Research On Control And Protection Of Energy Storage

The exploitation and utilization of energy sources is still a main subject for discussion nowadays in the world. While exploiting and utilizing new energy, people begin to pay much attention to how to make an efficient use of the energy in existence including the sources of energy saved, energy stored and energy recycled. Therefore, storage power station is gradually accepted by many people and is recognized as the most effective means to solve the problem of modulation of network peak. This paper deals with the control and protection system of storage power station.Storage battery power station is a comparatively independent system. Automation is needed both for the safe and stable operation and the putting into operation with or breaking off from the network. In order to make the power system run safely and economically and guarantee the quality of the electric energy, Automation and protection is the absolutely necessary means and meanwhile higher demand is required for them.Based on the characteristics of the application of storage power station in the power system, this paper puts forward the whole design plan of the microprocessor monitoring system of storage power station, which is layer-built distributed structure and meanwhile it works out hardware electric circuit of microprocessor protection and explains the operating principle of it. The paper especially makes a detail study on the microprocessor protection system of the storage power station mainly from the three aspects: microprocessor transformer protection, microprocessor transmission line protection and microprocessor bus line protection and schemes out the protecting device which is required to meet the need of the microprocessor monitoring system of storage power station and accord with the demand of the future trend that relay protection technology should develop in the way towards the integration of computerization, latticing, intelligentization, protection, control, measure and data communication. According to the load history of Liaoning Electric Power Company, the paper predicts the short-term load of power system and works over the module setting of the power system by improving BP network. The application of MATLAB NN (nerve network) toolbox to emulate makes it clear that it is feasible to make prediction over load.