Estimation of State of Charge of Storage Batteries in Photovoltaic Agricultural Systems
Photovoltaic agriculture is an effective combination of photovoltaic storage DC microgrid as a new type of energy structure and smart agriculture,which not only provides a reliable supply to the agricultural loads,but also reduces the cost of agricultural production.As a key component of photovoltaic DC microgrid,accurate estimation of the state of charge(SOC)of the storage battery is particularly important for system operation.Aiming at the difficulty of improving SOC estimation accuracy of energy storage batteries,a second-order RC circuit is proposed as the battery equivalent model,and a recursive least squares(VFFRLS)algorithm with variable forgetting factor is used to complete the online identification of battery model parameters.At the same time,the adaptive extended Kalman filter(AEKF)algorithm which updates the noise covariance in real time is used to estimate the SOC.The results show that this method has high precision and robustness,and improves the operation efficiency of the microgrid energy storage system.
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