Turkish Journal of Electrical Engineering and Computer Sciences




Complementary renewable energies like wind and solar power may be more sufficient to satisfy reliability requirements. This paper proposes a quantitative capacity allocation method of a hybrid wind and solar energy system. First, discrete probability distributions are established to model the random factors including the volatility of power outputs and the failure of components. Then a multiobjective optimization model is formulated with objectives of minimization of the total investment, the nodal voltages violating limits probability, and power supply inadequacy probability. For the purpose of fast probability computing with a satisfactory precision degree, an innovative probabilistic load flow algorithm is introduced, which deals with means and increments of random variables separately and uses cumulants as well as Gram--Charlier series to obtain probabilistic distributions of state variables. A modified parallel elitist nondominated sorting genetic algorithm II is used to search the Pareto optimal configuration solutions.


Wind turbine, photovoltaic, capacity allocation, discrete probability distribution, multiobjective optimization, probabilistic load flow, NSGA-II

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