Multivariate low-carbon scheduling of distribution network based on improved dynamic carbon emission factor

Abstract

The “load-following” characteristic of the power system makes the electricity consumption behavior on the load side crucial for the low-carbon operation of the distribution network. To address this, this paper proposes an improved dynamic carbon emission factor for the distribution network, taking into account the spatiotemporal characteristics of carbon emission intensity and the integration capacity of photovoltaics (PV). Based on this, a calculation method for the carbon emissions of the distribution network load is provided. Subsequently, for commercial and industrial user scenarios, demand response models are separately constructed for commercial and industrial loads based on different driving mechanisms. Using time-of-use electricity prices as decision variables, optimization scheduling of the distribution network is carried out with the objectives of minimizing scheduling costs and carbon emissions. At the same time, a case study is conducted in an improved IEEE-33 node distribution network. The results indicate that, under the guidance of the improved dynamic carbon emission factor, load transfer can be achieved through fluctuating electricity prices, effectively reducing the scheduling costs of the distribution network, decreasing carbon emissions, and enhancing the PV integration capacity of the distribution network in different user scenarios. Finally, it is hoped that in the future, this optimization method can be widely applied, and further research can explore coordinated strategies among generation, network, load, and storage to advance the development of the power industry.