The development of methods to forecast photovoltaic (PV) power generation regionally is of utmost importance to support the spread of such power systems in current power grids. The objective of this study is to propose and to evaluate methods to forecast regional PV power 1 day ahead of time and to compare their performances. Four forecast methods were regarded, of which two are new ones proposed in this study. Together, they characterize a set of forecast methods that can be applied in different scenarios regarding availability of data and infrastructure to make the forecasts. The forecast methods were based on the use of support vector regression and weather prediction data. Evaluations were performed for 1 year of hourly forecasts using data of 273 PV systems installed in two adjacent regions in Japan, Kanto, and Chubu. The results show the importance of selecting the proper forecast method regarding the region characteristics. For Chubu, the region with a variety of weather conditions, the forecast methods based on single systems' forecasts and the one based on stratified sampling provided the best results. In this case, the best annual normalized root mean square error (RMSE) and mean absolute error (MAE) were 0.25 and 0.15 kWh/kWh avg , respectively. For Kanto, with homogeneous weather conditions, the four methods performed similarly. In this case, the lowest annual forecast errors were 0.33 kWh/kWh avg for the normalized RMSE and 0.202 kWh/kWh avg for the normalized MAE. Copyright © 2014 John Wiley & Sons, Ltd. Main findings: 1 Method 1, based on single‐system information, yielded the lowest forecast errors in all regions. 2 Method 2, based on stratified sampling with weight correction for the rated power, presented a forecast error accuracy close to the that of method 1, being a good alternative to it. 3 The lowest annual forecast mean absolute errors, normalized by the average annual photovoltaic power generation found for Chubu and Kanto, were 0.156 and 0.202 kWh/kWh avg , respectively.


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    Title :

    Regional forecasts of photovoltaic power generation according to different data availability scenarios: a study of four methods



    Published in:

    Publication date :

    2015




    Type of media :

    Article (Journal)


    Type of material :

    Print


    Language :

    English



    Classification :

    BKL:    53.36 Energiedirektumwandler, elektrische Energiespeicher



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