Two-stage electricity production scheduling with energy storage and dynamic emission modelling
Bi Fan, Fengjie Liao, Chao Yang, Quande Qin
Abstract
With increasing environmental concerns and energy crisis, a variety of renewable energy sources (RES) are being increasingly utilised worldwide. However, the integration of RES such as wind power and photovoltaics in large-scale can lead to increased load fluctuations, which can undermine the overall environmental benefits and pose risks to the secure and stable operation of the power system. To mitigate this challenge, a two-stage electricity production scheduling is developed incorporating energy storage system (ESS) and dynamic emission modelling (DEM). In the first stage, a multi-objective mixed integer programming model schedules the production of RES, increasing penetration rate and system stability. In the second stage, a data-driven dynamic emission model is developed to optimise the load allocation of thermal power unit to reduce the carbon emissions. Furthermore, a flexible operating reserve strategy is proposed to handle the uncertainty resulting from the intermittent character of RES. Experimental results demonstrate that the proposed method effectively schedules the production of RES thereby alleviating the contradiction between high RES utilisation and stable system operation. Compared to the benchmark model, the proposed method can reduce the carbon emissions and total cost of the system by 20.34% and 10.65%, respectively.