Open Access

ARTICLE

Evaluation of Multi-Temporal-Spatial Scale Adjustment Capability and Cluster Optimization Operation Method for Distribution Networks with Distributed Photovoltaics

Jiaxin Qiao¹, Yuchen Hao², Yingqi Liao³, Fang Liang³, Jing Bian^1,*

1 Northeast Electric Power University, Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology, Ministry of Education, Jilin, 132011, China
2 State Grid Jiangsu Electric Power Co., Ltd., Power Dispatch Control Center, Nanjing, 210017, China
3 State Grid Jiangsu Electric Power Co., Ltd., Nanjing Power Supply Branch, Power Dispatch Control Center, Nanjing, 210019, China

* Corresponding Author: Jing Bian. Email:

Energy Engineering 2024, 121(9), 2655-2680. https://doi.org/10.32604/ee.2024.049509

Received 09 January 2024; Accepted 15 May 2024; Issue published 19 August 2024

Abstract

The massive integration of high-proportioned distributed photovoltaics into distribution networks poses significant challenges to the flexible regulation capabilities of distribution stations. To accurately assess the flexible regulation capabilities of distribution stations, a multi-temporal and spatial scale regulation capability assessment technique is proposed for distribution station areas with distributed photovoltaics, considering different geographical locations, coverage areas, and response capabilities. Firstly, the multi-temporal scale regulation characteristics and response capabilities of different regulation resources in distribution station areas are analyzed, and a resource regulation capability model is established to quantify the adjustable range of different regulation resources. On this basis, considering the limitations of line transmission capacity, a regulation capability assessment index for distribution stations is proposed to evaluate their regulation capabilities. Secondly, considering different geographical locations and coverage areas, a comprehensive performance index based on electrical distance modularity and active power balance is established, and a cluster division method based on genetic algorithms is proposed to fully leverage the coordination and complementarity among nodes and improve the active power matching degree within clusters. Simultaneously, an economic optimization model with the objective of minimizing the economic cost of the distribution station is established, comprehensively considering the safety constraints of the distribution network and the regulation constraints of resources. This model can provide scientific guidance for the economic dispatch of the distribution station area. Finally, case studies demonstrate that the proposed assessment and optimization methods effectively evaluate the regulation capabilities of distribution stations, facilitate the consumption of distributed photovoltaics, and enhance the economic efficiency of the distribution station area.

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