Genetic algorithm based optimization on modeling and design of hybrid renewable energy systems

M. S. Ismail, M. Moghavvemi, T.m. Indra Mahlia

Research output: Contribution to journalArticle

84 Citations (Scopus)

Abstract

A sizing optimization of a hybrid system consisting of photovoltaic (PV) panels, a backup source (microturbine or diesel), and a battery system minimizes the cost of energy production (COE), and a complete design of this optimized system supplying a small community with power in the Palestinian Territories is presented in this paper. A scenario that depends on a standalone PV, and another one that depends on a backup source alone were analyzed in this study. The optimization was achieved via the usage of genetic algorithm. The objective function minimizes the COE while covering the load demand with a specified value for the loss of load probability (LLP). The global warming emissions costs have been taken into account in this optimization analysis. Solar radiation data is firstly analyzed, and the tilt angle of the PV panels is then optimized. It was discovered that powering a small rural community using this hybrid system is cost-effective and extremely beneficial when compared to extending the utility grid to supply these remote areas, or just using conventional sources for this purpose. This hybrid system decreases both operating costs and the emission of pollutants. The hybrid system that realized these optimization purposes is the one constructed from a combination of these sources.

Original languageEnglish
Pages (from-to)120-130
Number of pages11
JournalEnergy Conversion and Management
Volume85
DOIs
Publication statusPublished - 01 Jan 2014

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Hybrid systems
Genetic algorithms
Costs
Loss of load probability
Global warming
Solar radiation
Operating costs

All Science Journal Classification (ASJC) codes

  • Renewable Energy, Sustainability and the Environment
  • Nuclear Energy and Engineering
  • Fuel Technology
  • Energy Engineering and Power Technology

Cite this

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Genetic algorithm based optimization on modeling and design of hybrid renewable energy systems. / Ismail, M. S.; Moghavvemi, M.; Mahlia, T.m. Indra.

In: Energy Conversion and Management, Vol. 85, 01.01.2014, p. 120-130.

Research output: Contribution to journalArticle

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