期刊
INTERNATIONAL JOURNAL OF ENERGY RESEARCH
卷 40, 期 7, 页码 971-982出版社
WILEY-HINDAWI
DOI: 10.1002/er.3493
关键词
optimal key performance indicators; KPIs; particle swarm optimization; pattern search; PSO-PS; hybrid methods; microgrid
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 (C) 2016 John Wiley & Sons, Ltd.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据