A Methodology to Estimate High-Resolution Gridded Datasets on Energy Consumption Drivers in Ecuador’s Residential Sector during the 2010–2020 Period
There are no methodologies in the literature for estimating the temporal and spatial distribution of consumption drivers for the residential sector of a region or country. Factors such as energy requirement, population density, outdoor temperature, and socioeconomic aspects are considered the major...
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-05-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/16/10/3973 |
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| author | Diego Moya César Arroba Christian Castro Cristian Pérez Sara Giarola Prasad Kaparaju Ángel Pérez-Navarro Adam Hawkes |
| author_facet | Diego Moya César Arroba Christian Castro Cristian Pérez Sara Giarola Prasad Kaparaju Ángel Pérez-Navarro Adam Hawkes |
| author_sort | Diego Moya |
| collection | DOAJ |
| description | There are no methodologies in the literature for estimating the temporal and spatial distribution of consumption drivers for the residential sector of a region or country. Factors such as energy requirement, population density, outdoor temperature, and socioeconomic aspects are considered the major drivers of consumption and have been found to directly influence residential energy consumption. In this study, a methodology is proposed to evaluate the impact of the above drivers in domestic energy consumption in Ecuador between 2010 and 2020 using publicly available data. This methodology aims to provide a spatiotemporal approach to estimate high-resolution gridded datasets for a 10-year period, 2010–2020, assessing seven energy drivers: (1) gridded population density, (2) gridded space heating requirements, (3) gridded space cooling requirements, (4) gridded water heating requirements, (5) gridded Gross Domestic Product (GDP), (6) gridded per capita GDP, and (7) the Human Development Index (HDI). Drivers 1 to 6 were analyzed at one square kilometer (1 km<sup>2</sup>), whereas HDI was analyzed at the city level. These results can be used to evaluate energy-planning strategies in a range of sustainable scenarios. This methodology can be used to evaluate a range of consumption drivers to evaluate long-term energy policies to reach the net-zero target by midcentury. The proposed methodology can be reproduced in other countries and regions. Future research could explore the spatiotemporal correlation of the consumption drivers provided in this study. |
| first_indexed | 2024-03-11T03:46:21Z |
| format | Article |
| id | doaj.art-0d6a978832fd48528eea24bfb0d79381 |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-03-11T03:46:21Z |
| publishDate | 2023-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-0d6a978832fd48528eea24bfb0d793812023-11-18T01:11:08ZengMDPI AGEnergies1996-10732023-05-011610397310.3390/en16103973A Methodology to Estimate High-Resolution Gridded Datasets on Energy Consumption Drivers in Ecuador’s Residential Sector during the 2010–2020 PeriodDiego Moya0César Arroba1Christian Castro2Cristian Pérez3Sara Giarola4Prasad Kaparaju5Ángel Pérez-Navarro6Adam Hawkes7Technology Outlook and Strategy, Technology Strategy and Planning Department, Saudi Aramco, Dhahran 34481, Saudi ArabiaCarrera de Ingeniería Mecánica, Facultad de Ingeniería Civil y Mecánica, Universidad Técnica de Ambato, Av. Los Chasquis y Río Payamino, Ambato 180207, EcuadorCarrera de Ingeniería Mecánica, Facultad de Ingeniería Civil y Mecánica, Universidad Técnica de Ambato, Av. Los Chasquis y Río Payamino, Ambato 180207, EcuadorCarrera de Ingeniería Mecánica, Facultad de Ingeniería Civil y Mecánica, Universidad Técnica de Ambato, Av. Los Chasquis y Río Payamino, Ambato 180207, EcuadorDepartment of Chemical Engineering, Imperial College London, South Kensington, London SW7 2BX, UKSchool of Engineering & Built Environment, Griffith University, Brisbane, QLD 4111, AustraliaInstituto de Ingeniería Energética, Universitat Politècnica de València, 46022 Valencia, SpainDepartment of Chemical Engineering, Imperial College London, South Kensington, London SW7 2BX, UKThere are no methodologies in the literature for estimating the temporal and spatial distribution of consumption drivers for the residential sector of a region or country. Factors such as energy requirement, population density, outdoor temperature, and socioeconomic aspects are considered the major drivers of consumption and have been found to directly influence residential energy consumption. In this study, a methodology is proposed to evaluate the impact of the above drivers in domestic energy consumption in Ecuador between 2010 and 2020 using publicly available data. This methodology aims to provide a spatiotemporal approach to estimate high-resolution gridded datasets for a 10-year period, 2010–2020, assessing seven energy drivers: (1) gridded population density, (2) gridded space heating requirements, (3) gridded space cooling requirements, (4) gridded water heating requirements, (5) gridded Gross Domestic Product (GDP), (6) gridded per capita GDP, and (7) the Human Development Index (HDI). Drivers 1 to 6 were analyzed at one square kilometer (1 km<sup>2</sup>), whereas HDI was analyzed at the city level. These results can be used to evaluate energy-planning strategies in a range of sustainable scenarios. This methodology can be used to evaluate a range of consumption drivers to evaluate long-term energy policies to reach the net-zero target by midcentury. The proposed methodology can be reproduced in other countries and regions. Future research could explore the spatiotemporal correlation of the consumption drivers provided in this study.https://www.mdpi.com/1996-1073/16/10/3973residential energy consumptionend-use energyspatial analysisspatiotemporal approachgeographical information systemgridded energy data |
| spellingShingle | Diego Moya César Arroba Christian Castro Cristian Pérez Sara Giarola Prasad Kaparaju Ángel Pérez-Navarro Adam Hawkes A Methodology to Estimate High-Resolution Gridded Datasets on Energy Consumption Drivers in Ecuador’s Residential Sector during the 2010–2020 Period Energies residential energy consumption end-use energy spatial analysis spatiotemporal approach geographical information system gridded energy data |
| title | A Methodology to Estimate High-Resolution Gridded Datasets on Energy Consumption Drivers in Ecuador’s Residential Sector during the 2010–2020 Period |
| title_full | A Methodology to Estimate High-Resolution Gridded Datasets on Energy Consumption Drivers in Ecuador’s Residential Sector during the 2010–2020 Period |
| title_fullStr | A Methodology to Estimate High-Resolution Gridded Datasets on Energy Consumption Drivers in Ecuador’s Residential Sector during the 2010–2020 Period |
| title_full_unstemmed | A Methodology to Estimate High-Resolution Gridded Datasets on Energy Consumption Drivers in Ecuador’s Residential Sector during the 2010–2020 Period |
| title_short | A Methodology to Estimate High-Resolution Gridded Datasets on Energy Consumption Drivers in Ecuador’s Residential Sector during the 2010–2020 Period |
| title_sort | methodology to estimate high resolution gridded datasets on energy consumption drivers in ecuador s residential sector during the 2010 2020 period |
| topic | residential energy consumption end-use energy spatial analysis spatiotemporal approach geographical information system gridded energy data |
| url | https://www.mdpi.com/1996-1073/16/10/3973 |
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