基于潮流计算的中压直流配电网协同优化调度
The Cooperative Optimal Dispatching of the Medium Voltage DC Distribution Network Based on Power Flow Calculation
曾光辉 1叶容慧 1刘伟斌 1黄永麟 1李家淇1
作者信息
- 1. 广东电网有限责任公司东莞供电局,广东东莞 523000
- 折叠
摘要
为保证中压直流配电网的运行稳定性,实现中压直流配电网协同优化调度,提出基于潮流计算的中压直流配电网协同优化调度方法.通过中压直流配电网潮流计算模型,分析该配电网中的潮流分布情况,确定采用均衡度指标描述网损结果;构建中压直流配电网在单个调度周期内的有功损耗和线路负载均衡目标函数,并设定潮流约束等多个约束条件;采用多目标粒子群优化算法求解目标函数,同时优化均衡度变量参数和整个网络,获取协同优化调度结果.测试结果显示:所提方法协同优化调度效果良好,电压标幺值的结果均低于 1.00 pu,各节点在日运行时间内的电压波动变化也在期望标准范围内;网损结果均低于 0.047 MW;可实现削峰填谷,避免电压发生越限.
Abstract
To ensure the operation stability and realize the cooperative optimal scheduling of the medium voltage DC distribution network,a cooperative optimal scheduling method based on power flow calculation is proposed in this paper.Through the power flow calculation model of the network,the power flow distribution is analyzed,and the output equalization index is determined to describe the network loss result.An active loss and line load balance objective function of the network in a single operation cycle is constructed,and constraints such as multiple constraints conditions are set.The multi-objective particle swarm optimization algorithm is used to solve the objective function and the equilibrium degree of variable parameters and the entire network are optimized at the same time to obtain the collaborative optimization scheduling results.The test results show that the cooperative optimization scheduling effect of the proposed method is satisfactory,and the voltage per-unit values are all lower than 1.00p.u.The fluctuation of voltage is within the expected standard range in the intra-day operation of each node;and the network losses are all lower than 0.047MW.In addition,peak clipping and valley filling can be realized to avoid voltage exceeding the limit.
关键词
潮流计算/中压直流/配电网/协同优化调度/潮流分布/负载均衡Key words
power flow calculation/medium voltage DC/distribution network/collaborative optimal scheduling/tidal current distribution/load balancing引用本文复制引用
基金项目
广东电网有限责任公司科技项目(031900202003 0103JH00062)
中国南方电网有限责任公司科技项目(2022T201A01)
出版年
2024
NETL
NSTL
万方数据