Research On The Optimal Operation Of The Micro Grid Of Inner Mongolia Wuhai

Micro grid can improve the efficiency of energy utilization, support the grid,promote the development of the distributed power, and it provides a effective way for the future of construction of the strong smart grid, so its development accepts the wide attention of the scholars around the world. Under the background of construction of strong smart grid of our country, Inner Mongolia wuhai built a experimental micro grid which consists of wind power, photovoltaic, miniature gas turbine etc, in order to make the operation scheme of the micro power of micro grid more reasonable and efficient,this paper studied the optimal operation of the micro power grid.This article had a good analyze on the micro power grid development of both at home and abroad, and it discussed the micro power grid of Inner Mongolia wuhai for the necessity of research on the optimal operation. Because of the micro grid's optimal operation problems are complex nonlinear optimization problems, and the differential evolution algorithm is adopted to optimize the problem is very easy to fall into local optimum, so this paper combined the teaching and learning algorithm with the differential evolution algorithm, proposed Hybrid differential evolution and the teaching and learning algorithm, and improved the ability of the algorithm, provided the optimal tool for this optimization problem. Then, this paper based on the running characteristics of micro power of Inner Mongolia wuhai micro power grid, established the mathematical model of the micro power, and on the base of it we established the optimization model of the grid, which has the objective function of minimum operation cost. For the analysis of example, cold, hot and electric load of winter and summer in Inner Mongolia, wind speed and illumination data are the original data model, and then optimized the micro power grid at the running way of connected and isolated, and the analysis verify the feasibility of optimization scheme.