Multi-stage stochastic wind-thermal generation expansion planning with probabilistic reliability criteria

Abstract

Due to the growing proportion of uncertain and fluctuating renewable energy sources in the power system, reasonable generation expansion considering the uncertainties is desperately needed. This paper proposes a novel three-stage wind-thermal generation expansion planning model based on representative day unit commitment that incorporates the uncertainty of wind power and load and the probabilistic reliability criteria. The probabilistic reliability criteria are considered by simulating random outage events of thermal units using a robust approach. The consequent robust reliability model is reformulated as mixed-integer linear programming models and integrated into the multi-stage generation expansion planning model. A decomposed strategy based on the Benders decomposition is adopted to tackle with the large-scale original model. Case studies are performed on both the revised IEEE 14-bus and IEEE 118-bus test systems to validate the effectiveness of proposed model and method. Numerical results show that the proposed generation planning method balances the economy and reliability of the system.