Scenario-based modeling of converter failures in energy hub management cost
Nowadays, load outages are one of the key factors influencing the costs of energy hubs (EHs). One of the most effective ways to reduce outage costs is through proper EH management. On the other hand, electric vehicle charging stations (EVCSs), due to their pollution-free nature and ability to supply...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-09-01
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| Series: | Results in Engineering |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2590123025025290 |
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| Summary: | Nowadays, load outages are one of the key factors influencing the costs of energy hubs (EHs). One of the most effective ways to reduce outage costs is through proper EH management. On the other hand, electric vehicle charging stations (EVCSs), due to their pollution-free nature and ability to supply loads during peak hours, serve as a valuable resource for EHs. This research proposes a new method for EH management that incorporates EVCSs, considering both energy carrier costs and outage costs in the objective function. Four scenarios are considered to evaluate the impact of storage devices on power losses. Additionally, various converter failure cases within each scenario are examined to assess their effect on the total EH cost. Finally, a comparison between the scenarios is conducted to identify the most effective option, particularly under peak load conditions. The objective function is modeled as a linear programming problem and solved using the Karush–Kuhn–Tucker (KKT) conditions. Simulation results indicate that in Scenario 1, the unserved energy of the electric load increases compared to Scenario 0 due to the absence of a heat storage device. This shortfall is compensated by a combined heat and power (CHP) unit. Moreover, in Scenario 3, the outage cost is higher than in other failure cases because CHP is the sole source for supplying electric loads, and it lacks the capacity to meet the full demand. The proposed approach provides a valuable tool for energy management and can help reduce unserved energy during peak load periods. |
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| ISSN: | 2590-1230 |