Optimal reliability evaluation method of bulk power system based on IGA

Combined with risk indices of comprehensive reliability assessment and economic assessment theory, there may be trade-off between system installations cost and power interruption cost in the competitive power market environment. To coordinate reliability and economy, this paper proposed an overall framework of optimal reliability algorithm for bulk power system based on total owning cost (TOC). Interruption cost can be obtained through quantitative reliability indices of probabilistic security and probabilistic adequacy comprehensive evaluation based on Monte-Carlo simulation. Through applying improved genetic algorithm (IGA) to solving these kinds of complex discontinuous reliability optimization problems, the optimal reliability indices of components are obtained, which minimize the total owning cost comprising apparatus investment cost and interruption cost. A case study of the IEEE-RTS test system is presented to demonstrate the effectiveness and feasibility of the proposed algorithm. The proposed method is a valuable and powerful tool for power system planning, and it makes research results of reliability evaluation become more practical in the competitive market environment.