Distributed peer-to-peer power energy markets are emerging quickly. Due to central governance and lack of effective information aggregation mechanisms, energy trading cannot be efficiently scheduled and tracked. We devise a new distributed energy transaction system over the energy Industrial Internet of Things based on predictive analytics, blockchain, and smart contract technologies. We propose a solution for scheduling distributed energy sources based on the Minimum Cut Maximum Flow theory. Blockchain is used to record transactions and reach consensus. Payment clearing for the actual power consumption is executed via smart contracts. Experimental results on real data show that our solution is practical and achieves a lower total cost for power energy consumption.
Abstract Renewable-energy resources require overwhelming adoption by the common masses for safeguarding the environment from pollution. In this context, the prosumer is an important emerging concept. A prosumer in simple terms is the one who consumes as well as produces electricity and sells it either to the grid or to a neighbour. In the present scenario, peer-to-peer (P2P) energy trading is gaining momentum as a new vista of research that is viewed as a possible way for prosumers to sell energy to neighbours. Enabling P2P energy trading is the only method of making renewable-energy sources popular among the common masses. For making P2P energy trading successful, blockchain technology is sparking considerable interest among researchers. Combined with smart contracts, a blockchain provides secure tamper-proof records of transactions that are recorded in distributed ledgers that are immutable. This paper explores, using a thorough review of recently published research work, how the existing power sector is reshaping in the direction of P2P energy trading with the application of blockchain technology. Various challenges that are being faced by researchers in the implementation of blockchain technology in the energy sector are discussed. Further, this paper presents different start-ups that have emerged in the energy-sector domain that are using blockchain technology. To give insight into the application of blockchain technology in the energy sector, a case of the application of blockchain technology in P2P trading in electrical-vehicle charging is discussed. At the end, some possible areas of research in the application of blockchain technology in the energy sector are discussed.
The aim of this work is to provide an up-to-date comprehensive review of the peer-reviewed articles, the research projects and the entrepreneurial efforts that consider the utilization of blockchain technology in the energy sector in general and the power grid in particular. Through our review study we systematically classify existing applications of blockchain technology in the energy sector according to their field of activity. The comprehensive and holistic picture provided aims to contribute to the body of knowledge of the applicability of blockchain technology within the energy sector and pave the way for further research in this field.
A blockchain, which is well known as one of the distributed ledgers, has attracted in many research fields. In this paper, we discuss the effectiveness and limitation of a blockchain in distributed optimization. In distributed optimization, the original problem is decomposed, and the local problems are solved by multiple agents. In this paper, ADMM (Alternating Direction Method of Multipliers) is utilized as one of the powerful methods in distributed optimization. In ADMM, an aggregator is basically required for collecting the computation result in each agent. Using blockchains, the function of an aggregator can be contained in a distributed ledger, and an aggregator may not be required. As a result, tampering from attackers can be prevented. As an application, we consider energy management systems (EMSs). By numerical experiments, the effectiveness and limitation of blockchain-based distributed optimization are clarified.
With the booming of smart grid, The ubiquitously deployed smart meters constitutes an energy internet of things. This paper develops a novel blockchain-based transactive energy management system for IoT-aided smart homes. We consider a holistic set of options for smart homes to participate in transactive energy. Smart homes can interact with the grid to perform vertical transactions, e.g., feeding in extra solar energy to the grid and providing demand response service to alleviate the grid load. Smart homes can also interact with peer users to perform horizontal transactions, e.g., peer-to-peer energy trading. However, conventional transactive energy management method suffers from the drawbacks of low efficiency, privacy leakage, and single-point failure. To address these challenges, we develop a privacy-preserving distributed algorithm that enables users to optimally manage their energy usages in parallel via the smart contract on the blockchain. Further, we design an efficient blockchain system tailored for IoT devices and develop the smart contract to support the holistic transactive energy management system. Finally, we evaluate the feasibility and performance of the blockchain-based transactive energy management system through extensive simulations and experiments. The results show that the blockchain-based transactive energy management system is feasible on practical IoT devices and reduces the overall cost by 25%.
In order to improve the economy and safety of multi-microgrids (MMGs) scheduling, this paper proposes a research on MMGs scheduling strategy that takes into account dynamic electricity prices based on the blockchain. We first introduce the principle of blockchain, analyze the security and economy of the combination of blockchain and MMGs scheduling, and design the scheduling architecture and process based on the blockchain platform. Second, we set a dynamic electricity price model according to the total power supply and demand of MMGs, and set a load optimization model. Finally, we take optimal system economy and minimum environmental pollution as the objective function, then use the linear programming method and the improved krill herd algorithm (KHA) with nonlinear changes in weights to solve the problem. The simulation results show that: (1) The dynamic electricity prices can reflect the power supply and demand of microgrids and optimize the load; (2) Comparing the three scheduling schemes, the strategy in this paper can improve the economic and environmental protection of MMGs by 37.33% and 39.34%, while reduce the interactive power between the microgrid and the distribution network by 56.28%, and the curtailment rate by 63.22%; (3) The improved krill herd algorithm has higher convergence speed and convergence accuracy;(4) The blockchain technology can ensure the security of scheduling data.
Shuguo Chen, Weibin Ding, Zhongzheng Xiang, Yuanyuan Liu
The power trading system has the characteristics of nonlinearity, dynamics, and complexity. Part of the business data in the trading system needs to be exposed to numerous external business systems. The traditional centralized power trading model has some problems, such as low data security and trust crisis of regulators. Blockchain technology provides prominent ideas for solving these problems. Firstly, the improved AdaBoost algorithm is used to predict the supply and demand gap of power trading nodes. Secondly, based on the fact that the information on the blockchain is only open to the power supply side, a two‐stage game model of asymmetric information between the power supply side and the power user is constructed to capture the price competition behavior between them in order to find the Nash equilibrium price in two stages. Finally, the US PJM market electricity market data are used to carry out an example analysis to verify the effectiveness of the algorithm and model.
Zhichao Ren, Wei Wang, Bo Chen, Xin Li · 7 authors
With the increase of the penetration rate of distributed generation on the distribution network side, the access of a large number of prosumers makes the trading information massive, and the demand of prosumers for more flexible power trading mechanism is also strengthened. Therefore, a weak-centralized power trading mode based on blockchain is proposed in this paper. Trading information is automatically stored in the blockchain in the form of smart contracts. The centralized organization only manages congestion and does not participate in the process of trading matching and settlement. In the distributed security verification, the successive over relaxation (SOR) iterative method is improved in this paper, which improves the iterative efficiency and convergence stability of the distributed algorithm. Finally, a case consisting of six nodes is presented to verify the feasibility of the method.
Adamu Sani Yahaya, Nadeem Javaid, Ahmad Almogren, Abrar Ahmed · 6 authors
Local energy trading has attracted the attention of many researchers as a result of its promising benefits. These benefits include minimizing gas emission, reducing power shortage, and establishing a competitive energy market. However, the energy trading between several prosumers causes trust, security, and privacy challenges in energy systems. On the other hand, a single point of failure and an increase in overall system cost occur when the energy system is managed using a centralized model. Therefore, to tackle the mentioned issues, this work proposes a two-layered secure Peer-to-Peer (P2P) energy trading model based on blockchain. The proposed model has two layers: authentication, and secure energy trading. In the authentication layer, in order to protect the proposed model from impersonation attacks, a mutual authentication process is implemented. In the energy trading layer, a new consensus mechanism is proposed to minimize the number of malicious validators. Afterwards, an incentive-punishment algorithm is introduced to motivate energy prosumers to contribute more energy in the model. Next, a dynamic contract theory based on supply-demand ratio pricing scheme is proposed. The purpose of the proposed pricing scheme is to solve the issues associated with the existing pricing schemes. It also preserves the privacy of the actual energy consumption behavior of the trading participants. Furthermore, a consensus mechanism validators’ selection model is proposed. The aim of the proposed work is to have an efficient and secure P2P energy trading platform. Simulations are executed to show the performance of the proposed model in terms of communication and computational costs, reputation, energy contributed, reward, and prices. The results for the authentication process show 7.45 ms computational cost and 1152 bits communication cost, which are better than the existing works. In the consensus process, 66.67% of the validators are selected to conduct the consensus for every transaction. This selection efficiently improves the consensus process and minimizes the number of malicious validators. In the proposed model, the increase in reward is observed for increased energy contribution, decreased non-malicious transactions and adjustment of energy consumption. The proposed model shows a satisfactory performance in terms of trust, security, and privacy.
The optimization problem for scheduling distributed energy resources (DERs) and battery energy storage systems (BESS) integrated with the power grid is important to minimize energy consumption from conventional sources in response to demand. Conventionally this optimization problem is solved in a centralized manner, limiting the size of the problem that can be solved and creating a high communication overhead because all the data is transferred to the central controller. These limitations are addressed by the proposed distributed consensus-based alternating direction method of multiplier (DC-ADMM) optimization algorithm, which decomposes the optimization problem into subproblems with private cost function and constraints. The distribution feeder is partitioned into low coupling subnetworks/regions, which solves the private subproblem locally and exchanges information with the neighboring regions to reach consensus. The relaxation strategy is employed for mixed-integer and coupled constraints introduced in the optimal power flow (OPF) problem by stationary and transportable BESS because DC-ADMM convergence is only guaranteed for strict convex problems. The information exchange and synchronization between subnetworks/regions are vital for distributed optimization. In this work, both of these aspects are addressed by the blockchain. The smart contract deployed on the blockchain network acts as a mediator for secure data exchange and synchronization in distributed computation. The blockchain-based distributed optimization problem's effectiveness is tested for a 0.5-MW laboratory microgrid for one hour ahead and day-ahead for the IEEE 123-bus and EPRI J1 test feeders, and results are compared with a centralized solution.
Vahid Hosseinnezhad, Barry Hayes, Brian O’Regan, Pierluigi Siano
Today, the development of decentralized energy management systems has accelerated due to the daily growth of renewable energy technologies and communications infrastructure. At the distribution system level, this approach has manifested itself with the emergence of the local energy market. In fact, the local energy market is becoming a new operating model to control local generation units. This paper describes the general architecture and elements used to implement a blockchain-based local energy market within a transactive management platform. After an overview of internet of things (IoT) communication technologies and the existing central-authority-based applications, the general structure and elements of peer-to-peer (P2P) networks are reviewed. Next, the concepts of blockchain-based technologies and the required specifications for different building layers are outlined based on the limited relevant literature available. The concepts and requirements are investigated to provide practical insights to design trading platforms.
Mohamed Hamouda, Mohammed E. Nassar, M.M.A. Salama
Inter-connected Microgrids (IMGs) have emerged as a promising structure for future grids, offering resilience and independence in energy exchangeability with neighbours. To enable such interconnected structure, an interconnected market between individual Microgrids (MGs) participating via an agent (i.e., Energy Management System [EMS]) is required. Each agent is Self-Benefit-Driven (SBD), which means that it works in the best interests of its own MG. Therefore, energy trading is established to enhance these benefits. In this paper, a new strategy is proposed for IMG energy trading that considers SBD actions for MGs' agents, and a unique utility function for each MG is defined. The function includes import and/or export benefits for each MG. Furthermore, the definition of the utility also considers the MG's different objectives when importing versus exporting. A centralized Nash bargaining model is proposed for IMG energy trading to ensure fair settlements through a central entity (e.g., Distributed System Operator [DSO]). The proposed algorithm is developed using an adapted blockchain that enhances the security and transparency of the platform. The effectiveness of the proposed strategy is verified using a number of case studies.
Ahmet Yagmur, Beyhan Adanur Dedetürk, Ahmet Soran, Jaesung Jung · 5 authors
This paper discusses blockchain-based energy applications from the distribution system operator (DSO) perspective. Blockchain has a potential impact on newly emergent actors, such as electric vehicles (EVs) and charging facility units (CFUs) of the electricity grid. Although Blockchain offers magnificent decentralized solutions, owing to the reality of the existing grid structure, the central management of DSOs still plays a significant, non-negligible role. Numerous studies of proposed blockchain-based EV systems have investigated the energy costs of EVs, fast and efficient charging, privacy and security, P2P energy trading, sharing economy, selection of appropriate CFUs location, and scheduling. However, cooperation with DSO organizations has not been adequately addressed. Blockchain-based solutions mainly suggest an entirely distributed and decentralized approach for energy trading; however, converting the entire power system infrastructure is considerably expensive. Building a thoroughly decentralized electricity network is nearly impossible in a short time, particularly at the national grid level. In this regard, the applicability of the solutions is as significant as their appropriateness, especially from the DSO perspective, and must be examined closely. We searched and analyzed the blockchain literature related to EVs, CFUs, DERs, microgrids, marketing, and DSOs to define the DSO-based requirements for potential blockchain applications in the energy sector, specifically EV evolution.
Optimal scheduling of reconfigurable interconnected microgrids is a precious and critical task for the residential consumers especially with the integration of renewable energy sources, dispatchable units and energy storage systems. In this regard, not only the optimal scheduling of the microgrids in a realistic and correlated environment is a necessity, but also the guarantied security and the prevention of cyber-attacks are mandatory tasks for the operators. This article first addresses these issues by developing a novel framework based on blockchain for secured data transaction from the individual microgrids’ components to the central control unit and then tries to find the optimal scheduling plan using stochastic programming based on point estimate method (PEM). Through such a hybrid PEM-blockchain based framework, the interconnected microgrids can supply the residential loads in a fully reliable, economic and secured structure. We also consider a social-economic framework to not only minimize the total operating cost of the microgrids, but also benefit the customers by enhancing the social factors through the optimal switching. Considering the complex and nonlinear nature of the problem, an effective corrected crow search (CCS) algorithm is deployed to find the most optimal operating point for the microgrids. The quality and capabilities of the proposed model are investigated using a practical residential interconnected microgrid. The results show that the optimal switching could reduce the total operation cost from $22,716 to $21,935 (3.56% reduction). Also, the average energy not supplied (AENS) has reduced from 1.4115 to 1.352 kWh/customer.yr (4.40% reduction), which are notable values. The results advocate the quality and functionality of the proposed framework.
Juan Carlos Olivares, Enrique Reyes‐Archundia, José Antonio Gutiérrez Gnecchi, Ismael Molina‐Moreno · 6 authors
The lowering cost of electricity generation technologies by renewable means has caused the role of end-users to change from being a simple consumer to a producer of their energy. This new role has been called a prosumer and has contributed to modifying electricity markets, by allowing prosumers to merchandize the energy surplus to electricity companies and other prosumers. The fundamental key to any economic transaction is trust between the parties. Recently, new technologies, such as blockchain, are transforming transaction security, and allowing decentralization of the smart power grid. This study presents the development of a transactional model of electrical energy using the infrastructure of smart metering and blockchain systems to allow the commercialization of electrical energy by prosumers. The results show that for the Mexican electricity market, they can be good alternatives by reducing subsidies and being more profitable than current rates.
Increasing electric vehicle (EV) penetration in distribution networks necessitate EV charging coordination. This paper proposes a two-stage EV charging coordination mechanism that frees the distribution system operator (DSO) from extra burdens of EV charging coordination. The first stage ensures that the total charging demand meets facility constraints, and the second stage ensures fair charging welfare allocation while maximizing the total charging welfare via Nash-bargaining trading. A decentralized algorithm based on the alternating direction method of multipliers (ADMM) is proposed to protect individual privacy. The proposed mechanism is implemented on the blockchain to enable trustworthy EV charging coordination in case a third-party coordinator is absent. Simulation results demonstrate the effectiveness and efficiency of the proposed approach.
The smart grid is emerging as a future paradigm for power networks. While it has many successful applications, peer-to-peer trading in the local energy market (LEM) is still challenging due to the lack of security and trading mechanisms. In this paper, we design a data-driven, secure, and smart solution DS2to address this problem. We first propose a five-layer design of LEM based on blockchain. We then model peer-to-peer trading in LEM as a cost minimization problem and derive an efficient online solution leveraging matrix factorization and integer linear programming. DS2is implemented and evaluated on a private Ethereum blockchain. We show that DS2achieves a mean absolute percentage error (MAPE) of 12.8% compared with the offline optimal method through extensive simulations on the real-world dataset.
The objective of this study is to introduce a new use case under smart energy cyber-physical-social system (CPSS) that brings together the competence of distributed ledger technology (DLT) and essence of peer-to-peer local energy markets. This use case involves donation sharing under a DLT-based charity system to support financially-disadvantaged citizens in covering their residential energy requirements in an anonymous and effective manner, as a means to contend the notorious energy poverty problem. Essential architecture and processes for such a sharing concept are discussed by adopting a layer-based representation of the smart energy CPSS. Fundamental step-by-step interactions among its functional layers for realizing prospective social welfare benefits are illustrated. Based on this framework, two distinct donation sharing mechanisms that work under a DLT-empowered local market setting are proposed. Operation of these donation sharing mechanisms are illustrated on a local energy market with resorting to a sample daily energy profile and a series of hybrid scenarios. Effect of donation sharing on accounts of market participants and charity system are detailed.
Daniël Reijsbergen, Zheng Yang, Aung Htein Maw, Tien Tuan Anh Dinh · 5 authors
Smart grids leverage data from smart meters to improve operations management and to achieve cost reductions. The fine-grained meter data also enable pricing schemes that simultaneously benefit electricity retailers and users. Our goal is to design a practical dynamic pricing protocol for smart grids in which the rate charged by a retailer depends on the total demand among its users. Realizing this goal is challenging because neither the retailer nor the users are trusted. The first challenge is to design a pricing scheme that incentivizes consumption behavior that leads to lower costs for both the users and the retailer. The second challenge is to prevent the retailer from tampering with the data, for example, by claiming that the total consumption is much higher than its real value. The third challenge is data privacy, that is, how to hide the meter data from adversarial users. To address these challenges, we propose a scheme in which peak rates are charged if either the total or the individual consumptions exceed some thresholds. We formally define a privacy-preserving transparent pricing scheme (PPTP) that allows honest users to detect tampering at the retailer while ensuring data privacy. We present two instantiations of PPTP, and prove their security. Both protocols use secure commitments and zero-knowledge proofs. We implement and evaluate the protocols on server and edge hardware, demonstrating that PPTP has practical performance at scale.
Mazin Debe, Haya R. Hasan, Khaled Salah, Ibrar Yaqoob · 5 authors
The massive adoption of electric vehicles (EVs) has caused an increasing demand for electric energy to charge the vehicles. Efficiently managing energy trading between energy providers and energy consumers can lead to meet the high demand for charging EVs while reducing its cost compared to traditional power provided by the utility company. However, a large portion of the existing systems leveraged for trading energy between EVs are centralized and fall short in providing transparency, reliability, audit, security, and trustworthy features. In this paper, we propose blockchain-based energy trading using an auctioning and reputation scheme. We develop Ethereum smart contracts which enable owners of EVs to automatically request electricity to charge their vehicles in a reliable, cost-effective, secure, and trustworthy manner. The proposed approach ensures the lowest rate available by implementing a reverse auctioning scheme for fair competition between providers to provide the requested service at the lowest cost. The proposed solution enforces high quality of service through a reputation-based approach that quantifies the performance of the service providers and gives an advantage to more reputable providers. We present the implementation details of the deployed system on a test Ethereum blockchain platform. We perform system testing and evaluation to validate and assess the functionality and performance of the proposed solution. Furthermore, we present security and cost analyses to show the affordability, robustness, and practicality of the proposed approach.
Pablo Mendez Royo, Jesús Rodríguez-Molina, Juan Garbajosa, Pedro Castillejo
Hardware solutions based on blockchain used in peer-to-peer electricity trading operations have been on rise during the last years. It is expected that due to their usage, it will become easier for prosumers to participate in the power grid on more equal terms when compared to the traditional players that have been settled in this market for the last decades. However, devices used to fully integrate prosumers are scarce and often offer minimal functionalities to perform the task of becoming integrated in those markets. This manuscript puts forward a Constrained Hardware Device enhanced with several software elements related to blockchain and cloud infrastructures, which make possible for any electricity generator or storage system to perform major actions like executing smart contracts, requesting energy prices to a Transmission System Operator and replicating the interchanged data in a cloud computing environment in case there are blockchain node failures. In this way, Renewable Energy Sources can be integrated by means of inexpensive, reliable devices with all the required software components preinstalled, with prosumers being able to further intervene in energy markets.