Power Generation Forecast of Hybrid PV-Wind System

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Sanjari, Mohammad Javad
Gooi, Hoay Beng
Nair, Nirmal-Kumar C
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2020
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Abstract

Due to their intermittency and unpredictability, increasing the penetration level of renewable energy (RE) resources to the power system leads to difficulties in operation. Reliable system operation requires a precise forecast of generated power by RE units. Photovoltaic (PV) and wind units are the significant portion of RE resources integrated into the power system. This paper proposes a forecast method for PV and wind generated power to achieve good prediction accuracy in different weather conditions. Not only is the relation between the wind and PV output power modeled, but the heat index (HI) is also taken into consideration as a useful meteorological variable to achieve the 15-min ahead precise expectation of PV/wind output power. Moreover, the input data is discretized in such a way that the best accuracy for the PV and wind power forecast is achieved. Comparing the results of the proposed method with the historical data recorded at actual PV and wind plants shows that the proposed forecast method results in high accuracy in PV and wind output power forecast. Moreover, the forecast model performance with HI consideration is compared with the model not using HI as an input variable.

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IEEE Transactions on Sustainable Energy

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© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

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This publication has been entered into Griffith Research Online as an Advanced Online Version.

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Electrical engineering

Electronics, sensors and digital hardware

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Sanjari, MJ; Gooi, HB; Nair, N, Power Generation Forecast of Hybrid PV-Wind System, IEEE Transactions on Sustainable Energy, 2019

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