Generation reliability assessment in power markets using Monte Carlo simulation and soft computing

Deregulation policy has caused some changes in the concepts of power systems reliability assessment and enhancement. In the present research, generation reliability is considered, and a method for its assessment is proposed using intelligent systems. Also, due to the stochastic behavior of power market and generators' forced outages, Monte Carlo Simulation is used for reliability evaluation. Generation reliability merely focuses on the interaction between generation complex and load. Therefore, in this research, based on the type of market and concentration, reserve margin and various future times, a Neuro-Fuzzy system is proposed for evaluation of generation reliability, which is valid and usable for all kinds of power pool markets. Finally, the proposed method is assessed on IEEE-Reliability Test System with satisfactory results. The results further showed that if market becomes more concentrated or price elasticity of demand increases, reliability will improve.