Economic dispatch of wind integrated power systems with a conditional risk method

Wind power is considered as one of the most promising and fastest growing renewable energy due to its low generation cost and the minimum environmental impact. However, with the features of randomness and non-scheduling, which brings risks to the operation stability and dispatch security of power system incorporating wind power. Due to the randomness of wind power and operation risk of power system, conditional value-at-risk (CVaR) theory is introduced in this paper, in order to quantify the uncertain risk of power system incorporating wind power. To characterize the security of power system by insecure probability as a risk constraint, quantization of the risk function has been realized by Monte Carlo simulation, An optimal objective function is constructed by energy-saving object, Then construct the stochastic optimization dispatch model based on conditional risk value by penalized the previous objective function model. In this paper, the penalized stochastic optimization model is solved by level-function method. A subgradient variable is introduced in level-function method to solve the optimum solutions, and put them back to objective function to calculate the optimum value. An IEEE-30 bus system is tested in this paper to analyze the proposed methods of solving the stochastic optimization model under different confidence levels, different CVaR and different capacity of wind power, Result shows that the level function method have much less compute time than linear program method, it provides theoretical basis for an economic and security stochastic optimization dispatch of power system.