Fuzzy Time Series Methods Applied to (In)Direct Short-Term Photovoltaic Power Forecasting

Energies

Joylan Nunes Maciel¹  Jorge Javier Gimenez Ledesma¹  Vanessa María Serrano Ardila¹  Oswaldo Hideo Ando Junior² 

[1] Latin American Institute of Technology, Infrastructure and Territory (ILATIT), Federal University of Latin American Integration (UNILA), Foz do Iguaçu 85867-000, PR, Brazil;Research Group on Energy & Energy Sustainability (GPEnSE), Cabo de Santo Agostinho 54518-430, PE, Brazil;

关键词: fuzzy time series;    photovoltaic energy prediction;    short-term forecasting;   

DOI  :  10.3390/en15030845

来源: DOAJ

【 摘 要 】

Solar photovoltaic energy has experienced significant growth in the last decade, as well as the challenges related to the intermittency of power generation inherent to this process. In this paper we propose to perform short-term forecasting of solar PV generation using fuzzy time series (FTS). Two FTS methods are proposed and evaluated to obtain a global horizontal irradiance (GHI) value. The first is the weighted method and the second is the fuzzy information granular method. Using the direct proportionality of the power with the GHI, the spatial smoothing process was applied, obtaining spatial irradiance on which a first-order low pass filter was applied to simulated power photovoltaic system generation. Thus, this study proposed indirect and direct forecasting of solar photovoltaic generation which was statistically evaluated and the results showed that the indirect prediction showed better performance with GHI than the power simulation. Error statistics, such as RMSE and MBE, show that the fuzzy information granular method performs better than the weighted method in GHI forecasting.

【 授权许可】

Unknown