The combined cooling, heating and power (CCHP) system is a typical distributed, electricity-gas integrated energy scheme in a community. First, it generates electricity by use of gas, and then exploits the waste heat to supply community with heat and cooling. In this paper, we consider a smart city consisting of a number of communities (CCHPs) and an agent of power grid (APG), where CCHPs can sell energy to the APG according to its bid. To study all utilities of entities in such a city from energy trading, a noncooperative Stackelberg game between APG and CCHPs is formulated. Here, the APG gives a bid for buying the energy from CCHPs, then CCHPs respond to the APG with their optimal energy supply that maximizing their utilities according to this bid. We show that the maximum profit to the APG and utilities to the CCHPs can be obtained at the Stackelberg equilibrium, which is guaranteed to exist and unique. Because the complete information about energy supply of each CCHP is unknown to the APG in advance, we propose a distributed algorithm that is able to find the point of equilibrium through a limited number of iterations. Taking privacy protection and transaction security into consideration, we design a blockchain-enabled energy management system. This system is composed of Internet of Energy (IoE) sub-system and blockchain sub-system, where the information interactions as well as energy transactions between APG and CCHPs can be carried out effectively and safely. Finally, security analysis and numerical simulations show the effectiveness and accuracy of our proposed mechanism.
The combined cooling, heating and power (CCHP) system is a typical distributed, electricity-gas integrated energy scheme in a community. First, it generates electricity by use of gas, and then exploits the waste heat to supply community with heat and cooling. In this paper, we consider a smart city consisting of a number of communities (CCHPs) and an agent of power grid (APG), where CCHPs can sell energy to the APG according to its bid. To study all utilities of entities in such a city from energy trading, a noncooperative Stackelberg game between APG and CCHPs is formulated. Here, the APG gives a bid for buying the energy from CCHPs, then CCHPs respond to the APG with their optimal energy supply that maximizing their utilities according to this bid. We show that the maximum profit to the APG and utilities to the CCHPs can be obtained at the Stackelberg equilibrium, which is guaranteed to exist and unique. Because the complete information about energy supply of each CCHP is unknown to the APG in advance, we propose a distributed algorithm that is able to find the point of equilibrium through a limited number of iterations. Taking privacy protection and transaction security into consideration, we design a blockchain-enabled energy management system. This system is composed of Internet of Energy (IoE) sub-system and blockchain sub-system, where the information interactions as well as energy transactions between APG and CCHPs can be carried out effectively and safely. Finally, security analysis and numerical simulations show the effectiveness and accuracy of our proposed mechanism.
Nowadays, unlike depleting fossil fuel resources, the integration of different types of renewable energy, as distributed generation sources, into power systems is accelerated and the technological development in this area is evolving at a frantic pace. Thus, inappropriate use of them will be irrecoverably detrimental. The power industry will reach a turning point in the pervasiveness of these infinite energy sources by three factors. Climate changes due to greenhouse gas accumulation in the atmosphere; increased demand for energy consumption all over the world, especially after the genesis of Bitcoin and base cryptocurrencies; and establishing a comprehensive perspective for the future of renewable energy. The increase in the pervasiveness of renewable energy sources in small-scale brings up new challenges for the power system operators to manage an abundant number of small-scale generation sources, called microsources. The current structure of banking systems is unable to handle such massive and high-frequency transactions. Thus the incorporation of cryptocurrencies is inevitable. In addition, by utilization of IoT-enabled devices, a large body of data will be produced must be securely transferred, stored, processed, and managed in order to boost the observability, controllability, and the level of autonomy of the smart power systems. Then the appropriate controlling measures must be performed through control signals in order to serve the loads in a stable, uninterruptible, reliable, and secure way. The data acquires from IoT devices must be analyzed using artificial intelligence methods such as big data techniques, data mining, machine learning, etc. with a scant delay or almost real-time. These measures are the controversial issues of modern power systems, which are yet a matter of debate. This study delves into the aforementioned challenges and opportunities, and the corresponding solutions for the incorporation of IoT and blockchain in power systems, particularly in the distribution level and residential section, are addressed. In the last section, the role of IoT in smart buildings and smart homes, especially for energy hubs schemes and the management of residential electric vehicle supply equipment is concisely discussed.
The increase of the number of electric vehicles leads to serious valley imbalance in the power grid. In order to achieve peak cutting and valley filling, according to the energy storage characteristics of electric vehicles, this paper proposes an electric vehicle group (EVG) energy trading method based on smart contract and double auction matching mechanism, and constructs the electric energy transaction process of the electric vehicle and electric vehicle in the electric vehicle group under the unbalanced load of the power grid. Through deploying the double auction matching algorithm to the smart contract, the automatic execution of matching transaction and automatic clearing of transaction cost are realized, which saves the economic cost of manual matching mode. In addition, the multi-stage quotation method proposed greatly improves the number of transactions. The simulation experiment based on Monte Carlo simulation shows that the power transaction method can not only effectively alleviate the valley problem of power grid load, achieve the effect of reducing and raising Valley, but also can improve the transaction efficiency.
The future of renewable energy transportation and distribution is dynamic and complex, with distributed renewable resources in required distributed control. It is suggested that Distributed Ledger Technology (DLT) is a timely innovation with the potential to facilitate this future. The transition to full renewable energy requires an infrastructure capable of handling intermittent production that has a low marginal cost. This requires a distributed control logic where devices with embedded intelligence coordinate local production, a decentralized energy market where prices are not primarily based on production, and an underlying digital infrastructure to enable both. Simulations and experiments have demonstrated great potential in such a digital infrastructure, but real-life tests have identified scalability as a remaining challenge. In this paper, we propose a DLT-based architecture for the energy grid with the development of existing solution concepts by implementing scalability solutions. To this end, we derive energy market components as a framework for building efficient microgrid. Then, we discuss the microgrid as a case study of such a market according to the required components within energy production, transmission, and distribution; distributed ledger platform operations, IoT device manufacturing,; software development; and research in IoT, edge and cloud computing, and energy systems.
Gijs van Leeuwen, Tarek AlSkaif, Madeleine Gibescu, Wilfried van Sark
In this paper, an integrated blockchain-based energy management platform is proposed that optimizes energy flows in a microgrid whilst implementing a bilateral trading mechanism. Physical constraints in the microgrid are respected by formulating an Optimal Power Flow (OPF) problem, which is combined with a bilateral trading mechanism in a single optimization problem. The Alternating Direction Method of Multipliers (ADMM) is used to decompose the problem to enable distributed optimization and a smart contract is used as a virtual aggregator. This eliminates the need for a third-party coordinating entity. The smart contract fulfills several functions, including distribution of data to all participants and executing part of the ADMM algorithm. The model is run using actual data from a prosumer community in Amsterdam and several scenarios of the model are tested to evaluate the impact of combining physical constraints and trading on social welfare of the community and scheduling of energy flows. The scenario variants are trade-only, where only a trading mechanism is implemented, grid-only where only OPF optimization is implemented and a combined scenario where both are implemented. Results are compared with a baseline scenario. Simulation results show that import costs of the whole community are reduced by 34.9% as compared to a baseline scenario, and total energy import quantities are reduced by 15%. Total social welfare is found to be highest without a trading mechanism, however this platform is only viable when all costs are equally shared between all households. Furthermore, peak imports are reduced by over 50% in scenarios including grid constraints.
The International Energy Agency has projected that the total energy demand for electricity in sub-Saharan Africa (SSA) is expected to rise by an average of 4% per year up to 2040. It implies that ~620 million people are living without electricity in SSA. Going with the 2030 vision of the United Nations that electricity should be accessible to all, it is important that new technology and methods are provided. In comparison to other nations worldwide, smart grid (SG) is an emerging technology in SSA. SG is an information technology-enhanced power grid, which provides a two-way communication network between energy producers and customers. Also, it includes renewable energy, smart meters, and smart devices that help to manage energy demands and reduce energy generation costs. However, SG is facing inherent difficulties, such as energy theft, lack of trust, security, and privacy issues. Therefore, this paper proposes a blockchain-based decentralized energy system (BDES) to accelerate rural and urban electrification by improving service delivery while minimizing the cost of generation and addressing historical antipathy and cybersecurity risk within SSA. Additionally, energy insufficiency and fixed pricing schemes may raise concerns in SG, such as the imbalance of order. The paper also introduces a blockchain-based energy trading system, which includes price negotiation and incentive mechanisms to address the imbalance of order. Moreover, existing models for energy planning do not consider the effect of fill rate (FR) and service level (SL). A blockchain levelized cost of energy (BLCOE) is proposed as the least-cost solution that measures the impact of energy reliability on generation cost using FR and SL. Simulation results are presented to show the performance of the proposed model and the least-cost option varies with relative energy generation cost of centralized, decentralized and BDES infrastructure. Case studies of Burkina Faso, Cote d'Ivoire, Gambia, Liberia, Mali, and Senegal illustrate situations that are more suitable for BDES. For other SSA countries, BDES can cost-effectively service a large population and regions. Additionally, BLCOE reduces energy costs by approximately 95% for battery and 75% for the solar modules. The future BLCOE varies across SSA on an average of about 0.049 $/kWh as compared to 0.15 $/kWh of an existing system in the literature.
The optimal deployment of heterogeneous energy storage (HES), mainly consisting of electrical and thermal energy storage, is essential for increasing the holistic energy utilization efficiency of multienergy systems. Consequently, this article proposes a risk-averse method for HES deployment in a residential multienergy microgrid (RMEMG), considering the diverse uncertainties and multienergy demand-side management (DSM). Apart from the HES size and location planning, its optimal investment phase is also determined by maximizing the system equivalent daily profit (EDP) and minimizing the risk. To handle the system uncertainties from renewable energy sources, power demands, outdoor temperature, and residential hot water needs, the multistage adaptive stochastic optimization approach is utilized. Then, through the constraint linearization and stochastic scenario sampling, the original nonlinear deployment model is converted to a mixed-integer linear programming one and tested on an IEEE 33-bus distribution network based RMEMG. The effectiveness of the proposed method is verified by comparing it with the existing practices. The comparison results indicate that the proposed risk-averse deployment method can effectively increase the system EDP and more immune to the uncertainties. Besides, this method can be practically applied for the emerging RMEMGs, such as smart buildings, intelligent homes, etc., which get long-term DSM contracts.
With the integration of highly permeable renewable energy to the grid at different levels (transmission, distribution and grid-connected), the volatility on both sides (source side and load side) leading to bidirectional power flow in the power grid complicates the control mechanism. In order to ensure the real-time power balance, energy exchange, higher energy utilization efficiency and stability maintenance in the electric power system, this paper proposes an integrated application of blockchain technology on energy routers at transmission and distribution networks with increased renewable energy penetration. This paper focuses on the safe and stable operation of a highly penetrated renewable energy grid-connected power system and its operation. It also demonstrates a blockchain-based negotiation model with weakly centralized scenarios for “source-network-load” collaborative scheduling operations; secondly, the QoS (quality of service) index of energy flow control and energy router node doubly-fed stability control model were designed. Further, it also introduces the MOPSO (multi-objective particle swarm optimization) algorithm for power output optimization of multienergy power generation; Thirdly, based on the blockchain underlying architecture and load prediction value constraints, this paper puts forward the optimization mechanism and control flow of autonomous energy coordination of b2u (bottom-up) between router nodes of transmission and distribution network based on blockchain.
Being a decentralized system makes Blockchain a suitable technology solution in many cases. The Smart Energy domain has the potential to benefit from the use of Blockchain, by improving data and transaction management, through applications such as peer-to-peer energy trading, grid enhancement, and electric vehicle support. Many researchers have proposed models and prototypes of blockchain-based applications, which are expected to improve the performance of smart energy systems. In this report, a qualitative literature review was performed to look into a sample of these application proposals and to try to identify the impacts of blockchain technology in Smart Energy. This resulted in the discovery of both positive and negative factors. The beneficial factors include increased security, improved data privacy, data transparency and immutability, removal of third-party control and trust, ubiquitous solution, and greater data accessibility. The list of challenges includes limited scalability and speed, off-chain support requirement, high establishment and maintenance cost, and requiring further practical tests. One of the interesting findings is that the impact of Blockchain technology as to whether it may increase or decrease transaction costs is still unclear. Finally, the paper recommends that a future study may focus on economic feasibility and transaction costs, and ascertain which Smart Energy cases and application designs are more appropriate for Blockchain technology.
Bogdan-Constantin Neagu, Ovidiu Ivanov, Gheorghe Grigoraş, Mihai Gavrilaș
A growing number of households benefit from the government subsidies to install renewable generation facilities such as PV panels, used to gain independence from the grid and provide cheap energy. In the Romanian electricity market, these prosumers can sell their generation surplus only at regulated prices, back to the grid. A way to increase the number of prosumers is to allow them to make higher profit by selling this surplus back into the local network. This would also be an advantage for the consumers, who could pay less for electricity exempt from network tariffs and benefitting from lower prices resulting from the competition between prosumers. One way of enabling this type of trade is to use peer-to-peer contracts traded in local markets, run at microgrid (μG) level. This paper presents a new trading platform based on smart peer-to-peer (P2P) contracts for prosumers energy surplus trading in a real local microgrid. Several trading scenarios are proposed, which give the possibility to perform trading based on participants’ locations, instantaneous active power demand, maximum daily energy demand and the principle of first come first served implemented in an anonymous blockchain trading ledger. The developed scheme is tested on a low-voltage (LV) microgrid model to check its feasibility of deployment in a real network. A comparative analysis between the proposed scenarios, regarding traded quatities and financial benefits is performed.
Mark Stefan, Paul Zehetbauer, Stephan Cejka, Franz Zeilinger · 5 authors
Energy communities will be an essential element of the future energy system. Especially renewable energy communities are gaining high attention in many European countries and their implementation, characteristics and use cases are elaborated in many research and development activities all around the world. Within the Austrian research project Blockchain Grid, a blockchain-based renewable energy community is implemented and field-tested in Heimschuh, Styria. It supports different technical applications like self-consumption optimisation and peer-to-peer energy trading for customers and a novel approach for grid capacity management supporting distribution system operators. These use cases have been implemented and validated in simulative studies showing promising potential for total energy costs for energy community members.
Miguel Gayo-Abeleira, Carlos Santos, Francisco J. Rodríguez, Pedro Martı́n · 6 authors
Since the advent of the microgrid (MG) concept, almost two decades ago, the energy sector has evolved from a centralized operational approach to a distributed generation paradigm challenged by the increasing number of distributed energy resources (DERs) mainly based on renewable energy. This has encouraged new business models and management strategies looking for a balance between energy generation and consumption, and promoting an efficient utilization of energy resources within MGs and minimizing costs for the market participants. In this context, this paper introduces an efficient management strategy, which is aimed at obtaining a fair division of costs billed by the utilities, without relying on a centralized utility or MG aggregator, through the design of a local event-based energy market within the MG. This event-driven MG energy market operates with blockchain (BC) technology based on smart contracts for electricity transactions to both guarantee veracity and immutability of the data and automate the transactions. The event-based energy market approach focuses on two of the design limitations of BC, namely the amount of information to be stored and the computational burden, which are significantly reduced while maintaining a high level of performance. Furthermore, the prosumer data is obtained by using IEC 61850 standard-based commands within the BC framework. By doing so, the system is compatible with any device irrespective of the manufacturer implementing the IEC 61850 standard. The advantages of this management approach are considerable for: MG participants, in terms of financial benefits; the MG itself, as it can operate more independently from the main grid; and the grid since the MG becomes less unpredictable due to the internal energy exchanges. The proposed strategy is validated on an experimental setup employing low-cost devices.
Our energy scenario is nowadays shaped by progressive electrification of energy final use. In this context, electricity networks are seeing a growing multitude of distributed assets entering from the edges of the grid and acquiring new ICT capabilities that were limited before to a restricted number of major players. Particularly, assets like Photovoltaic Inverter (PvI), Electric Vehicle (EV) chargers, wind turbines controllers, programmable loads, storage systems, and other Distributed Energy Resources (DER) are now able to communicate through different technologies and make conscious choices under human-decisions or even independently. This is leading to a decentralization of the system's view by increasing single actor independence. Notwithstanding, a problem arises when current centrally-managed electricity networks struggle to coordinate massive amounts of new figures and adapt to this new decentralized paradigm. Therefore, a decentralized coordination-and-control framework will ensure better integration of s and new figures as prosumers, while allowing higher exploitation of their potential compared to centrally managed systems. This article seeks in Blockchains the enabling technology for designing and supporting such a grid infrastructure. It develops a first framework to address this need by envisioning a grid-system based on the direct participation of nowadays-used embedded-energy-devices within a decentralized platform hosting specific coordination procedures. The platform was developed in an experimental research campaign performed at ABB Laboratories basing on embedded-devices currently designed as control-connectivity boards for smart-inverters. Therefore this article introduces the background theory and reasons behind this proposed system. The intent here is not to give all the specific details of the implementation, but introduce the supporting reason, high-level design, and required characteristic of the Blockchain-based platform for coordinating grid operations. Blockchain technology is seen here as the appropriate technology to enable the realization of a multi-actor energy-management system and enable distributed coordination in power grids.
In efforts to meet the targets of carbon emissions reduction in power systems, policy makers formulate measures for facilitating the integration of renewable energy sources and demand side carbon mitigation. Smart grid provides an opportunity for bidirectional communication among policy makers, generators and consumers. With the help of smart meters, increasing number of consumers is able to produce, store, and consume energy, giving them the new role of prosumers. This thesis aims to address how smart grid enables prosumers to be appropriately integrated into energy markets for decarbonising power systems. \n \nThis thesis firstly proposes a Stackelberg game-theoretic model for dynamic negotiation of policy measures and determining optimal power profiles of generators and consumers in day-ahead market. Simulation results show that the proposed model is capable of saving electricity bills, reducing carbon emissions, and increasing the penetration of renewable energy sources. Secondly, a data-driven prosumer-centric energy scheduling tool is developed by using learning approaches to reduce computational complexity from model-based optimisation. This scheduling tool exploits convolutional neural networks to extract prosumption patterns, and uses scenarios to analyse possible variations of uncertainties caused by the intermittency of renewable energy sources and flexible demand. Case studies confirm that the proposed scheduling tool can accurately predict optimal scheduling decisions under various system scales and uncertain scenarios. Thirdly, a blockchain-based peer-to-peer trading framework is designed to trade energy and carbon allowance. The bidding/selling prices of individual prosumers can directly incentivise the reshaping of prosumption behaviours. Case studies demonstrate the execution of smart contract on the Ethereum blockchain and testify that the proposed trading framework outperforms the centralised trading and aggregator-based trading in terms of regional energy balance and reducing carbon emissions caused by long-distance transmissions.
Ever since the invention of Bitcoin by the pseudonymous Satashi Nakamoto, cryptocurrency has provoked debate in banking and finance sectors, and is sometimes considered a potential successor to fiat currency. Blockchain, the new technology underpinning decentralised and immutable databases, has seen much discussion as a potentially game-changing development. Although many industries are exploring its value, the technology has thus far made only minor impacts. A rapidly expanding base of research has emerged on blockchain's role as a potential disruptor in the electrical energy industry. However, it may be difficult to distinguish hype from more imminently plausible impacts. This paper attempts to serve as a guide for engineering management wishing to make sense of blockchain's potential in electricity. This is accomplished by formulating a novel blockchain industry disruption framework, which exists across three tiers. These tiers extend from ideas with the least effect on an industry to total revolutionary concepts that could completely transform an industry. This taxonomy is constructed by examining existing research into disruption hierarchies and blockchain classification methods. Through the lens of this taxonomy, a literature review is performed on blockchain's role in energy to draw out themes and ideas characterising each tier. The potential likelihood of real-world application of various ideas are discussed, giving consideration to how established industries may be affected or disrupted. The authors provide some conjecture here. Finally, courses of action are suggested for those whose sector may be affected by blockchain.
In an integrated energy distribution system (IEDS), an energy hub has been introduced and deemed to be a suitable tool for managing and integrating multi-party energy forms. Due to different energies having diverse characteristics and being coupled with each other, it is difficult for an energy hub to implement the optimal scheduling of multiple energy sources. Therefore, an energy optimization management model is proposed based on the Stackelberg game, which considers the exergy conversion of multi-party energy sources in different operation modes. The problem is solved by the two-layer distributed optimization algorithm, in which the energy hub acts as the leader and is followed by the users. Furthermore, in order to alleviate the deception, malicious tampering, subpeption, and other secure risks in energy trading, blockchain is introduced into the energy hub and the concept of exergy coin (EC) is proposed. A credit-based blockchain framework and concurrent block building consensus process is explored to reduce the calculation cost and promote the exergy trading efficiency. Finally, the case study shows how the proposed method can effectively optimize energy scheduling and configure a more reasonable energy solution.
With the development and expansion of smart grid systems, vehicle-to-grid (V2G) has become a new type of energy interaction based on Internet of Electric Vehicles (IoEVs). By leveraging the charging/discharging capabilities of EVs, V2G can be implemented in smart grid to enable intelligent energy transactions and reduce the unbalance of supply and demand. However, the implementation of interaction between the existing V2G technology and IoEVs faces the problems of high-complexity energy transaction management, insufficient computing capability, poor scalability, and lack of incentive mechanisms. The three-tier bi-directional energy transaction management strategies based on game and contract theory have been proposed. Firstly, the optimal pricing and EV discharging strategy is obtained based on the non-cooperative Stackelberg game and the energy-price equilibrium. Secondly, in order to optimize the utility of EAG, the information asymmetry incentive mechanism based on contract theory is proposed. This mechanism can effectively stimulate EVs to contribute to V2G energy transaction and further improve social benefits considering the energy transmission loss and battery life cycle degradation. To reduce the communication as well as processing latency and improve the efficiency of energy transaction management, edge computing has been incorporated. Simulation results show that the performance of the proposed scheme significantly outperforms other existing schemes under various scenarios.
Eduardo Francisco, Luís Tiago Ferreira, Carlos Silva, Joaquim Braga
The electric vehicle (EV) market is evolving fast with an expected high penetration of EV in the coming years. These EVs are dependent on charging infrastructure and since most charging will happen at home this will bring challenges to the low-voltage distribution network. The main challenge addressed in this study is the available grid capacity and what could be done to prevent the massive request of residential buildings grid connection reinforcements, which represents significant costs to consumers, large waiting times, which are not compatible with the rising necessities for charging EV and a general oversizing of the distribution network, which will drive the already low utilisation factors even lower. The presented solution for this challenge is to introduce a flexible power grid connection, which takes advantage of smart charging technology and the applications of flexible power contracts to allow the charging of 5–7 times more EV in the common garages of residential buildings without any building grid connection reinforcement and for a fraction of the cost. The distribution system operator (DSO) will represent a key role in the implementation of this solution, not only regarding the technical aspects but also regarding the onboarding of the consumers.
Martin Onyeka Okoye, Junyou Yang, Jia Cui, Zhenjiang Lei · 9 authors
In the power sector, microgrids play a supportive role in bridging the adequacy gap in the conventional electricity supply. Trading of the generated energy has recently been improved by blockchain technology which offers a new cheap, secure, and decentralized transaction approach. Its operation is however associated with an undesired inherent delay during energy transactions initiated by the prosumers, thus, failure to timely attend to incidences of urgent demand could end up in catastrophe at the consumer's side. This article thus proposes a cyber-enhanced transactive microgrid model using blockchain technology with optimized participants' permission protocol to ameliorate this challenge. It is demonstrated that the optimized blockchain participants' permission model leads to improved transaction speed and greater convenience. The transaction speed simulation is thereafter performed and it was also demonstrated that the node population has a greater effect than the transaction block size on the transaction speed improvement.
The rapid growth of renewable energy has increased the requirements of the smart grid for communication and processing capabilities. As an effective solution to collect and manage information, the wireless network can improve the efficiency of renewable energy management. But due to the wireless data transmission risk and centralized power trading, the smart grid employing wireless networks cannot guarantee the security of the electricity market and the high consumption of renewable energy. Recently, as an emerging data-sharing technology, the blockchain has attracted widespread attention and is considered to have the potential to solve above problems. In this paper, we propose a blockchain-enabled secure power trading mechanism for the smart grid employing wireless networks. The blockchain is introduced to record power data collected by the wireless network, and the smart contract can make reasonable trading decisions based on this. The dual-chain structure composed of local energy trading blockchain and renewable energy trading blockchain improves the efficiency of power trading and renewable energy consumption. To strengthen the stability of renewable energy producers and expand their scale, we also design a blockchain-enabled renewable energy incentive mechanism. Finally, the modified Southern California Edison 56 bus test feeder model validated our mechanism.
Maria Luisa Di Silvestre, Pierluigi Gallo, Eleonora Riva Sanseverino, Giuseppe Sciumè · 5 authors
This article describes the possibility of using the blockchain technology for load and generation aggregation in a new distributed demand response (DR) service and customer remuneration system. The blockchain technology and the use of smart contracts for DR allow the creation of a distributed system, in which customers can communicate directly, in a transparent, secure, and traceable way, with the grid operator to provide their flexibility. In this article, the DR problem formulation takes into account several aspects, which are periodically executed. First, the blockchain records customers' energy consumption or production; then, the smart contract starts calculating the baseline and the potential support provided by each customer to fulfill the requested load adaptation. Customers' availability for generation and load profile modulation is also taken into account, as well as their privacy and an updated definition of the roles of grid and market operators in a new DR scenario supported by the blockchain technology. The blockchain used is Hyperledger Fabric, since it turned to be flexible for smart contract implementation while supporting multitenancy. Results show the possibility of successfully applying the blockchain technology to this particular topic, even considering privacy-preserving issues.
A Virtual Power Plant (VPP) is a network of distributed power generating units, flexible power consumers, and storage systems. A VPP balances the load on the grid by allocating the power generated by different linked units during periods of peak load. Demand-side energy equipment, such as Electric Vehicles (EVs) and mobile robots, can also balance the energy supply-demand when effectively deployed. However, fluctuation of the power generated by the various power units makes the supply power balance a challenging goal. Moreover, the communication security between a VPP aggregator and end facilities is critical and has not been carefully investigated. This paper proposes an AI-enabled, blockchain-based electric vehicle integration system, named AEBIS for power management in a smart grid platform. The system is based on an artificial neural-network and federated learning approaches for EV charge prediction, in which the EV fleet is employed as a consumer and as a supplier of electrical energy within a VPP platform. The evaluation results show that the proposed approach achieved high power consumption forecast with R2score of 0.938 in the conventional training scenario. When applying a federated learning approach, the accuracy decreased by only 1.7%. Therefore, with the accurate prediction of power consumption, the proposed system produces reliable and timely service to supply extra electricity from the vehicular network, decreasing the power fluctuation level. Also, the employment of AI-chip ensures a cost-efficient performance. Moreover, introducing blockchain technology in the system further achieves a secure and transparent service at the expense of an acceptable memory and latency cost.