Mobile Energy Storage Scheduling Under Traffic and Fault Constraints
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Solution Overview
Problem
Current methods for optimal scheduling of mobile energy storage systems lack effective spatio-temporal regulation strategies to enhance reliability in power distribution networks, particularly due to complex spatio-temporal coupling relationships and uncertainties in traffic and fault conditions.
Innovation Solution
A spatio-temporal combined optimal scheduling strategy for mobile energy storage systems, which involves inputting data on power and traffic systems, initializing a time interval, and solving an optimal regulation model to provide real-time path and power instructions for MES vehicles, incorporating constraints for load reduction, traffic, and power flow to ensure reliable operation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a traditional fixed energy storage system is used, then the system structure is simple and easy to operate, but the power supply reliability is limited and can only provide emergency power supply for key loads
Solution Approach 1:
The patent transforms the fixed energy storage system into a mobile energy storage system that can dynamically move and be deployed to different locations. The MES system includes movable chassis, battery modules, and control systems that enable dynamic repositioning to provide emergency power supply to different key loads as needed, thereby improving power supply reliability without significantly increasing system complexity
Solution Approach 2:
The mobile energy storage system is designed with multi-functional capabilities including emergency power supply, peak load shifting, and voltage support. The system can serve multiple purposes and be deployed to different locations, making it a universal solution that improves overall power supply reliability across the distribution network rather than being limited to a single fixed location
2Reliability
If spatio-temporal optimal regulation is implemented for MES system, then the power supply reliability is improved, but the model complexity increases due to large-scale mixed integer nonlinear programming
Solution Approach 1:
The patent segments the complex spatio-temporal optimization problem into separate spatial optimization and temporal optimization sub-problems. The spatial optimization determines the optimal location and deployment of MES systems, while the temporal optimization handles charging/discharging scheduling. This segmentation reduces the complexity of the overall mixed integer nonlinear programming model while still achieving improved power supply reliability through coordinated spatio-temporal regulation
3Productivity
If real-time regulation strategy is provided for MES system, then the responsiveness to power distribution network needs is improved, but the computational burden increases due to complex spatio-temporal coupling relationships
Solution Approach 1:
The patent implements preliminary action by pre-calculating and storing optimal regulation strategies for different power distribution network scenarios and conditions. When real-time regulation is needed, the system quickly retrieves and applies the pre-computed strategies based on current system state, significantly reducing the computational burden while maintaining high responsiveness and regulation efficiency
Data Source
AI summary
A method for making a spatio-temporal combined optimal scheduling strategy of a mobile energy storage (MES) system includes: inputting data of a power system, a traffic system, and an MES system; setting a time interval, and initializing a time interval counter; inputting real-time fault, traffic, and MES data; and performing rolling optimization and solving, and delivering regulation decision instructions of the MES system, till a fault is removed. The core of the present disclosure is to propose a spatio-temporal combined optimal model of the MES system to describe spatio-temporal coupling statuses of an energy storage vehicle, a traffic network, and a power distribution network. The present disclosure provides guidance for an optimal scheduling decision of the MES system by properly regulating a traveling path and charging and discharging power of the MES system, thereby supporting high-reliability operation of the power distribution network.