| Título | Scenario-based model predictive control for energy scheduling in a parabolic trough concentrating solar plant with thermal storage |
|---|---|
| Autores | VELARDE RUEDA, PABLO ANIBAL, Gallego A.J. , Bordons C. , Camacho E.F. |
| Publicación externa | No |
| Medio | Renew. Energy |
| Alcance | Article |
| Naturaleza | Científica |
| Cuartil JCR | 1 |
| Cuartil SJR | 1 |
| Impacto JCR | 9 |
| Impacto SJR | 1.923 |
| Web | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85149726090&doi=10.1016%2fj.renene.2023.02.114&partnerID=40&md5=33b3c3f74a096d676cf9d8c5e13c19ef |
| Fecha de publicacion | 01/03/2023 |
| ISI | 000954896500001 |
| Scopus Id | 2-s2.0-85149726090 |
| DOI | 10.1016/j.renene.2023.02.114 |
| Abstract | Optimal energy planning is a key topic in thermal solar trough plants. Obtaining a profitable energy schedule is difficult due to the stochastic nature of solar irradiance and electricity prices. This article focuses on optimal energy planning for thermal solar trough plants, particularly by developing a model predictive control algorithm based on multiple scenarios to deal with uncertainties. The results obtained using the proposed scheme have been tested and compared to other well-known approaches to energy scheduling through a realistic and reliable comparison to evaluate their performances and establish their advantages and weaknesses. Simulations were carried out for a 50 MW parabolic trough concentrating solar plant with a thermal energy storage system, considering different types of days classified according to their solar irradiance, meteorological forecast, and electrical market. Simulation results show that the proposed method outperforms other scheduling methods in dealing with uncertainties by selling energy to the grid at the right times, generating the highest income of about 7.58%. © 2023 The Author(s) |
| Palabras clave | Economic analysis; Electric energy storage; Heat storage; Model predictive control; Predictive control systems; Solar radiation; Stochastic control systems; Stochastic models; Stochastic systems; Concentrating solar; Energy; Energy planning; Model-predictive control; Optimal controls; Optimal energy; Parabolic trough; Solar plant; Stochastic mpc; Stochastics; Solar energy; algorithm; control system; electricity; energy planning; energy storage; solar power; stochasticity |
| Miembros de la Universidad Loyola |