基于CAR模型的短期光伏发电量预测

利用灰色关联度分析影响光伏发电量的关键气象环境因子,结合光伏电站历史数据,基于CAR模型建立了短期光伏发电量预测模型.以华中科技大学电力电子研究中心18 kW并网光伏电站资料进行预测试验,并通过调整模型参数获得了适合的模型,结果验证了该方法的有效性.应用结果表明,天气良好时,预测精度较高.;The grey relational analysis is conducted to determine the meteorological environment factors with the highest impact on photovoltaic power generation. Then the key factors to construct a model of forecasting short-term photovoltaic power generation with the multi-variable time series CAR (Controlled Auto-regression) model based on the historical daily data. Finally, the output of photovoltaic power station is predicted. The prediction experiment is conducted based on the operational data of 18 kW grid-connected PV plant in the Power Electronics Research Center of Huazhong University of Science and Technology. An appropriate model is obtained by adjusting model parameters. The experiment results verify the validity of this method, and indicate that the precision of the prediction is relatively high in a good weather condition