Energy Storage Systems in Micro-Grid of Hybrid Renewable Energy Solutions
[EN] This research evaluates Battery Energy Storage Systems (BESS) and Compressed Air Vessels (CAV) as complementary solutions for enhancing micro-grid resilience, flexibility, and sustainability. BESS units ranging from 5 to 400 kWh were modeled using a Nonlinear Autoregressive Neural Network with...
| Autores: | , , , , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2025 |
| País: | España |
| Institución: | Universitat Politècnica de València (UPV) |
| Repositorio: | RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia |
| Idioma: | inglés |
| OAI Identifier: | oai:riunet.upv.es:10251/230283 |
| Acceso en línea: | https://riunet.upv.es/handle/10251/230283 |
| Access Level: | acceso abierto |
| Palabra clave: | BESS CAV Hybrid renewable energy solutions Energy storage systems Micro-grid 06.- Garantizar la disponibilidad y la gestión sostenible del agua y el saneamiento para todos 07.- Asegurar el acceso a energías asequibles, fiables, sostenibles y modernas para todos |
| Sumario: | [EN] This research evaluates Battery Energy Storage Systems (BESS) and Compressed Air Vessels (CAV) as complementary solutions for enhancing micro-grid resilience, flexibility, and sustainability. BESS units ranging from 5 to 400 kWh were modeled using a Nonlinear Autoregressive Neural Network with Exogenous Inputs (NARX) neural network, achieving high SOC prediction accuracy with R2 > 0.98 and MSE as low as 0.13 kWh2. Larger batteries (400¿800 kWh) effectively reduced grid purchases and redistributed surplus energy, improving system efficiency. CAVs were tested in pumped-storage mode, achieving 33.9¿57.1% efficiency under 0.5¿2 bar and high head conditions, offering long-duration, low-degradation storage. Waterhammer-induced CAV storage demonstrated reliable pressure capture when Reynolds number ¿ 75,000 and Volume Fraction Ratio, VFR > 11%, with a prototype reaching 6142 kW and 170 kWh at 50% air volume. CAVs proved modular, scalable, and environmentally robust, suitable for both energy and water management. Hybrid systems combining BESS and CAVs offer strategic advantages in balancing renewable intermittency. Machine learning and hydraulic modeling support intelligent control and adaptive dispatch. Together, these technologies enable future-ready micro-grids aligned with sustainability and grid stability goals. |
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