Scheduling optimization and emission analysis of clean energy under the background of dual carbon

Under the dual-carbon background, promoting clean energy consumption and carbon emission reduction has become an important goal of power grid development. This paper presents an optimization method for system scheduling considering the uncertainty of renewable energy and system power reserve. Firstly, based on the prediction error analysis, an evaluation method based on load loss probability is proposed to determine the system operation reserve power. Then, the system operation cost and carbon dioxide emission are modeled as the optimization objectives. The optimization process includes two stages. In the first stage, the mixed integer linear programming (MILP) method is used for deterministic optimization to generate the generator set combination with specified power reserve requirements. In the second stage of optimization, the prediction uncertainty is considered, the operation plan is adjusted, and the controllable generator is used to deal with the prediction deviation. The available operating reserve power, cost and carbon dioxide emission under different methods are compared in the simulation. Compared with the traditional deterministic scheduling method, the proposed method saves about 15% of the economic and environmental costs while ensuring the target security level.