Robust optimal operating strategy for photovoltaic-storage-load virtual power plant considering dual uncertainties of photovoltaic output and electricity prices

Abstract

The widespread integration of photovoltaic (PV) power, energy storage systems, and other demand-side resources highlights the importance of optimal dispatching for the PV-storage-load virtual power plant (VPP). However, the fluctuation of the PV power generation and the uncertainty of the electricity prices exacerbate the economic operation risks of the VPP. To address these challenges, an optimal dispatching strategy for the PV-storage-load VPP is proposed, with due consideration given to the dual uncertainties of electricity prices and PV power output. Firstly, the conditional value-at-risk theory is employed to quantify the uncertainty risk of VPP revenue caused by electricity price fluctuations. Secondly, in view of the asymmetric fluctuation intervals of PV power output, a quantification method for PV uncertainty and dispatch robustness is developed using the confidence gap decision theory. Furthermore, by combining the regulation reserve model of multi-type flexible resources, a robust optimization model for the PV-storage-load VPP is constructed with the objective of maximizing comprehensive operational revenue, which includes the provision of upward and downward reserve services. Finally, case studies based on a PV-storage-load VPP in a Chinese province are conducted to validate the effectiveness and superiority of the proposed model. The simulation results indicate that the proposed robust optimization strategy effectively reflects the relationship between the uncertainty of PV power output and the risk preference of decision-maker, mitigates the fluctuation risks of electricity prices to ensure the stability of the power system, and enhances the economic efficiency and flexibility of the PV-storage-load VPP operation.