综合智慧能源 ›› 2023, Vol. 45 ›› Issue (1): 49-57.doi: 10.3969/j.issn.2097-0706.2023.01.006

• 电力系统规划 • 上一篇    下一篇

基于改进粒子群算法的分布式光伏及储能系统优化配置

胡祖源1, 靳现林1, 谭雅之2,*(), 樊静宜2   

  1. 1.国华能源投资有限公司,北京 100007
    2.华北电力大学 电气与电子工程学院,北京 102206
  • 收稿日期:2022-07-20 修回日期:2022-09-05 出版日期:2023-01-25 发布日期:2023-02-22
  • 通讯作者: *谭雅之(1999),女,在读硕士研究生,从事分布式电源接入电网、电网规划等方面的研究,1598817561@qq.com
  • 作者简介:胡祖源(1973),男,工程师,从事智慧楼宇、分布式发电、项目管理等方面的工作;
    靳现林(1974),男,高级工程师,硕士,从事新能源发电生产管理工作;
    樊静宜(1999),女,在读硕士研究生,从事新型电力系统规划应用研究。
  • 基金资助:
    国家自然科学基金项目(51977074)

Optimized configuration of distributed photovoltaic and energy storage system based on improved particle swarm algorithm

HU Zuyuan1, JIN Xianlin1, TAN Yazhi2,*(), FAN Jingyi2   

  1. 1. Guohua Energy Investment Company Limited, Beijing 100007,China
    2. School of Electrical and Electronic Engineering, North China Electric Power University, Beijing 102206, China
  • Received:2022-07-20 Revised:2022-09-05 Online:2023-01-25 Published:2023-02-22
  • Supported by:
    National Natural Science Foundation of China(51977074)

摘要:

“碳达峰、碳中和”目标的提出要求进一步推进分布式电源接入配电网,针对分布式光伏并网引起的不确定性问题,研究了分布式光伏及储能的优化配置,采用系统聚类筛选光伏的典型出力场景用于储能规划,综合考虑场景的经济效益、负荷的波动及削峰填谷率等,建立光伏及储能优化配置的混合整型非线性规划模型。采用自适应粒子群算法进行求解,分析不同负荷、不同电价时段对储能容量配置及系统运行的影响。算例结果表明,引入储能系统后可有效平抑光伏出力的不确定性,优化负荷曲线,同时提高系统的整体运行性能,验证了模型的可行性与求解方法的有效性。

关键词: 碳中和, 分布式光伏, 储能系统, 系统聚类, 改进粒子群算法, 容量配置, 分布式电源, 配电网

Abstract:

The proposal of the goals of carbon peaking and carbon neutrality makes a further request on the grid connection of distributed energy systems. To address the uncertainty triggered by the grid-connected distributed photovoltaic (PV) systems, the optimal configuration of distributed PV and energy storage systems is studied. Based on the typical PV output scenarios selected by clustering process, a hybrid integral non-linear programming model for the optimal configuration of a photovoltaic and energy storage system was established while taking economic benefits, load fluctuation and peak-shaving rates into consideration. The model was solved by adaptive particle swarm optimization algorithm, and the influence of different loads and electricity prices on energy storage capacity and on the operation of the system was analyzed. The results show that the energy storage system can effectively stabilize the photovoltaic output, optimize the load curve and improve the overall operating performance of the system, which verifies the feasibility of the model and the effectiveness of the solution.

Key words: carbon neutrality, distributed photovoltaic, energy storage system, clustering, improved particle swarm algorithm, capacity allocation, distributed power source, distribution network

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