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Energies 2018, 11(3), 528; https://doi.org/10.3390/en11030528

Ultra-Short-Term Forecast of Photovoltaic Output Power under Fog and Haze Weather

State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources of North China Electric Power University, Baoding 071003, China
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Received: 27 January 2018 / Revised: 18 February 2018 / Accepted: 24 February 2018 / Published: 28 February 2018
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Abstract

Fog and haze (F-H) weather has been occurring frequently in China since 2012, which affects the output power of photovoltaic (PV) generation dramatically by directly weakening solar irradiance and aggravating dust deposition on PV panels. The ultra-short-term forecast method presented in this study would help to fully reflect the dual effects of F-H on PV output power. Aiming at the weakening effect on solar irradiance, estimation models of atmospheric aerosol optical depth (AOD) based on particle matter (PM) concentration were established with machine learning (ML) method, and the total irradiance received by PV panels was calculated based on simplified REST2 model. Aiming at the aggravating effect on dust deposition on PV panels, sample set of “cumulative PM concentration—efficiency reduction” was constructed through special measurement experiments, then the efficiency reduction under certain dust deposition state was estimated with similar-day choosing method. Based on photoelectric conversion model, PM concentration prediction and weather forecast information, ultra-short-term forecast of PV output power was realized. Experimental results proved the validity and feasibility of the presented forecast method. View Full-Text
Keywords: fog and haze; photovoltaic output power; forecast; aerosol optical depth; particle matter concentration; machine learning; efficiency reduction fog and haze; photovoltaic output power; forecast; aerosol optical depth; particle matter concentration; machine learning; efficiency reduction
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Liu, W.; Liu, C.; Lin, Y.; Ma, L.; Xiong, F.; Li, J. Ultra-Short-Term Forecast of Photovoltaic Output Power under Fog and Haze Weather. Energies 2018, 11, 528.

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