基于海量场景降维的配电网源网荷储协同规划

doi:10.11930/j.issn.1004-9649.202208020

中国电力 ›› 2022, Vol. 55 ›› Issue (12): 78-85.DOI: 10.11930/j.issn.1004-9649.202208020

• 面向数字化转型的电力系统大数据分析技术 • 上一篇下一篇

基于海量场景降维的配电网源网荷储协同规划

刘金森¹, 罗宁¹, 王杰¹, 徐常¹, 曹毅², 刘志文²

1. 贵州电网有限责任公司电网规划研究中心，贵州贵阳 550003;
2. 南方电网能源发展研究院有限责任公司，广东广州 510663

收稿日期:2022-08-04 修回日期:2022-09-08 发布日期:2022-12-28
作者简介:刘金森（1983—），男，通信作者，硕士，高级工程师，从事配电网规划及新型电力系统研究，E-mail：guizhoujsliu@163.com;罗宁（1986—），女，硕士，高级工程师，从事配电网规划及新型电力系统研究，E-mail：547091372@qq.com;刘志文（1981—），男，博士，高级工程师（教授级），从事新能源并网与配电网规划研究，E-mail：lzw32347@126.com
基金资助:
南方电网公司重点科技项目（GZKJXM20210368）

Massive Scenario Reduction Based Distribution-Level Power System Planning Considering the Coordination of Source, Network, Load and Storage

LIU Jinsen¹, LUO Ning¹, WANG Jie¹, XU Chang¹, Cao Yi², Liu Zhiwen²

1. Power Grid Planning and Research Center, Guizhou Power Grid Co., Ltd., Guiyang 550003, China;
2. Energy Research Institute of China Southern Power Grid Co., Ltd., Guangzhou 510663, China

Received:2022-08-04 Revised:2022-09-08 Published:2022-12-28
Supported by:
This work is supported by the Key Science and Technology Project of China Southern Power Grid (No.GZKJXM20210368).

摘要/Abstract

摘要： 风电、光伏等新能源大规模接入配电网，给配电网规划方法的效率和规划结果的经济性带来了极大挑战。为了解决配电网中新能源海量运行数据与配电网源网荷储协调规划之间的配合问题，提出了基于海量场景降维的配电网源网荷储协同规划方法。首先，通过主成分-高斯混合聚类算法对风-光-荷海量高维场景进行降维聚类，得到风-光-荷的典型场景集；然后，构建了面向海量场景的配电网源网荷储协同规划模型，并采用二阶锥松弛技术将模型中非凸约束转凸处理；最后，在Portugal 54节点配电网算例上验证了海量场景降维聚类方法和规划模型的有效性。

关键词: 配电网, 主成分分析法, 高斯混合聚类, 源网荷储, 协同规划

Abstract: The integration of high-proportion renewable power generation has brought great challenges to the efficiency of distribution network planning methods and the economy of planning results. In order to solve the problem of coordination between the massive operation data of renewable power generation and the coordinated planning of the source-network-load-storage, this paper proposes a coordinated planning method of the source-network-load-storage based on the massive scenario dimension reduction. Firstly, the dimensionality reduction clustering is carried out on the wind-light-load mass high-dimensional scenarios by the principal component Gaussian mixture clustering algorithm, and the typical scenario set of wind and power loads is obtained; then, a source-network-load-storage coordination planning model of distribution network for massive scenarios is constructed, and the second-order cone relaxation technique is adopted to convert the non-convex constraints to convex ones; finally, the effectiveness of the proposed massive scenario dimension reduction clustering method and distribution network planning model is verified on the Portugal 54-node distribution network.

Key words: distribution network, principal component analysis method, Gaussian mixed clustering, source-network-load-storage, coordinated planning

刘金森, 罗宁, 王杰, 徐常, 曹毅, 刘志文. 基于海量场景降维的配电网源网荷储协同规划[J]. 中国电力, 2022, 55(12): 78-85.

LIU Jinsen, LUO Ning, WANG Jie, XU Chang, Cao Yi, Liu Zhiwen. Massive Scenario Reduction Based Distribution-Level Power System Planning Considering the Coordination of Source, Network, Load and Storage[J]. Electric Power, 2022, 55(12): 78-85.

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基于海量场景降维的配电网源网荷储协同规划

Massive Scenario Reduction Based Distribution-Level Power System Planning Considering the Coordination of Source, Network, Load and Storage

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基于海量场景降维的配电网源网荷储协同规划

Massive Scenario Reduction Based Distribution-Level Power System Planning Considering the Coordination of Source, Network, Load and Storage

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