Optimization Method for Low-carbon Economic Dispatch of Virtual Power Plants under Source Load Mutual Feedback Tension

To address the challenges of random fluctuations in wind and solar power output caused by high renewable energy integration, as well as the mutual feedback tensions between generation and load resulting from bidirectional responses of flexible loads, this paper investigates optimization methods for low-carbon economic dispatching of virtual power plants under such mutual feedback conditions. A collaborative dispatch framework integrating carbon capture and electro-gasification facilities was established to quantify mutual feedback constraints arising from renewable energy generation on the supply side and flexible load responses on the demand side. A multi-objective dispatch model was developed with objectives including minimized comprehensive dispatch costs, lowest system net carbon emissions, and smallest unit output fluctuations. The proposed algorithm employs a triple-improved particle swarm optimization strategy to achieve efficient low-carbon dispatching. Simulation results demonstrate that the proposed method reduces comprehensive dispatch costs over a 16-hour cycle to ￥11,000 while achieving an average system net carbon emission of only 0.30 tons, conclusively proving the effectiveness of the proposed algorithm and model in resolving mutual feedback tensions and ensuring stable low-carbon operation of virtual power plants.