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Optimal Placement and Sizing of PV-STATCOM in Power Systems Using Empirical Data and Adaptive Particle Swarm Optimization

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  • Reza Sirjani

    (Department of Electrical and Electronic Engineering, Eastern Mediterranean University, Gazimagusa, 99628 Mersin 10, Turkey)

Abstract

Solar energy is a source of free, clean energy which avoids the destructive effects on the environment that have long been caused by power generation. Solar energy technology rivals fossil fuels, and its development has increased recently. Photovoltaic (PV) solar farms can only produce active power during the day, while at night, they are completely idle. At the same time, though, active power should be supported by reactive power. Reactive power compensation in power systems improves power quality and stability. The use during the night of a PV solar farm inverter as a static synchronous compensator (or PV-STATCOM device) has recently been proposed which can improve system performance and increase the utility of a PV solar farm. In this paper, a method for optimal PV-STATCOM placement and sizing is proposed using empirical data. Considering the objectives of power loss and cost minimization as well as voltage improvement, two sub-problems of placement and sizing, respectively, are solved by a power loss index and adaptive particle swarm optimization (APSO). Test results show that APSO not only performs better in finding optimal solutions but also converges faster compared with bee colony optimization (BCO) and lightening search algorithm (LSA). Installation of a PV solar farm, STATCOM, and PV-STATCOM in a system are each evaluated in terms of efficiency and cost.

Suggested Citation

  • Reza Sirjani, 2018. "Optimal Placement and Sizing of PV-STATCOM in Power Systems Using Empirical Data and Adaptive Particle Swarm Optimization," Sustainability, MDPI, vol. 10(3), pages 1-15, March.
    • Handle: RePEc:gam:jsusta:v:10:y:2018:i:3:p:727-:d:135070
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    References listed on IDEAS

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    1. Gayatri, M.T.L. & Parimi, Alivelu.M. & Pavan Kumar, A.V., 2018. "A review of reactive power compensation techniques in microgrids," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 1030-1036.
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    3. Luo, Lizi & Gu, Wei & Zhang, Xiao-Ping & Cao, Ge & Wang, Weijun & Zhu, Gang & You, Dingjun & Wu, Zhi, 2018. "Optimal siting and sizing of distributed generation in distribution systems with PV solar farm utilized as STATCOM (PV-STATCOM)," Applied Energy, Elsevier, vol. 210(C), pages 1092-1100.
    4. Sirjani, Reza & Rezaee Jordehi, Ahmad, 2017. "Optimal placement and sizing of distribution static compensator (D-STATCOM) in electric distribution networks: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 688-694.
    5. Schönleber, Kevin & Collados, Carlos & Pinto, Rodrigo Teixeira & Ratés-Palau, Sergi & Gomis-Bellmunt, Oriol, 2017. "Optimization-based reactive power control in HVDC-connected wind power plants," Renewable Energy, Elsevier, vol. 109(C), pages 500-509.
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    Cited by:

    1. Zedequias Machado Alves & Renata Mota Martins & Gustavo Marchesan & Ghendy Cardoso Junior, 2022. "Metaheuristic for the Allocation and Sizing of PV-STATCOMs for Ancillary Service Provision," Energies, MDPI, vol. 16(1), pages 1-16, December.
    2. Gregorio Fernández & Alejandro Martínez & Noemí Galán & Javier Ballestín-Fuertes & Jesús Muñoz-Cruzado-Alba & Pablo López & Simon Stukelj & Eleni Daridou & Alessio Rezzonico & Dimosthenis Ioannidis, 2021. "Optimal D-STATCOM Placement Tool for Low Voltage Grids," Energies, MDPI, vol. 14(14), pages 1-31, July.
    3. Víctor M. Garrido-Arévalo & Walter Gil-González & Oscar Danilo Montoya & Harold R. Chamorro & Jorge Mírez, 2023. "Efficient Allocation and Sizing the PV-STATCOMs in Electrical Distribution Grids Using Mixed-Integer Convex Approximation," Energies, MDPI, vol. 16(20), pages 1-19, October.
    4. Abdullah M. Shaheen & Ragab A. El-Sehiemy & Ahmed Ginidi & Abdallah M. Elsayed & Saad F. Al-Gahtani, 2023. "Optimal Allocation of PV-STATCOM Devices in Distribution Systems for Energy Losses Minimization and Voltage Profile Improvement via Hunter-Prey-Based Algorithm," Energies, MDPI, vol. 16(6), pages 1-20, March.
    5. Mostafa Elshahed & Mohamed A. Tolba & Ali M. El-Rifaie & Ahmed Ginidi & Abdullah Shaheen & Shazly A. Mohamed, 2023. "An Artificial Rabbits’ Optimization to Allocate PVSTATCOM for Ancillary Service Provision in Distribution Systems," Mathematics, MDPI, vol. 11(2), pages 1-19, January.

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