Low-carbon operation constrained Two-stage Stochastic Energy and Reserve Scheduling: A Worst-case Conditional Value-at-Risk approach

The optimal scheduling of power systems with a high penetration of wind power integration has always been a hot research topic due to their dramatic uncertainty. Furthermore, it is increasingly aware that the economic benefits should not be the sole optimal benchmark. A more dynamic low-carbon operation mechanism is needed to build an environment-friendly power system. In this paper, a Two-stage Stochastic Energy and Reserve Scheduling (TSERS) model with low-carbon operation constraints is proposed, which can effectively hedge against the worst-case distribution of wind power. First, a copula-based Worst-case Conditional Value-at-Risk (WCVaR) model is developed to quantify the operational risk of economic dispatch under uncertain wind power. Then, a carbon quota optimization (CQO) model is presented, taking into account both generation and carbon costs. Numerical experiments are conducted on the modified IEEE systems. Simulation results exhibit the ability of the WCVaR method, as is evident from a 44.8% reduction in the extreme loss with respect to Distributionally Robust Optimization (DRO). the proposed CQO model achieves 37.27% more profit compared to the conventional model at an average carbon price growth rate of 36.1%. This demonstrates the model's ability to adjust to carbon cost fluctuations and provide a sensible optimization proposal.