Logistic and scheduling optimization of the mobilized and distributed battery in urban energy systems

Building a new power system with renewable energy as the main body is the only way to solve the problem of global climate change and achieve the dual carbon goal. However, the increasing penetration rate of renewable energy and large-scale electric vehicles have brought great challenges to the safe and reliable operation of traditional power system, resulting in the inability to effectively meet the enormous urban electricity demand in real time. In response, this paper proposes to adopt mobilized and distributed batteries and establishes a two-stage logistic and scheduling optimization model, thereby realizing the power transportation between renewable energy power plants and cities. The first stage model aims to optimize the battery transportation and logistics scheme with minimizing the total battery procurement and transportation cost as the objective function, considering various constraints including railway transport capacity limitation, battery supply and demand balance, and other technologies. The second stage model aims to maximize the peak shaving effect of urban power system and optimize the railway departure time with mobile batteries, considering the train operation, battery supply limitation, and battery transportation balance constraints. Finally, a quantitative economic evaluation of six cities (Heilongjiang, Gansu, Fujian, Shanghai, Jilin, and Liaoning) in China is presented, and the results indicate that the average levelized cost of electricity is as low as 0.052 $/kWh, illustrating the great technical and economic performance of battery logistics and scheduling. In addition, the impact of various sensitive factors on the economic performance of the urban energy system is implemented.