Modeling, Simulation and Optimal Sizing of a Hybrid Wind, Solar PV Power System in Northern Kenya

Victor Omondi Okinda, Nicodemus Abungu Odero

Abstract


There is a global push towards green and sustainable energy which has seen several initiatives being developed to spearhead and promote development of renewable energy generation sources however, this has not been without challenge.  Solar and wind, the most abundant renewable energy resources are still expensive to deploy and unreliable as they suffer from intermittency.

It has long been postulated in open published literature that solar and wind   have complementary regimes and that it is possible to make headways in reliability of renewable energy systems by hybridization sources that have complementary regimes. A hybrid solution however is only viable if optimally sized.

 This paper reports on the findings of research examining the problem of optimally sizing a hybrid wind and solar renewable energy power system. In the research a target location was first identified and meteorological data collected. Components of the system were then mathematically modelled from which an objective function was developed. A parallel multi-deme implementation of genetic algorithms was used to perform the optimization. Multiple scenarios were prepared and simulated to obtain an optimal configuration of the hybrid power system. The results obtained were validated against openly published results from real word projects. A conclusion was then drawn on the basis of the results obtained.

 The research was successful as all objective were met. The key findings were first and foremost that in deed on some locations wind and solar have complementary regimes and can thus be hybridized. To this end an optimal configuration of the system for off grid deployment was developed with an attractive levelized cost of energy of 17 US cents per kWh. Secondly, the research from the results obtained decoupled resource optimal solutions from cost optimal solutions. It was shown that the least cost configuration didn’t necessary maximize on utility of the abundant resource. Lastly a clear direction for future research was proposed.


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Keywords


Energy storage; hybrid power systems; optimization methods; renewable energy sources; Genetic Algorithms; solar energy; wind energy.

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