Portfolio theory applied to solar and wind resources forecast

• Published in: IET renewable power generation 2017-06, Vol.11 (7), p.973-978
• Main Authors: Lima, Marcello Anderson F.B, Carvalho, Paulo C.M, Carneiro, Tatiane C, Leite, Josileudo R, Bessa Neto, Luiz J. de, Rodrigues, Géssica K.L, Melo, Francisco E. de
• Format: Article
• Language: English
• Subjects: Brazilian region; forecast error; portfolio theory; Research Article; solar irradiance; solar plants; solar power stations; solar resources forecast; wind conditions; wind plants; wind power plants; wind resources forecast; wind speed
• ISSN: 1752-1416; 1752-1424; 1752-1424
• DOI: 10.1049/iet-rpg.2017.0006

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.