Inherent Risk Analysis of Power Supply Management: Case of Belize’s System Operator and Third-Party Actors
System operators (SOs) manage power supply, focusing on risk management. In small emerging economies, proactive risk management is crucial as major disruptions require SOs to redirect resources into recovery efforts. Therefore, SOs prioritize risk reduction, proactively minimizing the possibility of...
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MDPI AG
2024-12-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/18/1/49 |
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| author | Khadija Sherece Usher Benjamin Craig McLellan |
| author_facet | Khadija Sherece Usher Benjamin Craig McLellan |
| author_sort | Khadija Sherece Usher |
| collection | DOAJ |
| description | System operators (SOs) manage power supply, focusing on risk management. In small emerging economies, proactive risk management is crucial as major disruptions require SOs to redirect resources into recovery efforts. Therefore, SOs prioritize risk reduction, proactively minimizing the possibility of major disruption to ensure the industry’s long-term advancement. However, SOs frequently focus on residual risk mitigation while ignoring their exposure to inherent risk. This study investigated the inherent risks associated with power supply management using the SO’s operations and pertinent third parties. It used a seasonal multivariate strategy to identify risk factors, create univariate distribution models, and generate multivariate distributions using the copula method. Joint risk exposure was calculated using different percentile metrics for each scenario, allowing for a comparison of exposure levels. The study found that risk variables can sometimes reinforce or offset each other, impacting exposure behaviour. Exposure levels indicate periods of increased or decreased exposure to risk variables. Copula-modelled interdependencies captured larger exposure levels but had lower unit likelihoods, presenting less conservative exposure forecasts for SO managers. Case 1 exhibited the highest exposure levels in the early dry season (0.237 and 0.179), while case 2 showed peak exposure levels in the late wet season (1.009 and 0.948), along with cases 3 (0.977 and 0.908) and 4 (0.950 and 0.879). |
| format | Article |
| id | doaj-art-4dd731a187c44c09a61f8a83c0d177ca |
| institution | Kabale University |
| issn | 1996-1073 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj-art-4dd731a187c44c09a61f8a83c0d177ca2025-01-10T13:16:56ZengMDPI AGEnergies1996-10732024-12-011814910.3390/en18010049Inherent Risk Analysis of Power Supply Management: Case of Belize’s System Operator and Third-Party ActorsKhadija Sherece Usher0Benjamin Craig McLellan1Graduate School of Energy Science, Kyoto University, Yoshida-honmachi, Sakyo-ku, Kyoto 606-8501, JapanGraduate School of Energy Science, Kyoto University, Yoshida-honmachi, Sakyo-ku, Kyoto 606-8501, JapanSystem operators (SOs) manage power supply, focusing on risk management. In small emerging economies, proactive risk management is crucial as major disruptions require SOs to redirect resources into recovery efforts. Therefore, SOs prioritize risk reduction, proactively minimizing the possibility of major disruption to ensure the industry’s long-term advancement. However, SOs frequently focus on residual risk mitigation while ignoring their exposure to inherent risk. This study investigated the inherent risks associated with power supply management using the SO’s operations and pertinent third parties. It used a seasonal multivariate strategy to identify risk factors, create univariate distribution models, and generate multivariate distributions using the copula method. Joint risk exposure was calculated using different percentile metrics for each scenario, allowing for a comparison of exposure levels. The study found that risk variables can sometimes reinforce or offset each other, impacting exposure behaviour. Exposure levels indicate periods of increased or decreased exposure to risk variables. Copula-modelled interdependencies captured larger exposure levels but had lower unit likelihoods, presenting less conservative exposure forecasts for SO managers. Case 1 exhibited the highest exposure levels in the early dry season (0.237 and 0.179), while case 2 showed peak exposure levels in the late wet season (1.009 and 0.948), along with cases 3 (0.977 and 0.908) and 4 (0.950 and 0.879).https://www.mdpi.com/1996-1073/18/1/49risk managementinherent riskpower mixelectricity sectorsystem operator |
| spellingShingle | Khadija Sherece Usher Benjamin Craig McLellan Inherent Risk Analysis of Power Supply Management: Case of Belize’s System Operator and Third-Party Actors Energies risk management inherent risk power mix electricity sector system operator |
| title | Inherent Risk Analysis of Power Supply Management: Case of Belize’s System Operator and Third-Party Actors |
| title_full | Inherent Risk Analysis of Power Supply Management: Case of Belize’s System Operator and Third-Party Actors |
| title_fullStr | Inherent Risk Analysis of Power Supply Management: Case of Belize’s System Operator and Third-Party Actors |
| title_full_unstemmed | Inherent Risk Analysis of Power Supply Management: Case of Belize’s System Operator and Third-Party Actors |
| title_short | Inherent Risk Analysis of Power Supply Management: Case of Belize’s System Operator and Third-Party Actors |
| title_sort | inherent risk analysis of power supply management case of belize s system operator and third party actors |
| topic | risk management inherent risk power mix electricity sector system operator |
| url | https://www.mdpi.com/1996-1073/18/1/49 |
| work_keys_str_mv | AT khadijashereceusher inherentriskanalysisofpowersupplymanagementcaseofbelizessystemoperatorandthirdpartyactors AT benjamincraigmclellan inherentriskanalysisofpowersupplymanagementcaseofbelizessystemoperatorandthirdpartyactors |