Distributed coordination control optimization method for an urban rail transit ground super-capacitor energy storage system

Abstract

The invention provides a distributed coordination control optimization method for an urban rail transit ground super-capacitor energy storage system, and belongs to the technical field of urban rail transit super-capacitor energy storage system control. The method comprises the steps of obtaining an SOC state of a super-capacitor, the state of a substation and the operation state of a train, and constructing a state set; taking the super-capacitor of each substation as an energy storage agent, and determining a revenue function of each energy storage agent according to the energy flow theory analysis of a traction power supply system and a multi-objective coordination optimization function; constructing a multi-agent dynamic game model, and solving and optimizing the distributed coordination control of the ground super-capacitor energy storage system by combining a distributed Q learning algorithm based on the model. According to the invention, the distributed independent control is carried out on each energy storage system, so that the calculation complexity is effectively reduced and the reliability of a control strategy is improved. The dynamic cooperative game theory and the reinforcement learning theory are combined. The game equilibrium point efficiency is effectively improved. Therefore, the online optimization of the overall energy saving effect of the whole line energystorage system can be achieved.

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

Images