Low-carbon dispatch optimizationof wind-solar-thermal-storage multi-energy system based on stochastic chance constraints and carbon trading mechanism

To improve the low-carbon economic performance of renewable energy-dominated power systems, a multi-energy coordinated optimization dispatch model for wind, solar, thermal, and storage systems considering uncertainties on both the supply and demand sides is proposed. This paper comprehensively considers the economic costs of thermal power unit operation, wind and solar power curtailment, energy storage operation, carbon trading and spinning reserve. The model incorporates a penalizing carbon trading mechanism and uses a stochastic chance- constrained approach to handle fluctuations in wind and solar power generation as well as uncertainties in load forecasting. The study, based on the IEEE 30-bus system, is solved using a stochastic simulation particle swarm optimization algorithm. Results show that after introducing the carbon trading mechanism, the system's carbon emissions were reduced by 8.35%, wind and solar curtailment penalties were reduced by 65.48%, and overall costs decreased by 14.94%. Additionally, the chance-constrained model effectively reduced the system's reserve capacity requirements, with reserve capacity decreasing by 31.84%, leading to a further reduction of 26.83% in overall costs. In the scenario of combined wind-solar-thermal-storage output, the wind and solar curtailment rate dropped to 7.37%, and carbon emissions decreased to 6474.69 tons. Through the "energy shifting" function, the energy storage system provided effective support during peak loads, further optimizing the dispatch outcomes.