In recent years, the increasing penetration level of renewable generation and combined heat and power(CHP) technology in power systems is leading to significant changes in energy production and consumption patterns. A...In recent years, the increasing penetration level of renewable generation and combined heat and power(CHP) technology in power systems is leading to significant changes in energy production and consumption patterns. As a result, the integrated planning and optimal operation of a multi-carrier energy(MCE) system have aroused widespread concern for reasonable utilization of multiple energy resources and efficient accommodation of renewable energy sources. In this context, an integrated demand response(IDR) scheme is designed to coordinate the operation of power to gas(P2 G) devices, heat pumps,diversified storage devices and flexible loads within an extended modeling framework of energy hubs. Subsequently, the optimal dispatch of interconnected electricity,natural gas and heat systems is implemented considering the interactions among multiple energy carriers by utilizing the bi-level optimization method. Finally, the proposed method is demonstrated with a 4-bus multi-energy systemand a larger test case comprised of a revised IEEE 118-bus power system and a 20-bus Belgian natural gas system.展开更多
In recent years,much attention has been devoted to the development and applications of smart grid technologies,with special emphasis on flexible resources such as distributed generations(DGs),energy storages,active lo...In recent years,much attention has been devoted to the development and applications of smart grid technologies,with special emphasis on flexible resources such as distributed generations(DGs),energy storages,active loads,and electric vehicles(EVs).Demand response(DR) is expected to be an effective means for accommodating the integration of renewable energy generations and mitigating their power output fluctuations.Despite their potential contributions to power system secure and economic operation,uncoordinated operations of these flexible resources may result in unexpected congestions in the distribution system concerned.In addition,the behaviors and impacts of flexible resources are normally highly uncertain and complex in deregulated electricity market environments.In this context,this paper aims to propose a DR based congestion management strategy for smart distribution systems.The general framework and procedures for distribution congestion management is first presented.A bi-level optimization model for the day-ahead congestion management based on the proposed framework is established.Subsequently,the robust optimization approach is introduced to alleviate negative impacts introduced by the uncertainties of DG power outputs and market prices.The economic efficiency and robustness of the proposed congestion management strategy is demonstrated by an actual 0.4 kV distribution system in Denmark.展开更多
文摘In recent years, the increasing penetration level of renewable generation and combined heat and power(CHP) technology in power systems is leading to significant changes in energy production and consumption patterns. As a result, the integrated planning and optimal operation of a multi-carrier energy(MCE) system have aroused widespread concern for reasonable utilization of multiple energy resources and efficient accommodation of renewable energy sources. In this context, an integrated demand response(IDR) scheme is designed to coordinate the operation of power to gas(P2 G) devices, heat pumps,diversified storage devices and flexible loads within an extended modeling framework of energy hubs. Subsequently, the optimal dispatch of interconnected electricity,natural gas and heat systems is implemented considering the interactions among multiple energy carriers by utilizing the bi-level optimization method. Finally, the proposed method is demonstrated with a 4-bus multi-energy systemand a larger test case comprised of a revised IEEE 118-bus power system and a 20-bus Belgian natural gas system.
基金supported by National Basic Research Program of China (973 Program) (No. 2013CB228202)National Natural Science Foundsation of China (No. 51477151)+1 种基金Specialized Research Fund for the Doctoral Program of Higher Education (No. 20120101110112)a Project by China Southern Power Grid Company (No. K-GD2014-192)
文摘In recent years,much attention has been devoted to the development and applications of smart grid technologies,with special emphasis on flexible resources such as distributed generations(DGs),energy storages,active loads,and electric vehicles(EVs).Demand response(DR) is expected to be an effective means for accommodating the integration of renewable energy generations and mitigating their power output fluctuations.Despite their potential contributions to power system secure and economic operation,uncoordinated operations of these flexible resources may result in unexpected congestions in the distribution system concerned.In addition,the behaviors and impacts of flexible resources are normally highly uncertain and complex in deregulated electricity market environments.In this context,this paper aims to propose a DR based congestion management strategy for smart distribution systems.The general framework and procedures for distribution congestion management is first presented.A bi-level optimization model for the day-ahead congestion management based on the proposed framework is established.Subsequently,the robust optimization approach is introduced to alleviate negative impacts introduced by the uncertainties of DG power outputs and market prices.The economic efficiency and robustness of the proposed congestion management strategy is demonstrated by an actual 0.4 kV distribution system in Denmark.
