Multi-objective Volt-Var Optimization Considering Operation Cost of OLTC in Distribution Networks

Frequent voltage fluctuations caused by the increasing penetration of renewable resources pose many challenges to distribution systems, which burdens the operation and maintenance cost of the regulated devices. The conventional methods of Volt-Var Optimization (VVO) regard the real power losses and voltage variation as the objectives. However, the ignorance of the operation cost of transformers degrades the efficiency and the economic performance of the distribution networks. This work engages the operation cost with the objectives. To overcome the non-convexity caused by the nature of power flow calculation, a genetic algorithm (GA) is employed to address the multiple-objectives problem. The proposed approach is validated in a modified 33-bus network. The results illustrate the proposed method can achieve losses reduction, voltage regulation and economic operation of the distribution networks.

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Publication Details

Published
2024-10-15
DOI
https://doi.org/10.1109/ichqp61174.2024.10768816
Primary Topic
Power Systems and Renewable Energy
Type
article
Field-Weighted Citation Impact
0.00

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article

Multi-objective Volt-Var Optimization Considering Operation Cost of OLTC in Distribution Networks

Zhenhuan Ding, Qianqian Zhang, Yi Xie, Lei Ding
Power Systems and Renewable Energy
article

Multi-objective Volt-Var Optimization Considering Operation Cost of OLTC in Distribution Networks

Zhenhuan Ding, Qianqian Zhang, Yi Xie, Lei Ding
article en

Abstract

Frequent voltage fluctuations caused by the increasing penetration of renewable resources pose many challenges to distribution systems, which burdens the operation and maintenance cost of the regulated devices. The conventional methods of Volt-Var Optimization (VVO) regard the real power losses and voltage variation as the objectives. However, the ignorance of the operation cost of transformers degrades the efficiency and the economic performance of the distribution networks. This work engages the operation cost with the objectives. To overcome the non-convexity caused by the nature of power flow calculation, a genetic algorithm (GA) is employed to address the multiple-objectives problem. The proposed approach is validated in a modified 33-bus network. The results illustrate the proposed method can achieve losses reduction, voltage regulation and economic operation of the distribution networks.

Anhui University (CN), State Grid Corporation of China (China) (CN)
National Science Foundation
Openalex Percentile: Top 78%
Power Systems and Renewable Energy
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