Optimum Design of Hybrid Solar-wind-diesel Power Generation System Using Genetic Algorithm

Zhou Wei, Yang Hongxing, Lu Lin, Fang Zhaohong

Research output: Journal article publicationJournal articleAcademic researchpeer-review

3 Citations (Scopus)

Abstract

This paper recommended an optimum design method for sizing stand-alone hybrid solarwind- diesel system with the help of genetic algorithm (GA). Minimisation of the objective function (annualised cost of system) is achieved not only by selecting an appropriate system configuration, but also by finding a suitable control strategy for the diesel generator. The eight decision variables included in the optimisation process are the PV module number, PV module slope angle, wind turbine number, wind turbine installation height, battery number, diesel generator (DG) type, DG starting and stopping points. The optimum design method was applied to analyse a hybrid project for obtaining the optimum configuration and control strategy that can satisfy the load requirements for 5-year period from 1996 to 2000, resulting in zero load rejection with minimum annualised cost of system (ACS). Good optimisation performance has been found. Furthermore, the complementary characteristic between the solar and wind energy, the priority sequence for choosing renewable energy systems in the studied area, were also analysed together with the influence of different diesel generator control strategies.
Original languageEnglish
Pages (from-to)82-89
Number of pages8
JournalHKIE Transactions Hong Kong Institution of Engineers
Volume14
Issue number4
DOIs
Publication statusPublished - 1 Jan 2007

Keywords

  • Genetic Algorithm
  • Hybrid Solar-wind-diesel System
  • Renewable Energy Fraction
  • System Cost

ASJC Scopus subject areas

  • Engineering(all)

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