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计及共享储能与光伏的园区多用户综合收益优化
引用本文:马佳伊,刘海涛,仲聪,袁宇波,张效诚. 计及共享储能与光伏的园区多用户综合收益优化[J]. 电力工程技术, 2024, 43(1): 60-67
作者姓名:马佳伊  刘海涛  仲聪  袁宇波  张效诚
作者单位:南京工程学院电力工程学院,南京工程学院电力工程学院,南京工程学院电力工程学院,国网江苏省电力有限公司电力科学研究院,南京工程学院电力工程学院
基金项目:国家重点研发计划“高效协同充换电关键技术及装备(2021YFB2501600)”
摘    要:针对含共享储能与户用光伏的园区场景,文中提出一种用户侧综合收益双层优化方法,充分挖掘共享储能灵活性及用户用电需求差异性,在实现用户整体经济效益最优的同时提升光伏消纳能力。模型上层为月前优化阶段,以用户月度用电成本最低为目标,考虑系统能量平衡、储能充放电约束以及储能荷电状态约束,优化工业用户最大用电功率,降低需量电费;模型下层为日前优化阶段,综合考虑用户综合收益及光伏消纳能力,以上层优化结果为约束条件,兼顾功率、储能等约束,提出共享储能充放电功率及用户与电网交互功率等日前优化策略,在用户月度整体经济性最优的前提下,实现用户侧每日经济效益的优化。最后,以南方某实际园区作为算例验证了文中所提方法的有效性。

关 键 词:共享储能  户用光伏  双层优化  用户综合收益  光伏消纳能力  需量电费
收稿时间:2022-11-04
修稿时间:2023-03-30

Research on comprehensive benefits optimization method for multiple types of users con-nected to the same industrial park considering shared energy storage and distributed photo-voltaic
MA Jiayi,LIU Haitao,ZHONG Cong,YUAN Yubo and ZHANG Xiaocheng. Research on comprehensive benefits optimization method for multiple types of users con-nected to the same industrial park considering shared energy storage and distributed photo-voltaic[J]. Electric Power Engineering Technology, 2024, 43(1): 60-67
Authors:MA Jiayi  LIU Haitao  ZHONG Cong  YUAN Yubo  ZHANG Xiaocheng
Affiliation:School of Electric Power Engineering,Nanjing Institute of Technology,School of Electric Power Engineering,Nanjing Institute of Technology,School of Electric Power Engineering,Nanjing Institute of Technology,State Grid Jiangsu Electric Power Co,Ltd Research Institute,School of Electric Power Engineering,Nanjing Institute of Technology
Abstract:Considering the flexibility of shared energy storage and the different electricity demand of multiple types of users, a bi-level optimization method is proposed to achieve the optimal overall economic benefits of users and improve the photovoltaic consumption capacity for industrial users. Aiming at the lowest monthly power consumption cost of us-ers, the upper layer model is established considering the system energy balance, energy storage charging and dis-charging constraints and energy storage state of charge constraints, so as to reduce the monthly maximum electricity demand. Taking the optimized monthly demand from the upper model as one part of the constraints, the day-ahead model is established, and the charging and discharging power of the shared energy storage, as well as the interactive power between users and the power grid are output to optimize comprehensive benefits of multiple types of industrial users and improve the photovoltaic absorption ability. Finally, the effectiveness of the proposed method is verified with the case study.
Keywords:Shared energy storage   Household photovoltaic   Double layer optimization   User comprehensive revenue   Photovol-taic absorption capacity   Demand of electricity.
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