Performance optimization of integrated gas and power within microgrids using hybrid PSO–PS algorithm |
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| Authors: | Hossam A Gabbar Yacine Labbi Lowell Bower Devarsh Pandya |
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| Affiliation: | 1. Faculty of Energy Systems and Nuclear Science, University of Ontario Institute of Technology, UOIT, Oshawa, ON, Canada;2. Faculty of Engineering and Applied Science, University of Ontario Institute of Technology, UOIT, Oshawa, ON, Canada |
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| Abstract: | In this paper, a hybrid algorithm consisting of particle swarm optimization and pattern search algorithm is proposed to evaluate and optimize the design and operation of microgrids (MGs) in combined gas and power networks. Key performance indicators (KPIs) are modeled and proposed to evaluate and assess MGs. The paper begins by proposing a comprehensive study to define KPIs, which are used to evaluate the following MG parameters: economical efficiency, reliability, environmental conservation, and power quality. Multi‐objective evaluation functions are then developed by building a relationship matrix of MG and KPI components. The results are then displayed as optimized power generation percentages for each technology with values for four KPI categories: cost, quality, reliability and environmental friendliness. Two case studies are examined in this paper; both the province of Ontario and Toronto regional zone under all system parameters with varying percentage of generation via gas technology. Results indicated that the optimal scenario for both Ontario and Toronto was achieved at hybrid PSO–patern search percentage generation via gas technology with improved cost KPI and other KPIs remaining approximately constant. Copyright © 2016 John Wiley & Sons, Ltd. |
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| Keywords: | optimal key performance indicators KPIs particle swarm optimization pattern search PSO– PS hybrid methods microgrid |
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