Journal
APPLIED ENERGY
Volume 206, Issue -, Pages 1464-1483Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.apenergy.2017.09.115
Keywords
Solar forecasting; Intra-hour; Sensor network; Time lag correlation; Irradiance variability
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Funding
- Netherlands Enterprise Agency (RVO) [TKISG02017]
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Solar forecasting is a necessary component of economical realitation of high penetration levels of photovoltaic (PV) systems. This paper presents a short term, intra-hour solar forecasting method. This peer-to-peer (P2P) forecasting method is based on the cross-correlation time lag between clear-sky index time series of pairs of PV systems that are influenced by the (assumed) same cloud sequentially, with the feature that the forecast horizon (FH) can be set at a fixed value. The P2P forecasting algorithm was evaluated for 11 central PV-systems (out of 202) over a half year period from the 1st of March through the 31st of August 2015 using the forecast skill (FS) metric. Positive FS means improvement over reference clear-sky index persistence forecasting. The P2P forecasting method was evaluated over a subset of days with either high, all or low irradiance variability. The average forecast skill (avgFS) concerning forecast horizons between 5 and 8 min. was 5.99%, -1.61% and -16.0% over these periods respectively, indicating the superior performance of the P2P method over persistence during the highly variable days, which are most interesting from the perspective of electricity grid management.
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