Economic scheduling optimization of microgrids combining generalized energy storage and reward and penalty ladder carbon trading

As the connection between the upgraded power grid and users, the microgrid can not only control the output of the local distributed power but also realize a low-carbon transition of users in order to achieve the carbon reduction target. With the aim of reducing operating costs and carbon emissions at the same time, this paper proposes a sustainable economic scheduling strategy combining a ladder-type reward and punishment carbon trading mechanism with generalized energy storage. Initially, the charge and discharge process is analyzed in detail for the energy storage system, and mathematical models relating the actual energy storage system with the virtual energy storage system in the microgrid are established. The composition of the energy supplied to the microgrid and the emission intensity of different power supply sources are analyzed, and a multi-ladder carbon trading mechanism with rewards and penalties is proposed. Subsequently, the typical wind power and photovoltaic power generation cases are simulated by an improved generative adversarial network, which considers the randomness of renewable energy. Eventually, based on MATLAB, a simulation verification is carried out on the proposed scheduling scheme, and the experimental results show that the proposed scheme can effectively reduce operating costs and carbon emissions by 2.03% and 14.08%, respectively, which improves the economy and sustainability of the microgrid.