of different types of prosumers, their economic incentives and sanctions for violation of the rules is studied. The prosumer model is discussed in detail, including loads, renewable energy sources, battery system for energy storage, and switching equipment. It is noted that the purpose of market regulation is to solve a centralized problem that can be solved by a central operator with access to consumers' private information. The proposed method uses a low-voltage flexibility market in which consumers are connected to a single feeder. They form a community of prosumers among themselves and participate in the flexibility market. Limiting consumers to the level of low-voltage networks reduces flexibility, but allows to increase the efficiency of calculations. In addition, prosumers at the connection point can compete with each other to provide aggregate flexibility at low voltage levels. ORG provides the necessary flexibility of the peer-to-peer market in view of voltage limitations and congestion of distribution networks.
This paper proposes a joint electricity and carbon sharing framework with photovoltaic (PV) and energy storage system (ESS) for deep decarbonization, allowing distributed PV prosumers to participate in a sharing network established by aggregator of prosumers (AOP). The ESS-equipped AOP plays multiple roles as a carbon aggregator, an ESS operator, and an energy-sharing provider at the same time. First, a demand response (DR)-based model that incorporates the multi-strategy of ESS is proposed to optimize energy-carbon transaction. A low-carbon DR with consideration of electricity-carbon coupling is developed to incentivize prosumers to adjust consumption behavior for costs and emissions reduction. Second, a joint optimization based on Stackelberg game is proposed, where AOP is leader, and prosumers act as followers. A dynamic pricing mechanism is proposed for AOP to determine the electricity-carbon coupled selling and buying prices simultaneously. Meanwhile, prosumers would adjust their energy consumption as response to different sharing prices. In addition, a distributed optimization algorithm with interactions is used to reach the Stackelberg game equilibrium. Finally, through a practical testing case, the effectiveness of the method is validated in terms of economic benefits and PV sharing enhancement, as well as the reduction of carbon emissions.
As transportation evolves with greater adoption of electric vehicles (EVs), vehicle-to-vehicle (V2V) energy trading stands out as an important innovation for managing energy resources more effectively as it reduces dependency on traditional energy infrastructures and, hence, alleviates the pressure on the power grid during peak demand times. Thus, this paper conducts a systematic review of the V2V energy trading frameworks. Through the included article analysis (n = 61), this paper discusses the state-of-the-art energy trading frameworks’ structure, employed methodologies, encountered challenges, and potential directions for future research. To the best of the authors’ knowledge, this is the first review explicitly focused on V2V energy trading. We detail four critical challenges to face while establishing the framework in current research, providing an overview of various methodologies, including auctions, blockchain, game theory, optimisation, and demand forecasting, that are used to address these challenges and explore their integration within the research landscape. Additionally, this paper forecasts the evolution of V2V energy trading, highlighting the potential incorporation of advanced and established technologies like artificial intelligence (AI), digital twins, and smart contracts. This review aims to encapsulate the existing state of V2V energy trading research and stimulate future advancements and technological integration within the field.
The extension of emerging renewable energy sources such as wind and water turbines, solar panels, and the increasing usage of electric vehicles requires the supply and distribution of energy in a small device on local scale and it has created new methods of supplying and selling electricity. Middle buyers and end users can obtain the local energy with the peer‐to‐peer trading method in this large and hierarchical market. This method enables market to manage and exchange the electricity between major suppliers and medium and local levels. Blockchain technology is developing in peer‐to‐peer exchange of electricity and acts as a reliable, efficient, and safe technology in the electricity trading market. In this method, while preserving the privacy of electricity users, by using smart contracts and by removing intermediaries in the energy supply and demand market, direct commercial interactions between energy suppliers and consumers are done. The blockchain technology, while creating trust between the parties in the energy market, reduces the cost of electricity trading and increases its scalability with using the intermediate energy aggregators. In this research, the blockchain‐based model, is presented for distribution and peer‐to‐peer transactions in the energy market. The suggested model provides the possibility of registration low‐cost instant transactions at the power grid in any specific period of time. The above method, unlike periodic payments, provides immediate access to bills and small payments. Since the transactions outside the blockchain chain are not recorded, this system guarantees its honest and independent operation without fraud and failure. The smart contract method based on blockchain, reduces the transaction fees and speeds up electricity trading. Also, the experimental investigation in 20 nodes shows the time required to determine the exchange contract in the blockchain method. The average is improved by 49.7% in this method. Also, the negotiation convergence time has become 47% faster.
The rapid development of residential and commercial grid connected photovoltaic power projects led the research to energy optimization under mismatched operating conditions. The energy losses from partial shading photovoltaic panels can cause significant reduction in the produced energy of a PY system based on the classic topology of string inverter. The solution to this kind of problems can be given by incorporating embedded systems in the photovoltaic plants.
This paper presents the simulation results from the comparison of the main topologies which used for power optimization of a shading PY system, the DC/DC power optimizers, cell string optimizers and microinverters, and stress their effectiveness against the conventional string inverter scheme. The financial benefits of the participation of a grid-connected PY system to a demand response program by using loT and loE technologies are analyzed in techno economic basis.
Peer-to-peer (P2P) electricity trading has become the next generation of energy management strategies that economically benefit prosumers by trading electricity as goods and services. The P2P electricity market is expected to support the grid to minimize reserve requirements, lower investment and operational costs, reduce peak demand, and improve reliability. Nonetheless, the deployment of P2P electricity trading in the electricity networks is challenging in terms of modelling the transactions in both the physical and virtual layers of the network. The physical layer is a physical network that enables the transfer of electricity from the sellers to the buyers once financial settlements between both parties are completed over the virtual layer platform. The virtual layer facilitates a secured connection for participants to decide on their electricity trading parameters. This paper systematically reviews the current developments in the P2P electricity trading literature. Importantly, the systematic literature review brings to light six essential components in P2P electricity trading processes, namely: P2P electricity trading platforms, P2P market schemes, P2P electricity trading market clearance algorithms, policy supporting P2P electricity trading, P2P electricity trading networks and P2P ICT infrastructure, which are discussed in detail in the paper. Accordingly, for each component, state-of-the-art technologies, notable findings, and best practice insights are comprehensively reviewed, based on which directions for future research are presented. The P2P electricity market is a rapidly emerging research domain with significant opportunities and prospects globally in the industry and academia.
The current structure of energy networks was not initially designed to support the high penetration of volatile renewable energy systems. The old form of the energy structure suffers substantial losses caused by long-distance transmission lines as well as traditional energy production and distribution supply process coming from the centralized energy generation mechanism. However, new localized forms of energy grids such as microgrids, prosumers, and energy hubs have recently appeared that allow for decentralized energy generation along with reliable and sustainable energy supply producers. Indeed, new energy network paradigms can provide suitable conditions for adopting decentralized energy production systems, especially renewable types, and upsurging affordability to invest in domestic renewable systems. However, reaching from the energy network decentralization to its decarbonization accompanies by the challenge of stochastic variations in renewable outputs. In such a network status, different grid paradigms require sustainable ways of energy supply to better manage their energy supply and demand and procure a satisfactory level of economic and social benefits. Peer-to-peer (P2P) energy trading is one of these ways that adds strong flexibility ability to grids equipped with numerous renewable energy systems. However, previous models and platforms for P2P energy sharing are no longer appropriate for the future modern energy infrastructure. Hence, market mechanisms and platforms need to be modernized for the P2P energy sharing that easily allows for the new emerging technologies to play a central role in improving the grid characteristics. This is why the present chapter is planned for analyzing the modernized P2P energy trading market model and platforms to lighten the aforementioned burden for future modern energy networks.
This paper reviews a peer-to-peer energy market for prosumers of a regulated utility. Utilities pay retail prices to prosumers regardless of demand, forcing utilities to pass the cost of distribution to other consumers. As prosumers grow in numbers, utilities need a better compensation method. A real-time peer-to-peer energy market application may provide higher incentives. Utilities adopt the service because it would allow for compensation of overhead. By including the utility, a micro-grid is not needed for a peer-to-peer market. The prosumer community can be virtual. The proposed implementation can become an intermediary step to decentralized energy markets. The application shall leverage the real-time demand of consumers and adjust payment instantly to prosumers that can meet that demand. A shared cloud account can allow the community to manage the application and create transparency and trust.
Cooperative energy sharing frameworks have quickly emerged among a cluster of residential communities with more in-situ distributed energy resources (DERs). The interest of such prosumers in participating in energy cooperative sharing requires a robust framework for energy and revenue exchanges. One such framework for sharing energy among prosumers and between the cluster and an aggregator has been developed in this article. A business model using a distributed ledger technology (DLT) for such an energy cooperative has been proposed. The proposed business model employs the Ethereum blockchain for an appropriate and fair accounting of the energy transferred. A case study with four prosumers using realistic data is presented to demonstrate the usefulness of the proposed cooperative energy sharing framework.
With the complication of energy structure and increment of energy consumption, the convention energy system can no longer fit the situation. The Energy Internet (EI) is proposed to address these issues. The key idea of the EI is that industry system, weather system, traffic system, ecology system, business system, and energy system are coupling with each other to modify the performance of energy system through modern information and communication technologies. In this chapter, the concept of EI is first introduced, and comparisons of the conventional energy system and new energy system are revealed. Then, the integration of different systems with energy system is discussed. Meanwhile, specific approaches with information and communication technologies are introduced.KeywordsEnergy internetNew energy systemEnergy savingEmission reductionEnergy ecology
Local uses of photovoltaic (PV) energy within neighborhood PV prosumers become more economical than the individual operation of prosumers. In the present work, the hourly optimized total cost of energy sharing of peer-to-peer (P2P) PV prosumers for a microgrid is proposed. Initially, a dynamic internal pricing model is prepared for the energy sharing operation. Furthermore, considering the adjustable load of prosumers, an equiponderant cost model is formulated concerning economic costs and user interest. Finally, the formulated cost model is transformed into an optimization problem and is solved using the krill herd algorithm to get the ultimate optimized hourly total cost of energy sharing. This optimized cost provides the maximum economic profit to all the participating PV prosumers in the microgrid.
The Peer-to-peer (P2P) trading strategy is one of the valuable methods that could be used in various local electricity markets with different aims, such as peak shaving and energy cost reduction. In this paper, due to the enforcement of financial risks, a risk evaluation procedure called the downside risk constraint (DRC) method is applied to analyze the effects of the P2P method and shared storage trading in an industrial area in both risk-neutral risk-averse models. The industrial zone includes various buildings that are connected to each other and include different DERs. The investigation is performed in three separate cases: base case, P2P case, and P2P+shared storage case. According to the obtained results, for a high-level risk, we need to spend more currency to keep the system's security at a high level. For example, the amount of achieved cost in the risk-averse model is 816,000$ in the third case. Besides, the potential savings are attained in electricity costs; for instance, in the risk-neutral model, 14.8% of electricity cost is reduced in the second and 21.5% in the third cases. The reduction of electricity price is because the amount of purchasing power from the grid is declined with the help of DERs.
In this paper, we provide a real options model framing prosumers’ investment in photovoltaic plants. This is presented in a Smart Grid context where the exchange of energy among prosumers is possible. We determine the optimal size of the photovoltaic installations based on the influence the self-consumption profiles on the exchange of energy among prosumers. We calibrate the model using figures relative to the Northern Italy energy market and investigate the investment decision allowing for different prosumer profiles and consider several combinations of their individual energy demand and supply. Our findings show that the shape of individual energy demand and supply curves is crucial to the exchange of energy among prosumers, and that there could be circumstances under which no exchange occurs.
In this paper, a multi-objective optimization technique is proposed for the planning of a networked microgrid based on peer-to-grid (P2G) and peer-to-peer (P2P) energy trading schemes. Two different criteria's including annual profit and energy index of reliability are taken into consideration to form a multi-objective function. The networked microgrid consists of three individual microgrids containing their own combinations of generation resources, batteries and residential loads. All microgrids are connected together and also to the main grid to meet the energy exchange requirements of P2P energy trading. A cooperative game theory technique based on a particle swarm optimization algorithm is used to model the networked microgrid, and to find the suitable sizes of the players that simultaneously maximize the payoff values of both objective functions. Besides, a comparative analysis is carried out for both P2G and P2P energy trading schemes. The results show that the outcomes are maximum when both criteria are considered in the optimization and P2P energy trading is carried out. The sensitivity analysis is performed on the selected parameters and verified the right change 0.003% and 4.5% in discount rate and electricity prices, respectively.
The wide variety of customers in power grids makes it challenging for the network's operator to anticipate the new load in demand response (DR) programs. For optimal scheduling of generation units, this article presents a novel method for the operator to predict market prices and electrical load under a real-time pricing (RTP) demand response program in a microgrid. Inspired by the Stackelberg game, the proposed model establishes simulated trading between the network's operator (leader) optimizing the generation cost and offering market prices to the customers (followers) who optimize their behavior. The model is formulated as a one-leader, N-follower iterative game where the optimization problems are solved using deterministic and stochastic optimization techniques. The proposed model considers a detailed representation of the power system as well as the industrial and residential loads. Simulations are performed on three microgrid systems where results show the significance of the detailed representation.
The relationships between producers and consumers have changed radically by the recent growth of sharing economy. Promoting resource sharing can contribute to finding a solution to environmental issues (e.g. reducing food waste, consuming surplus electricity, and so on). Although prosumers have both roles as consumers and suppliers, matching between suppliers and consumers should be determined when the prosumers share resources. Especially, it is important to achieve envy-freeness that is a metric indicating how the number of prosumers feeling unfairness is kept small since the capacity of prosumers to supply resources is limited. Changing resource capacity and demand will make the situation more complex. This paper proposes a resource sharing model based on a temporal network and flows to realize envy-free resource sharing among prosumers. Experimental results demonstrate the deviation of envy among prosumers can be reduced by setting appropriate weights in a flow network.
As the solar photovoltaic (PV) matures, the economic feasibility of PV projects is increasingly being evaluated using the levelized cost of electricity (LCOE) generation in order to be compared to other electricity generation technologies. Unfortunately, there is lack of clarity of reporting assumptions, justifications and degree of completeness in LCOE calculations, which produces widely varying and contradictory results. This paper reviews the methodology of properly calculating the LCOE for solar PV, correcting the misconceptions made in the assumptions found throughout the literature. Then a template is provided for better reporting of LCOE results for PV needed to influence policy mandates or make invest decisions. A numerical example is provided with variable ranges to test sensitivity, allowing for conclusions to be drawn on the most important variables. Grid parity is considered when the LCOE of solar PV is comparable with grid electrical prices of conventional technologies and is the industry target for cost-effectiveness. Given the state of the art in the technology and favourable financing terms it is clear that PV has already obtained grid parity in specific locations and as installed costs continue to decline, grid electricity prices continue to escalate, and industry experience increases, PV will become an increasingly economically advantageous source of electricity over expanding geographical regions.
In the service-centric Internet, multiple virtual services (tenants) are overlayed on top of the same infrastructure (both in wide-area networks and in datacenter networks). We propose conserving energy, in this setting, by virtualizing network power consumed by each tenant, feeding back that information to the tenant, and incentivizing the tenant to conserve energy by making their bill proportional to this virtual power. However, virtualizing power in these multitenant networks is tricky since the network is not energy-proportional, i.e., the energy consumption and its monetary expenditure do not reduce with a decrease in load per component. We overcome this limitation by proposing a simple heuristic for billing, that further motivates tenants to align their workload in a manner conducive to optimization by the infrastructure provider.
The smart grid vision relies on active interaction with all of its stakeholders. As consumers are acquiring energy generation capabilities, hence becoming prosumers (producers and consumers), a meaningful way to interact among them would be to trade over a marketplace. Market-driven interactions have been proposed as a promising potential interaction method due to the monetary incentives and other benefits involved for the participants [1]. In the Internet era an on-line marketplace is an thriving concept as it overcomes potential accessibility issues, however it is not clear how they should be structured, operated, what their limits and benefits might be. The design, implementation, modus-operandi as well as the assessment of such an energy market place for smart grid neighbourhoods is presented.
Future smart cities are expected to be very large and complex ecosystems, where interactions among the various involved entities may lead to emergent behaviours (system of systems characteristic). Managing better the energy footprint is one of those challenging goals, and the smartgrid may provide a key tool in achieving that. We expect that smart city neighbourhoods will be more autonomous and able to manage more efficiently and dynamically their energy by taking into consideration local resources, prosumption and needs of their stakeholders. Additionally they will be able to interact with each-other and enable the smart city to dynamically take advantage of its optimal resource usage. We explore here directions that we follow in order to realize this view with the help of the smartgrid infrastructure, prosumer interactions, enterprise energy services and neighbourhood energy marketplaces.
As the solar photovoltaic (PV) matures, the economic feasibility of PV projects is increasingly being evaluated using the levelized cost of electricity (LCOE) generation in order to be compared to other electricity generation technologies. Unfortunately, there is lack of clarity of reporting assumptions, justifications and degree of completeness in LCOE calculations, which produces widely varying and contradictory results. This paper reviews the methodology of properly calculating the LCOE for solar PV, correcting the misconceptions made in the assumptions found throughout the literature. Then a template is provided for better reporting of LCOE results for PV needed to influence policy mandates or make invest decisions. A numerical example is provided with variable ranges to test sensitivity, allowing for conclusions to be drawn on the most important variables. Grid parity is considered when the LCOE of solar PV is comparable with grid electrical prices of conventional technologies and is the industry target for cost-effectiveness. Given the state of the art in the technology and favourable financing terms it is clear that PV has already obtained grid parity in specific locations and as installed costs continue to decline, grid electricity prices continue to escalate, and industry experience increases, PV will become an increasingly economically advantageous source of electricity over expanding geographical regions.
Distributed generation of energy coming from various vendors, even private homes, is a big challenge for tomorrows power management
systems that, unlike today, will not dispatch energy centrally or under central control. On the contrary, the production,
distribution and management of energy will be treated and optimized in a distributed manner using local data. Even today,
parts of the power system are highly nonlinear with fast changing dynamics. It is hard to predict disturbances and undertake
countermeasures on time. In existing approaches electricity is distributed to the final users according to its expected estimated
demand. Such non-dynamic approaches, are difficult to evolve and can not accommodate rapid changes in the system. By having
a cross-layer and open information flow among the different actors involved we can make better and more timely predictions,
and inject new dynamics in the system that will lead to better energy management and achieve better energy savings. The NOBEL
project is building an energy brokerage system with which individual energy prosumers can communicate their energy needs directly
to both large-scale and small-scale energy producers, thereby making energy use more efficient.
The Great East Japan Earthquake of March 11, 2011 has changed our attitude regarding energy supply in Japan. In the past, we needed only to follow the guidelines of the annual energy usage amount indicated in the "Revised Act on the Energy Saving." However, we are now and in the future requested to personally comprehend the per-hour energy usage amount per building and even for each area or section of a building. The summer of 2011 was the socalled "summer of patience," and enterprises were asked to reduce their investment in facilities, etc. However, for the winter of 2011 towards the summer of 2012 and into the future we have been requested to introduce systems to monitor energy wastage and to control energy usage for optimum saving. NEC offers solutions for the "visualization" and "optimum controls for saving energy" as well as "Smart Buildings" (BEMS) to provide optimum energy supply and demand by developing grid interconnection control systems. These solutions are intended to support energy storage and to enable the creation of stable energy supply.
Energy poverty at the household level is a serious hindrance to economic and social development, especially in off-grid, remote villages in the developing world. Some initiatives have sought to provide these households with resources such as renewable generation units and electric batteries to enable access to electricity. At present, these resources are operated in isolation, fulfilling individual home needs, which results in an inefficient and costly use of resources, especially in the case of electric batteries which are expensive and have a limited number of charging cycles. To address this problem, we investigate the exchange of energy between homes in a community to reduce the overall battery usage, thus prolonging the life of batteries. We take an agent-based approach to this problem and show that agents (acting on the behalf of households) can coordinate and regulate the exchange of energy between homes which leads to two surpluses: reduction in the overall battery usage and reduction in the energy losses. To ensure a fair distribution of these surpluses among agents, we model this problem as a coalitional game where each agent's contribution to both surpluses is computed using the Shapley value. Using real world data, we empirically evaluate our solution to show that energy exchange (i) can reduce the need for battery charging (by close to 65%) in a community and (ii) can improve the efficient use of energy (by up to 80% under certain conditions). In addition, we show how approximated Shapley values can be used to enable energy exchange in large communities.
A smart house which equips power generators, power storage systems, and a smart meter which controls those equipments to utilize renewable energy efficiently has attracted attentions. Smart house is expected to reduce energy cost of residential by efficient usage of energy resources. Scheduling methods of the equipments to reduce energy cost have been proposed. However, since they focus on only one house, the effect of the scheduling decreases due to the imbalance of the equipments and the concentration of selling energy to power grid at same time. This paper proposes a new scheduling method to operate multi smart houses totally by virtually sharing their equipments. The proposed method can improve the imbalance of the equipments and reduce the amount of disposal energy. By computer simulation, it is shown that the proposed method can reduce over 16 % the energy cost to the conventional method.
Distributed energy resources can provide power to local loads in the electric distribution system and benefits such as improved reliability. Microgrids are intentional islands formed at a facility or in an electrical distribution system that contains at least one distributed resource and associated loads. Microgrids that operate both electrical generation and loads in a coordinated manner can offer additional benefits to the customer and local utility. The loads and energy sources can be disconnected from and reconnected to the area or local utility with minimal disruption to the local loads, thereby improving reliability. This paper details the development and testing of a highspeed static switch for distributed energy and microgrid applications.
An approach to the design of a transaction agreement in an
electric power pool is proposed. The electricity exchange takes place
over a fixed time interval in a stochastic environment. The incentive
for the electricity exchanges is due to disparity in the time patterns
of the marginal operating costs between the utilities. Electricity
produced at the different periods is used as the medium of exchange and
no monetary payments between the utilities take place. The exchange
policy is chosen so that the savings are distributed to the participants
in an equitable manner. The contract definition problem is approached
from the point of view of cooperative game theory. Because of the
uncertainty, the contract is adjusted at each period so that fair
division of the cost savings is obtained
Status and Trends in the U.S. Voluntary Green Power Market
- J Heeterm
- T Nicholas
J. Heeterm, T. Nicholas, "Status and Trends in the U.S.
Voluntary Green Power Market (2012 Data)", NREL Technical
Report NREL/TP-6A20-60210, October 2013
NOBEL-a neighborhood oriented brokerage electricity and monitoring system
- A Marqúes
- M Serrano
- S Karnouskos
- P J Marŕon
- R Sauter
- E Bekiaris
- E Kesidou
- J Oglund
A. Marqúes, M. Serrano, S. Karnouskos, P. J. Marŕon, R. Sauter,
E. Bekiaris, E. Kesidou, and J. H oglund, "NOBEL-a
neighborhood oriented brokerage electricity and monitoring
system," in 1st Int. ICST Conference on E-Energy, 2010.