Optimal Scheduling Strategy for New Energy and High-Energy-Consuming Industrial Park Self-Owned Power Plants Based on Generation Rights-Carbon-Green Certificate Trading
High-energy-consuming industrial parks account for 42% of China's industrial carbon emissions, with an emission intensity of 1.2 t CO2 per 10,000 CNY, necessitating innovative market mechanisms to reduce carbon costs. This study proposes an optimal scheduling model integrating short-term generation rights trading with a ladder-type carbon emission-green certificate hybrid market mechanism for a system comprising a concentrated solar power (CSP) plant, wind power, photovoltaic (PV) generation, and a self-owned power plant in a high-energy-consuming park. The CSP thermal energy storage (TES) system enables energy time-shifting and electro-thermal coupling, constructing a multi-energy complementary power coordination model to smooth wind/PV fluctuations and enhance consumption. A joint short-term generation rights trading strategy is designed, dynamically matching renewable output with the self-owned plant's regulation demand through a generation rights-carbon quota-green certificate conversion mechanism. Simulation on a high-energy-consuming park in Jiuquan, Gansu Province, demonstrates that the proposed method effectively reduces carbon emissions and improves renewable energy consumption. The introduction of the CSP plant further lowers total park costs, achieving dual optimization of environmental and economic benefits. The model is linearized using the big-M method, transforming a mixed-integer nonlinear programming problem into a mixed-integer linear programming problem for solution. This approach addresses the mismatch between medium-to-long-term generation rights trading and short-term supply-demand fluctuations, as well as the lack of linkage among generation rights, carbon, and green certificate trading, thereby synergizing emission reduction incentives with power trading objectives.