首页|Day-ahead Voltage-stability-constrained Network Topology Optimization with Uncertainties

Day-ahead Voltage-stability-constrained Network Topology Optimization with Uncertainties

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A day-ahead voltage-stability-constrained network topology optimization(DVNTO)problem is proposed to find the day-ahead topology schemes with the minimum number of operations(including line switching and bus-bar splitting)while ensuring the sufficient hourly voltage stability margin and the engineering operation requirement of power systems.The AC continuation power flow and the uncertainty from both renew-able energy sources and loads are incorporated into the formu-lation.The proposed DVNTO problem is a stochastic,large-scale,nonlinear integer programming problem.To solve it trac-tably,a tailored three-stage solution methodology,including a scenario generation and reduction stage,a dynamic period par-tition stage,and a topology identification stage,is presented.First,to address the challenges posed by uncertainties,a novel problem-specified scenario reduction process is proposed to ob-tain the representative scenarios.Then,to obtain the minimum number of necessary operations to alter the network topologies for the next 24-hour horizon,a dynamic period partition strate-gy is presented to partition the hours into several periods ac-cording to the hourly voltage information based on the voltage stability problem.Finally,a topology identification stage is per-formed to identify the final network topology scheme.The effec-tiveness and robustness of the proposed three-stage solution methodology under different loading conditions and the effec-tiveness of the proposed partition strategy are evaluated on the IEEE 118-bus and 3120-bus power systems.

Network topology optimizationstatic voltage stabilityline switchingbus-bar splittingrenewable energy source

Dingli Guo、Lei Wang、Ticao Jiao、Ke Wu、Wenjing Yang

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School of Electrical and Electronic Engineering,Shandong University of Technology,Zibo 255000,China

National Natural Science Foundation of ChinaNatural Science Foundation of Shandong ProvinceTaishan Scholar Project of Shandong Province

52377109ZR2022ME187TSQN202306191

2024

10.35833/MPCE.2023.000673

现代电力系统与清洁能源学报(英文版)

现代电力系统与清洁能源学报(英文版)

ISSN：
年,卷(期)：2024.12(3)
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