Peer-to-peer(P2P)energy trading in active distribution networks(ADNs)plays a pivotal role in promoting the efficient consumption of renewable energy sources.However,it is challenging to effectively coordinate the powe...Peer-to-peer(P2P)energy trading in active distribution networks(ADNs)plays a pivotal role in promoting the efficient consumption of renewable energy sources.However,it is challenging to effectively coordinate the power dispatch of ADNs and P2P energy trading while preserving the privacy of different physical interests.Hence,this paper proposes a soft actor-critic algorithm incorporating distributed trading control(SAC-DTC)to tackle the optimal power dispatch of ADNs and the P2P energy trading considering privacy preservation among prosumers.First,the soft actor-critic(SAC)algorithm is used to optimize the control strategy of device in ADNs to minimize the operation cost,and the primary environmental information of the ADN at this point is published to prosumers.Then,a distributed generalized fast dual ascent method is used to iterate the trading process of prosumers and maximize their revenues.Subsequently,the results of trading are encrypted based on the differential privacy technique and returned to the ADN.Finally,the social welfare value consisting of ADN operation cost and P2P market revenue is utilized as a reward value to update network parameters and control strategies of the deep reinforcement learning.Simulation results show that the proposed SAC-DTC algorithm reduces the ADN operation cost,boosts the P2P market revenue,maximizes the social welfare,and exhibits high computational accuracy,demonstrating its practical application to the operation of power systems and power markets.展开更多
As an emerging hot technology,smart grids(SGs)are being employed in many fields,such as smart homes and smart cities.Moreover,the application of artificial intelligence(AI)in SGs has promoted the development of the po...As an emerging hot technology,smart grids(SGs)are being employed in many fields,such as smart homes and smart cities.Moreover,the application of artificial intelligence(AI)in SGs has promoted the development of the power industry.However,as users’demands for electricity increase,traditional centralized power trading is unable to well meet the user demands and an increasing number of small distributed generators are being employed in trading activities.This not only leads to numerous security risks for the trading data but also has a negative impact on the cost of power generation,electrical security,and other aspects.Accordingly,this study proposes a distributed power trading scheme based on blockchain and AI.To protect the legitimate rights and interests of consumers and producers,credibility is used as an indicator to restrict untrustworthy behavior.Simultaneously,the reliability and communication capabilities of nodes are considered in block verification to improve the transaction confirmation efficiency,and a weighted communication tree construction algorithm is designed to achieve superior data forwarding.Finally,AI sensors are set up in power equipment to detect electricity generation and transmission,which alert users when security hazards occur,such as thunderstorms or typhoons.The experimental results show that the proposed scheme can not only improve the trading security but also reduce system communication delays.展开更多
Distributed power market trading has the characteristics of large number of participants,scattered locations,small single trading scale,and point-to-point trading.The traditional centralized power trading model has th...Distributed power market trading has the characteristics of large number of participants,scattered locations,small single trading scale,and point-to-point trading.The traditional centralized power trading model has the problems of large load,low efficiency,high cost,reliance on third parties and unreliable data.With the characteristics of decentralization and nontampering,blockchain can establish a point-to-point trusted trading environment and provide effective solutions to the above problems.Therefore,this paper proposed a distributed power market trading framework based on blockchain.In this framework,the distributed power supply characteristics and trading needs of each participant are analyzed,a complete distributed trading process based on blockchain is designed.In addition,we have studied the key technologies of distributed power market trading.With the goal of power service reputation and maximum revenue of distributed power providers,we have established a matching degree model,a distributed power market trading optimization model,and designed a smart contract-based power market trading optimization strategy and power trading settlement strategy.Finally,we designed experiments to verify the performance of the proposed framework.展开更多
基金supported by the National Natural Science Foundation of China(No.52177085).
文摘Peer-to-peer(P2P)energy trading in active distribution networks(ADNs)plays a pivotal role in promoting the efficient consumption of renewable energy sources.However,it is challenging to effectively coordinate the power dispatch of ADNs and P2P energy trading while preserving the privacy of different physical interests.Hence,this paper proposes a soft actor-critic algorithm incorporating distributed trading control(SAC-DTC)to tackle the optimal power dispatch of ADNs and the P2P energy trading considering privacy preservation among prosumers.First,the soft actor-critic(SAC)algorithm is used to optimize the control strategy of device in ADNs to minimize the operation cost,and the primary environmental information of the ADN at this point is published to prosumers.Then,a distributed generalized fast dual ascent method is used to iterate the trading process of prosumers and maximize their revenues.Subsequently,the results of trading are encrypted based on the differential privacy technique and returned to the ADN.Finally,the social welfare value consisting of ADN operation cost and P2P market revenue is utilized as a reward value to update network parameters and control strategies of the deep reinforcement learning.Simulation results show that the proposed SAC-DTC algorithm reduces the ADN operation cost,boosts the P2P market revenue,maximizes the social welfare,and exhibits high computational accuracy,demonstrating its practical application to the operation of power systems and power markets.
基金supported by the National Natural Science Foundation of China with Grants 61771289 and 61832012the Natural Science Foundation of Shandong Province with Grants ZR2021QF050 and ZR2021MF075+3 种基金Shandong Natural Science Foundation Major Basic Research with Grant ZR2019ZD10Shandong Key Research and Development Program with Grant 2019GGX1050Shandong Major Agricultural Application Technology Innovation Project with Grant SD2019NJ007National Natural Science Foundation of Shandong Province Grants ZR2022MF304.
文摘As an emerging hot technology,smart grids(SGs)are being employed in many fields,such as smart homes and smart cities.Moreover,the application of artificial intelligence(AI)in SGs has promoted the development of the power industry.However,as users’demands for electricity increase,traditional centralized power trading is unable to well meet the user demands and an increasing number of small distributed generators are being employed in trading activities.This not only leads to numerous security risks for the trading data but also has a negative impact on the cost of power generation,electrical security,and other aspects.Accordingly,this study proposes a distributed power trading scheme based on blockchain and AI.To protect the legitimate rights and interests of consumers and producers,credibility is used as an indicator to restrict untrustworthy behavior.Simultaneously,the reliability and communication capabilities of nodes are considered in block verification to improve the transaction confirmation efficiency,and a weighted communication tree construction algorithm is designed to achieve superior data forwarding.Finally,AI sensors are set up in power equipment to detect electricity generation and transmission,which alert users when security hazards occur,such as thunderstorms or typhoons.The experimental results show that the proposed scheme can not only improve the trading security but also reduce system communication delays.
文摘Distributed power market trading has the characteristics of large number of participants,scattered locations,small single trading scale,and point-to-point trading.The traditional centralized power trading model has the problems of large load,low efficiency,high cost,reliance on third parties and unreliable data.With the characteristics of decentralization and nontampering,blockchain can establish a point-to-point trusted trading environment and provide effective solutions to the above problems.Therefore,this paper proposed a distributed power market trading framework based on blockchain.In this framework,the distributed power supply characteristics and trading needs of each participant are analyzed,a complete distributed trading process based on blockchain is designed.In addition,we have studied the key technologies of distributed power market trading.With the goal of power service reputation and maximum revenue of distributed power providers,we have established a matching degree model,a distributed power market trading optimization model,and designed a smart contract-based power market trading optimization strategy and power trading settlement strategy.Finally,we designed experiments to verify the performance of the proposed framework.
