PSO-based Hybrid Generating System Design Incorporating Reliability Evaluation and Generation/Load Forecasting

Traditional fuel-fired power generation is receiving tighter pressure primarily due to its severe consequences of pollutants emission. Alternatively, renewable sources of energy appear promising in reducing emissions and slowing down world´s energy consumption. However, these are intermittent in nature and also demand high capital investments. Thus, in a hybrid generation system, the contributions of these intermittent sources should be determined by different design requirements in terms of cost, reliability, and environmental restrictions. There are many uncertain factors in a hybrid power-generating system including equipment failures and random variations in both generation and load. In this paper, all of these uncertainties are considered during design via adequacy assessment and generation/load forecasting. Due to the complexity and nonlinearity of the intended design problem, a guided stochastic search algorithm called particle swarm optimization is modified and applied to derive a set of design alternatives fulfilling different application needs. Furthermore, a numerical example is used to demonstrate how a hybrid power-generating system is designed based on the proposed optimization procedure.