stochastic unit commitment of wind farms integrated in power system

integration of wind power generation creates new concerns for operation engineers in a power system. unlike conventional power generation sources, wind power generators supply intermittent power due to uncertainty in parameters of wind such as its velocity. this paper presents probabilistic model for load and wind power uncertainty which can be used in operation planning (with durations up to one or two years). a stochastic model is proposed to simulate the status of units that are directly affected by the load and wind power generation uncertainties. this paper develops a solution method for generation scheduling of power system, while taking into account the stochastic behavior of the load magnitude and the wind power generation. the stochastic trend in uncertainty of these parameters has been simulated by creating scenarios that can be solved by deterministic methods. mixed integer nonlinear programming (minlp) is used for solving deterministic unit commitment problems, the reserve power requirement, load–generation balance, and available wind power constraints. the proposed approach is developed to make decision on fixed state of units operation in different scenarios which can be employed efficiently in unit scheduling of power system. the proposed approach is applied to a 12-unit test system (including 10 conventional units and 2 wind farms). the performance of the proposed approach is more investigated through analysis of its results for two other test systems.