Step-Based Carbon Trading Model for the Thermal-Electric Optimization of Integrated Energy Systems Considering the Correlation Between Wind and PV

The uncertainty and correlation of wind and PV power have significant impacts on the operational mode and energy utilization efficiency of integrated energy systems (IESs). It is necessary to optimize the operational flexibility of IESs equipment to lower the carbon emission (CE) levels of the IESs. This paper proposed a step-based carbon trading model for the thermal-electric optimization of IESs considering the correlation between wind and PV. Firstly, Latin Hypercube Sampling (LHS) method is used to sample random variables and generate scenarios that satisfy specific wind power and PV correlations to study the influence of wind and photovoltaic correlation on optimization scheduling. Then, a step-based carbon trading model is introduced to optimize the carbon emission control strategy considering the participation of IESs in the carbon trading market. Thirdly, an adjustable thermal-electric ratio for combined heat and power (CHP) and hydrogen fuel cell (HFC) operational strategies are formed to enhance the low-carbon and economic performance of IESs. And an economic objective function is formulated by minimizing the purchasing cost, CE cost, wind curtailment cost, and PV curtailment cost, which is transformed into a mixed-integer linear programming problem, worked using the CPLEX commercial solver. Finally, the multiple operating scenarios simulation results validate the effectiveness and accuracy of the proposed optimization strategies.