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Two-stage Planning Method for Energy Router Considering Its Optimal Operation in Distribution Networks

CSEE Journal of Power and Energy Systems 2024年第2期10卷 605-616页

作者： Meifu Chen Mingchao Xia Qifang Chen School of Electrical Engineering Beijing Jiaotong UniversityBeijing 100044China

An energy router can effectively optimize the network loss and power quality of distribution networks. The optimal configuration of the energy router is relatively complex because issues dynamically influence each other, such as the location of the energy router, optimal number and capacity of its ports, and building new distribution lines for the ports. Presently, there has been very few research studies on the practical problems for the energy router. In this paper, a planning model of an energy router combined with the distribution network is established, which fully exploits the active and reactive power control abilities of the energy router to optimize the operation of the grid. The configuration problem is decoupled into two stages. The upper layer determines the location of the energy router and the parameters of the candidate new distribution lines for the ports. The lower layer calculates the optimal configuration of the energy router by minimizing the total annual cost. Because of the same rated bus voltage in the distribution network, the existing structure of the energy router is changed to be more applicable for the distribution network, and then the power flow model of the energy router is also modified. Due to the nonlinearity of the model, the planning model is converted into a mixed-integer second-order cone model to solve efficiently. In addition, some core factors influencing the optimal scheme of the energy router are also analyzed in this paper. Simulation results show that the optimal scheme of the energy router can significantly improve the economic deployment of the energy router, and optimize the network loss and power quality of the distribution network.

关键词： Capacity allocation distribution network energy router optimal operation

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Planning Model for Energy Routers Considering Peer-to-Peer Energy Transactions Among Multiple Distribution Networks

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CSEE Journal of Power and Energy Systems 2024年第3期10卷 1026-1043页

作者： Meifu Chen Mingchao Xia Qifang Chen School of Electrical Engineering Beijing Jiaotong UniversityBeijing 100044China IEEE

A high proportion of renewable energy affects the power quality of distribution networks,and surplus energy will be sold to the upstream grid at a low *** this paper,considering peer-to-peer energy transactions,the energy router-based multiple distribution networks are analyzed to solve the above problems and realize collaborative consumption of renewable ***,the investing cost of an energy router is high,and research on the economic operation of energy routers in distribution networks is ***,this paper establishes a planning model for energy routers considering peer-to-peer energy transactions among distribution networks,and explores the benefits of peer-to-peer energy transactions through energy router based multiple distribution networks.A structure of an energy router suitable for peer-to-peer energy transactions is selected,and a power flow calculation model based on a multilayer structure is *** energy router’s scheduling model is established,and unique functions of the energy router and revenue of each distribution network are considered.A power flow calculation model based on peer-to-peer interconnection of multiple distribution networks through energy routers is also ***,simulation results verify the effectiveness of the proposed planning *** show that peer-topeer energy transaction among distribution networks through energy routers can effectively reduce the comprehensive cost of distribution networks,significantly improve the power quality of the distribution networks,and reduce the impact of power fluctuation on the upstream grid incurred by the distribution network.

关键词： Capacity allocation energy router multiple distribution networks peer-to-peer energy transaction power flow optimization

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