Earticle

There are strong randomness in wind power, its output is not controllable. Large scale wind power grid-connection to dispatch system brings new uncertainty. This paper constructs the wind-fire random optimal model based on combined MIPSO algorithm and achieves the multi-objective optimizations on the minimization of power cost and pollution emissions of thermal power units. Firstly, wind power outputs can be forecasted by utilizing BP neural network algorithm. Then random multi-objective optimal solution is obtained through MIPSO algorithm. Finally, multi-objective optimal scheduling is illustrated by using the IEEE-30 node. The results show that the combination arithmetic solution set uniform distribution, predict accuracy and qualified rate were 0.9962 and 0.7651, using MIPSO algorithm is out of the solution of the highest degree of coordination, get each time specific unit output of the plan, according to the calculation results make corresponding power generation plan, to access a fairly large wind power dispatch system has the actual reference value, so the proposed method is feasible and effective.