Research And Implementation Of Central Monitor And Energy Management System Of Grid-connected PV Power Plant

In recent years, the development and utilization of renewable energy has becomean important part of the national economy sustainable development strategies andenvironmental protection. The rapid development of the solar photovoltaic industry,increasing the installed capacity of photovoltaic power plants, how to betterequipment for grid-connected photovoltaic power plant in the real-time monitoring,operation and maintenance, to ensure the stable operation of high-qualityphotovoltaic power plants has become a hot research. In addition, large-scaleconcentrated photovoltaic grid will have an impact on the power grid. In order toensure the stability of the power system, grid scheduling departments to dispatchinstructions issued under the photovoltaic power plants, photovoltaic power plantsneed to respond to the dispatch order to achieve optimal allocation of the entirephotovoltaic plant active and regulation.In this paper, the design and development of a central monitoring and energymanagement system can be extended set of compatibility and good performance ofgrid-connected photovoltaic power plants to achieve a unified performancemonitoring for grid-connected photovoltaic power station inside the power plantequipment; photovoltaic power plant operating data to be centralized withinmanagement; provide predictive power generation of photovoltaic power plants andother advanced applications reliable data interface; and can automatically receive thenext dispatch center master control instructions issued by the active, automaticcontrol of each grid inverters, photovoltaic power plants to meet the schedulingrequirements based on the full and stable operation.PV power plant output forecasts can provide automatic generation control PVpower plant energy management data support, the paper affect the PV array powergeneration meteorological factors were path analysis, various meteorological factors on photovoltaic power influence weight, custom the similarity statistic. History Dayby Day is similar to classification and prediction samples selected date to the inverterphotovoltaic power plant in the basic prediction unit, BP neural network predictionmodel based on the respective grid PV power plant inverter output power for shortforecasts. And short-term forecasting results in grid-connected inverter output poweris based on studies of the energy management control strategy for active control ofphotovoltaic power plants, and verify the effectiveness and feasibility of the controlstrategy.