This paper presents a transactive demand response(TDR)scheme for a network of residential customers with generation assets that emphasizes interoperability within a transactive energy architecture.A complete laborator...This paper presents a transactive demand response(TDR)scheme for a network of residential customers with generation assets that emphasizes interoperability within a transactive energy architecture.A complete laboratory-based implementation provides the first(to our knowledge)realization of a comprehensive TDR use case that is fully compliant with the Institute of Electrical and Electronics Engineers(IEEE)2030.5 standard,which addresses interoperability within a cybersecure smart energy profile(SEP)context.Verification is provided by a full system integration with commercial hardware using Internet Protocol(IP)-based(local area network(LAN)and Wi-Fi)communication protocols and transport layer security(TLS)1.2 cryptographic protocol,and validation is provided by emulation using extensive residential smart meter data.The demand response(DR)scheme is designed to accommodate privacy concerns,allows customers to select their DR compliance level,and provides incentives to maximize their participation.The proposed TDR scheme addresses privacy through the implementation of the SEP 2.0 messaging protocol between a transactive agent(TA)and home energy management system(HEMS)agents.Customer response is handled by a multi-input multi-output(MIMO)fuzzy controller that manages negotiation between the customer agent and the TA.We take a multi-agent system approach to neighborhood coordination,with the TA servicing multiple residences on a common transformer,and use a reward mechanism to maximize customer engagement during the event-based optimization.Based on a set of smart meter data acquired over an extended time period,we engage in multiple TDR scenarios,and demonstrate with a fully-functional IEEE 2030.5-compliant implementation that our scheme can reduce network peak power consumption by 22%under realistic conditions.展开更多
2025年2月11日,由IEEE技术工程管理学会(IEEE Technology and Engineering Management Society)区块链与分布式账本技术委员会与南洋理工大学金融计算技术中心联合评选的“IEEE TEMS TC on Blockchain and DLT Awards”正式揭晓。北京...2025年2月11日,由IEEE技术工程管理学会(IEEE Technology and Engineering Management Society)区块链与分布式账本技术委员会与南洋理工大学金融计算技术中心联合评选的“IEEE TEMS TC on Blockchain and DLT Awards”正式揭晓。北京大学李挥教授指导的博士生王菡凭借其博士学位论文《许可链CAP三难困境的协同优化研究》(On the Collaborative Optimization of the CAP Trilemma in Permissioned Blockchains)从全球被邀请参评成果中脱颖而出,成功获选优秀博士学位论文奖(Outstanding Ph.D. Dissertation/Thesis Award)。展开更多
基金Natural Sciences and Engineering Council of Canada(CRDPJ 477238-14)and Hydro Ottawa。
文摘This paper presents a transactive demand response(TDR)scheme for a network of residential customers with generation assets that emphasizes interoperability within a transactive energy architecture.A complete laboratory-based implementation provides the first(to our knowledge)realization of a comprehensive TDR use case that is fully compliant with the Institute of Electrical and Electronics Engineers(IEEE)2030.5 standard,which addresses interoperability within a cybersecure smart energy profile(SEP)context.Verification is provided by a full system integration with commercial hardware using Internet Protocol(IP)-based(local area network(LAN)and Wi-Fi)communication protocols and transport layer security(TLS)1.2 cryptographic protocol,and validation is provided by emulation using extensive residential smart meter data.The demand response(DR)scheme is designed to accommodate privacy concerns,allows customers to select their DR compliance level,and provides incentives to maximize their participation.The proposed TDR scheme addresses privacy through the implementation of the SEP 2.0 messaging protocol between a transactive agent(TA)and home energy management system(HEMS)agents.Customer response is handled by a multi-input multi-output(MIMO)fuzzy controller that manages negotiation between the customer agent and the TA.We take a multi-agent system approach to neighborhood coordination,with the TA servicing multiple residences on a common transformer,and use a reward mechanism to maximize customer engagement during the event-based optimization.Based on a set of smart meter data acquired over an extended time period,we engage in multiple TDR scenarios,and demonstrate with a fully-functional IEEE 2030.5-compliant implementation that our scheme can reduce network peak power consumption by 22%under realistic conditions.
文摘2025年2月11日,由IEEE技术工程管理学会(IEEE Technology and Engineering Management Society)区块链与分布式账本技术委员会与南洋理工大学金融计算技术中心联合评选的“IEEE TEMS TC on Blockchain and DLT Awards”正式揭晓。北京大学李挥教授指导的博士生王菡凭借其博士学位论文《许可链CAP三难困境的协同优化研究》(On the Collaborative Optimization of the CAP Trilemma in Permissioned Blockchains)从全球被邀请参评成果中脱颖而出,成功获选优秀博士学位论文奖(Outstanding Ph.D. Dissertation/Thesis Award)。
