MF-APSO-Based Multiobjective Optimization for PV System Reactive Power Regulation

Hong-Tzer Yang, Jian Tang Liao

Research output: Contribution to journalArticle

10 Citations (Scopus)

Abstract

This paper proposes a reactive power-regulation strategy for a distribution system connected with high-penetration photovoltaic (PV) generation. The PV reactive power regulation is formulated as a multiobjective optimization problem to relieve the overvoltage caused by high PV penetration and to minimize total line loss. With integrated power-flow analysis, a new mutation fuzzy adaptive particle swarm optimization (MF-APSO) algorithm is proposed to solve the multiobjective optimization problem. The proposed reactive power-regulation strategy and MF-APSO algorithm are, respectively, compared with conventional methods for overvoltage mitigation and total line-loss reduction, as well as with the referenced optimization algorithms for the problems of concern. Numerical results verify that the proposed multiobjective optimization method can more effectively mitigate the overvoltage issue and greatly reduce the total line loss as compared to other methods. Utilization of high-penetration PV systems can thus be further enhanced with reduced power curtailment owing to the added functions of voltage regulation and line-loss minimization.

Original languageEnglish
Article number7124516
Pages (from-to)1346-1355
Number of pages10
JournalIEEE Transactions on Sustainable Energy
Volume6
Issue number4
DOIs
Publication statusPublished - 2015 Oct 1

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Multiobjective optimization
Reactive power
Particle swarm optimization (PSO)
Voltage control

All Science Journal Classification (ASJC) codes

  • Renewable Energy, Sustainability and the Environment

Cite this

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abstract = "This paper proposes a reactive power-regulation strategy for a distribution system connected with high-penetration photovoltaic (PV) generation. The PV reactive power regulation is formulated as a multiobjective optimization problem to relieve the overvoltage caused by high PV penetration and to minimize total line loss. With integrated power-flow analysis, a new mutation fuzzy adaptive particle swarm optimization (MF-APSO) algorithm is proposed to solve the multiobjective optimization problem. The proposed reactive power-regulation strategy and MF-APSO algorithm are, respectively, compared with conventional methods for overvoltage mitigation and total line-loss reduction, as well as with the referenced optimization algorithms for the problems of concern. Numerical results verify that the proposed multiobjective optimization method can more effectively mitigate the overvoltage issue and greatly reduce the total line loss as compared to other methods. Utilization of high-penetration PV systems can thus be further enhanced with reduced power curtailment owing to the added functions of voltage regulation and line-loss minimization.",
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MF-APSO-Based Multiobjective Optimization for PV System Reactive Power Regulation. / Yang, Hong-Tzer; Liao, Jian Tang.

In: IEEE Transactions on Sustainable Energy, Vol. 6, No. 4, 7124516, 01.10.2015, p. 1346-1355.

Research output: Contribution to journalArticle

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