RLS and EKF algorithms based full-vanadium flow battery SOC estimation method

Abstract

The invention discloses an RLS and EKF algorithms based full-vanadium flow battery SOC estimation method, comprising: 1) building a mathematical model for a full-vanadium flow battery; 2) using the RLS algorithm to identify parameters of the mathematical model for the full-vanadium flow battery; 3) using the EKF algorithm to estimate the SOC of the full-vanadium flow battery; and 4) combining the RLS algorithm and the EKF algorithm; updating in real time the model parameters for the full-vanadium flow battery; and according to the updated model parameters, conducting new SOC estimations. The method of the present invention achieves on-line updating of model parameters and accurate SOC estimation without additional system configuration.

Description

technical field [0001] The invention relates to the technical field of SOC detection of all-vanadium redox flow batteries, in particular to a method for estimating the SOC of all-vanadium redox flow batteries based on RLS and EKF algorithms. Background technique [0002] With the increasingly serious environmental pollution and energy crisis, it is imperative to develop renewable energy power generation systems. However, the inherent randomness and intermittent characteristics of renewable energy power generation have seriously affected the safety and economic operation of the power grid system; the problem of "abandoning light and wind" has seriously hindered the development of new energy and has become a major bottleneck that needs to be solved urgently question. [0003] As an effective way, energy storage turns intermittent, unstable, and uncontrollable renewable energy into stable, controllable, high-quality energy with high power quality, and at the same time provides...

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Problems solved by technology

Patent "On-line detection method of charge state of flow battery based on potential difference parameters" (patent number: 200910088258.0), the reference solution with known state of charge is combined with positive electrode and negative electrode electrolyte respectively to form a new battery, increasing The system configuration; literature (State of charge monitoring for vanadium redox flow batteries by the transmission spectrum ofV(IV) / V(V)electrolytes) and literature (Research on State of Charge Monitoring for Vanadium Redox Flow Batteries) by installing state monitoring batteries To measure the open circuit voltage of the all-vanadium redox flow battery, and then estimate the battery SOC according to the open circuit voltage, but this method needs to connect the state monitoring battery with the pipeline in the system, the installation is complicated, and the system configuration is increased. Not easy to maintain; the literature (A new control method for VRB SOCestimation in stand-alone wind energy systems) points out that the SOC of the all-vanadium redox flow battery is updated in every step of calculation, but the parameters in the all-vanadium redox flow battery model are based on the battery The calculation of the loss is a fixed parameter; the literature (Extended Kalman filter method for state of charge estimation of vanadium redox flow battery using thermal-dependent electrical model) and (Vanadium redox flow battery SOC state estimation based on Kalman filter algorithm) and so on through The Kalman filter estimates the SOC value, but the parameters in the model do not consider that it will change with the battery state, resulting in inaccurate SOC estimation

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