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Sustainability 2018, 10(3), 727; https://doi.org/10.3390/su10030727

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

Department of Electrical and Electronic Engineering, Eastern Mediterranean University, Gazimagusa, 99628 Mersin 10, Turkey
Received: 12 February 2018 / Revised: 1 March 2018 / Accepted: 4 March 2018 / Published: 7 March 2018
(This article belongs to the Collection Power System and Sustainability)
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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. View Full-Text
Keywords: photovoltaic; static synchronous compensator; power loss; peak load; optimization photovoltaic; static synchronous compensator; power loss; peak load; optimization
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
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Sirjani, R. Optimal Placement and Sizing of PV-STATCOM in Power Systems Using Empirical Data and Adaptive Particle Swarm Optimization. Sustainability 2018, 10, 727.

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