A new method based on Type-2 fuzzy neural network for accurate wind power forecasting under uncertain data

Amir Sharifian, M. Jabbari Ghadi, Sahand Ghavidel, Li Li and Jiangfeng Zhang

Renewable Energy, 2018, vol. 120, issue C, 220-230

Abstract: Nowadays, due to some environmental restrictions and decrease of fossil fuel sources, renewable energy sources and specifically wind power plants have a major part of energy generation in the industrial countries. To this end, the accurate forecasting of wind power is considered as an important and influential factor for the management and planning of power systems.

Keywords: Type-2 fuzzy neural network; PSO algorithm; Medium-term and long-term wind power forecasting; Uncertain information (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (22)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:120:y:2018:i:c:p:220-230

DOI: 10.1016/j.renene.2017.12.023

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