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邱桂华, 区伟潮, 聂家荣. 基于C&CG算法的含高比例分布式光伏配电网双层优化调度策略[J]. 太阳能学报, 2025,46(9):555-563.
邱桂华, 区伟潮, 聂家荣. 基于C&CG算法的含高比例分布式光伏配电网双层优化调度策略[J]. 太阳能学报, 2025,46(9):555-563. DOI: doi:10.19912/j.0254-0096.tynxb.2024-0861.
提出一种基于列与约束(C&CG)算法含高比例分布式光伏配电网双层优化调度策略。首先
建立配电网双层优化调度模型
上层模型考虑电压偏移水平以及静态电压稳定度
以配电网网络损耗最小及多元化电能质量最优为目标;下层模型考虑储能设备、需求响应是否参与调度等策略
以配电网综合运行成本最小为目标;然后
使用自适应ε约束法多目标粒子群算法获得均匀帕累托前沿
并利用TOPSIS决策法选取最优解;最后使用C&CG算法迭代求解双层模型。通过改进IEEE 33节点系统算例验证表明
所提策略可在保证配电网电能质量最优的前提下
降低网络损耗并提高新能源消纳率
减少配电网综合运行成本。
This paper proposes a two-layer optimization scheduling strategy for distribution networks with a high proportion of distributed PV systems based on the C&CG algorithm. Firstly
a two-layer optimization scheduling model for distribution networks is established. The upper-layer model multi-dimensional voltage deviation levels and static voltage stability
with the objectives of minimizing distribution network losses and optimizing multi-dimensional power quality. The lower-layer model considers energy storage devices
strategies such as demand response participation in scheduling
with the objective of minimizing the overall operational expenses of the distribution network. The adaptive ε-constraint method combined with multi-objective particle swarm optimization algorithm is employed to obtain a uniformly distributed Pareto frontier
and the TOPSIS decision-making method is used to select the optimal solution. Finally
the C&CG algorithm is used to iteratively solve the two-layer model. The proposed strategy is validated through improved IEEE 33-node system example
demonstrating that it can reduce network losses
increase the consumption rate of renewable energy sources
and decrease the comprehensive operating costs of distribution networks while ensuring the optimal power quality of the distribution network.
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