Univariate modeling and forecasting of energy consumption
In Lebanon, electric power is becoming the main energy form relied upon in all economic sectors of the country. Also, the time series of electrical energy consumption in Lebanon is unique due to intermittent power outages and increasing demand. Given these facts, it is critical to model and forecast...
محفوظ في:
| المؤلف الرئيسي: | |
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| مؤلفون آخرون: | , |
| التنسيق: | article |
| منشور في: |
2001
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| الوصول للمادة أونلاين: | http://hdl.handle.net/10725/3161 http://dx.doi.org/10.1016/S0360-5442(00)00049-9 http://www.sciencedirect.com/science/article/pii/S0360544200000499 |
| الوسوم: |
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| _version_ | 1864513460170129408 |
|---|---|
| author | Saab, Samer |
| author2 | Badr, Elie Nasr, George |
| author2_role | author author |
| author_facet | Saab, Samer Badr, Elie Nasr, George |
| author_role | author |
| dc.creator.none.fl_str_mv | Saab, Samer Badr, Elie Nasr, George |
| dc.date.none.fl_str_mv | 2001 2016-02-23T08:36:29Z 2016-02-23T08:36:29Z 2016-02-23 |
| dc.identifier.none.fl_str_mv | 0360-5442 http://hdl.handle.net/10725/3161 http://dx.doi.org/10.1016/S0360-5442(00)00049-9 Saab, S., Badr, E., & Nasr, G. (2001). Univariate modeling and forecasting of energy consumption: the case of electricity in Lebanon. Energy, 26(1), 1-14. http://www.sciencedirect.com/science/article/pii/S0360544200000499 |
| dc.language.none.fl_str_mv | en |
| dc.relation.none.fl_str_mv | Energy |
| dc.rights.*.fl_str_mv | info:eu-repo/semantics/openAccess |
| dc.title.none.fl_str_mv | Univariate modeling and forecasting of energy consumption the case of electricity in Lebanon |
| dc.type.none.fl_str_mv | Article info:eu-repo/semantics/publishedVersion info:eu-repo/semantics/article |
| description | In Lebanon, electric power is becoming the main energy form relied upon in all economic sectors of the country. Also, the time series of electrical energy consumption in Lebanon is unique due to intermittent power outages and increasing demand. Given these facts, it is critical to model and forecast electrical energy consumption. The aim of this study is to investigate different univariate-modeling methodologies and try, at least, a one-step ahead forecast for monthly electric energy consumption in Lebanon. Three univariate models are used, namely, the autoregressive, the autoregressive integrated moving average (ARIMA) and a novel configuration combining an AR(1) with a highpass filter. The forecasting performance of each model is assessed using different measures. The AR(1)/highpass filter model yields the best forecast for this peculiar energy data. |
| eu_rights_str_mv | openAccess |
| format | article |
| id | LAURepo_2a35e33fab543b7979ad15cde7bdaa4f |
| identifier_str_mv | 0360-5442 Saab, S., Badr, E., & Nasr, G. (2001). Univariate modeling and forecasting of energy consumption: the case of electricity in Lebanon. Energy, 26(1), 1-14. |
| language_invalid_str_mv | en |
| network_acronym_str | LAURepo |
| network_name_str | Lebanese American University repository |
| oai_identifier_str | oai:laur.lau.edu.lb:10725/3161 |
| publishDate | 2001 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| spelling | Univariate modeling and forecasting of energy consumptionthe case of electricity in LebanonSaab, SamerBadr, ElieNasr, GeorgeIn Lebanon, electric power is becoming the main energy form relied upon in all economic sectors of the country. Also, the time series of electrical energy consumption in Lebanon is unique due to intermittent power outages and increasing demand. Given these facts, it is critical to model and forecast electrical energy consumption. The aim of this study is to investigate different univariate-modeling methodologies and try, at least, a one-step ahead forecast for monthly electric energy consumption in Lebanon. Three univariate models are used, namely, the autoregressive, the autoregressive integrated moving average (ARIMA) and a novel configuration combining an AR(1) with a highpass filter. The forecasting performance of each model is assessed using different measures. The AR(1)/highpass filter model yields the best forecast for this peculiar energy data.PublishedN/A2016-02-23T08:36:29Z2016-02-23T08:36:29Z20012016-02-23Articleinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article0360-5442http://hdl.handle.net/10725/3161http://dx.doi.org/10.1016/S0360-5442(00)00049-9Saab, S., Badr, E., & Nasr, G. (2001). Univariate modeling and forecasting of energy consumption: the case of electricity in Lebanon. Energy, 26(1), 1-14.http://www.sciencedirect.com/science/article/pii/S0360544200000499enEnergyinfo:eu-repo/semantics/openAccessoai:laur.lau.edu.lb:10725/31612019-07-25T10:15:17Z |
| spellingShingle | Univariate modeling and forecasting of energy consumption Saab, Samer |
| status_str | publishedVersion |
| title | Univariate modeling and forecasting of energy consumption |
| title_full | Univariate modeling and forecasting of energy consumption |
| title_fullStr | Univariate modeling and forecasting of energy consumption |
| title_full_unstemmed | Univariate modeling and forecasting of energy consumption |
| title_short | Univariate modeling and forecasting of energy consumption |
| title_sort | Univariate modeling and forecasting of energy consumption |
| url | http://hdl.handle.net/10725/3161 http://dx.doi.org/10.1016/S0360-5442(00)00049-9 http://www.sciencedirect.com/science/article/pii/S0360544200000499 |