Mobile Energy Storage Spatio-temporal Dispatch in Low-carbon Distribution Networks

Abstract

As the proportion of new energy generation increases, optimizing the scheduling of energy storage devices to achieve decarbonized grid operation becomes a key issue. This paper proposes a low-carbon joint dispatch optimization model based on mobile energy storage. By constructing a spatio-temporal network model of the energy storage device, the charging and discharging behaviors, mobility characteristics, distribution network current constraints, and carbon emission factors of the energy storage device are considered comprehensively to optimize its operation. With the objective of minimizing the operating cost and carbon emission, the model adopts the mixed integer programming method to optimize the variables such as the movement path, charging and discharging power, and the state of the energy storage device. The model introduces the carbon emission factor of gas turbine and grid power purchase, combines the scheduling of energy storage devices with the low-carbon objective, and ensures the feasibility of the scheme through the tidal current constraints, SOC limits and path continuity constraints. The example results show that the proposed model effectively reduces the grid operation cost and carbon emission, while enhancing the capacity of renewable energy consumption, providing a new idea for the application of mobile energy storage in low-carbon grid scheduling.