Day-Ahead Optimal Scheduling Of Island Microgrid Considering Uncertainty

With the continuous advancement of the energy revolution,on the one hand,the large-scale use of wind energy is the inevitable development trend of power grid.On the other hand,there will be a large number of microgrids facing end users,and the future will show a pattern of coexistence of large grids and microgrids.Based on the above background,the accuracy of wind power forecasting will affect the safety of grid connection,but the existing research ignores the difference of the error distribution under different wind speed intervals,and often uses a certain known distribution for simple fitting.Therefore,this paper studies the day-ahead forecast of wind power considering the fitting error of power characteristics.Since the wind speed-power distribution is actually a wide frequency band between the cut-in wind speed and the rated wind speed,there are different error sets for different wind speed sections.The fitting method of mixed Gaussian distribution and Fourier approximation is used to obtain the probability density function of the errors of different wind speed segments,and the prediction errors of different periods are obtained by combining the rejection sampling and roulette methods to improve the accuracy of wind power forecasting.In order to improve the utilization efficiency of wind power,and considering wind energy as the main energy source of the microgrid in an island state,an island microgrid including demand response and combined heat and power systems was constructed to realize the joint dispatch of equipment on the supply and demand side.The strategy of time of use pricing is formulated to reasonably adjust the power consumption mode of users,so as to further improve the utilization rate of wind power.The scheduling strategy aims at the economy and environmental protection of the system,and at the same time pays attention to the comfort of users’ energy use,and try to avoid load shedding.Coordinate the working status of equipment on both sides of supply and demand to obtain better scheduling results from the perspective of economy and environmental protection.Taking into account the uncertainty on both sides of the source and load is also an important cause of serious wind abandonment.Therefore,this paper analyzes the impact of uncertainty of wind power output and demand response on wind power consumption and islanded microgrid scheduling.The K-means algorithm is improved on the energy supply side combined with the contour coefficient and the Freche distance,and the improved clustering algorithm is used to divide the wind power output scene,count the probability of different scenes,and select the output mode through roulette.The load side introduces the difference between the actual use time and the expected use time of the equipment as a random variable to explore the influence of the error distribution on the scheduling results.Introduce the confidence level to relax the constraints of user equipment use time,and explore the influence of different confidence levels on the dispatch of the combined heat and power system.