A Novel Price-Oriented Supply-Demand Interaction Scheduling Model Optimizing Virtual Power Plant Operations

Virtual Power Plants (VPPs) provide a promising direction for managing the complexities and uncertainties in operating Distributed Energy Resources (DERs). However, existing approaches rely on a “source-following-load” static strategy, falling short in dynamically leveraging market opportunities and transferable demands. To pursue optimal economic performance, this paper introduces a novel price-oriented supply-demand interaction scheduling (SDIS) model for VPP operation. SDIS integrates transferable demands and price signals from the market, renewable generators, and storage systems, enabling VPPs to dynamically balance supply and demand while optimizing both operational efficiency and economic returns. Case studies sampled from the Shanghai energy market with uncertain climatic conditions demonstrate that our model improves the operational efficiency of VPP, reduces economic costs, and enhances the grid stability. Our model paves a way to deal with the complex VPP operation, e.g. grid scenarios involving solar generators, urban metro systems, and central air conditioning clusters.