A Weibull and finite mixture of the von Mises distribution for wind analysis in Mersing, Malaysia

Sanusi, Nortazi; Zaharim, Azami; Mat, Sohif; Sopian, Kamaruzzaman

doi:10.1080/15435075.2017.1357124

Cited by 6 publications

(5 citation statements)

References 8 publications

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“…Therefore, it must be identified for all utilized data. Numerous studies in Thailand [13], Yemen [14], Bangladesh [5], Senegal [7] and Malaysia [15] determined that the Weibull distribution best matched their data. Thus, researchers typically employed the Weibull distribution as a standard [16], [17].…”

Section: Introductionmentioning

confidence: 99%

Distribution cycle of wind speed: A case study in the Southern Part of Malaysia

Derome

Razali²,

Fazlizan³

et al. 2023

IOP Conf. Ser.: Mater. Sci. Eng.

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Wind energy has historically helped many people and has been utilized for farming and seafaring. Today, modern usage is more comprehensive such as generating electricity. However, its usage in Malaysia remains at an all-time low. Numerous factors contribute to this result. Consequently, a full assessment of wind energy in a particular region is deemed necessary. This study investigates wind speed distribution in Mersing. It also illustrates the period during which the regional distribution statistics changed. The researcher used Autofit 5.6 and the Maximum Likelihood Method to figure out the parameter value of each distribution for wind speed data from 2012 to 2016. This study utilized three distinct methods of Goodness of fit (GOF) to estimate the optimal distribution ranking, such as Chi-Square, Anderson-Darling, and Kolmogorov-Smirnov. The results reveal that the Burr, Gamma, and Lognormal distributions correlate to the wind speed data in Mersing and the Burr distribution is the most appropriate. In addition, the findings indicate that distribution changes occur at a minimum rate of 8.89%. In conclusion, these findings reveal that there has been no significant change over the five years. This information enables stakeholders to determine whether they will earn a profit owing to changes in the distribution of a particular area, reducing risk.

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Section: Introductionmentioning

confidence: 99%

Distribution cycle of wind speed: A case study in the Southern Part of Malaysia

Derome

Razali²,

Fazlizan³

et al. 2023

IOP Conf. Ser.: Mater. Sci. Eng.

View full text Add to dashboard Cite

show abstract

“…In addition, the area, which is situated opposite the South China Sea, experiences a great deal of wind throughout the year. Thus, Mersing is affected by both the sea breeze, the land breeze, and the monsoon seasons [50]. In addition, Mersing was chosen based on 100 per cent of the sources that can be used for analysis purposes.…”

Section: Site Description and Data Collectionmentioning

confidence: 99%

Forecasting Weibull Parameters With a Novel Alternative Graphical Technique for Low Wind Speeds

et al. 2022

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This paper analyses wind speed estimation for Weibull distribution using various methods. According to a previous study, the existing methods primarily target areas with moderate to high-velocity rates, and Malaysia is a tropical country with pleasant breezes all year. As a result, this research aims to devise the most efficient method of forecasting wind speeds in low-speed areas. The researcher compared existing methods such as the Moment of Method, Empirical Method, Graphical Method, Maximum Likelihood Method and the newly proposed Alternative Graphical method. The finding indicates that the novel proposed approach, the Alternative Graphical Method, is superior regarding Goodness of Fit, Kolmogorov Smirnov and Chi-Square. For Kolmogorov Smirnov, the Alternative Graphical Method is 3.4 % better than the second-best method. At the same time, the usage of Chi-Square is again at a top position, with a 61 % disparity between it and the second and third best places. However, the Alternative Graphical Method is in second place for Anderson Darling, but the forecast performance with a minimum difference of 0.3 %. These findings imply that the Alternative Graphical Method capable of making more precise predictions than current methods.

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“…The study concluded that the combination of Gama and a finite mixture of vM distributions is the perfect bivariate model regarding the clarification of wind data of Kuala Terengganu. Accordingly, Sanusi et al [28] investigated the effects of wind direction on producing wind energy in Mersing. The mvMF and Weibull distributions were applied for modeling wind speed and wind direction and speed data respectively.…”

Section: A Wind Directionmentioning

confidence: 99%

“…Saberi et al [65] used the Weibull distribution model to assess the quality of wind data that were collected in 2017 in Kuala Terengganu. Likewise, the Weibull distribution model has been extensively used as a method for determining the potentiality of wind energy as shown in Table 2 such as [28,41,63,68,69,81]. In most of these studies, the use of the Malaysia Meteorological Department (MMD) wind data was found to be dominant.…”

Section: B Wind Speed Distribution Modelsmentioning

confidence: 99%

Comprehensive Review of Wind Energy in Malaysia: Past, Present, and Future Research Trends

et al. 2020

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In recent years, wind energy has gained extensive attention in the recent years in various countries due to the high energy demand of energy and shortage of traditional electric energy sources. Because wind energy constitutes a cost effective and environmentally friendly source, it can significantly contribute toward the reduction of the ever-increasing carbon emissions. It is one of the fastest growing green technologies worldwide, with a total generation share of 564 GW as of the end of 2018. In Malaysia, wind energy has been a hot topic in both academia and green energy industry. In this paper, the current status of wind energy research in Malaysia is reviewed. Different contributing factors such as potentiality and assessments, wind speed and direction modeling, wind prediction and spatial mapping, and optimal sizing of wind farms are extensively discussed. This paper discusses the progress of all studies related to wind energy and presents conclusions and recommendations for improving wind energy research in Malaysia.

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A Weibull and finite mixture of the von Mises distribution for wind analysis in Mersing, Malaysia

Cited by 6 publications

References 8 publications

Distribution cycle of wind speed: A case study in the Southern Part of Malaysia

Distribution cycle of wind speed: A case study in the Southern Part of Malaysia

Forecasting Weibull Parameters With a Novel Alternative Graphical Technique for Low Wind Speeds

Comprehensive Review of Wind Energy in Malaysia: Past, Present, and Future Research Trends

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