基于CAR模型的短期光伏发电量预测

Forecasting Short-term Photovoltaic Power Generation on CAR Model Basis

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 oper- ational data of 18 kW grid-connected PV plant in the Power Electronics Research Center of Hua- zhong 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 preci- sion of the prediction is relatively high in a good weather condition.