Capacity configuration optimisation for stand-alone micro-grid based on an improved binary bat algorithm

Capacity configuration optimisation (CCO) for stand-alone micro-grid has become an urgent issue that needs to be addressed effectively, which is of great significance for saving operational costs, raising renewable energy source utilisation ratio and improving reliability of power supply in island....

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Bibliographic Details
Published in:	Journal of engineering (Stevenage, England) Vol. 2017; no. 13; pp. 2083 - 2087
Main Authors:	Sheng, Siqing, Zhang, Jingjing
Format:	Journal Article
Language:	English
Published:	The Institution of Engineering and Technology 2017
Subjects:	battery storage plants capacity configuration optimisation CCO model conflictive objective functions continuous optimisation algorithm diesel‐electric generators differential evolution distributed power generation evolutionary computation hybrid power systems IBBA improved BBA improved binary bat algorithm integer programming local optimal problem multiobjective integer programming problem nonlinear constraints nonlinear programming operational costs photovoltaic power systems power generation reliability power supply reliability improvement renewable energy source utilisation ratio search problems standalone microgrid standalone wind‐PV‐diesel‐battery system wind power plants integer programming nonlinear programming diesel-electric generators distributed power generation operational costs CCO model improved BBA standalone wind-PV-diesel-battery system renewable energy source utilisation ratio wind power plants search problems hybrid power systems power generation reliability local optimal problem photovoltaic power systems standalone microgrid nonlinear constraints improved binary bat algorithm differential evolution evolutionary computation power supply reliability improvement capacity configuration optimisation multiobjective integer programming problem continuous optimisation algorithm battery storage plants IBBA conflictive objective functions
ISSN:	2051-3305, 2051-3305
Online Access:	Get full text
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