PSO-based hybrid generating system design incorporating reliability evaluation and generation/load forecasting
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abstract
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. 2007 IEEE.
