An artificial neural network to assess the impact of neighbouring photovoltaic systems in power forecasting in Utrecht, the Netherlands
Renewable Energy(2016)
摘要
In order to perform predictions of a photovoltaic (PV) system power production, a neural network architecture system using the Nonlinear Autoregressive with eXogenous inputs (NARX) model is implemented using not only local meteorological data but also measurements of neighbouring PV systems as inputs. Input configurations are compared to assess the effects of the different inputs. The added value of the information of the neighbouring PV systems has demonstrated to further improve the accuracy of predictions for both winter and summer seasons. Additionally, forecasts up to 1 month are tested and compared with a persistence model. Normalized root mean square errors (nRMSE) ranged between 9% and 25%, with the NARX model clearly outperforming the persistence model for forecast horizons greater than 15 min.
更多查看译文
关键词
Photovoltaics,Artificial neural network,NARX model,Time series,Forecasting
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要