Optimal dispatch of electricity considering shared source-load carbon responsibility

The coordinated energy management of "source-load-storage" is essential to achieve maximum energy savings and emission reductions while reducing the economic costs of both source and load. Compared with existing work, this paper aims to incentivize the joint reduction of carbon emissions from both the source and the load by apportioning the precise responsibility for carbon emissions to each subject. Concretely, this paper proposes a two-stage low carbon optimal scheduling model based on source-load coordination. In the first stage, the costs and carbon emissions on the source side are reduced according to the real-time demand of the load nodes, the responsibility for carbon emissions is apportioned in detail according to the results of the optimal tide and a carbon trading mechanism is proposed. It is worth noting that the trading mechanism can reflect both the effects of load size, spatial and temporal differences. The second stage aims to minimize the sum of the daily operating costs of customer microgrids (MGs) subject to the uncertainty of distributed generation (DG), electricity trading mechanisms, carbon trading mechanisms, smart devices and conventional energy storage devices. Therefore, this paper proposes a real-time rolling optimal scheduling method for daily electricity consumption by introducing cloud energy storage (CES) rental services. Hence, this paper proposes a real-time rolling optimal dispatching method for daily electricity consumption by introducing CES rental services. Finally, an arithmetic analysis is carried out based on the improved PJM-5 node system for scenarios containing multiple types of generating units. The results show that the method reduces costs on both the generation side and the load side, with significant reductions in carbon emissions. In addition, the impact of different pricing criteria for trading mechanisms on scheduling outcomes is explored.