Blockchain-based Energy Trading Research Articles

A Reliable and Privacy-Preserving Vehicular Energy Trading Scheme Using Decentralized Identifiers

As the usage of electric vehicles (EVs) expands, various energy management technologies, including battery energy storage systems, are being developed to efficiently charge EVs using various energy sources. In recent years, many blockchain-based energy trading schemes have been proposed for secure energy trading. However, existing schemes cannot fully solve privacy issues and security problems during energy trading. In this paper, we propose a reliable and privacy-preserving vehicular energy trading scheme utilizing decentralized identifier technology. In the proposed scheme, identity information and trading result information are not revealed publicly; this is due to the use of decentralized identifiers and verifiable credential technologies. Additionally, only parties who have successfully conducted energy trading can manage complete transaction information. We also demonstrate our method’s security and ensure privacy preservation by performing informal and formal security analyses. Furthermore, we analyze the performance and security features of the proposed scheme and related works and show that the proposed scheme has competitive performance.

ETradeChain: Blockchain-Based Energy Trading in Local Energy Market (LEM) Using Modified Double Auction Protocol

ETradeChain: Blockchain-Based Energy Trading in Local Energy Market (LEM) Using Modified Double Auction Protocol

Blockchain-Based energy trading in Renewable-Based community based Self-Sufficient Utility: Analysis of Technical, Economic, and regulatory aspects

In this ongoing research, a variety of sustainable energy sources, decentralized power generation entities, energy storage solutions, and hybrid electric vehicles with plug-in capability are taken into account. The aim is to present a dependable framework for managing large-scale energy, applicable to both isolated and network-connected modes of renewable hybrid microgrids (HMGs). This framework employs a novel adaptation of Cultural Algorithms (CA) with a two-step modification to minimize the operational expenses of the network. Additionally, it incorporates an innovative intrusion detection system (IDS) based on a deep learning model. The IDS is designed to identify cyber threats related to identity, such as Sybil attacks and masquerading attacks, within the cyber layer. The proposed IDS utilizes the real-time data gathered from the digital twin of the HMG and then uses the LSTM model to differentiate between various signal sources and identify instances of cyberattacks. The data transaction security over the messaging is first preserved by the blockchain technology and later is assessed by the proposed IDS system. To assess the reliability and effectiveness of the proposed framework, a real-time hybrid microgrid is simulated partly in physical layer and partly by digital twin of renewable units to check the model performance.

Towards a blockchain and machine learning-based framework for decentralised energy management

In most domestic buildings, gas and electricity are supplied by energy and utility companies through centralised energy systems. This often results in a high burden on central management systems and has adverse effects on energy prices. Blockchain-based peer-to-peer energy trading platforms can deliver strategic operation of decentralised multi-energy network among multiple domestic buildings to reduce global greenhouse gas emissions and address global climate change issues. However, prevailing blockchain-based energy trading platforms focused on system implementation for peer-to-peer electricity trading while lacking predictive control and energy scheduling optimisation. Therefore, this paper presents an integrated blockchain and machine learning-based energy management framework for multiple forms of energy (i.e., heat and electricity) allocation and transmission, among multiple domestic buildings. Machine learning is harnessed to predict day-ahead energy generation and consumption patterns of prosumers and consumers within the multi-energy network. The proposed blockchain and machine learning-based decentralised energy management framework will establish optimal and automated energy allocation among multiple energy users through peer-to-peer energy transactions. This approach focuses on energy-matching from both the supply and demand sides while encouraging direct energy trading between prosumers and consumers. The security and fairness of energy trading can also be enhanced by using smart contracts to strictly execute the energy trading and bill payment rules. A case study of 4 real-life domestic buildings is introduced to determine the economic and technical potential of the proposed framework. In comparison to prevailing approaches, a key benefit from the proposed approach is an improved computational load/failure of a single point, energy trading strategy, workload, and capital cost energy. Findings suggest that energy costs reduced between 7.60% and 25.41% for prosumer buildings and a fall of 5.40%-17.63% for consumer buildings. In practical applications, the proposed approach can involve a larger number of prosumer and consumer buildings within the community to decentralise multiple energy trading, thus significantly contributing to the reduction of greenhouse gas emissions and enhancing environmental sustainability.

Peer-to-Peer Energy Trading through Swarm Intelligent Stackelberg Game

The development of smart grids has paved the way for sustainable energy infrastructure to transition towards decentralized energy trading. As intelligent agents, energy sources engage in energy trading based on their energy surplus or deficit. Buyers and sellers (participants) should achieve maximum payoffs in which buyers cut costs and sellers improve their utilities, and the security of sensitive information of smart agents must be guaranteed. This paper provides a blockchain-based energy trading network where intelligent agents can exchange energy in a secure manner, without the intervention of third parties. We model energy trading as a Stackelberg game, ensuring that the platform maximizes social welfare while participants increase their payoffs. Using the inherited characteristics of blockchain technology, a novel decentralized swarm intelligence technique is applied to solve the game while ensuring the privacy of the smart agents’ sensitive information. The numerical analysis demonstrates that the suggested method outperforms the present methods (Constant Utility Optimization, average method...) for optimizing the objectives of each agent by maximizing the sellers’ utilities and reducing the buyers’ costs. In addition, the experimental results demonstrate that it significantly reduces carbon footprint (15%) by enhancing energy exchange between intelligent agents.

A trusted peer-to-peer market of joint energy and reserve based on blockchain

• A joint energy-reserve prosumer-centric market is proposed. • The trading mechanism not only enables peer-to-peer (P2P) energy trading but also quantifies the reserve cost and the value of flexibility. • A blockchain-based trading algorithm is proposed to implement an autonomous and trustworthy prosumer-centric market. • A pipelined delegated Byzantine fault tolerance (PDBFT) consensus algorithm is proposed to improve the efficiency of blockchain-based energy trading. With the increasing penetration of distributed energy resources, the traditional producer-centric electricity market is moving to a prosumer-centric market, where prosumers can trade with each other in an autonomous pattern. However, there remain research gaps on the pricing and allocation of joint energy and reserves in an autonomous prosumer-centric market. This paper firstly designs a joint energy-reserve peer-to-peer (P2P) trading mechanism. The mechanism not only enables P2P energy trading but also quantifies the reserve cost and the value of flexibility. Then, a blockchain-based trading algorithm is proposed to implement a trustworthy prosumer-centric market. A pipelined delegated Byzantine fault tolerance (PDBFT) consensus algorithm is proposed to ensure robustness and improve the efficiency of the autonomous trading process. Numerical results show the effectiveness of the trading mechanism and the performance of the blockchain-based trading algorithm. Compared with only considering energy trading, the proposed mechanism reduces the total cost of the market by 16.03%. Compared with using the traditional practical Byzantine fault tolerance (PBFT) consensus algorithm, the computational time of market clearing on blockchain is decreased by 45.90%.

Enabling Energy Trading in Cooperative Microgrids: A Scalable Blockchain-Based Approach With Redundant Data Exchange

Blockchain has recently been regarded as an important enabler for building secure energy trading in microgrid systems because of its inherent features of distributively providing immutable data record, storage, and sharing across networks in a peer-to-peer (P2P) manner. However, designing highly efficient and scalable blockchain-enabled energy trading mechanisms is extremely challenging because of the unique features of microgrid systems, e.g., bandwidth-constrained and high-latency communications and large-scale renewable energy source (RES) integration. To address this challenge, in this article, we propose a novel scalable blockchain-based energy trading framework for cooperative microgrid systems, which include four planes, i.e., data plane, consensus plane, smart plane, and application plane. Different from the existing solutions without consideration of network transmission, these four planes are designed with the capability of perceiving the status of block generation and transmission over interrupted P2P networks, and thus proactively improving the consensus process to guarantee the reliability of energy trading in cooperative microgrids. Meanwhile, built on this framework, a novel redundant data exchange strategy is proposed to improve the scalability of block creation with the presence of large-scale RES penetration and interrupted and dynamic communication links. Simulation results show that the proposed system framework outperforms the benchmark blockchain solutions. Furthermore, we investigate the potential applications of the proposed solutions in the practical microgrid systems to facilitate a clear understanding of the mechanisms of the proposed solutions.

Energy System 4.0: Digitalization of the Energy Sector with Inclination towards Sustainability.

The United Nations’ sustainable development goals have emphasized implementing sustainability to ensure environmental security for the future. Affordable energy, clean energy, and innovation in infrastructure are the relevant sustainable development goals that are applied to the energy sector. At present, digital technologies have a significant capability to realize the target of sustainability in energy. With this motivation, the study aims to discuss the significance of different digital technologies such as the Internet of Things (IoT), artificial intelligence (AI), edge computing, blockchain, and big data and their implementation in the different stages of energy such as generation, distribution, transmission, smart grid, and energy trading. The study also discusses the different architecture that has been implemented by previous studies for smart grid computing. Additionally, we addressed IoT-based microgrids, IoT services in electrical equipment, and blockchain-based energy trading. Finally, the article discusses the challenges and recommendations for the effective implementation of digital technologies in the energy sector for meeting sustainability. Big data for energy analytics, digital twins in smart grid modeling, virtual power plants with Metaverse, and green IoT are the major vital recommendations that are discussed in this study for future enhancement.

Blockchain Based Peer-To-Peer Energy Trading Between Wind Power Producer and Prosumers in Short-Term Market

With the increase of wind power penetration, the deviation caused by its volatility and intermittency poses a growing threat to the grid. Energy trading in short-term markets for wind power and backup storage helps compensate for the deviations. Furthermore, the introduction of peer-to-peer (P2P) energy trading can effectively reduce the risk of centralized market management. However, the higher cost of energy storage are not conducive to wind power producers (WPPs). And P2P trading also suffers from trust and efficiency problems. This paper provides a blockchain based short-term energy trading market, which resolves generation deviations through efficient and trusted real-time transactions between WPP and prosumers. The blockchain-based energy trading market is a trustless P2P structure, and the trading is triggered by smart contracts to ensure efficiency. Furthermore, a reputation mechanism is designed to incentivize WPP’s generation forecasts to be accurate and prosumers to participate in the market. A bilevel optimization method is designed to increase the revenue of WPP and reduce the costs of prosumers. The market can effectively balance the deviation of wind power generation, increase the revenue of WPP by 9.55%, and reduce the costs for consumers by 5.6%.

Blockchain based energy trading scheme for vehicle-to-vehicle using decentralized identifiers

A blockchain-based energy trading system is a new paradigm of grid infrastructure, which allows that energy purchaser and seller can efficiently exchange the energy through two-way communication. However, because energy trading services are provided through public networks, these systems are vulnerable to potential security breaches. This paper proposed a privacy-preserving blockchain-based energy trading scheme for vehicle-to-vehicle to resolve the security issues of contemporary systems and provide secure energy trading services. The proposed scheme has high efficiency by applying decentralized identifiers and verifiable credentials technologies because the records of energy trading are not stored on blockchain and blockchain is only utilized in the validation of users. After completing the energy trading, the vehicle issues a verifiable credential to the counterpart to prove the legitimacy of the transaction. We also perform informal and formal security analysis to demonstrate its security and achieve secure mutual authentication, confidentiality, and session key security. Furthermore, we implement AVISPA simulation to show that our scheme is resistant to man-in-the-middle and replay attacks. As a result, the proposed scheme can be used in distributed smart grid environments.

Towards Blockchain-Based Energy Trading: A Smart Contract Implementation of Energy Double Auction and Spinning Reserve Trading

The decentralization of power generation driven by the rise in the adoption of distributed energy resources paves the way for a new paradigm in grid operations. P2P energy trading is beneficial to the grid as well as the connected peers. A blockchain-based smart contract is well suited to transparently facilitate trades between energy consumers and producers without the services of intermediaries. In this paper, Ethereum-based smart contracts that facilitate double energy auction and spinning reserve trading are developed with Solidity, compiled, and deployed within the Remix IDE. Willing energy sellers/buyers submit offers/bids to a contract that implements the double auction procedure. In order to fulfil energy supply obligations, sellers are also able to purchase spinning reserves via another smart contract. The smart contracts’ effectiveness in performing the auction procedure and making payments is confirmed using an energy/reserve market scenario. The proposed scheme encourages further adoption of distributed energy resources and participation in local P2P energy trading.

Blockchain based energy trading in ADN with its probable impact on aggregated load profile, available distribution capability and loadability margin

AbstractPower grids monitoring, operation, control, and commercialisation are transforming gradually due to technological advancements, and new frontiers of distinct applications are emerging in this field. Global emphasis on increasing the dependence on renewable sources of generation and the introduction of electric vehicles as means of transformation can potentially affect the traditional notion of grid analysis, monitoring, and control. The prevalence of communicable intelligent devices enables peers to transact and sell/buy power locally or to the grid. Ensuring security, privacy, and avoidance of double‐spending in these transactions could be manifested by utilising the developments in blockchain technologies. In this paper, modified IEEE 123 bus distribution system has been considered. The effect of incorporating the energy transactions over block‐chain in ADN on Available Distribution Capability, aggregated load profile, and load‐ability is evaluated. The effect has been quantified using blockchain efficiency factor proposed in this article. It has been observed that enabling intelligent electronic devices peers to transact over blockchain can improve the performance of the ADN.

Towards sustainable smart cities: A secure and scalable trading system for residential homes using blockchain and artificial intelligence

• The paper proposes a secure blockchain based energy trading system for homes. • A new proof-of-computational closeness consensus protocol is proposed for selection of miners. • An analytical energy pricing policy is designed to solve the problem of existing energy pricing policies. • A dynamic multi-pseudonym is developed for prosumers for privacy during trading. • A Jaya optimization accelerates error convergence rate reducing connections between neurons layers This paper proposes a secure blockchain based energy trading system for residential homes. In the system, a new proof-of-computational closeness (PoCC) consensus protocol is proposed for the selection of miners and the creation of blocks. Moreover, an analytical energy pricing policy is designed to solve the problem of existing energy pricing policies in a distributed trading environment. A dynamic multi-pseudonym mechanism is developed for the prosumers to preserve their transactional privacy during energy trading. Since it requires extra storage and computing resources for the blockchain miners to simultaneously execute both mining process and application intensive tasks, therefore, an improved sparse neural network (ISNN) is proposed for computation offloading to the cloud servers. In ISNN, a Jaya optimization algorithm is used to accelerate the error convergence rate while reducing the number of connections between different layers of neurons. Besides, ISNN optimizes the overall computational cost of the system. Furthermore, the security of the prosumers is ensured using blockchain technology while security analysis shows that the system is robust against the Sybil attack. The proposed blockchain based peer-to-peer secure energy trading system is extremely important for sustainable cities and society. Simulations are conducted to evaluate the effectiveness of the proposed system. The proposed pricing policy is compared with time-of-use pricing, critical peak pricing and real-time pricing policies. From the results, it is proved that the prosumers achieve a higher degree of satisfaction and utility when using the proposed pricing policy. Moreover, the probability of a successful Sybil attack is zero as the number of attackers’ identities and computational capacities increases. Under different sizes of data to be uploaded, the proposed ISNN scheme has the least average computational cost and data transmission time as compared to deep reinforcement learning combined with genetic algorithm (DRGO) and sparse evolutionary training and multi-layer perceptron (SET-MLP) schemes in the literature. Moreover, the proposed system is tested for scalability by increasing the number of prosumers. Extensive simulations are performed and the results depict the satisfactory performance of the proposed system.

V2GNet: Robust Blockchain-Based Energy Trading Method and Implementation in Vehicle-to-Grid Network

V2GNet: Robust Blockchain-Based Energy Trading Method and Implementation in Vehicle-to-Grid Network

A consortium blockchain based energy trading scheme for Electric Vehicles in smart cities

The real time Vehicle-to-Grid (V2G) and Vehicle-to-Vehicle (V2V) energy trading have ameliorated the smart city environment. Electric Vehicles (EVs) in smart cities have made it possible to balance the energy demand and supply without burdening the power grids. They also help in minimizing both the heap amounts of pollution and the greenhouse gas emissions. EVs not only charge their batteries from Charging Stations (CSs), but when the smart city faces energy deficiency, they supply their surplus energy to the power grids to fulfill energy demand as well. In addition, EVs also balance the energy demand and supply through energy trading at the local level during peak hours, which strengthens V2V energy trading. However, some issues, such as security threats and privacy leakage prevent EVs from participating in the energy trading process. In addition, the lack of incentives and knowledge about the cost of reaching the energy trading place within minimum time are also big challenges. Therefore, to solve the aforementioned challenges, a secure and efficient scheme for V2V and V2G energy trading is proposed in this paper. The proposed scheme also helps in promoting environmental friendliness and making the smart cities sustainable and reliable. In the proposed scheme, energy trading transactions are secured using consortium blockchain, wherein the Local Aggregators (LAGs) are selected as authorized nodes. LAGs perform their role as energy brokers and are responsible for validating the energy trading requests using Proof of Authority (PoA) consensus mechanism. Moreover, a solution to find accurate distance with required expenses and time to reach the charging destination is also proposed, which effectively guides EVs to reach the relevant CSs and encourages energy trading. Besides, we propose a fair payment mechanism using a smart contract to avoid financial irregularities. An incentive provisioning mechanism is also given in the proposed work to prevent EVs from acting selfishly. The efficient power flow having minimized losses in the vehicular network is of much importance. Therefore, the energy losses incurred in both V2G and V2V are discussed in this work. Furthermore, Oyente is used for smart contract’s security analysis and for testing Ethereum’s resilience against different security flaws. Two attacker models are proposed and the security analyses of the models are also provided. The analyses show that the proposed system is robust against the double spending and Sybil attacks. Finally, the efficient performance of our proposed scheme is validated and analyzed. The simulation results proved that our proposed work outperforms existing work in terms of providing a secure and efficient energy trading platform for both V2G and V2V environments.

A Consortium Blockchain-Based Energy Trading for Demand Response Management in Vehicle-to-Grid

In this paper, we propose a Peer-to-Peer (P2P) energy trading scheme between EVs and the SPs to manage the demand response in V2G environment. Unlike the traditional schemes, which consists of complex energy-transportation meshes, the proposed scheme achieves a balance between demand and response by providing incentives to EVs out of their self-interests. However, the online transactions security and privacy protection of EVs poses challenges with respect to confidentiality and integrity preservation. To cope up with the issues, we design a consortium blockchain-based scheme to ensure secure energy transactions between EVs and the SPs without trusted third-party intervention. Moreover, the energy pricing and the amount of traded energy problems for demand response are solved by a double auction mechanism to maximize the social welfare. Numerical results based on a real-time implementation on a private Ethereum network having smart contract demonstrated that the auction-based mechanism achieves social welfare maximization with privacy protection of online transactions between EVs and the SPs. The results obtained show that the rate of convergence, scalability metric average latency, and standard deviation of the energy transactions have been improved by approximately 18.18%, 15%, and 28.1%, respectively in comparison to the existing schemes. Moreover, security and privacy analysis of the proposed scheme shows that it improves the transaction security substantially in comparison to the existing state-of-the-art proposals.

Privacy-Preserving Blockchain-Based Energy Trading Schemes for Electric Vehicles

An energy trading system is essential for the successful integration of Electric Vehicles (EVs) into the smart grid. In this paper, leveraging blockchain technology, we first propose a privacy-preserving charging-station-to-vehicle (CS2V) energy trading scheme. The CS2V scheme is useful in crowded cities where there is a need for a charging infrastructure that can charge many EVs daily. We also propose a privacy-preserving vehicle-to-vehicle (V2V) energy trading scheme. The V2V scheme is useful when charging stations are not available or far and cheaper prices can be offered from EVs, e.g., if they charge from renewable energy sources. In the V2V scheme, the privacy of both charging and discharging EVs including location, time, and amount of power are preserved. To preserve privacy in both schemes, EVs are anonymous, however, a malicious EV may abuse the anonymity to launch Sybil attacks by pretending as multiple non-exiting EVs to launch powerful attacks such as Denial of Service (DoS) by submitting multiple reservations/offers without committing to them, to prevent other EVs from charging and make the trading system unreliable. To thwart the Sybil attacks, we use a common prefix linkable anonymous authentication scheme, so that if an EV submits multiple reservations/offers at the same timeslot, the blockchain can identify such submissions. To further protect the privacy of EV drivers, we introduce an anonymous and efficient blockchain-based payment system that cannot link individual drivers to specific charging locations. Our experimental results indicate that our schemes are secure and privacy-preserving with low communication and computation overheads.

Application of Blockchain Technology in Energy Trading: A Review

As blockchain and energy trading have become hot topics in industry and academia, this paper presents a brief literature regarding the blockchain-based energy trading in the fields of energy trading with blockchain. At first, the background and development process is presented, and then the applications of blockchain in energy trading are surveyed and analyzed. Finally, conclusions are summarized and important directions are highlighted in this field.

Feasibility of Blockchain-Based Energy Trading within Islanded Microgrids in Alexandria, Egypt

Recent developments in power system and internet technology introduced blockchain technology to energy trading. In addition, the growing penetration of distributed energy resources made the division of distribution systems into microgrids a tempting solution for technical and economical problems. In this paper, the feasibility of applying blockchain technology as an accounting system for energy trading within each island and between interconnected islands is considered. The distribution system is considered after being optimally divided into islands. Energy hubs, aggregated thermostatically controlled loads and aggregated electric vehicles (EVs) are considered. Optimal demand-side management is applied taking into consideration the uncertainties arising from renewable energy sources due to their nature, load forecasting, energy price due to bidding actions accompanying energy transactions, and energy exchange in EV parking stations due to EV availability patterns. The blockchain-based energy trading (BET) system is considered in three steps. The first step is carried out considering EV parking stations for energy trading between EVs and then between parking stations and island consumers with billing transfer between different blockchains. The second step considers the trading between prosumers and consumers within each island. In the third step, the BET system is applied for energy trading between interconnected islands. The feasibility of the proposed energy trading system is validated using a realistic case of the distribution system of Alexandria, Egypt. The simulation results show the positive impact of applying blockchain-based energy trading on energy cost.

A Novel Power Market Mechanism Based on Blockchain for Electric Vehicle Charging Stations

This work presents a novel blockchain-based energy trading mechanism for electric vehicles consisting of day-ahead and real-time markets. In the day-ahead market, electric vehicle users submit their bidding price to participate in the double auction mechanism. Subsequently, the smart match mechanism will be conducted by the charging system operator, to meet both personal interests and social benefits. After clearing the trading result, the charging system operator uploads the trading contract made in the day-ahead market to the blockchain. In the real-time market, the charging system operator checks the trading status and submits the updated trading results to the blockchain. This mechanism encourages participants in the double auction to pursue higher interests, in addition to rationally utilize the energy unmatched in the auction and to achieve the improvement of social welfare. Case studies are used to demonstrate the effectiveness of the proposed model. For buyers and sellers who successfully participate in the day-ahead market, the total profit increase for buyer and seller are 22.79% and 53.54%, respectively, as compared to without energy trading. With consideration of social welfare in the smart match mechanism, the peak load reduces from 182 to 146.5 kW, which is a 19.5% improvement.