Research On Coordinated Optimal Operation Of Distribution Network With High Penetration Distributed Renewable Energy

As the global warming and environmental pollution becoming more and more serious,how to save energy and reduce emissions has been paid more and more attention by people all over the world.Vigorous development of renewable energy has become an unstoppable trend.Although a large number of renewable energy connected to the distribution network has made outstanding contributions to energy conservation and emission reduction,the high penetration distributed renewable energy has also brought about a non-negligible impact.And the uncertainty of the high penetration distributed renewable energy also makes the operation control of the distribution network face challenges.This thesis focuses on the problem of coordinated optimization operation of distribution network in uncertain environment.The main work of this thesis is as follows:1)Based on the distribution network with high penetration renewable energy,the research on coordinated operation strategy of distribution network considering load uncertainty and distributed renewable energy uncertainty is proposed.Based on the robust optimization theory and linear programming method,the two-stage robust optimization problem is transformed into a linear problem that can be solved by column and constraint generation algorithm.In addition,the worst-case scenario of the optimal operation of the distribution network,as well as the operating costs in the worst-case scenario and the charging and discharging strategy of the energy storage can be obtained.Through the analysis of the case,the rationality of the proposed algorithm is verified.And the robust problem can be solved reasonably.Finally,the worst-case scenario and the effects of uncertainty adjustment parameters on operation problem can be obtained.2)Based on the day-ahead operation optimization,this thesis proposes a multi-period coordinated optimization operation strategy for distribution network considering the fluctuation of renewable energy output and load forecasting.The real-time correction of the operation strategy of the day-ahead scheduling is made,which takes the minimum deviation of the intra-day real-time correction operation strategy as the goal.Through the analysis of the example,it is verified that the model predictive control method can propose an intra-day rolling optimization model based on the day-ahead scheduling,and reasonably responses to the error of the previous forecast.3)In order to reasonably verify the proposed day-ahead robust optimization scheduling method and the intra-day real-time rolling optimization model based on model prediction control,this thesis validates an actual feeder in Heze,Shandong Province,China.The analysis of the example shows that the charging and discharging strategy of energy storage can be obtained by the robust optimization scheduling method,based on the previous forecast data.In order to avoid the conservation of the day-ahead scheduling,the proposed method could correct the day-ahead scheduling strategy in real time,which proves the feasibility and effectiveness of the proposed method.