Optimal scheduling of distributed energy resources as a virtual power plant in a transactive energy framework

Abstract

A transactive energy framework can provide an integral management scheme that facilitates power delivery with high efficiency and reliability. To close the gap between wholesale and retail markets, this study presents a two-stage optimal scheduling model for distributed energy resources in the form of a virtual power plant (VPP) participating in the day-ahead (DA) and real-time (RT) markets. In the first stage, the hourly scheduling strategy of the VPP is optimised, in order to maximise the total profit in the DA market. In the second stage, the outputs of the VPP are optimally adjusted, in order to minimise the imbalance cost in the RT market. The conditional-value-at-risk is used to assess the risk of profit variability due to the presence of uncertainties. Furthermore, formulated two-stage models are solved by the enhanced particle swarm optimisation algorithm and a commercial solver. Case study results show that the proposed approach can identify optimal and accurate scheduling results, and is a useful decision-making tool.