Distributed coordinated control optimization method for urban rail transit ground supercapacitor energy storage system

Abstract

The invention provides a distributed coordinated control optimization method for an urban rail transit ground supercapacitor energy storage system, and belongs to the technical field of urban rail transit supercapacitor energy storage system control. This method obtains the SOC state of the supercapacitor, the state of the substation and the running state of the train, and constructs a state set; takes the supercapacitor of each substation as an energy storage agent, and analyzes the energy flow theory and multi-objective coordination optimization of the traction power supply system The function determines the income function of each energy storage agent; constructs a multi-agent dynamic game model, based on this model, combines the distributed Q-learning algorithm to solve and optimize the distributed coordinated control of the ground supercapacitor energy storage system. The invention performs distributed and independent control on each energy storage system, effectively reduces the computational complexity, and improves the reliability of the control strategy; combines the dynamic cooperative game theory and the reinforcement learning theory, and the efficiency of the game equilibrium point is effectively improved. Therefore, it can Realize the online optimization of the overall energy-saving effect of the full-line energy storage system.

Description

technical field [0001] The invention relates to the technical field of supercapacitor energy storage system control in urban rail transit, in particular to a distributed coordination optimization control method for ground supercapacitor energy storage systems in urban rail transit based on dynamic cooperative game. Background technique [0002] In the traction power supply system of urban rail transit, the traction substation usually adopts 24-pulse diode rectification to convert 10kV / 35kVAC AC power into 750V / 1500V DC power to provide traction energy for line trains. Due to the unidirectionality of diode rectification, when the train brakes, the braking energy is transmitted to the traction network. If there is no traction train nearby to absorb it, the voltage of the traction network will rise rapidly, causing the start-up of the braking resistor and the occurrence of regenerative failure. In order to fully recover the regenerative energy of the train, reduce regenerative ...

AI Technical Summary

Problems solved by technology

[0009] Although the above-mentioned energy management method for supercapacitor energy storage systems based on reinforcement learning can realize the optimization of the energy saving effect and voltage stabilization effect of a single energy storage system, when multiple energy storage devices are installed on the whole line, the joint learning of different energy storage systems will As a result, the system environment is non-stationary, and the overall energy-saving effect of multiple energy storage systems cannot be guaranteed to be improved and optimized

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