| In recent years,as electricity demand has continued to grow and the proportion of new energy generation has increased significantly,the shortage of power resources has intensified,leading to a further increase in the peak-valley difference.Introducing energy storage into the power system can effectively alleviate peak demand,improve the daily load rate of the power system,and greatly increase the utilization rate of power generation equipment.However,currently used energy storage devices have fixed installation locations and low flexibility,resulting in relatively low utilization rates.Compared with fixed energy storage devices,mobile energy storage system is not limited by location,and can not only fully utilize energy storage resources in both spatial and temporal dimensions but also serve as emergency power sources.Based on this,this paper aims to study the scheduling optimization methods for mobile energy storage system in two scenarios: daily energy storage scheduling services and emergency power supply,providing theoretical references for the efficient utilization of mobile energy storage system in practice.An optimization model for the day-ahead scheduling of mobile energy storage system was constructed.A typical scenario for the day-ahead scheduling of mobile energy storage system was set,the decision variable vector that fully characterizes the scheduling of mobile energy storage system movement paths and charging and discharging power was determined,and a series of constraints on mobile energy storage scheduling such as vehicle movement and battery operation were constructed.A target function that comprehensively considers the charging and discharging benefits of the system,mobile operating costs,and battery decay costs was designed.The day-ahead mobile energy storage system scheduling problem was abstracted as a typical mixedinteger linear programming problem.The Gurobi solver was used to solve the optimization problem.The optimization model for day-ahead scheduling was applied and studied using actual load data.Based on the actual load data of a certain city,a research scenario was set for optimizing the scheduling of mobile energy storage system in five access point areas.The scheduling decision results obtained by optimization were compared with conventional fixed energy storage and rule-based scheduling decisions to verify the effectiveness of the optimization method.On this basis,the influence of real-time electricity price characteristics,access point distance,and other factors on the optimization scheduling results was studied,and the rules for the optimal spatial scheduling of mobile energy storage were more comprehensively analyzed.The scheduling strategy for mobile energy storage system to provide emergency power supply services is studied.The load demand of power users is classified,and an emergency power supply optimization model that comprehensively considers user waiting time satisfaction and load recovery degree satisfaction is designed.A case study is conducted for the scenario of five access points,and it is verified through the case study that when the total supply capacity of mobile energy storage system is insufficient,the optimization algorithm in this paper can better allocate the mobile energy storage system’ guarantee supply strategy based on the urgency of user needs.The vehicle dispatching plan is more reasonable compared to the model that does not classify the load. |
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