TY - JOUR
T1 - Design and implementation of Model-Based Predictive Control for two-axis Solar Tracker
AU - Palomino-Resendiz, S. I.
AU - Flores-Hernández, D. A.
AU - Cantera-Cantera, L. A.
AU - Lozada-Castillo, N.
AU - Luviano-Juárez, A.
N1 - Publisher Copyright:
© 2023 International Solar Energy Society
PY - 2023/11/15
Y1 - 2023/11/15
N2 - This paper presents the design and implementation of a model-based predictive controller (MPC) with the aim of reducing electrical energy consumption during the development of solar trajectory tracking tasks for a two-axis Solar Tracker. For the design of the MPC, it is necessary to know the specific parameters of each actuator of the Solar Tracker. Therefore, the design and implementation of an experimental methodology based on an algebraic approach to offline parameter identification is also presented. On the other hand, to validate the MPC proposal, an experimental methodology was carried out that allows evaluating and comparing its performance with that of two classical controllers. The above, in terms of tracking error and energy consumption. The results show that the MPC reduces on average 90% of the energy consumption, but it has a higher tracking error of approximately 0.5°. Therefore, based on this, analysis and discussion are provided.
AB - This paper presents the design and implementation of a model-based predictive controller (MPC) with the aim of reducing electrical energy consumption during the development of solar trajectory tracking tasks for a two-axis Solar Tracker. For the design of the MPC, it is necessary to know the specific parameters of each actuator of the Solar Tracker. Therefore, the design and implementation of an experimental methodology based on an algebraic approach to offline parameter identification is also presented. On the other hand, to validate the MPC proposal, an experimental methodology was carried out that allows evaluating and comparing its performance with that of two classical controllers. The above, in terms of tracking error and energy consumption. The results show that the MPC reduces on average 90% of the energy consumption, but it has a higher tracking error of approximately 0.5°. Therefore, based on this, analysis and discussion are provided.
KW - Parameters identification
KW - Photovoltaic system
KW - Predictive control
KW - Solar energy
KW - Solar tracker
UR - http://www.scopus.com/inward/record.url?scp=85174358227&partnerID=8YFLogxK
U2 - 10.1016/j.solener.2023.112080
DO - 10.1016/j.solener.2023.112080
M3 - Artículo
AN - SCOPUS:85174358227
SN - 0038-092X
VL - 265
JO - Solar Energy
JF - Solar Energy
M1 - 112080
ER -