Adaptative state-space model predictive control of a parabolic-trough field
Model Predictive control algorithms for trough solar plants make use of solar radiation measurements and the overall efficiency knowledge which are very useful in order to reject disturbances. However, direct solar radiation, mirror reflectivity and metal absorptance which affect overall efficiency,...
| Autores: | , |
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| Formato: | artículo |
| Estado: | Versión aceptada para publicación |
| Fecha de publicación: | 2012 |
| País: | España |
| Recursos: | Universidad de Sevilla (US) |
| Repositorio: | idUS. Depósito de Investigación de la Universidad de Sevilla |
| OAI Identifier: | oai:idus.us.es:11441/166401 |
| Acesso em linha: | https://hdl.handle.net/11441/166401 https://doi.org/10.1016/j.conengprac.2012.05.010 |
| Access Level: | acceso abierto |
| Palavra-chave: | State-space model predictive control Unscented Kalman filter Parabolic-trough Solar radiation Distributed collector field |
| Resumo: | Model Predictive control algorithms for trough solar plants make use of solar radiation measurements and the overall efficiency knowledge which are very useful in order to reject disturbances. However, direct solar radiation, mirror reflectivity and metal absorptance which affect overall efficiency, can only be measured locally. In this paper, an adaptative model predictive control using an unscented Kalman filter (UKF) to estimate both the effective solar radiation and the metal–fluid temperature profiles is proposed. The control algorithm is validated by tests with real data taken from the ACUREX field of the PSA in Almería (Spain). |
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