Wind speed forecasting in Nepal using self-organizing map-based online sequential extreme learning machine

Sharma, Neelesh and Deo, Ravinesh ORCID: https://orcid.org/0000-0002-2290-6749 (2021) Wind speed forecasting in Nepal using self-organizing map-based online sequential extreme learning machine. In: Predictive modelling for energy management and power systems engineering. Elsevier, Amsterdam, Netherlands, pp. 437-484. ISBN 978-0-12-817772-3


Abstract

Renewable energy is often depicted as a clean source of energy and could have an effect in minimizing environmental impacts by reducing global warming and mitigating the greenhouse effect (Panwar et al., 2011; Wang and Han, 2014). A transition from fossil fuels to renewable sources has been growing in the past 30 years since the price of oil seems to increase constantly and, in contrast, there is a decline in the cost of renewable sources of energy (Herzog et al., 2018). Renewable energy was first adopted by most countries as an integral aspect of national energy policy goals after the 1973 oil crisis (Nepal, 2012). It also ignited interest in wind energy, water pumps, power supply in remote areas, and production of grid electricity powered by wind (Herzog et al., 2018).

Among other renewable sources, wind energy has become a major attraction in today’s world because of its low pollution emissions and high efficiency (Wu and Hong, 2007). Wind energy is accepted globally as a clean energy ource and the cheapest replacement to coal (Nepal, 2012; Herzog et al., 2018). A 24% average annual growth in wind energy production across the world has been observed since 1990. Based on the trending decline in cost, analysts had forecasted that by the end of 2015 the electricity production cost of wind reached 2.5 US cents/KWh; lower than most fossils fuels (Herzog et al., 2018). According to a Greenpeace organization plan, by 2020 12% of all electricity production should be achieved from wind energy (Wang et al., 2011).

Nepal, the focus of this chapter, is one of the developing countries that has been in the dark ages of the electricity crisis, with persistent power cuts since 2006 (Laudari, 2016). At present, hydroelectricity is the main source of grid electricity in Nepal, and only 56% of households in Nepal have access to the grid. Fig. 14.1 shows the power supply and demand for electricity from the year 2009 to 2018. It is observed that both supply and demand is increasing constantly throughout the year, however, the supply of power has not met its demand. According to Solar and Wind Energy Resource Assessment (SWERA), Nepal has the potential to generate 2100 MW electricity from solar, 50 MW from microhydro, and 3000 MW from wind (SWERA, 2006; Gurung et al., 2013). Thus wind energy seems to be a viable solution as an alternative source to overcome the yearly drought of electricity in Nepal.


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Item Type: Book Chapter (Commonwealth Reporting Category B)
Refereed: Yes
Item Status: Live Archive
Additional Information: Permanent restricted access to Published version + Front Matter in accordance with the copyright policy of the publisher.
Faculty/School / Institute/Centre: Current - Faculty of Health, Engineering and Sciences - School of Sciences (6 Sep 2019 -)
Faculty/School / Institute/Centre: Current - Faculty of Health, Engineering and Sciences - School of Sciences (6 Sep 2019 -)
Date Deposited: 06 Oct 2020 03:13
Last Modified: 06 Oct 2020 06:14
Uncontrolled Keywords: renewable energy; wind energy; Nepal
Fields of Research (2008): 05 Environmental Sciences > 0599 Other Environmental Sciences > 059999 Environmental Sciences not elsewhere classified
08 Information and Computing Sciences > 0801 Artificial Intelligence and Image Processing > 080108 Neural, Evolutionary and Fuzzy Computation
Fields of Research (2020): 41 ENVIRONMENTAL SCIENCES > 4199 Other environmental sciences > 419999 Other environmental sciences not elsewhere classified
46 INFORMATION AND COMPUTING SCIENCES > 4699 Other information and computing sciences > 469999 Other information and computing sciences not elsewhere classified
Socio-Economic Objectives (2008): E Expanding Knowledge > 97 Expanding Knowledge > 970108 Expanding Knowledge in the Information and Computing Sciences
URI: http://eprints.usq.edu.au/id/eprint/39839

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