Real-time Power Dispatch With Storages Using Point Estimation-based Affinely Adjustable Robust Optimization
To adapt to the large-scale wind power penetration,this paper proposes a real-time power dispatch where the units and storages jointly participate in the automatic generation control.Besides,a point estimate-based affinely adjustable robust optimization is put forward for the wind uncertainty.Different from the traditional affinely adjustable robust optimization which optimizes the base operation cost,the proposed point estimate-based affinely adjustable robust optimization optimizes the expected operation cost to improve the economical efficiency.In this paper,a deterministic point estimation method is introduced to quickly and accurately evaluate the expected operating cost.The proposed model is a mixed integer bilinear constraint problem,which uses a"estimation-correction"convexified method to solve the problem.In the estimation stage,the state variables of storages are relaxed,while in the correction stage,the state variables are directly corrected.Finally,a difference-of-convex optimization is introduced to convexify the bilinear constraint problems in these two stages in order to improve the solution quality of the real-time dispatch with storages.The simulations in the IEEE 39,118 and 300 node systems verify the effectiveness of the proposed model and method.
wind uncertaintyreal-time power dispatchaffinely adjustable robust optimizationpoint estimation methoddifference-of-convex optimization
万方数据
维普
