Szczegóły publikacji
Opis bibliograficzny
ANN-based variable PWM control strategy for the discharge process in a CAES system / Zuzanna Fitowska, Dominik GRYBOŚ, Jan MARKOWSKI, Jacek LESZCZYŃSKI // W: ICEE 2026 [Dokument elektroniczny] : sustainability, innovation and transitions - bringing together economics and engineering : 7th International Conference on Energy & Environment : 18 - 19 June, Porto, Portugal : proceedings / eds. Susana Silva, Vitor Miguel Ribeiro. — Wersja do Windows. — Dane tekstowe. — Porto : School of Economics and Management of the University of Porto Publisher, 2026. — S. 417–422. — Wymagania systemowe: Adobe Reader. — Tryb dostępu: https://icee2026.fep.up.pt/wp-content/uploads/sites/1070/2026... [2026-08-20]. — Bibliogr. s. 422, Abstr. — Dostęp po zalogowaniu
Autorzy (4)
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 169510 |
|---|---|
| Data dodania do BaDAP | 2026-09-21 |
| Rok publikacji | 2026 |
| Typ publikacji | materiały konferencyjne (aut.) |
| Otwarty dostęp |  |
Abstract
The expanding share of renewable energy in the global energy mix demands balancing electricity supply and demand through the implementation of energy storage systems. Power generation from renewable sources is inherently intermittent, which creates a need for technologies capable of stabilizing energy delivery. One of the promising solutions is Compressed Air Energy Storage (CAES). However, a major barrier to expanding this technology is its relatively low round-trip efficiency, which is not higher than 50% in currently installed systems. Efficient operation of CAES requires precise control of the discharge process to optimize efficiency and maintain stable output power. In micro-scale installations, alternative design approaches are necessary, including the elimination of throttling devices that introduce great energy losses and reduce system efficiency. This paper investigates the discharge control of a piston expander by implementing a controlled discharge strategy based on pulse-width modulation (PWM). The development of such a control algorithm is challenging due to the complexity of the process including mechanical and thermal phenomena. However, it can be achieved using artificial intelligence. The proposed artificial neural network-based control strategy can improve discharge efficiency and enable stable outputs in the micro- CAES system.
