A Study of the Flexibility Region of Virtual Power Plant considering the Uncertainty of Other Virtual Power Plants

Abstract

In recent years, the increased numbers of distributed energy resources (DERs) have reduced the stability of distribution networks. To address this issue, Virtual Power Plant (VPP) technology has emerged and research has been conducted on aggregating various DERs. However, existing studies assume that VPPs exist independently within distribution networks. In reality, though, multiple VPPs can exist within the same system. Therefore, this paper proposes a method for estimating the flexibility region of a VPP that considers the uncertainty of other VPPs in the grid. As historical data on other VPPs is private, it is impossible to create a probability distribution. This paper therefore models the uncertainty using multi-source distributionally robust chance constraints (MS-DRJCC), based on a theoretical approach that allows modelling of uncertainty in the absence of historical data. The results show that curtailment is reduced compared to stochastic programming (SP), which schedules based on the available data distribution. This indicates that modelling with MS-DRJCC is effective in the absence of historical data.