With the rapid development and technological innovation in the energy market, peer-to-peer (P2P) energy trading, as a decentralised and efficient trading model, has been widely studied and practically applied. However, in P2P energy transactions involving multiple prosumers, there are challenges such as information asymmetry, trust issues, and transaction transparency. To address these challenges, blockchain technology, as a distributed ledger technology, provides solutions. In this paper, we propose a blockchain technology-based prosumer–virtual power plant (VPP) two-tier interactive energy management framework to assist P2P energy transactions between multiple prosumers. In this framework, the virtual power plant acts as a leader and sets differentiated tariffs for different prosumers to equal the distribution of social welfare. The various prosumers act as followers and respond to the leader’s decisions in a cooperative manner. Blockchain’s immutability and transparency enable prosumers to participate in P2P energy trading with greater trust, share idle energy, and share revenues based on contribution. In addition, given the uncertainty of renewable energy, this paper employs a stochastic planning approach with conditional value at risk (CVaR) to describe the expected loss of VPP. Ultimately, as verified by the arithmetic simulation, the blockchain co-governance transaction model effectively supports energy coordination and optimization of complementarities while ensuring the utility of each transaction node. This model promotes the application of renewable energy in local consumption, while facilitating the innovation and sustainable development of the energy market.
The remarkable success of deep learning (DL) in predicting battery health has prompted interest in its application in recent years. While state-of-the-art DL models have achieved high accuracy in battery health prediction, they have not been widely adopted in industrial workflows, primarily due to their lack of interpretability and security. To address this issue, we propose a blockchain-based interpretable prediction algorithm for battery health prediction in electric vehicles (EVs) within the Internet of Vehicles (IoV). Specifically, the proposed method includes a platform architecture for a blockchain-based DL system, ensuring secure storage of user data during the prediction process. Notably, we develop a novel battery life prediction algorithm called BLP-Transformer, which leverages short-term relationships between degraded data and explains the impact of feature extraction on predicted results through the contribution of aggregated features based on a feature focusing mechanism. Experimental results demonstrate that the system is feasible for security and can provide accurate battery life prediction. In addition, the comparison study further highlights the superiority of the proposed algorithm in terms of robustness, prediction accuracy, and model interpretability.
There has been a growing penetration of renewable energy sources (RES) into power grids in recent years. As extreme weather events and cyber-attacks frequently occur, grid resilience has been an important issue. Vehicle-to-Vehicle (V2V) energy trading has great potential to improve the stability and reliability of resilient power grids integrated with high-penetrated RES. V2V energy trading is a distributed peer-to-peer (P2P) application. As a decentralized distributed ledger technology, blockchain is an ideal platform for V2V energy trading. The consensus mechanism of blockchain determines whether the V2V energy trading blockchain (ETB) can improve grid resilience. However, most studies in the ETB currently utilize conventional consensus mechanisms. Due to their substantial computational requirements and communication overhead, these consensus algorithms are not well-suited for real-time service applications like energy trading. We propose a novel BAC-SDS consensus specifically for V2V ETB, thus enabling resilient grids to maximise the use of renewable energy. We propose an Electric Vehicle (EV) leader election based on cryptography and adopt the sharding technique to enhance the system's scalability. Furthermore, our approach ensures the secure transfer of energy and value, contingent upon the condition that all EVs exhibit reasonable behavior and retain the proofs they possess. We implement the V2V ETB on Hyperledger Fabric. The experiments demonstrate (1) that V2V ETB significantly enhances the resilience of the power grid compared to traditional centralized trading models and (2) the consensus mechanism proposed in this article is better suited for V2V energy trading than existing mechanisms, exhibiting superior performance in terms of security, throughput, and scalability, thus further enhancing the resilience of the power grid.
Liaqat Ali, M. Imran Azim, Nabin B. Ojha, Jan Peters · 9 authors
The electricity market has increasingly played a significant role in ensuring the smooth operation of the power grid. The latest incarnation of the electricity market follows a bottom-up paradigm, rather than a top-down one, and aims to provide flexibility services to the power grid. The blockchain-based local energy market (LEM) is one such bottom-up market paradigm. It essentially enables consumers and prosumers (those who can generate power locally) within a defined power network topology to trade renewable energy amongst each other in a peer-to-peer (P2P) fashion using blockchain technology. This paper presents the development of such a P2P trading-facilitated LEM and the analysis of the proposed blockchain-based LEM by means of a case study using actual German residential customer data. The performance of the proposed LEM is also compared with that of BAU, in which power is traded via time-of-use (ToU) and feed-in-tariff (FiT) rates. The comparative results demonstrate: (1) the participants’ bill savings; (2) mitigation of the power grid’s export and import; (3) no/minimal variations in the margins of energy suppliers and system operators; and (4) cost comparison of Ethereum versus Polygon blockchain, thus emphasising the domineering performance of the developed P2P trading-based LEM mechanism.
Providing equitable and resilient electric vehicle supply equipment (EVSE) to remote locations with limited access to the Internet infrastructure is one of the paradoxes in the decarbonization plan. In this paper, we develop an electric vehicle (EV) charging management system comprised of offline EVSEs based on a Federated Byzantine Agreement (FBA) system. To enable offline peer-to-peer (P2P) authentication between the user’s device (UD) and EVSE stations, we use a distributed certificate management based on Shamir’s algorithm and blind signing approach using the ring signature. We introduce extended FBA for charge point operator (FBA-CPO) systems and include explicit operational functions to ensure the ledger dissemination and scalability of the network. We specifically employ a pre-authorized mechanism for deferral vouchers using a pre-signed and weighted signing method. In the FBA-CPO network, each charger records all transactions on a local ledger and publicly publishes ledgers through random UD nodes. Under a generalization of the property of the federated quorum system, the proposed approach could provide a reliable network centrality with or without offline EVSEs. Eventually, we examined the performance of the proposed model using a system of real devices and their digital twins. Results show the FBA-CPO satisfies all functional and cross-cutting requirements for a consistent transnational mechanism.
Blockchain technology is very useful. This paper considers the application of blockchain technology to smart contracts, green certification, and market information disclosure, and introduces the carbon trading market price as a parameter to solve the dynamic incentive problem of the government for port enterprises to reduce emissions under the carbon trading policy. Based on the state change of port carbon emission reduction, this paper uses principal–agent theory to construct the dynamic incentive contract model of government without blockchain, with blockchain, and when carbon trading is considered under blockchain, respectively, and uses the optimal control method to solve and analyze the model. This paper finds that only when the opportunity cost of port enterprises is greater than a certain critical point and the fixed cost of blockchain is less than a certain critical point, the implementation of blockchain will help improve government efficiency. However, only when the critical value of carbon emission reduction of port enterprises and the unit operating cost of blockchain are small, the government should start the carbon trading market under blockchain technology. Through numerical simulation, this paper also finds that it is usually beneficial for the government to regulate and appropriately increase the carbon trading market price.
Yubao Zhang, Xin Chen, Yi Gu, Zhicheng Li · 5 authors
With the growing prevalence of electric vehicles (EVs) and advancements in EV electronics, vehicle-to-grid (V2G) techniques and large-scale scheduling strategies have emerged to promote renewable energy utilization and power grid stability. This study proposes a multi-stakeholder hierarchical V2G coordination based on deep reinforcement learning (DRL) and the Proof of Stake algorithm. Furthermore, the multi-stakeholders include the power grid, EV aggregators (EVAs), and users, and the proposed strategy can achieve multi-stakeholder benefits. On the grid side, load fluctuations and renewable energy consumption are considered, while on the EVA side, energy constraints and charging costs are considered. The three critical battery conditioning parameters of battery SOX are considered on the user side, including state of charge, state of power, and state of health. Compared with four typical baselines, the multi-stakeholder hierarchical coordination strategy can enhance renewable energy consumption, mitigate load fluctuations, meet the energy demands of EVA, and reduce charging costs and battery degradation under realistic operating conditions.
The concept of "energy prosumer" is a relatively new phenomenon resulting from distributed energy production through photovoltaic (PV) technology, which has blurred the line between energy producers and consumers. Blockchain technology has facilitated secure and cost-effective energy transactions among consumers, prosumers, and utilities, automating the process. This study aims to develop an agent-based modeling (ABM) simulation framework for energy exchange, demonstrating the power profiles of households and the operation of blockchain operations. The simulation was conducted in the Education City Community Housing (ECCH) microgrid, using a multi-agent framework for a transactive energy (TE) distributed energy resource (DER) that requires blockchain technology. The current blockchain-based local energy market (LEM) aims to balance supply and demand using precise short-term energy generation forecasts and home consumption estimates. This study evaluated the accuracy of state-of-the-art energy forecasting methods in predicting household energy generation and consumption. It examined the impact of forecasting errors on market outcomes under different supply scenarios. Although LSTM models may provide low forecasting errors, the researchers found that the prediction process needs modification for a LEM built on a blockchain. This study stands out from previous research by forecasting the timeline of smart meters in general.
Manuel Sivianes, J. M. Maestre, Ascensión Zafra‐Cabeza, Carlos Bordons
In this article, a stochastic programming method is used to control a residential microgrid where possible disturbance realizations over a horizon are shaped into a tree structure with a given probability. This tree is used by model predictive controllers within a hierarchical and distributed scheme. The upper layer is characterized by a smart contract deployed in the blockchain, acting as a fully distributed coordinator that performs control tasks and collects and distributes relevant data. The bottom layer consists of individual agents that solve locally a reduced tree-based model predictive control (TBMPC) problem and interact with the smart contract to iteratively optimize the overall problem in a distributed fashion. The performance of the approach is demonstrated through several simulations in which various power-trading configurations are assessed.
Many countries have implemented different carbon reduction policies to achieve carbon neutrality in the current century. As one of the popular policies, the cap-and-trade policy provides carbon emission quotas for power generation companies. Each company must carefully determine its energy production based on the carbon emission quota and renewable uncertainty. This paper analyzes the cooperation among different power generation companies using the coalitional game theory. Power generation companies can form a union to share the total carbon emission quotas to maximize their total profit. We show the optimality of the grand coalition by proving that the profit function is superadditive. This result highlights the benefits of cooperation. Besides, we propose a profit allocation mechanism that allocates the total profit to different power generation companies. Furthermore, we prove that the proposed profit allocation mechanism is in the core of the coalitional game such that no group of power generation companies has any incentives to leave the grand coalition. We design a smart contract to enable power generation companies to form a coalition. We further implement the smart contract on the Ethereum platform to validate its effectiveness. Numerical studies have been conducted to validate the established theoretical results.
Syed Muhammad Ahsan, Hassan Abbas Khan, Sarmad Sohaib, Anas Hashmi
The operation of smart buildings (with solar, storage and suitable power routing infrastructure) can be optimized with the addition of parking stations for electric vehicles (EVs) with vehicle-to-everything (V2X) operations including vehicle-to-vehicle (V2V), vehicle-to-building (V2B) and vehicle-to-grid (V2G) operations. In this paper, a multi-objective optimization framework is proposed for the smart charging and discharging of EVs along with the maximization of revenue and savings of smart building (prosumers with solar power, a battery storage system and a parking station) and non-primary/ordinary buildings (consumers of electricity without solar power, a battery storage system and parking station). A mixed-integer linear program is developed to maximize the profits of smart buildings that have bilateral contracts with non-primary buildings. The optimized charging and discharging (V2X) of EVs at affordable rates utilizing solar power and a battery storage system in the smart building helps to manage the EV load during on-peak hours and prevent utility congestion. The results indicate that in addition to the 4–9% daily electricity cost reductions for non-primary buildings, a smart building can achieve up to 60% of the daily profits. Further, EVs can save 50–69% in charging costs while performing V2X operations.
Electric Vehicles (EVs) have emerged in smart cities as one of the prominent solutions to improve environmental protection and reduce carbon gas emissions. However, with limited charging stations and battery life, EV owners are not inclined to cover long distances. So, Vehicle-to-Vehicle (V2V) has been introduced lately for energy sharing among EVs through the wireless power transfer (WPT) mechanism in the Internet of EVs (IoEV) environment. But the existing approaches suffered from security and privacy issues along with single-point-of-failure with energy trading between EVs. So, in this paper, we propose a blockchain-based V2V wireless energy sharing scheme, i.e., V2V-ES, to ensure secure transactions among EVs in the WPT process. First, the energy sharing is executed in a clustered IoEV environment, where block generation, validator selection, and PoA consensus processes are performed in every cluster. Next, the Bayesian game-based mechanism is adopted for optimal energy price in the IoEV environment. Here, a linear equilibrium strategy is obtained for optimal pricing that maximizes the utilities of both energy buyer and seller in the energy sharing process and increases social welfare. The game-based pricing is achieved through dedicated smart contracts (SCs) to guarantee trustworthiness, reliability, and security. Finally, the simulation results show the proposed V2V-ES scheme reduces the buyer's costs by 16% and increases the seller's utility by 19%. Moreover, the effectiveness of V2V-ES scheme is compared with benchmark approaches based on various parameters like network latency, system throughput, and optimal transaction price.
The complexities associated with modern energy grids, including high penetration levels of renewable energy sources at the end use customers, the proliferation of electric vehicles (EVs), as well as decentralized energy management systems and energy data portals and services, require secure, reliable and cost-effective new platforms to administer such systems in a transparent manner. Blockchain technology can address such challenging complexities efficiently. This paper presents a thorough literature review of all potential blockchain applications in electric energy systems. First, all potential blockchain application possibilities and constraints in electric energy systems have been identified. Then, the implementations of blockchain technology in power systems are divided into various categories, such as demand response (DR), EVs, decentralized energy management, energy trading and distributed renewable energy. A detailed literature analysis is conducted by following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines in a systematic approach using credible and reliable database systems such as IEEE Xplore, ScienceDirect, and Scopus to highlight current advancements in blockchain technology uses in electric energy systems particularly in DR, as well as future potential and existing problems. The paper is divided into three parts. The first part lists the important publications that have delved into the implementation of Blockchain in demand response. Trends of Blockchain applications in other electric energy system areas are detailed in the second section. The final part highlights the evolution and advancement of blockchain-based electric energy systems including favourable attributes of structures and designs, as well as the challenges and future trends.
Liaqat Ali, M. Imran Azim, Jan Peters, Nabin B. Ojha · 10 authors
In this paper, a framework is proposed for integration of peer-to-peer (P2P) trading-based local energy market (LEM) with the blockchain technology. The proposed LEM model allows prosumers and consumers to trade electricity among each other ensuring the presence of the retailer and network utility – who are also essential parts of a P2P network. The P2P contracts settled between various prosumers and consumers are governed by mutually agreed upon smart contracts – which are then written in an Ethereum blockchain to record and store bidding history, P2P transactions, and settlements. An effective formulation is also presented to capture P2P trading quantities and prices among participating prosumers and consumers in a decentralised fashion with an appropriate analysis of financial viability. Finally, a case study is conducted in a real Australian context; in which the engagement of both prosumers and consumers are taken into account, and the performance of the proposed blockchain-enabled LEM is compared with business-as-usual (BAU) to demonstrate the model's superiority.
Liaqat Ali, M. Imran Azim, Jan Peters, Nabin B. Ojha · 10 authors
This paper presents a local energy market (LEM) model to conduct peer-to-peer (P2P) energy trading between a number of participants by dint of the Ethereum-based blockchain technology. The proposed LEM mechanism is structured by considering relevant functional constraints while energy trading is arranged between several participants in the presence of other stakeholders including energy retailer and network operator. LEM participants’ mutual bidding intended P2P trading, actual settlement, and final billing are executed using the smart contracts in Ethereum blockchain to record LEM transactions and related data in an unchangeable and distributed fashion. Lastly, a case study is performed in an Australian suburb with 300 LEM participants, and the simulation results are benchmarked with an existing business-as-usual (BAU)scenario. The simulation results outline that the formulated LEM mechanism 1) reduces the electricity cost of participants remarkably while improving their self-sufficiency, 2) minimises power grid export and import, and 3) retains income margins for the energy retailer and network operator.
Renewable Energy Sources (RESs) are gaining considerable attention to reduce human dependence on fossil fuels and minimize harmful gases in our surroundings. Existing literature on energy trading focused on providing renewable energy to smart homes, smart buildings, and smart offices to fulfill their daily energy demands obtained from RESs. Besides, Electric Vehicles (EVs) use either power grid energy or a battery exchange mechanism to recharge their low EV batteries. The continuous use of power grids to recharge low EV batteries causes a significant load on power grids. Due to this, power grids are inadequate to fulfill the ever-increasing demands of EVs in the future. In this context, we propose a Blockchain Enabled Energy Trading (BEET) framework oriented EV charging. A system architecture of the BEET framework is presented to describe the functioning of each layer and its associated entities. We formulate an optimization problem that maximizes the revenue in the energy trading process using a knapsack optimization. Smart contracts are designed on the consortium blockchain network to sell and buy renewable energy to aggregators and from producers, respectively. Moreover, an EV charging mechanism is designed to intelligently allocate renewable energy to consumers at a low price. A comparative analysis is performed with state-of-the-art works in terms of charging price, revenue, throughput, and latency. The results indicate that the BEET framework outperforms compared to state-of-the-art works to address the renewable energy demand problem to realize E-mobility. It is clarified that the data considered in the experimental analysis were obtained from statistical simulations in realistic E-Mobility environment settings.
In recent years, user-side energy storage has begun to develop. At the same time, independent energy storage stations are gradually being commercialized. The user side puts shared energy storage under coordinated operation, which becomes a new energy utilization scheme. To solve the many challenges that arise from this scenario, this paper proposes a community power coordinated dispatching model based on blockchain technology that considers shared energy storage and demand response. First of all, this paper analyzes the operating architecture of a community coordinated dispatching system under blockchain. Combined with the electricity consumption mode of communities using a shared energy storage station service, the interactive operation mechanism and system framework of block chain for coordinated dispatching are designed. Secondly, with the goal of minimizing the total cost of coordinated operation of the community alliance, an optimal dispatching model is established according to the relevant constraints, such as the community demand response, shared energy storage system operation and so on. Thirdly, the blockchain application scheme of community coordinated dispatching is designed, including the incentive mechanism based on the improved Shapley value allocation coordination cost, and the consensus algorithm based on the change rate of users’ electricity utilization utility function. Finally, the simulation results show that the proposed community coordinated dispatching strategy in this paper can effectively reduce the economic cost, reduce the pressure on the power grid, and promote the consumption of clean energy. The combination of the designed cost allocation and other methods with blockchain technology solves the trust problem and promotes the innovation of the power dispatching mode. This study can provide some references for the application of blockchain technology in user-side energy storage and shared energy storage.
Hydrogen has recently been proposed as a versatile energy carrier to contribute to archiving universal access to clean cooking. In hard-to-reach rural settings, decentralized produced hydrogen may be utilized (i) as a clean fuel via direct combustion in pure gaseous form or blended with Liquid Petroleum Gas (LPG), or (ii) via power-to-hydrogen-to-power (P2H2P) to serve electric cooking (e-cooking) appliances. Here, we present the first techno-economic evaluation of hydrogen-based cooking solutions. We apply mathematical optimization via energy system modeling to assess the minimal cost configuration of each respective energy system on technical and economic measures under present and future parameters. We further compare the potential costs of cooking for the end user with the costs of cooking with traditional fuels. Today, P2H2P-based e-cooking and production of hydrogen for utilization via combustion integrated into the electricity supply system have almost equal energy system costs to simultaneously satisfy the cooking and electricity needs of the isolated rural Kenyan village studied. P2H2P-based e-cooking might become advantageous in the near future when improving the energy efficiency of e-cooking appliances. The economic efficiency of producing hydrogen for utilization by end users via combustion benefits from integrating the water electrolysis into the electricity supply system. More efficient and cheaper hydrogen technologies expected by 2050 may improve the economic performance of integrated hydrogen production and utilization via combustion to be competitive with P2H2P-based e-cooking. The monthly costs of cooking per household may be lower than the traditional use of firewood and charcoal even today when applying the current life-line tariff for the electricity consumed or utilizing hydrogen via combustion. Driven by likely future technological improvements and the expected increase in traditional and fossil fuel prices, any hydrogen-based cooking pathway may be cheaper for end users than using charcoal and firewood by 2030, and LPG by 2040. The results suggest that providing clean cooking in rural villages could economically and environmentally benefit from utilizing hydrogen. However, facing the complexity of clean cooking projects, we emphasize the importance of embedding the results of our techno-economic analysis in holistic energy delivery models. We propose useful starting points for future aspects to be investigated in the discussion section, including business and financing models.
The proliferation of electric vehicles (EVs) and the advancement of vehicle-to-everything energy trading systems are expected to play a crucial role in alleviating the stress on the electric grid during peak hours. However, the wide adoption of these paradigms requires intelligent mechanisms that protect the security and privacy of EV users. This article proposes a novel federated reinforcement learning system combined with blockchain technology to maximize EV users' utility while preserving the security and privacy of trading transactions. Furthermore, we develop the concept of proof of state of charge as a consensus mechanism to determine the winning EVs and reward them as block miners in the blockchain. The proposed system is validated through comprehensive simulation experiments utilizing a real-world dataset. The model is implemented on the Avalanche blockchain platform to demonstrate its real-world feasibility. The test results show that the proposed scheme improves EV users' utility significantly compared to the existing studies. The obtained simulation results indicate the effectiveness and robustness of the proposed system.
Irvylle Cavalcante, Jamilson Júnior, Jônatas Augusto Manzolli, L.A.L. de Almeida · 7 authors
In the present day, it is crucial for individuals and companies to reduce their carbon footprints in a society more self-conscious about climate change and other environmental issues. In this sense, public and private institutions are investing in photovoltaic (PV) systems to produce clean energy for self-consumption. Nevertheless, an essential part of this energy is wasted due to lower consumption during non-business periods. This work proposes a novel framework that uses solar-generated energy surplus to charge external electric vehicles (EVs), creating new business opportunities. Furthermore, this paper introduces a novel marketplace platform based on blockchain technology to allow energy trading between institutions and EV owners. Since the energy provided to charge the EV comes from distributed PV generation, the energy’s selling price can be more attractive than the one offered by the retailers—meaning economic gains for the institutions and savings for the users. A case study was carried out to evaluate the feasibility of the proposed solution and its economic advantages. Given the assumptions considered in the study, 3213 EVs could be fully charged by one institution in one year, resulting in over EUR 45,000 in yearly profits. Further, the economic analysis depicts a payback of approximately two years, a net present value of EUR 33,485, and an internal rate of return of 61%. These results indicate that implementing the proposed framework could enable synergy between institutions and EV owners, providing clean and affordable energy to charge vehicles.
With the realization of the “dual carbon” goal, urban public transport with an increasing proportion of new energy vehicles will become the key subject to achieve the carbon emission reduction goal. Under the new background of deep coupling between transport networks and power grids, it is of great significance to study the carbon-trading mode of urban public transport participation in promoting the development of new energy vehicles and improving the operating efficiency and low-carbon level of the “energy-transport” system. In this paper, based on blockchain technology, a framework for urban public transportation networks to participate in carbon trading is established to solve the current problems of urban public transportation’s insufficient motivation to reduce emissions, lax operation strategy and lack of carbon-trading matching mechanisms. Finally, Hyperledger Fabric was selected as the simulation platform, and we simulated the model through the calculation example. The results show that the proposed scheme can effectively improve the operating efficiency of urban public transport and reduce its operating costs and carbon emissions. In addition, policy recommendations on carbon price, carbon quota and penalties are proposed to improve the institutional system of the carbon-trading market.
Zhangwei Feng, Na Luo, Timofey Shalpegin, Huan Cui
The new energy vehicle (NEV) is emerging as an important alternative in the automobile industry in its potential to alleviate environmental pollution and contribute to carbon neutrality. The rapid growth of NEVs has been reflected in the scaling up of electric vehicle battery production. The dramatic increase of retired batteries, however, exposes the technological limitations in current recycling operations, which will ultimately impede the sustainable development of the NEV supply chain. Blockchain technology (BT) adoption provides a solution by contributing to the construction of an efficient recycling network. Our research investigates the influence of carbon reduction instruments on the uptake of BT. The key findings are as follows. Under a carbon tax system, (1) carbon emission reduction encourages the battery supplier to adopt BT; (2) BT adoption increases the profits of NEV supply chain stakeholders. Under carbon cap-and-trade regulations, (1) the unit outsourcing fee and the performance of the BT impact the investment decision of the manufacturer; (2) the profit of the third-party enterprise is increased by introducing the BT. Under both policies, improving the efficiency of BT helps to upgrade the traceability level and contribute to carbon neutrality in the NEV supply chain.