Genetic Algorithm Based Adequacy Evaluation of Hybrid Power Generation System Including Wind Turbine Generators

The adequacy of power generation should be properly evaluated to facilitate the reliable operations of power systems under uncertainties. More recently, wind power has attracted significant attention primarily because it does not consume fossil fuels and is environmentally benign. However, the output from wind turbine generator (WTG) can not be precisely predicted due to the intermittent nature of wind resources. In this paper, a genetic algorithm (GA) based search procedure is adopted to accomplish the adequacy assessment for power generating system including wind turbine generators. The most probable failure states are sought out, which contribute significantly to the adequacy indices including loss of load expectation (LOLE), loss of load frequency (LOLF), and expected energy not supplied (EENS). A modified IEEE Reliability Test System (IEEE-RTS) is used to verify the applicability and effectiveness of the proposed approach.