面向有源配电网电压质量提升的电能路由器和储能联合规划方法OA
Joint planning method of electric energy router and energy storage for voltage quality enhancement in active distribution networks
随着新型电力系统的发展,新能源的大量接入使配电网的电压控制面临挑战.电能路由器能够快速主动调节端口电压和功率,可应对由新能源引发的节点电压波动.本文采用 K均值聚类算法基于历史数据得出新能源典型场景,在此基础上建立电能路由器和储能双层规划模型,其中上层以综合成本最优为目标,实现电能路由器和储能的选址定容,下层以电压偏移和网损最小为目标进行日内优化,选择离散粒子群和二进制粒子群算法进行求解.最后,通过 IEEE 33 节点算例进行验证,证明了电能路由器和储能对有源配电网电压质量的提升作用.
With the development of new power systems,the large-scale integration of renewable energy resources poses challenges to voltage regulation in distribution networks.Power routers are able to rapidly and actively regulate port voltages and power flows,thereby mitigating node voltage fluctuations induced by renewables.This paper employs a K-means clustering method on historical data to derive typical renewable generation scenarios.On this basis,a two-level planning model for power routers and energy storage is formulated:the upper level minimizes total system cost to determine siting and sizing of power routers and storage units,while the lower level carries out intra-day operational optimization with objectives of minimizing voltage deviations and network losses.The model is solved using discrete particle swarm optimization(DPSO)and binary particle swarm optimization(BPSO).Finally,case studies on the IEEE 33-node test feeder validate that power routers combined with energy storage can effectively improve voltage quality in active distribution networks.
李理;杨成凡;郭坤;王仁杰
云南电网有限责任公司普洱供电局,云南 普洱 665000云南电网有限责任公司普洱供电局,云南 普洱 665000云南电网有限责任公司普洱供电局,云南 普洱 665000清华四川能源互联网研究院,成都 610213
有源配电网电能路由器双层规划模型粒子群算法聚类算法
active distribution networkelectric energy routerbi-level planning modelparticle swarm optimizationclustering algorithm
《电气技术》 2026 (3)
13-21,9
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