Optimal Microgrids in Buildings with Critical Loads and Hybrid Energy Storage
[EN] This research aims to optimize and compare the annual costs of energy services in buildings with critical loads and analyze case studies for hospitals and higher education institutions in the United States. Besides electricity and natural gas costs, the study considers all the infrastructure co...
| Autores: | , , , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2024 |
| País: | España |
| Institución: | Universidad de León |
| Repositorio: | BULERIA. Repositorio Institucional de la Universidad de León |
| OAI Identifier: | oai:buleria.unileon.es:10612/26618 |
| Acceso en línea: | https://hdl.handle.net/10612/26618 |
| Access Level: | acceso abierto |
| Palabra clave: | Ingenierías Resilience Analysis Load Profiles Solar Radiation Tariff Structure Carbon Mitigation Energy Storage 3306 Ingeniería y Tecnología Eléctricas |
| Sumario: | [EN] This research aims to optimize and compare the annual costs of energy services in buildings with critical loads and analyze case studies for hospitals and higher education institutions in the United States. Besides electricity and natural gas costs, the study considers all the infrastructure costs of capital amortization and maintenance. In addition, it studies energy resilience improvement due to distributed generation, including solar photovoltaic, solar thermal, internal combustion engine, and fuel cell sources. The optimization considers the electrical consumption, the heating and cooling demands, and the operational strategy of the energy storage systems. To simulate real scenarios, energy tariffs were modeled and considered, and final optimization results were produced. Some of the microgrid load was considered critical to model resilience benefits. The results show that if favorable energy tariffs are applied, the benefits of increasing energy resilience represent a novel market with high potential in facilities with significant critical loads. This methodology can be used in similar scenarios, adapting each particular load profile and critical load to provide a combined optimal solution regarding resilience and economic benefits. |
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