Robust Optimal Scheduling of Virtual Power Plant Considering Output Uncertainty of Distributed Generation
With the large-scale integration of distributed generation(DG)into the distribution network,in order to stabilize the impact of output fluctuation and intermittence,and make full use of flexible resources such as energy storage and controllable loads in the distribution network,virtual power plant optimal scheduling has become an effective method.However,how to achieve the robustness of virtual power plant optimal scheduling strategies under uncertainty has become a research topic.For this purpose,this paper presents a robust optimal scheduling model and optimization method of virtual power plant considering output uncertainty of distributed generation.Firstly,a virtual power plant optimal scheduling model is constructed in deterministic scenarios.The virtual power plant optimal scheduling model in deterministic scenarios is transformed from a difficult to solve mixed integer nonlinear model to an easy to solve mixed integer second-order cone model through second-order cone transformation,and solved accordingly.Then,using robust optimization theory,a robust optimal scheduling model considering the uncertainty of DG output is constructed,and it is transformed into two virtual power plant optimal scheduling models under two deterministic scenarios using robust equivalence transformation and cutting plane method.The two alternate iterations are used to obtain robust optimal solutions corresponding to the uncertainty model.Finally,the effectiveness of the proposed model and solution method is demonstrated through an IEEE33 node example analysis.
virtual power plantrobust optimizationuncertaintyDG output
万方数据
维普
