Research On The Monitoring Technology Of Batteries In The Pitch System Of Wind Power

For the energy storage technic in renewable energy power generation system, there are two important requirements. The first one is that the charge and discharge control strategy must be impeccable, which can satisfy the demand of storage battery under complex and variable circumstance and extend its service life. Another requirement is high-precision of battery monitoring system, which can catch the battery’s working state in real time and guaranty the safe operation of the system strictly. A condition monitoring system for lead-acid battery in the variable pitch system was proposed in this paper, and the surplus capacity of storage battery was predicted by BP neural network.Valve Regulated Lead Acid Battery(VRLA) was chosen as the research object in this paper, the theoretical knowledge of which was introduced, and the internal resistance’s model and detection methods were also analysed. The condition monitoring system was based on CY8C4245AXI-483controller, and several hardware circuits were introduced, such as supply circuit, pre-amplification electric circuit, AD630modulator circuit, serial communication circuit and AD acquisition circuit.32-bit high-performance processor Psoc4200of CYPRESS was used, which can measure voltage, charging and discharging current and internal resistance. Touch key-press and display modules were designed for man-machine interaction. The test results show that the system can well judge the state of storage battery.The knowledge of storage battery’s SOC was introduced. A three-layer LM-BP network was established to predict SOC. MATLAB was used for simulation. The prediction result shows that using LM-BP neural network to predict storage battery’s SOC is feasible.