Site-specific adjustment of a NWP-based photovoltaic production forecast

Abstract

Despite the increased share of photovoltaic (PV) systems, several integration challenges are still present. For small-scale PV, the incentives for monitoring and forecasting the output are generated from the gains of optimizing of local electricity usage. PV output can often be the only measured parameter available from a PV site. Thereby, its efficient utilization in adjusting the PV conversion model is essential. The aim of this study is to develop a straightforward and explicit approach for utilizing PV output data in adjusting a site-specific PV output forecast. A parametric PV output conversion model is utilized as the baseline model for 23 PV sites in Finland, implemented on top of five summer months of day-ahead Numerical Weather Prediction (NWP) forecasts, provided by the MetCoOp system. The proposed approach is validated by comparing the performance of the baseline and adjusted forecasts against actual PV output. The method is shown to provide a solution for adjusting a generic PV output forecast to any specific site, reducing the hourly Mean Absolute Error (MAE) of the aggregated forecast from 0.08 to 0.06 W/Wp, while reducing bias from 0.05 to 0.01 W/Wp, respectively. The adjustment increases modeling accuracy by capturing potential systematic biases of the NWP forecast and site-specific conditions, e.g., variable shadowing and conversion losses, affecting the output of the PV system. Due to the fact that the approach can be implemented both for observations and forecast input data, the method is considered to be a helpful approach for several different PV modeling applications.