The authors developed a forecasting model for Luxembourg, able to predict the expected regional PV power up to 72 hours ahead. The model works with solar irradiance forecasts, based on numerical weather predictions in hourly resolution. Using a set of physical equations, the algorithm is able to predict the expected hourly power production for PV systems in Luxembourg, as well as for a set of 23 chosen PV-systems which are used as reference systems. Comparing the calculated forecasts for the 23 reference systems to their measured power over a period of 2 years, revealed a comparably high accuracy of the forecast. The mean deviation (bias) of the forecast was 1.1% of the nominal power – a relatively low bias indicating low systemic error. The root mean square error (RMSE), lies around 7.4% – a low value for single site forecasts. Two approaches were tested in order to adapt the short-term forecast, based on the present forecast deviations for the reference systems. Thereby, it was possible to improve the very short term forecast on the time horizon of 1-3 hours ahead, specifically for the remaining bias, but also systemic deviations can be identified and partially corrected (e.g. snow cover).

Introduction

The share of decentralized and fluctuating energy sources, such as wind power and photovoltaic (PV), is constantly increasing and will represent a major part of the future energy mix. The reliable management of our electricity supply and grids as well as the containment of increasing price volatility on the electricity market, will depend on the ability to handle these fluctuating renewable sources. The forecasting of the dynamics of PV power production is therefore crucial for the integration of high shares of photovoltaic into our energy system and market. The different stakeholders involved in the electricity supply and operation of the grids, have their specific needs for load and production forecasting and these needs are changing with the rising shares of fluctuating, distributed generation. Electricity retailers require accurate day-ahead forecasts of PV systems (hourly resolution; updated once or twice a day) for their energy procurement and sales forecast. Since many small scale PV system feed in behind the meter of their customers, they reduce their demand and need to be considered in load forecasting. But also the utility scale PV systems have increased their share in the production portfolios and force the providers to account for them accurately in their production forecasts. The inaccuracies in day-ahead forecasts for production and demand need to be balanced out on the intra-day level, by procurement, respectively sales on the spot market. Hence, forecasting on intra-day (down to 5 minutes resolution and hourly updates) and day-ahead level is of high economic importance for energy retailers. 38 [1] [2]