Electrification Planning for Healthcare Facilities in Low-Income Countries, Application of a Portfolio-Level, Multi Criteria Decision-Making Approach
This study presents a multi-platform analysis for accelerating the deployment of distributed renewable energy (DRE) systems for the electrification of healthcare facilities (HCFs) in low-income regions. While existing tools capture national and regional scale planning for DRE deployment in HCFs, the...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-11-01
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| Series: | ISPRS International Journal of Geo-Information |
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| Online Access: | https://www.mdpi.com/2220-9964/10/11/750 |
| _version_ | 1797510090275684352 |
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| author | Mohammad H. Pakravan Andrea C. Johnson |
| author_facet | Mohammad H. Pakravan Andrea C. Johnson |
| author_sort | Mohammad H. Pakravan |
| collection | DOAJ |
| description | This study presents a multi-platform analysis for accelerating the deployment of distributed renewable energy (DRE) systems for the electrification of healthcare facilities (HCFs) in low-income regions. While existing tools capture national and regional scale planning for DRE deployment in HCFs, there are limited tools for facility level energy needs and no existing data-driven approach for systematic decision-making and resource allocation across a portfolio of HCFs. We address this gap by utilizing decentralized data collection, and multi-criteria decision-making to evaluate each HCF against a set of weighted decision criteria. We applied the approach presented in this research in a case study across 56 HCF in Uganda. Results present current and future energy needs for each individual clinic and the prioritization of HCFs for allocation of resources for DRE deployment. Additionally, results provide insight for best practices for reliability of services that are specific to each HCF. For example, failures in the existing solar photovoltaic (PV) systems are approximately up to 60% due to a lack of proper operation and management (O&M) strategy, and 40% is attributable to improper system design and installation. Thus, this study enables decision-makers to better understand the electrification needs of different HCFs, prioritize DRE deployment, financial investments, cost-effective procurement, and long-term O&M. |
| first_indexed | 2024-03-10T05:26:48Z |
| format | Article |
| id | doaj.art-a8f996584262482e850812787ca22e7b |
| institution | Directory Open Access Journal |
| issn | 2220-9964 |
| language | English |
| last_indexed | 2024-03-10T05:26:48Z |
| publishDate | 2021-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | ISPRS International Journal of Geo-Information |
| spelling | doaj.art-a8f996584262482e850812787ca22e7b2023-11-22T23:36:17ZengMDPI AGISPRS International Journal of Geo-Information2220-99642021-11-01101175010.3390/ijgi10110750Electrification Planning for Healthcare Facilities in Low-Income Countries, Application of a Portfolio-Level, Multi Criteria Decision-Making ApproachMohammad H. Pakravan0Andrea C. Johnson1Green Empowerment, Portland, OR 97204, USAGreen Empowerment, Portland, OR 97204, USAThis study presents a multi-platform analysis for accelerating the deployment of distributed renewable energy (DRE) systems for the electrification of healthcare facilities (HCFs) in low-income regions. While existing tools capture national and regional scale planning for DRE deployment in HCFs, there are limited tools for facility level energy needs and no existing data-driven approach for systematic decision-making and resource allocation across a portfolio of HCFs. We address this gap by utilizing decentralized data collection, and multi-criteria decision-making to evaluate each HCF against a set of weighted decision criteria. We applied the approach presented in this research in a case study across 56 HCF in Uganda. Results present current and future energy needs for each individual clinic and the prioritization of HCFs for allocation of resources for DRE deployment. Additionally, results provide insight for best practices for reliability of services that are specific to each HCF. For example, failures in the existing solar photovoltaic (PV) systems are approximately up to 60% due to a lack of proper operation and management (O&M) strategy, and 40% is attributable to improper system design and installation. Thus, this study enables decision-makers to better understand the electrification needs of different HCFs, prioritize DRE deployment, financial investments, cost-effective procurement, and long-term O&M.https://www.mdpi.com/2220-9964/10/11/750renewable energy planningoff-grid electrificationhealthcare facilitycloud-based data collectionmulti-criteria decision-makingTOPSIS |
| spellingShingle | Mohammad H. Pakravan Andrea C. Johnson Electrification Planning for Healthcare Facilities in Low-Income Countries, Application of a Portfolio-Level, Multi Criteria Decision-Making Approach ISPRS International Journal of Geo-Information renewable energy planning off-grid electrification healthcare facility cloud-based data collection multi-criteria decision-making TOPSIS |
| title | Electrification Planning for Healthcare Facilities in Low-Income Countries, Application of a Portfolio-Level, Multi Criteria Decision-Making Approach |
| title_full | Electrification Planning for Healthcare Facilities in Low-Income Countries, Application of a Portfolio-Level, Multi Criteria Decision-Making Approach |
| title_fullStr | Electrification Planning for Healthcare Facilities in Low-Income Countries, Application of a Portfolio-Level, Multi Criteria Decision-Making Approach |
| title_full_unstemmed | Electrification Planning for Healthcare Facilities in Low-Income Countries, Application of a Portfolio-Level, Multi Criteria Decision-Making Approach |
| title_short | Electrification Planning for Healthcare Facilities in Low-Income Countries, Application of a Portfolio-Level, Multi Criteria Decision-Making Approach |
| title_sort | electrification planning for healthcare facilities in low income countries application of a portfolio level multi criteria decision making approach |
| topic | renewable energy planning off-grid electrification healthcare facility cloud-based data collection multi-criteria decision-making TOPSIS |
| url | https://www.mdpi.com/2220-9964/10/11/750 |
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