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Please use this identifier to cite or link to this item: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/49952

Title: Effects of Battery Energy Storage System on the Operating Schedule of a Renewable Energy Based TOU Rate Industrial User under Competitive Environment
Authors: Chun-Lung Chen
Y. L. Lin
W. Y. Fu
Contributors: 國立臺灣海洋大學:輪機工程學系
Keywords: smart grid
renewable energy sources
battery energy storage system
particle swarm optimization
intelligent particle swarm optimization
Date: 2015-08
Issue Date: 2018-09-04T03:53:21Z
Publisher: Journal of Marine Science and Technology
Abstract: Abstract: With increasing development of smart grid and restructuring
of the power industry, the problem of operating schedule for a
time-of-use (TOU) rate industrial customer may become a more
important issue due to the inclusion of the variations in the
TOU rate structures. This paper develops a new algorithm,
named intelligent particle swarm optimization (INPSO), to
solve the operating schedule of a renewable energy based
TOU rate industrial user with battery energy storage system
(BESS). Adding another particle best (Pbestap) item with a
diversity based judgment mechanism, proposed INPSO algorithm
can give a good direction to enhance its search capacity
that leads to a higher probability of obtaining the global optimal
solution. A TOU rate industrial customer of Taiwan
Power Company (TPC) is used as an example to validate the
feasibility of the INPSO algorithm for the application considered.
Numerical experiments are included to understand
how variations in the rate structures on the optimal operation
of the TOU rate customer system. The computer program
developed in this paper can also be a power tool for TOU rate
industrial users to evaluate the economic benefits of the renewable
energy sources (RES) and BESS.
Relation: 23(4) pp.541-550
URI: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/49952
Appears in Collections:[輪機工程學系] 期刊論文

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