Abstract
Component capacity and energy management strategy are two key issues for the optimal sizing of a hybrid renewable energy system. In this study, a two-stage stochastic programming problem is proposed for the optimal sizing of a hybrid renewable energy system consisted of wind turbine, concentrated solar plant, and electric heater. In the problem, component capacity optimization is the first-stage problem to minimize the levelized cost of energy while satisfying the reliability constraint, and energy management strategy optimization is the second-stage problem to minimize the loss of power supply probability while satisfying the operation constraints. The problem is solved by combining of an improved differential evolution algorithm, namely JADE, and Cplex, and the superiority of JADE is validated by algorithm comparisons with several popular intelligent optimization algorithms. Furthermore, economic benefits of the electric heater in the hybrid system are investigated by techno-economic comparisons with a reference wind turbine/concentrated solar plant hybrid energy system without electric heater under their optimal capacity. The results show the electric heater is beneficial for a lower levelized cost of energy, reducing by 0.004 ($/kWh) and 0.009 ($/kWh) respectively when the loss of power supply probability is 2% and 5%.
Published Version
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