Optimal day-ahead dispatching strategy for VPP using dynamic grouping DER aggregation method based on improved virtual battery model

Abstract

The day-ahead dispatching strategy of heterogeneous distributed energy resources (DER) for virtual power plants (VPP) is critical to participating in power system and electricity market operation. To achieve the optimal dispatching strategy, efficient modelling of the operational characteristics of DER and accurate evaluation of DER's operational flexibility are two necessary preconditions. However, DER show different operating characteristics reflecting massive nonlinear modelling constraints, which increases the computational complexity. Moreover, the existing methods ignore the DER's flexibility leading to the underutilization and neglection of DER with higher and lower flexibility, respectively, which lower dispatching performance and VPP's profits. Therefore, an optimal day-ahead dispatching strategy for VPP using dynamic grouping DER aggregation method based on improved virtual battery (VB) model is proposed in this paper. Firstly, an improved VB model was constructed to unify the modelling parameters including energy, power and response performance. Secondly, a dynamic grouping method of DER based on high-low match principle is proposed, and DER's flexibility is accurately evaluated based on Minkowski sum and maximum inner approximation algorithm. Finally, a day-ahead dispatching model is proposed to maximize VPP's profits. The numerical results validate the proposed method's effectiveness in the aspects of VPP's operating profits, DER aggregation and dispatching performance.