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Wind Generation Forecasting Methods and Proliferation of Artificial Neural sustainability Review Wind Generation Forecasting Methods and Proliferation of Artificial Neural Network: A Review of Five Years Research Trend Muhammad Shahzad Nazir 1,* , Fahad Alturise 2 , Sami Alshmrany 3, Hafiz. M. J Nazir 4, Muhammad Bilal 5 , Ahmad N. Abdalla 6, P. Sanjeevikumar 7 and Ziad M. Ali 8,9 1 Faculty of Automation, Huaiyin Institute of Technology, Huai’an 223003, China 2 Computer Department, College of Science and Arts in Ar Rass, Qassim University, Ar Rass 51921, Saudi Arabia; [email protected] 3 Faculty of Computer and Information Systems, Islamic University of Madinah, Madinah 42351, Saudi Arabia; [email protected] 4 Institute of Advance Space Research Technology, School of Networking, Guangzhou University, Guangzhou 510006, China; [email protected] 5 School of Life Science and Food Engineering, Huaiyin Institute of Technology, Huai’an 223003, China; [email protected] 6 Faculty of Information and Communication Engineering, Huaiyin Institute of Technology, Huai’an 223003, China; [email protected] 7 Department of Energy Technology, Aalborg University, 6700 Esbjerg, Denmark; [email protected] 8 College of Engineering at Wadi Addawaser, Prince Sattam Bin Abdulaziz University, Wadi Addawaser 11991, Saudi Arabia; [email protected] 9 Electrical Engineering Department, Faculty of Engineering, Aswan University, Aswan 81542, Egypt * Correspondence: [email protected] or [email protected]; Tel.: +86-1322-271-7968 Received: 8 April 2020; Accepted: 23 April 2020; Published: 6 May 2020 Abstract: To sustain a clean environment by reducing fossil fuels-based energies and increasing the integration of renewable-based energy sources, i.e., wind and solar power, have become the national policy for many countries. The increasing demand for renewable energy sources, such as wind, has created interest in the economic and technical issues related to the integration into the power grids. Having an intermittent nature and wind generation forecasting is a crucial aspect of ensuring the optimum grid control and design in power plants. Accurate forecasting provides essential information to empower grid operators and system designers in generating an optimal wind power plant, and to balance the power supply and demand. In this paper, we present an extensive review of wind forecasting methods and the artificial neural network (ANN) prolific in this regard. The instrument used to measure wind assimilation is analyzed and discussed, accurately, in studies that were published from May 1st, 2014 to May 1st, 2018. The results of the review demonstrate the increased application of ANN into wind power generation forecasting. Considering the component limitation of other systems, the trend of deploying the ANN and its hybrid systems are more attractive than other individual methods. The review further revealed that high forecasting accuracy could be achieved through proper handling and calibration of the wind-forecasting instrument and method. Keywords: environment; sustainability; quality of life; forecasting; instrument; ANN; wind energy 1. Introduction The advancement of civilizations, and their capability to withstand bulk populations, are similar challenges to changes in the volume and nature of energy available to meet the demand for nourishment, quality of life and to complete tasks [1–3]. Lower access to energy is an undesirable impact of poverty Sustainability 2020, 12, 3778; doi:10.3390/su12093778 www.mdpi.com/journal/sustainability SustainabilityTheThe advancementadvancement2020, 12, 3778 ofof civilizations,civilizations, andand theirtheir capabicapabilitylity toto withstandwithstand bulkbulk populations,populations, areare similarsimilar2 of 27 challengeschallenges toto changeschanges inin thethe volumevolume andand naturenature ofof energyenergy availableavailable toto meetmeet thethe demanddemand forfor nourishment,nourishment, qualityquality ofof lifelife andand toto completecomplete tasktaskss [1–3].[1–3]. LowerLower accessaccess toto energyenergy isis anan undesirableundesirable impactimpactand the ofof most povertypoverty probable andand thethe cause mostmost of probable inferiorprobable e causefficauseciency ofof inferior andinferior a human’s efficiencyefficiency quality andand aa of human’shuman’s life. Indeed, qualityquality energy ofof life.life. is Indeed,Indeed,fundamental energyenergy to isis providing fundamentalfundamental suffi tocientto providingproviding services sufficiesufficie such asntnt food, servicesservices primary suchsuch as healthcare,as food,food, primaryprimary water, healthcare,healthcare, education, water,water,communication, education,education, and communication,communication, reasonable employment. andand reasonablereasonable The employment.employment. majority of electricity TheThe majoritymajority used ofof by electricityelectricity our societies usedused hasbyby ourourbeen societiessocieties generated hashas from beenbeen fossil generatedgenerated and nuclear fromfrom fossilfossil fuels, andand which nuclnucl areearear today fuels,fuels, facing whichwhich severe areare todaytoday issues, facingfacing such severe assevere diminished issues,issues, suchsuchsupply asas diminished anddiminished security, supplysupply financial andand a ff security,security,ordability, financialfinancial ecological affoaffo sustainabilityrdability,rdability, ecologicalecological and disaster susustainabilitystainability hazards andand [4,5 ].disasterdisaster For fix hazardshazardsthese undesirable [4,5].[4,5]. ForFor issues, fixfix thesethese many undesirableundesirable countries are issues,issues, enacting manymany sustainable countriescountries energy areare enacting policiesenacting to sustainablesustainable focus on increasing, energyenergy policiespoliciesintegrating toto focusfocus and on developingon increasing,increasing, renewable integratingintegrating energy andand developing technologies.developing renewablerenewable Resources energyenergy are increasing technologies.technologies. significantly ResourcesResources in arearethe increasing energyincreasing mix significantlysignificantly around the globeinin thethe [ 4energyenergy,6]. Among mixmix arar renewableoundound thethe energy globeglobe [4,6]. resources,[4,6]. AmongAmong the renewablerenewable wind is one energyenergy of the resources,resources,oldest renewable thethe windwind sources isis oneone used ofof thethe for oldestoldest power renewarenewa generationbleble sourcessources worldwide. usedused Globalforfor powerpower wind generationgeneration power generation worldwide.worldwide. has GlobalGlobalreached windwind about powerpower 20% annually generationgeneration within hashas the reachedreached past decade. aboutabout Figure20%20% annuallyannually1 depicts withinwithin the annual thethe past additionpast decade.decade. and previousFigureFigure 11 depictsdepictsyear’s capacity thethe annualannual atlas additionaddition of wind andand power previousprevious (2014–2018), year’syear’s while capacitycapacity the atlas worldatlas ofof top windwind 10 countries powerpower (2014–2018),(2014–2018), wind energy whilewhile capacity thethe worldworldis presented toptop 1010 incountriescountries Figure2 wind[wind7]. energyenergy capacitycapacity isis presentedpresented inin FigureFigure 22 [7].[7]. FigureFigure 1.1. TheTheThe worldworld world annualannual annual additionaddition addition andand and previousprevious previous year’syear’s capacitycapacity capacity atlasatlas atlas ofof of windwind wind powerpower (2014–2018).(2014–2018). FigureFigureFigure 2.2. TheTheThe worldworld world toptop top 1010 10 countriescountries countries atlasatlas atlas ofof of instinst installedalledalled windwind powerpower capacitycapacity inin 20182018 [7].[7]. [7]. SustainabilitySustainabilityWind 20202020 energy,, 1212,, x;x; has doi:doi: become FORFOR PEERPEER an REVIEWREVIEW essential source of energy worldwide,www.www. andmdpi.com/journal inmdpi.com/journal 2018, the global/sustainability/sustainability capacity reached 600 GW, so the construction of a new generation of wind energy varies from year to year and by region. For example, in Europe, wind power capacity has decreased by 32% in 2018, compared to Sustainability 2020, 12, 3778 3 of 27 2017. The countries with the largest wind capacity are China, the United States, the United Kingdom, Germany, Canada, Italy, France, India, and Brazil [7]. China’s installed capacity is 221 GW, and is the world leader in wind energy, producing more than a third of the world’s capacity. The province of Gansu has the largest onshore wind farm in the world, and currently has an output of 7965 MW: five times more than its closest rival. The farm currently operates at only 40% of its capacity, and a total of 120,000 MW can be installed by 2020 to achieve a total capacity of 20,000 MW (20 GW), which is expected to cost USD 17.5 billion. Despite their size, Gansu turbines appear to be “scarecrow inactive”, due to lower demand [8,9]. The USA occupies second place, with 96.4 GW installed capacity, and is particularly resistant to onshore wind energy. Six of the ten largest onshore wind farms are located in the United States. These include the Alta Wind Energy Center in California, the second-largest onshore wind farm in the world with an output of 1548 MW, Shepherd’s Flat wind farm in Oregon (845 MW), and the Roscoe wind farm in Texas (781 MW). Texas alone produces 24.9 GW of American wind power, delivering more wind power than the other 25 countries. Germany has the highest installed wind power in Europe with 59.3 GW. The
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