Generation Adequacy Evaluation Incorporating an Aggregated Probabilistic Model of Active Distribution Network Components and Features

This paper presents a generic methodology for assessing the generation adequacy of power systems incorporating an aggregated probabilistic model representing several active distribution network (ADN) components and features in the form of a virtual power plant (VPP). Randomly varying hourly outputs of individual ADN components like distributed energy resources and loads are combined with information about important distribution network features like topology and constraints to form the aggregated probabilistic model of the VPP using a linearized network flow-based optimization formulation proposed in this paper. The proposed formulation therefore facilitates the VPP's modeling as a single equivalent `unit' with respect to the transmission grid. This equivalent model is used together with new indices introduced for quantifying different aspects of the VPP's performance. Impacts of changes in the total installed VPP generation capacity as well as the load forecast uncertainty on the VPP performance indices and the system reliability indices are also investigated. The overall proposed methodology is implemented on the Roy Billinton Test System and the IEEE 69-bus distribution network using Monte Carlo sequential simulation techniques, and results obtained are discussed in detail.