Research on Low-Carbon Economic Peaking Considering Energy Storage and Stepwise Carbon Trading Cost

In a new power system dominated by clean energy sources such as hydropower, wind and PV, source-load uncertainty leads to insufficient system flexibility, and it is difficult to accurately quantitatively assess the carbon reduction benefits of the system. This paper proposes a low-carbon economic peaking model that takes into account energy storage and stepped carbon trading costs. The upper layer aims to minimise net load fluctuation and wind and light abandonment costs, and relaxes the deterministic constraints into fuzzy variable constraints that take into account the source-load uncertainty through the introduction of fuzzy chance constraint planning methods, so as to realise robust treatment of uncertain scenarios. stepped carbon trading cost and thermal power operation cost. In order to verify the effectiveness of the model, two scenarios of positive and negative peaking of wind power are set up, and the model is optimally solved by using a nonlinear planning solver. The example analysis shows that the proposed model can effectively reduce the net load fluctuation, improve the level of wind power consumption, reduce the carbon emission of the system, and take into account the economy and environmental protection of power system peaking by optimising the energy storage output.