%0 Generic %1 felice2018scoping %A Felice, Matteo De %A Soares, Marta Bruno %A Alessandri, Andrea %A Troccoli, Alberto %D 2018 %J EarthArXiv %K MyECEMpaper colleagues ecem energy renewables seasonal solar %R 10.31223/osf.io/vfn35 %T Scoping the potential usefulness of seasonal climate forecasts for solar power management %U https://eartharxiv.org/vfn35/ %X Solar photovoltaic energy is widespread worldwide and particularly in Europe, which became in 2016 the first region in the world to pass the 100 GW of installed capacity. As for all the renewable energy sources, for an intelligent management of solar power, it is essential to have reliable and accurate information about weather/climate conditions that affect the production of electricity. This type of information can include both an estimate of past weather as well as a prediction for the next days and months. Operations in the solar energy industry are normally based on daily (or intra-daily) forecasts. Nevertheless, information about the incoming months can be relevant to support and inform operational and maintenance activities as well as to help secure future power contracts. This need will likely increase in a low-carbon economy, which is one the goals of the European Union. This paper illustrates how the state-of-art seasonal climate forecasts pro- vide a useful prediction for the average PV power production over European regions. The quality of the forecasts is evaluated by exploiting their probabilistic nature. Such assessment provides useful insights on their advantages and limitations of these forecasts. Subsequently we describe how to assess the potential usefulness of seasonal climate forecasts for the solar industry by proposing an approach that takes into account not only their accuracy but also other potentially relevant factors. This novel approach – called index of opportunity – is described and an example is presented for solar power over Europe.

@preprint{felice2018scoping, abstract = {Solar photovoltaic energy is widespread worldwide and particularly in Europe, which became in 2016 the first region in the world to pass the 100 GW of installed capacity. As for all the renewable energy sources, for an intelligent management of solar power, it is essential to have reliable and accurate information about weather/climate conditions that affect the production of electricity. This type of information can include both an estimate of past weather as well as a prediction for the next days and months. Operations in the solar energy industry are normally based on daily (or intra-daily) forecasts. Nevertheless, information about the incoming months can be relevant to support and inform operational and maintenance activities as well as to help secure future power contracts. This need will likely increase in a low-carbon economy, which is one the goals of the European Union. This paper illustrates how the state-of-art seasonal climate forecasts pro- vide a useful prediction for the average PV power production over European regions. The quality of the forecasts is evaluated by exploiting their probabilistic nature. Such assessment provides useful insights on their advantages and limitations of these forecasts. Subsequently we describe how to assess the potential usefulness of seasonal climate forecasts for the solar industry by proposing an approach that takes into account not only their accuracy but also other potentially relevant factors. This novel approach – called index of opportunity – is described and an example is presented for solar power over Europe.}, added-at = {2018-09-05T14:14:41.000+0200}, author = {Felice, Matteo De and Soares, Marta Bruno and Alessandri, Andrea and Troccoli, Alberto}, biburl = {https://www.bibsonomy.org/bibtex/27e6acbaf046f57d2faf999041b4219ae/pbett}, description = {EarthArXiv Preprints | Scoping the potential usefulness of seasonal climate forecasts for solar power management}, doi = {10.31223/osf.io/vfn35}, interhash = {a78bcbf91288b66bf15f0ceedeac152f}, intrahash = {7e6acbaf046f57d2faf999041b4219ae}, journal = {EarthArXiv}, keywords = {MyECEMpaper colleagues ecem energy renewables seasonal solar}, month = sep, timestamp = {2018-10-08T18:25:43.000+0200}, title = {Scoping the potential usefulness of seasonal climate forecasts for solar power management}, url = {https://eartharxiv.org/vfn35/}, year = 2018 }