Multi-stage robust optimal economic accommodation method for renewable energy considering carbon emission cost

The integration of renewable energy contributes to the target of energy saving and emission reduction, which helps to realize “2030 carbon peak, 2060 carbon neutral” strategy of China. Renewable outputs, on the other hand, exhibit uncertainties, intermittentness, and volatility. To accommodate renewable energy, traditional generator assets such as thermal units must incur higher operating costs. To that end, optimizing power system scheduling requires balancing the benefits and costs of renewable integration. In addition, with the establishment of the carbon trading market, carbon emission cost has become one of the essential costs of power generation. As a result, this paper develops a multi-stage robust optimal economic accommodation model that accounts for both operation and carbon emission costs. Besides, the solution nonanticipativity and robustness can be guaranteed by the established. The optimal economic accommodation model is then equivalently reformed into a single-level mixed integer linear programming (MILP) structure using a multi-stage robust explicit decision method with affine policies. Furthermore, a fast evaluation method for economic accommodation rate is proposed based on the solved affine coefficients. Numerical testing confirms that the proposed method outperforms traditional methods. Furthermore, the proposed method avoids paying 52.93% more cost to increase the accommodation rates by 5.74%, 0.74%, 2.28%, and 1.14% for four farms.