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考虑SOP与智能负载特性的配电网灵活性提升方法OA北大核心CSTPCD

A Method for Improving the Flexibility of Distribution Networks Considering Soft Open Point and Smart Load Characteristics

中文摘要英文摘要

随着高渗透率分布式新能源接入电网,其出力的随机性与波动性对配电网的灵活性需求提出了更高的要求.为此提出一种计及智能软开关(soft open point,SOP)与智能负载(smart load,SL)互补特性的配电网灵活性提升方法.首先,对SOP、SL与可控分布式电源(distributed generation,DG)的灵活性特性与数学模型进行分析,从节点灵活性适应度与含SOP线路的负载裕度两个方面建立灵活性评估指标.其次,构建考虑运行成本、电压质量与灵活性指标的目标函数,力求在最小化灵活性缺额与电压越限的情况下实现经济性最优.同时提出了改进鲸鱼优化算法(reconstruction whale optimization algorithm,Re-WOA)对优化模型求解;在该算法中引入了两种改进的搜索捕食策略,并以SL容量裕度指标平衡搜索阶段的SL负载均衡度.最后,通过改进的IEEE 33节点系统验证了该模型对配电网的优化作用与所提Re-WOA算法的有效性.

The integration of new high-permeability distributed energy into the power grid has increased the demand for flexibility in the distribution network owing to the randomness and volatility of its output. A method for improving the flexibility of distribution networks that considers the complementary characteristics of soft open point (SOP) and smart load (SL) is proposed. First,the flexibility characteristics and mathematical models of the SOP,SL,controllable DG,and flexibility evaluation indicators were established from two aspects:node flexibility adaptability and the load margin of lines containing the SOP. Second,we constructed an objective function that considers the operating costs,voltage quality,and flexibility indicators,striving to achieve optimal economic performance while minimizing flexibility gaps and voltages exceeding the limits. Simultaneously,a reconstruction whale optimization algorithm (Re-WOA) was proposed to solve the optimization model,and two improved search predator strategies were introduced in the algorithm. The SL load balancing degree during the search phase was balanced using the SL capacity margin index. Finally,the optimization effect of the model on the distribution network and the effectiveness of the proposed Re-WOA were verified using an improved IEEE33 node system.

王天宇;李晓露;柳劲松;林顺富

上海电力大学电气工程学院,上海市 200090国网上海市电力公司电力科学研究院,上海市 200437

动力与电气工程

智能软开关灵活性评估智能负载改进鲸鱼优化算法负载均衡度

soft open pointflexibility assessmentsmart loadreconstructed whale optimization algorithmload balancing

《电力建设》 2024 (006)

47-57 / 11

国家自然科学基金项目(51907114)This work is supported by the National Natural Science Foundation of China(No.51907114).

10.12204/j.issn.1000-7229.2024.06.005

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