VPP-Based Park-Level Integrated Energy Scheduling System with Carbon Emission and Integrated Demand Response Mechanism Using Data-Driven Distributionally Robust Optimization

This paper investigates the effective management of distributed Renewable Energy (RE) sources in multi-user Park-level Integrated Energy Systems (PIESs), aiming to coordinate power supply, cooling, and other forms of energy through a Virtual Power Plant (VPP) while enhancing environmental and economic benefits in regulation markets. Beyond the uncertain influence of solar PhotoVoltaic (PV) power on VPP operation, the challenge exists in establishing carbon trading and Integrated Demand Response (IDR) mechanisms to enable internal regulation of VPP. To address the above problem, a data-driven two-stage Distributed Robust Optimization (2-DRO) model is proposed. The overall goal is to minimize the operating costs of VPP by maintaining a supply-demand balance in PIESs along with protecting the electricity for production tasks. A case study of an actual PIES in eastern China reveals that our model is more practical and cost-effective. It integrates the deployment of both electricity and cooling energy under the mechanism of IDR and carbon emissions, realising flexible scheduling for multi-scenario operation of PIES.