Open AccessPortfolio theory applied to solar and wind resources forecast
Author(s) -
Lima Marcello Anderson F.B.,
Carvalho Paulo C.M.,
Carneiro Tatiane C.,
Leite Josileudo R.,
Bessa Neto Luiz J.,
Rodrigues Géssica K.L.,
Melo Francisco E.
Publication year - 2017
Publication title -
iet renewable power generation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.005
H-Index - 76
eISSN - 1752-1424
pISSN - 1752-1416
DOI - 10.1049/iet-rpg.2017.0006
Subject(s) - solar resource , meteorology , renewable energy , predictability , wind power , environmental science , solar irradiance , wind speed , portfolio , environmental economics , business , engineering , geography , mathematics , economics , finance , statistics , electrical engineering
Power generation from decentralised renewable energy (RE) sources has been increasingly used worldwide. The authors apply portfolio theory (PT) to solar and wind resource forecast, combining those two intermittent RE sources in different percentages to investigate the resultant effects on the prediction error with the use of a proposed impact factor. They use solar and wind data from a weather station in Brazil's Northeast region. The use of PT to improve resource forecast of the specific solar and wind conditions found in that Brazilian region is a pioneer project and an original contribution of their research. Traditionally, PT has been used in the finance sector to reduce investment risks by diversifying applications. Considering predictability, the efficient frontier indicates an optimum portfolio for the period under investigation composed by 30% solar and 70% wind resource, obtained by the smallest calculated standard deviation. The obtained average forecast error for wind speed was −1.54% and for solar irradiance was 3.16%; the average forecast error resulting from the integration of 30% solar and 70% wind was −0.13%. This study innovates by using PT to solar and wind forecast in the planning phase, before the installation of wind and solar plants.