| 引用本文: | 杜鹏,米增强,贾雨龙,等.基于网损灵敏度方差的配电网分布式储能位置与容量优化配置方法[J].电力系统保护与控制,2019,47(6):103-109.[点击复制] |
| DU Peng,MI Zengqiang,JIA Yulong,et al.Optimal placement and capacity of distributed energy storage in distribution system based on the sensitivity variance of network loss[J].Power System Protection and Control,2019,47(6):103-109[点击复制] |
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| 摘要: |
| 针对典型日负荷曲线，提出基于网损灵敏度方差的配电网分布式储能位置和容量优化配置方法。该方法考虑了分布式储能的充放电运行状态，基于网损灵敏度方差确定配电网中各节点接入分布式储能的优先顺序。以配电网网损和节点电压波动为目标函数，运用改进的粒子群算法对分布式储能的充放电功率进行优化，并确定分布式储能的最优配置容量。仿真结果表明，采用该方法确定分布式储能在配电网中的位置和容量可最大化实现功率就地平衡、降低配电网网损和降低配电网节点电压波动，实现分布式储能在配电网中的优化配置。 |
| 关键词: 分布式储能 配电网 网损灵敏度方差 改进粒子群算法 有功网损 |
| DOI：10.7667/PSPC180402 |
| 投稿时间：2018-04-11修订日期：2018-06-05 |
| 基金项目:国家电网公司科技项目资助(KJGW2018-014);中央高校基本科研业务费专项资金资助(2018QN075) |
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| Optimal placement and capacity of distributed energy storage in distribution system based on the sensitivity variance of network loss |
| DU Peng,MI Zengqiang,JIA Yulong,LIN Liqian |
| (State Key Laboratory of Alternate Electrical Power System with Renewable Energy Source, North China Electric Power University, Baoding 071003, China) |
| Abstract: |
| In view of typical daily load curve, a method of optimal placement and capacity of distributed energy storage in distribution system based on the sensitivity variance of network loss is proposed. In the method, the charging and discharging operation state of distributed energy storage are taken into account. The priority of all nodes in the distribution network to locate distributed energy storage based on the sensitivity variance of network loss is determined. Taking the distribution network loss and node voltage fluctuation as the objective function, the modified particle swarm algorithm is used to optimize the charging and discharging power of distributed energy storage. And the optimal capacity of distributed energy storage is determined. Finally, the simulation results show that the optimal method can effectively maximize the balance of power on the ground, optimize the network loss of the distribution network and lower the voltage fluctuation of the nodes, and achieve the optimal configuration of distributed energy storage in the distribution network. This work is supported by Science and Technology Project of State Grid Corporation of China (No. KJGW2018-014) and Fundamental Research Funds for the Central Universities (No. 2018QN075). |
| Key words: distributed energy storage distribution network sensitivity variance of network loss modified particle swarm optimization algorithm power loss |
