Parabolic modeling forecasts of space and time european hydropower production
| dc.authorid | 0000-0002-8072-031X | |
| dc.contributor.author | Lincaru, Cristina | |
| dc.contributor.author | Grigorescu, Adriana | |
| dc.contributor.author | Dinçer, Hasan | |
| dc.date.accessioned | 2024-07-09T08:08:16Z | |
| dc.date.available | 2024-07-09T08:08:16Z | |
| dc.date.issued | 2024 | |
| dc.department | İstanbul Medipol Üniversitesi, İşletme ve Yönetim Bilimleri Fakültesi, Bankacılık ve Sigortacılık Bölümü | |
| dc.department | İstanbul Medipol Üniversitesi, İşletme ve Yönetim Bilimleri Fakültesi, Uluslararası Ticaret ve Finansman Bölümü | |
| dc.description.abstract | Renewable sources of energy production are some of the main targets today to protect the environment through reduced fossil fuel consumption and CO2 emissions. Alongside wind, solar, marine, biomass and nuclear sources, hydropower is among the oldest but still not fully explored renewable energy sources. Compared with other sources like wind and solar, hydropower is more stable and consistent, offering increased predictability. Even so, it should be analyzed considering water flow, dams capacity, climate change, irrigation, navigation, and so on. The aim of this study is to propose a forecast model of hydropower production capacity and identify long-term trends. The curve fit forecast parabolic model was applied to 33 European countries for time series data from 1990 to 2021. Space-time cube ArcGIS representation in 2D and 3D offers visualization of the prediction and model confidence rate. The quadratic trajectory fit the raw data for 14 countries, validated by visual check, and in 20 countries, validated by FMRSE 10% threshold from the maximal value. The quadratic model choice is good for forecasting future values of hydropower electric capacity in 22 countries, with accuracy confirmed by the VMRSE 10% threshold from the maximal value. Seven local outliers were identified, with only one validated as a global outlier based on the Generalized Extreme Studentized Deviate (GESD) test at a 5% maximal number of outliers and a 90% confidence level. This result achieves our objective of estimating a level with a high degree of occurrence and offering a reliable forecast of hydropower production capacity. All European countries show a growing trend in the short term, but the trends show a stagnation or decrease if policies do not consider intensive growth through new technology integration and digital adoption. Unfortunately, Europe does not have extensive growth potential compared with Asia–Pacific. Public policies must boost hybrid hydro–wind or hydro–solar systems and intensive technical solutions. | |
| dc.description.sponsorship | Romanian Ministry of Research, Innovation, and Digitalization, Programme NUCLEU, 2022-2026 | en_US |
| dc.identifier.citation | Lincaru, C., Grigorescu, A. ve Dinçer, H. (2024). Parabolic modeling forecasts of space and time european hydropower production. Processes, 12(6). http://dx.doi.org/10.3390/pr12061098 | |
| dc.identifier.doi | 10.3390/pr12061098 | |
| dc.identifier.issn | 2227-9717 | |
| dc.identifier.issue | 6 | |
| dc.identifier.scopus | 2-s2.0-85197219137 | |
| dc.identifier.scopusquality | Q2 | |
| dc.identifier.uri | http://dx.doi.org/10.3390/pr12061098 | |
| dc.identifier.uri | https://hdl.handle.net/20.500.12511/12708 | |
| dc.identifier.volume | 12 | |
| dc.identifier.wos | 001255731500001 | en_US |
| dc.identifier.wosquality | Q2 | |
| dc.indekslendigikaynak | Web of Science | |
| dc.indekslendigikaynak | Scopus | |
| dc.institutionauthor | Dinçer, Hasan | |
| dc.language.iso | en | |
| dc.relation.ec | info:eu-repo/grantAgreement/PN/22/10/0105 | |
| dc.relation.ispartof | Processes | en_US |
| dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | |
| dc.rights | Attribution 4.0 International | * |
| dc.rights | info:eu-repo/semantics/openAccess | |
| dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | * |
| dc.subject | ArcGIS | |
| dc.subject | Curve Fit Forecast | |
| dc.subject | Hydropower Production | |
| dc.subject | Parabolic Curve Trend | |
| dc.subject | Renewable Energy | |
| dc.subject | Space-Time Cube | |
| dc.title | Parabolic modeling forecasts of space and time european hydropower production | |
| dc.type | Article |
