Research On Optimal Scheduling Of Power System Considering Wind Risk

With the energy and environment issues becoming more prominent, wind power and other new energy generation technology become more and more spread. Large-scale wind power generators connecting to power grid has good economic and social benefits, meanwhile, it brings a lot of problems to power system, for example, day-ahead scheduling scheme of power system will have the risk of lack of spinning reserve, etc. In this paper, wind power risk is considered in the conventional optimization scheduling models, in order to control the risk of scheduling strategy and enhance reliability of power system.The main research work and innovative points of this paper are as follows:(1) Two kinds of optimization scheduling models of power system are presented in this paper. The first model uses extra spinning reserves to balance wind power risk, to reduce risk in certain extent. The second model is based on the first model, and wind speed and load forecasting errors which are random variables are introduced into the mathematical model. Risk constraint is used to replace the reserve constraint in traditional optimization model, in order to control risk more accurately.(2) Risk assessment is used to determine day-ahead risk. In the process of risk evaluation, large amount of historic data is analyzed by statistic methods, and probability distributions of wind speed and load forecast errors are obtained. The distributions are sampled using sampling with unequal probabilities, which could reduce sampling size and sampling time greatly.(3) The Orthogonal Genetic Simulated Annealing Algorithm is used to optimize the two models; meanwhile, simulated annealing idea is introduced into the algorithm to control over-limit penalty degree, which enhances convergence speed of the algorithm. Finally, a unit commitment test system and the Shanghai power grid system are used to test the above models and algorithm, which shows that the Orthogonal Genetic Simulated Annealing Algorithm and sampling with unequal probabilities employed in this paper have good performance; Large-scale wind power generators connecting to power grid increases the risk of day-ahead scheduling, meanwhile, the risk control could bring a small increase of coal consumption of the system.