Study On The SOC Of The Battery In Transformer Substation With Balanced Control

With the rapid development of the power industry,the battery energy management system(BMS)has become the research focus and research hotspot.In this paper,the SOC estimation and the battery balance control in the energy management system of substation are studied.In this paper,the current background of the analysis,briefly introduced the battery SOC estimation methods and balanced control circuit research status,and analysis of the advantages and disadvantages of the current method,and to determine the research program and research content.Then the development of neural network and the concept of neural network are briefly introduced.Then the basic principles,network structure and learning algorithm of BP neural network and RBF neural network are introduced in detail.The advantages and disadvantages of each method are analyzed on the basis of introducing the estimation methods of several kinds of battery SOC which are widely used at present.Then the neural network estimation method is used to estimate the SOC of the battery.The input and output parameters of the neural network are selected and the estimation model of the battery SOC is constructed.The parameters of the lithium iron phosphate battery experimental platform are measured and analyzed in the MTALAB simulation environment.This method is verifiedby simulation.In this paper,a capacitance equalization scheme based on LC oscillating circuit is proposed.The transfer energy is directly transferred from the single cell with high terminal voltage to the single cell with low voltage through LC oscillation circuit.Using the inductance element L to increase the voltage of the capacitive element C can overcome the drawback that the equalization circuit of the stored energy of the capacitor has poor energy transfer.Using high-frequency PWM control to suppress the current amplitude.To achieve a balanced control of the battery pack.