Forecasting Uncertainty Intervals for Return Period of Extreme Daily Electricity Consumption
The use of extreme value theory (EVT) is usually aimed at quantifying the asymptotic behaviour of extreme quantiles. The generalised Pareto distribution (GPD) with peaks-over-threshold (POT) approach is applied to bootstrap uncertainty intervals for the return periods of extreme daily electricity c...
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| Format: | Article |
| Language: | English |
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EconJournals
2022-07-01
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| Series: | International Journal of Energy Economics and Policy |
| Subjects: | |
| Online Access: | https://econjournals.com/index.php/ijeep/article/view/12901 |
| _version_ | 1797923869709828096 |
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| author | Katleho Makatjane |
| author_facet | Katleho Makatjane |
| author_sort | Katleho Makatjane |
| collection | DOAJ |
| description |
The use of extreme value theory (EVT) is usually aimed at quantifying the asymptotic behaviour of extreme quantiles. The generalised Pareto distribution (GPD) with peaks-over-threshold (POT) approach is applied to bootstrap uncertainty intervals for the return periods of extreme daily electricity consumption in South Africa. The leeway of extremes on daily electricity consumption studied here is the impetus behind this study. To examine the effect of a time-based and extreme non-stationary trend in a dataset, a non-stationary GPD is cast-off in computing the shape parameter and, this resulted in the establishment of a type III GPD known as a Weibull class for the South African electricity sector. Results of this study revealed a non-stationary trend with a prediction power of 89.6% for the winter season and 85.65% non-winter season. This means that EVT provides a robust basis for statistical modelling of extreme values. Furthermore, a base for future researchers for conducting studies on emerging markets, more specifically in the South African context has also been contributed.
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| first_indexed | 2024-04-10T14:52:55Z |
| format | Article |
| id | doaj.art-03e5327bd11c4879849466eb169ff2c4 |
| institution | Directory Open Access Journal |
| issn | 2146-4553 |
| language | English |
| last_indexed | 2024-04-10T14:52:55Z |
| publishDate | 2022-07-01 |
| publisher | EconJournals |
| record_format | Article |
| series | International Journal of Energy Economics and Policy |
| spelling | doaj.art-03e5327bd11c4879849466eb169ff2c42023-02-15T16:07:30ZengEconJournalsInternational Journal of Energy Economics and Policy2146-45532022-07-0112410.32479/ijeep.12901Forecasting Uncertainty Intervals for Return Period of Extreme Daily Electricity ConsumptionKatleho Makatjane0Department of Statistics, University of Botswana, Gaborone, Botswana. The use of extreme value theory (EVT) is usually aimed at quantifying the asymptotic behaviour of extreme quantiles. The generalised Pareto distribution (GPD) with peaks-over-threshold (POT) approach is applied to bootstrap uncertainty intervals for the return periods of extreme daily electricity consumption in South Africa. The leeway of extremes on daily electricity consumption studied here is the impetus behind this study. To examine the effect of a time-based and extreme non-stationary trend in a dataset, a non-stationary GPD is cast-off in computing the shape parameter and, this resulted in the establishment of a type III GPD known as a Weibull class for the South African electricity sector. Results of this study revealed a non-stationary trend with a prediction power of 89.6% for the winter season and 85.65% non-winter season. This means that EVT provides a robust basis for statistical modelling of extreme values. Furthermore, a base for future researchers for conducting studies on emerging markets, more specifically in the South African context has also been contributed. https://econjournals.com/index.php/ijeep/article/view/12901Bayesian; Extreme Value Theory; Generalised Pareto Distribution; Markov-chain-Monte-Carlo; Peaks-Over-Threshold. |
| spellingShingle | Katleho Makatjane Forecasting Uncertainty Intervals for Return Period of Extreme Daily Electricity Consumption International Journal of Energy Economics and Policy Bayesian; Extreme Value Theory; Generalised Pareto Distribution; Markov-chain-Monte-Carlo; Peaks-Over-Threshold. |
| title | Forecasting Uncertainty Intervals for Return Period of Extreme Daily Electricity Consumption |
| title_full | Forecasting Uncertainty Intervals for Return Period of Extreme Daily Electricity Consumption |
| title_fullStr | Forecasting Uncertainty Intervals for Return Period of Extreme Daily Electricity Consumption |
| title_full_unstemmed | Forecasting Uncertainty Intervals for Return Period of Extreme Daily Electricity Consumption |
| title_short | Forecasting Uncertainty Intervals for Return Period of Extreme Daily Electricity Consumption |
| title_sort | forecasting uncertainty intervals for return period of extreme daily electricity consumption |
| topic | Bayesian; Extreme Value Theory; Generalised Pareto Distribution; Markov-chain-Monte-Carlo; Peaks-Over-Threshold. |
| url | https://econjournals.com/index.php/ijeep/article/view/12901 |
| work_keys_str_mv | AT katlehomakatjane forecastinguncertaintyintervalsforreturnperiodofextremedailyelectricityconsumption |