| Extreme events such as natural disasters and cyber attacks may lead to large-scale power outages in the power grid,affecting critical infrastructure,and causing significant social and economic losses.In recent years,climate change has increased the frequency and scale of extreme events,and improving grid resilience can help alleviate the damage caused by these events.Mobile energy storage,as an emerging technology that enhances the spatial flexibility of energy storage facilities,can provide various services for the power system,including peak shifting,valley filling,frequency regulation,and congestion management.It can more effectively promote the interaction between source network load storage in the power system.When the power system is affected by extreme events,mobile energy storage is also an active regulation strategy to support high elastic operation of the power system.With the development of energy storage,it is necessary to study the dispatching strategy of large-scale energy storage in power system.Therefore,this article establishes a grid transportation network collaborative optimization model that takes into account the participation of mobile energy storage,and proposes a scheduling strategy for large-scale mobile energy storage to achieve collaborative optimization between mobile energy storage and the power grid.The following three innovative achievements have been achieved:A more flexible "vehicle storage decoupling" mobile energy storage application model is proposed to address the gap between the practical application of mobile energy storage and existing research.The vehicle and energy storage equipment are decoupled and optimized for scheduling separately.A spatiotemporal network model based mobile energy storage vehicle path model was established to address the spatiotemporal state capture problem during the operation of large-scale mobile energy storage.At the level of energy state,on the premise that the energy storage size meets modular fine customization,the energy storage capacity and energy storage are further decoupled and modeled as continuous variables,each making decisions and constraining each other,greatly improving computational efficiency.A grid transportation network collaborative optimization model was established for the scheduling problem of large-scale mobile energy storage in the power system,with the goal of minimizing system operating costs.In order to solve the problem that the traffic system and power system have information barriers in actual operation and cannot realize real-time collaborative scheduling,a decentralized algorithm based on Lagrange decomposition is proposed.The coordination level is responsible for collecting the boundary information of the two systems,and coordinating the two sub problems to achieve the overall optimization through Lagrange multiplier.In the example analysis,a comparative analysis is conducted on the value of mobile energy storage with equal capacity and distributed fixed energy storage on the power grid.The results indicate that compared to distributed fixed energy storage with equal capacity,mobile energy storage significantly improves the economic value provided by the power grid.In response to the issue of improving the elasticity of large-scale mobile energy storage on the power generation side of the power system,a power grid security dispatch model is established based on the grid transportation network collaborative optimization model,with the goal of minimizing generation costs and load shedding costs during faults.A power grid security dispatch strategy that takes into account the participation of mobile energy storage is proposed.In the case analysis,quantitative analysis is conducted on the improvement of grid elasticity when mobile energy storage responds to sudden shutdown of large capacity units.The results indicate that when considering the participation of mobile energy storage,the power system’s ability to cope with faults is significantly improved. |
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