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An energy trading Method Based on Alliance Blockchain and Multi-Signature

Computers, Materials & Continua 2024年第2期78卷 1611-1629页

作者： Hongliang Tian Jiaming Wang College of Electrical Engineering Northeast Electric Power UniversityJilin132012China

Blockchain,known for its secure encrypted ledger,has garnered attention in financial and data transfer realms,including the field of energy trading.However,the decentralized nature and identity anonymity of user nodes raise uncertainties in energy transactions.The broadcast consensus authentication slows transaction speeds,and frequent single-point transactions in multi-node settings pose key exposure risks without protective measures during user signing.To address these,an alliance blockchain scheme is proposed,reducing the resource-intensive identity verification among nodes.It integrates multi-signature functionality to fortify user resources and transac-tion security.A novel multi-signature process within this framework involves neutral nodes established through central nodes.These neutral nodes participate in multi-signature’s signing and verification,ensuring user identity and transaction content privacy.Reducing interactions among user nodes enhances transaction efficiency by minimizing communication overhead during verification and consensus stages.Rigorous assessments on reliability and operational speed highlight superior security performance,resilient against conventional attack vectors.Simulation shows that compared to traditional solutions,this scheme has advantages in terms of running speed.In conclusion,the alliance blockchain framework introduces a novel approach to tackle blockchain’s limitations in energy transactions.The integrated multi-signature process,involving neutral nodes,significantly enhances security and privacy.The scheme’s efficiency,validated through analytical assessments and simulations,indicates robustness against security threats and improved transactional speeds.This research underscores the potential for improved security and efficiency in blockchain-enabled energy trading systems.

关键词： Alliance blockchain multi-signature energy trading security performance transaction efficiency

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Bi-level energy trading Model Incorporating Large-scale Biogas Plant and Demand Response Aggregator

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Journal of Modern Power Systems and Clean energy 2023年第2期11卷 567-578页

作者： Hanyu Yang Canbing Li Ruanming Huang Feng Wang Lili Hao Qiuwei Wu Long Zhou College of Electrical Engineering and Control Science Nanjing Tech UniversityNanjingChina School of Electronic Information and Electrical Engineering Shanghai Jiao Tong UniversityShanghai 200240China Economic and Technological Research Institute of Shanghai Electric Power Company ShanghaiChina College of Electrical and Information Engineering Hunan UniversityChangsha 410082China Tsinghua-Berkeley Shenzhen Institute Tsinghua Shenzhen International Graduate SchoolTsinghua UniversityShenzhen 518055China Information Center of Guangdong Power Grid Company Limited Guangzhou 528000China

Increasing intermittent renewable energy sources(RESs)intensifies the imbalance between demand and generation,entailing the diversification of the deployment of electrical energy storage systems(ESSs).A large-scale biogas plant(LBP)installed with heating devices and biogas energy storage(BES)usually exhibits a storage-like characteristic of accommodating an increasing penetration level of RES in rural areas,which is addressed in this paper.By utilizing the temperature-sensitive characteristic of anaerobic digestion that enables the LBP to exhibit a storage-like characteristic,this paper proposes a bi-level energy trading model incorporating LBP and demand response aggregator(DRA)simultaneously.In this model,social welfare is maximized at the upper level while the profit of DRA is maximized at the lower level.Compared with cases only with DRA,the results show that the proposed model with the LBP improves the on-site accommodation capacity of photovoltaic(PV)generation up to 6.3%,18.1%,and 18.9%at 30%,40%,and 50%PV penetration levels,respectively,with a better economic performance.This nonlinear bi-level problem is finally recast by a single-level mathematical program with equilibrium constraints(MPEC)using Karush-Kuhn-Tucker(KKT)conditions and solved by the Cplex solver.The effectiveness of the proposed model is validated using a 33-bus test system and a sensitivity analysis is provided for analyzing what parameter influences the accommodation capacity most.

关键词： Biomass energy renewable energy resource energy trading demand response distribution system

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Directed Acyclic Graph Blockchain for Secure Spectrum Sharing and energy trading in Power IoT

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China Communications 2023年第5期20卷 182-197页

作者： Zixi Zhang Mingxia Zhang Yu Li Bo Fan Li Jiang School of Automation Guangdong-HongKong-Macao Joint Laboratory for Smart Discrete Manufacturing(Guangdong University of Technology)Guangzhou 510006China Chongqing Key Laboratory of Intelligent Perception and BlockChain Technology (Chongqing Technology and Business University)Chongqing 40067China Beijing Key Laboratory of Traffic Engineering College of Metropolitan Transportation(Beijing University of Technology)Beijing 100124China

Peer-to-peer(P2P)spectrum sharing and energy trading are promising solutions to locally satisfy spectrum and energy demands in power Internet of Things(IoT).However,implementation of largescale P2P spectrum sharing and energy trading confronts security and privacy challenges.In this paper,we exploit consortium blockchain and Directed Acyclic Graph(DAG)to propose a new secure and distributed spectrum sharing and energy trading framework in power IoT,named spectrum-energy chain,where a set of local aggregators(LAGs)cooperatively confirm the identity of the power devices by utilizing consortium blockchain,so as to form a main chain.Then,the local power devices verify spectrum and energy micro-transactions simultaneously but asynchronously to form local spectrum tangle and local energy tangle,respectively.Moreover,an iterative double auction based micro transactions scheme is designed to solve the spectrum and energy pricing and the amount of shared spectrum and energy among power devices.Security analysis and numerical results illustrate that the developed spectrum-energy chain and the designed iterative double auction based microtransactions scheme are secure and efficient for spectrum sharing and energy trading in power IoT.

关键词： power Internet of Things(IoT) spectrum sharing energy trading security and privacy consortium blockchain Directed Acyclic Graph(DAG) iterative double auction

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Deep Learning Enabled Predictive Model for P2P energy trading in TEM

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Computers, Materials & Continua 2022年第4期71卷 1473-1487页

作者： Pudi Sekhar T.J.Benedict Jose Velmurugan Subbiah Parvathy E.Laxmi Lydia Seifedine Kadry Kuntha Pin Yunyoung Nam Department of Electrical and Electronics Engineering Vignan’s Institute of Information Technology(Autonomous)Visakhapatnam530049India Department of Computer Applications Government Arts&Science CollegeKanyakumari629401India Department of Electronics and Communication Engineering Kalasalingam Academy of Research and EducationKrishnankoil626126India Department of Computer Science and Engineering Vignan’s Institute of Information Technology(Autonomous)Visakhapatnam530049India Department of Applied Data Science Noroff University CollegeKristiansandNorway Department of ICT Convergence Soonchunhyang UniversityKorea Department of Computer Science and Engineering Soonchunhyang UniversityKorea

With the incorporation of distributed energy systems in the electric grid,transactive energy market(TEM)has become popular in balancing the demand as well as supply adaptively over the grid.The classical grid can be updated to the smart grid by the integration of Information and Communication Technology(ICT)over the grids.The TEM allows the Peerto-Peer(P2P)energy trading in the grid that effectually connects the consumer and prosumer to trade energy among them.At the same time,there is a need to predict the load for effectual P2P energy trading and can be accomplished by the use of machine learning(DML)models.Though some of the short term load prediction techniques have existed in the literature,there is still essential to consider the intrinsic features,parameter optimization,etc.into account.In this aspect,this study devises new deep learning enabled short term load forecasting model for P2P energy trading(DLSTLF-P2P)in TEM.The proposed model involves the design of oppositional coyote optimization algorithm(OCOA)based feature selection technique in which the OCOA is derived by the integration of oppositional based learning(OBL)concept with COA for improved convergence rate.Moreover,deep belief networks(DBN)are employed for the prediction of load in the P2P energy trading systems.In order to additional improve the predictive performance of the DBN model,a hyperparameter optimizer is introduced using chicken swarm optimization(CSO)algorithm is applied for the optimal choice of DBN parameters to improve the predictive outcome.The simulation analysis of the proposed DLSTLF-P2P is validated using the UK Smart Meter dataset and the obtained outcomes demonstrate the superiority of the DLSTLF-P2P technique with the maximum training,testing,and validation accuracy of 90.17%,87.39%,and 87.86%.

关键词： energy trading distributed systems power generation load forecasting deep learning peer-to-peer

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Peer-to-Peer energy trading Method of Multi-Virtual Power Plants Based on Non-Cooperative Game

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energy Engineering 2023年第5期120卷 1163-1183页

作者： Jingjing Bai Hongyi Zhou Zheng Xu Yu Zhong Yancheng Power Supply Company of State Grid Jiangsu Electric Power Co. Ltd.Yancheng224008China

The current electricity market fails to consider the energy consumption characteristics of transaction subjects such as virtual power plants.Besides,the game relationship between transaction subjects needs to be further explored.This paper proposes a Peer-to-Peer energy trading method for multi-virtual power plants based on a non-cooperative game.Firstly,a coordinated control model of public buildings is incorporated into the scheduling framework of the virtual power plant,considering the energy consumption characteristics of users.Secondly,the utility functions of multiple virtual power plants are analyzed,and a non-cooperative game model is established to explore the game relationship between electricity sellers in the Peer-to-Peer transaction process.Finally,the influence of user energy consumption characteristics on the virtual power plant operation and the Peer-to-Peer transaction process is analyzed by case studies.Furthermore,the effect of different parameters on the Nash equilibrium point is explored,and the influence factors of Peer-to-Peer transactions between virtual power plants are summarized.According to the obtained results,compared with the central air conditioning set as constant temperature control strategy,the flexible control strategy proposed in this paper improves the market power of each VPP and the overall revenue of the VPPs.In addition,the upper limit of the service quotation of the market operator have a great impact on the transaction mode of VPPs.When the service quotation decreases gradually,the P2P transaction between VPPs is more likely to occur.

关键词： Virtual power plant Peer-to-Peer energy trading public building non-cooperative game

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V2V energy trading Considering User Satisfaction under Low-Carbon Objectives via Bayesian Game

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Journal of Power and energy Engineering 2023年第12期11卷 15-35页

作者： Yue Yu Yu Liu Xiang Feng Huaichao Wen School of Rail Transit Hunan University of Technology Zhuzhou China

In response to the additional load impact caused by the integration of electric vehicles (EVs) into the grid or microgrids (MGs), as well as the issue of low responsiveness of EV users during vehicle-to-vehicle (V2V) power exchange processes, this paper explores a multi-party energy trading model considering user responsiveness under low carbon goals. The model takes into account the stochastic charging and discharging characteristics of EVs, user satisfaction, and energy exchange costs, and formulates utility functions for participating entities. This transforms the competition in multi-party energy trading into a Bayesian game problem, which is subsequently resolved. Furthermore, this paper primarily employs sensitivity analysis to evaluate the impact of multi-party energy trading on user responsiveness and green energy utilization, with the aim of promoting incentives in the electricity trading market and aligning with low-carbon requirements. Finally, through case simulations, the effectiveness of this model for the considered scenarios is demonstrated.

关键词： Multi Electric Vehicles Multi Microgrid energy trading Bayesian Game Multi Party Game Network Constraints

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energy trading in Smart Grid:A Deep Reinforcement Learning-based Approach

Energy Trading in Smart Grid:A Deep Reinforcement Learning-b...

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第32届中国控制与决策会议

作者： Feiye Zhang Qingyu Yang School of Automation Science and Engineering Xi'an Jiaotong University SKLMSE Lab MOE Key Laboratory for Intelligent Networks and Network SecuritySchool of Automation Science and EngineeringXi'an Jiaotong University

To achieve the efficient operation of the smart grid,appropriate energy trading strategy plays an important role in reducing multi-agent costs in the trading process as well as alleviating grid pressure.However,with the increase of the number of participants in smart grid,energy trading has been greatly challenged in terms of stable and effective operation.In this paper,we propose a deep reinforcement learning-based energy double auction trading strategy.Through the deep reinforcement learning algorithm,buyers and sellers can gradually learn the environment by treating the three elements:total supply,total demand and their own supply and demand as states,in addition,regarding both bidding price and quantity as bidding strategy.Results from simulation indicate that as the learning continues and reaches the convergence,both the cost which buyers pay in the auction has decreased significantly,and the profit which sellers earn in the auction will increase.

关键词： Smart Grid energy trading Double Auction Deep Reinforcement Learning

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Robust energy trading for Interconnected Microgrids under Uncertain Electricity Price

Robust Energy Trading for Interconnected Microgrids under Un...

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第40届中国控制会议

作者： Hengdu Hu Bing Wang Shiqin Yang School of Mechatronic Engineering and Automation Shanghai University

This paper studies the energy trading between the interconnected microgrid, considering the uncertain electricity price of the microgrid and main grid for energy trading, we design a robust energy trading strategy, which not only considers the individual interests of the microgrid, but also enables the microgrid participating in the energy trading to get a fair share of the benefits from the cooperation. The uncertain electricity price is described by discrete scenarios. In order to give consideration to the optimization and conservatism of the solution, a robust optimization method based on the threshold of bad scenario set is used to consider more bad scenarios. To solve the robust energy trading model, an alternating direction method of multipliers based on the update of bad scenario set is proposed. The final experimental results show that the robust energy trading strategy based on the threshold of bad scenario set can reduce the total operating cost of the society by 11.11%, and the cost of a single microgrid can be reduced by 15.36% at most.

关键词： Microgrid energy trading Uncertain Electricity Price Bad Scenario Set Robust Optimization Alternating Direction Method of Multipliers（ADMM）

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Blockchain in energy systems:values,opportunities,and limitations

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Frontiers in energy 2022年第1期16卷 9-18页

作者： Sijie CHEN Jian PING Zheng YAN Jinjin LI Zhen HUANG Key Laboratory of Control of Power Transmission and Conversion(Ministry of Education) Shanghai Jiao Tong UniversityShanghai 200240China Key Laboratory for Thin Film and Microfabrication(Ministry of Education) Department of Micro/Nano-electronicsShanghai Jiao Tong UniversityShanghai 200240China Key Laboratory for Power Machinery and Engineering(Ministry of Education) Shanghai Jiao Tong UniversityShanghai 200240China

The structure of a power energy system is becoming more distributed than before.It becomes challenging to manage such a system in a centralized way,because a central authority may not exist or may not be trusted by all parties.Blockchain is a promising tool to address this challenge,by enabling trusted collaboration in the absence of a trusted central authority.Its use in the energy sector has been pioneered by several pilot projects.However,to date the energy sector has not seen large-scale deployment of blockchain,partly because the founders of those pilot projects,the public,and utilities have not reached consensus on the values and limitations of blockchain in energy.This perspective aims to bridge this gap.First,the philosophy and unique values of blockchain are discussed.Second,some promising blockchain-based applications in energy systems are presented.Third,some common misunderstandings of blockchain in energy are discussed.Last,some frequently-asked questions from utilities are discussed.Hopefully this perspective can help advance large-scale deployment of blockchain in energy systems.

关键词： blockchain immutability energy trading energy management data synchronization

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Joint energy trading and Scheduling for Multi-energy microgrids with Storage

Joint Energy Trading and Scheduling for Multi-Energy microgr...

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第三十九届中国控制会议

作者： Dafeng Zhu Bo Yang Qi Liu Kai Ma Shanying Zhu Xinping Guan Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China School of Electrical Engineering Yanshan University

Considering that energy trading might not completely absorb excess renewable energy, we propose a multi-energy management framework including fuel cell vehicles, energy storage, combined heat and power system, and renewable energy to further realize the local absorption of renewable energy and enhance the economic benefits of microgrids. In order to reduce the influence of multi-energy coupling, stochastic renewable energy generation and energy demand, this paper designs a joint energy scheduling and trading algorithm based on Lyapunov optimization and a double-auction mechanism to optimize the long-term energy cost of each microgrid. Coupling with the auction mechanism is a dynamic, efficient energy trading and scheduling algorithm, which carefully decides the valuations of energy in the auction, optimally schedules energy, and judiciously purchases and sells energy on the current electricity prices. Simulations based on real data show that each individual microgrid, by carrying out the proposed algorithm, can achieve a time-averaged profit arbitrarily close to an optimum value while not compromising its own comfort.

关键词： Multi-energy microgrid energy storage energy trading Lyapunov optimization double-auction

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