Article
Green & Sustainable Science & Technology
Sara Ruiz-Moreno, Jose Ramon D. Frejo, Eduardo F. Camacho
Summary: Using artificial neural networks to approximate the optimal flow rate given by an MPC controller significantly reduces the computational load to 3% of the MPC computation time. The neural network controllers provide practically the same mean power as the MPC controller with less abrupt changes at the output and slight violations of the constraints.
Article
Green & Sustainable Science & Technology
Tahereh Gholaminejad, Ali Khaki-Sedigh
Summary: In this paper, a deep Model Predictive Control (MPC) method based on the Koopman operator is proposed to control the Heat Transfer Fluid (HTF) temperature in concentrated solar power plants. A deep Long Short-Term Memory (LSTM) autoencoder is designed to calculate Koopman eigenfunctions, which are used to convert a non-linear model to a Koopman-based linear model. The results of simulations demonstrate the satisfactory tracking performance of the proposed approach.
Article
Green & Sustainable Science & Technology
Paula Chanfreut, Jose M. Maestre, Antonio Gallego, Anuradha M. Annaswamy, Eduardo F. Camacho
Summary: This paper proposes a clustering-based model predictive controller to optimize the heat transfer fluid (HTF) flow rates in solar parabolic trough plants. The hierarchical approach consists of two layers: a bottom layer of model predictive control agents and a top layer that dynamically partitions the loops into clusters. The dynamic clustering reduces the variables to be coordinated and speeds up the computations. Numerical results are provided for a 10-loop and an 80-loop plant.
Article
Thermodynamics
Hongtao Liu, Rongrong Zhai, Kumar Patchigolla, Peter Turner, Yongping Yang
Summary: Integrating solar tower and parabolic trough technology into coal-fired power generation can significantly reduce coal consumption, especially in high radiation conditions. The method is insensitive to forecast errors but sensitive to system configurations.
APPLIED THERMAL ENGINEERING
(2021)
Article
Green & Sustainable Science & Technology
Anass Zaaoumi, Abdellah Bah, Mihaela Ciocan, Patrick Sebastian, Mugur C. Balan, Abdellah Mechaqrane, Mohammed Alaoui
Summary: In this study, three models were used to estimate the hourly electric production of a parabolic trough solar thermal power plant in Eastern Morocco. The results show that the artificial neural networks (ANN) model performs better than the analytical models, accurately estimating the energy production.
Article
Energy & Fuels
Eva Masero, Jose M. Maestre, Eduardo F. Camacho
Summary: This article proposes a market-based clustering model predictive control strategy for maximizing the thermal energy collected by parabolic-trough solar collector fields. The hierarchical algorithm fosters the formation of coalitions dynamically to improve the overall control objective, resulting in a 12% increase in energy efficiency compared to traditional controllers. The method is implementable in real-time for controlling large-scale solar collector fields and can achieve significant gains in thermal collected energy due to its scalability.
Article
Automation & Control Systems
Xian-hua Gao, Shangshang Wei, Minli Wang, Zhi-gang Su
Summary: This paper proposes an optimal disturbance predictive and rejection controller in a composite scheme to address the control challenges faced by the parabolic trough solar field (PTSF). By reconstructing field disturbances, estimating and predicting lumped disturbance sequence, and real-time correction of steady-state sequence, the proposed design demonstrates effective disturbance rejection and target tracking performance.
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2022)
Article
Energy & Fuels
Ana Sanchez-Amores, Juan Martinez-Piazuelo, Jose M. Maestre, Carlos Ocampo-Martinez, Eduardo F. Camacho, Nicanor Quijano
Summary: This paper proposes a novel coalitional control approach for large-scale parabolic-trough solar collector fields. The approach splits the field into smaller subsystems, each governed by a local controller. Controllers are clustered into coalitions to solve local optimization problems, achieving an approximate solution to the centralized problem in a decentralized manner. A population-dynamics-assisted resource allocation strategy is proposed to decouple the optimization problems of the coalitions, reducing computational burden while ensuring operational constraints and overall performance.
Article
Green & Sustainable Science & Technology
Diogo Ortiz Machado, Adolfo J. Sanchez, Antonio J. Gallego, Gustavo A. de Andrade, Julio E. Normey-Rico, Carlos Bordons, Eduardo F. Camacho
Summary: This paper proposes the first application of a split-range control technique on a concentrating solar collector to improve the production of an absorption plant. Control techniques are simulated and compared in an absorption plant in Spain. The results demonstrate that the proposed controllers significantly reduce the effort of control actuators and improve energy and exergy production.
Article
Energy & Fuels
Guangjun Wang, Qing Zhu, Fei Yan, Hong Chen
Summary: This paper proposes a multi-model adaptive control scheme based on the heat-steam ratio and its reference trajectory to solve the control problem of the outlet steam temperature of the DSG solar parabolic-trough collector.
Article
Energy & Fuels
A. J. Sanchez, A. J. Gallego, J. M. Escano, E. F. Camacho
Summary: The paper proposes a FeedForward-based strategy to control the outlet temperature of collectors in a solar thermal plant by adjusting the defocus angle. By dynamically obtaining set-point temperatures and optimizing based on a concentrated parameter model, energy losses can be avoided.
Article
Energy & Fuels
Eva Masero, Jose Ramon D. Frejo, Jose M. Maestre, Eduardo F. Camacho
Summary: This article demonstrates how coalitional model predictive control can be used to maximize the thermal power of large-scale solar parabolic-trough plants. The proposed strategy divides the plant into subsystems controlled by their corresponding loop valves, resulting in improved performance and faster computation of control inputs. The scalability of the strategy is evaluated using decentralized and centralized MPC in simulated solar parabolic-trough fields.
Article
Energy & Fuels
Georgios E. Arnaoutakis, Dimitris Al. Katsaprakakis, Dimitris G. Christakis
Summary: This paper investigates the potential of two concentrating solar power technologies, central power towers and parabolic trough collectors, in the same plant configuration through dynamic modeling. The results show that the configuration of a power tower and parabolic trough collectors has a more stable power profile and higher capacity factor compared to standalone plants based on a single technology.
Article
Energy & Fuels
Andrea Gilioli, Francesco Cadini, Luca Abbiati, Giulio Angelo Guido Solero, Massimo Fossati, Andrea Manes, Lino Carnelli, Carla Lazzari, Stefano Cardamone, Marco Giglio
Summary: The design of large-scale structures can be improved by adopting numerical models and combining them with experimental testing. This approach can enhance the understanding of structural behavior, reduce costs and uncertainties in implementing final products, and decrease the number of required experimental tests.
Article
Green & Sustainable Science & Technology
Qiliang Wang, Gang Pei, Hongxing Yang
Summary: The novel parabolic trough solar receiver with a radiation shield, based on the theory of the negative thermal-flux region, shows great potential for significant enhancement of the techno-economic performance of solar power plants, improving electrical energy production and reducing the levelized cost of energy.
Article
Automation & Control Systems
Antonio J. Gallego, Adolfo J. Sanchez, M. Berenguel, Eduardo F. Camacho
JOURNAL OF PROCESS CONTROL
(2020)
Article
Computer Science, Information Systems
Alireza Namadmalan, Kumars Rouzbehi, Juan Manuel Escano, Carlos Bordons
Article
Energy & Fuels
Morteza Hesami, Ali Bakhshi, Sheyda Mousavi, Kumars Rouzbehi, Juan Manuel Escano
Summary: This study focuses on the power loss issue of hybrid HVDC breakers. By developing a full-bridge hybrid breaker (FBHB) structure, the amount of power lost during normal operation and fault current breaking is substantially decreased.
Article
Automation & Control Systems
J. M. Escano, A. J. Sanchez, M. Ceballos, A. J. Gallego, E. F. Camacho
Summary: This paper presents an observer based on a fuzzy inference system to estimate the temperature profiles of the loops in a solar field, addressing the issue of unmeasurable state variables in solar trough plants. A complexity reduction technique is applied to make the estimator practical without consuming excessive memory or programming time in industrial devices.
REVISTA IBEROAMERICANA DE AUTOMATICA E INFORMATICA INDUSTRIAL
(2021)
Article
Energy & Fuels
A. J. Sanchez, A. J. Gallego, J. M. Escano, E. F. Camacho
Summary: The paper proposes a FeedForward-based strategy to control the outlet temperature of collectors in a solar thermal plant by adjusting the defocus angle. By dynamically obtaining set-point temperatures and optimizing based on a concentrated parameter model, energy losses can be avoided.
Article
Automation & Control Systems
Antonio J. Gallego, Manuel Macias, Fernando de Castilla, Adolfo J. Sanchez, Eduardo F. Camacho
Summary: The size of current commercial solar trough plants brings new challenges in the applications of advanced control strategies, while Model Predictive Control algorithms have been proven to perform well in controlling these plants.
CONTROL ENGINEERING PRACTICE
(2022)
Article
Green & Sustainable Science & Technology
Diogo Ortiz Machado, Adolfo J. Sanchez, Antonio J. Gallego, Gustavo A. de Andrade, Julio E. Normey-Rico, Carlos Bordons, Eduardo F. Camacho
Summary: This paper proposes the first application of a split-range control technique on a concentrating solar collector to improve the production of an absorption plant. Control techniques are simulated and compared in an absorption plant in Spain. The results demonstrate that the proposed controllers significantly reduce the effort of control actuators and improve energy and exergy production.
Article
Automation & Control Systems
Antonio J. Gallego, Adolfo J. Sanchez, J. M. Escano, Eduardo F. Camacho
Summary: This paper proposes a non-linear model predictive algorithm that uses a hydraulic model of the solar field to compute the aperture of the input valves, aiming to solve the challenges of thermal balance and energy losses in commercial solar trough plants when applying advanced control strategies.
EUROPEAN JOURNAL OF CONTROL
(2022)
Article
Energy & Fuels
Salvatore Vergine, Cesar Alvarez-Arroyo, Guglielmo D'Amico, Juan Manuel Escano, Lazaro Alvarado-Barrios
Summary: Currently, efforts are being made by governments and electricity companies to integrate renewable energy sources into grids and microgrids, aiming to reduce carbon footprint and increase social welfare. This study developed a Stochastic Unit Commitment plan for a hybrid and isolated microgrid, managing multiple renewable energy sources to meet demand response. The results indicate the accuracy of stochastic models in simulating renewable energy production, which significantly impacts the total cost of the microgrid.
Article
Energy & Fuels
Diogo Ortiz Machado, William D. Chicaiza, Juan M. Escano, Antonio J. Gallego, Gustavo A. de Andrade, Julio E. Normey-Rico, Carlos Bordons, Eduardo F. Camacho
Summary: This work develops digital models of a commercial Fresnel Solar Collector (FSC) in an absorption cooling plant. Two modeling approaches are employed and their twinning/adaptation time and performance validation are evaluated. The results show that both models perform well and are suitable for control and optimization.
Article
Green & Sustainable Science & Technology
Javier Gomez, William D. Chicaiza, Juan M. Escano, Carlos Bordons
Summary: This article presents a formulation for optimizing a manufacturing process using genetic algorithms to manage energy generation and demand in a factory. The strategy aims to minimize daily energy costs while maximizing the utilization of renewable energy sources and potential battery banks. The study considers a 24-hour time series of renewable energy production and electricity prices from the market operator. Simulation results show that the proposed strategy can achieve a 6% reduction in daily energy costs compared to the current management approach.
Article
Green & Sustainable Science & Technology
Diogo Ortiz Machado, William D. Chicaiza, Juan M. Escano, Antonio J. Gallego, Gustavo A. de Andrade, Julio E. Normey-Rico, Carlos Bordons, Eduardo F. Camacho
Summary: The aim of this study is to create a digital twin of a commercial absorption chiller using Adaptive Neuro-fuzzy Inference System (ANFIS) for control and optimization purposes. The ANFIS models show good accuracy and precision, outperforming literature models in terms of Mean Absolute Percentage Error (MAPE). The resulting digital twin is suitable for Model Predictive Control applications and fast what-if analysis and optimization.
Article
Computer Science, Interdisciplinary Applications
Fabio Rodriguez, William D. Chicaiza, Adolfo Sanchez, Juan M. Escano
Summary: The Digital Twin (DT) is an integration between cyber and physical spaces that has gained popularity in smart manufacturing and Industry 4.0. However, updating DT models in real time poses a challenge. This study proposes a novel methodology to ensure data quality in the interconnection between digital and physical spaces, using a neurofuzzy system for failure detection and a recurrent neural network for error prediction.
COMPUTERS IN INDUSTRY
(2023)
Article
Energy & Fuels
Hamza Assia, Houari Merabet Boulouiha, William David Chicaiza, Juan Manuel Escano, Abderrahmane Kacimi, Jose Luis Martinez-Ramos, Mouloud Denai
Summary: The study proposes an active fault-tolerant control system that combines BADRC theory, ANFIS detector, and PCA method to address the issue of actuator generator torque failure in offshore wind farms. The results demonstrate the effectiveness of the proposed method in maintaining system performance and detecting false data.
Article
Energy & Fuels
Siddharth Sradhasagar, Omkar Subhasish Khuntia, Srikanta Biswal, Sougat Purohit, Amritendu Roy
Summary: In this study, machine learning models were developed to predict the bandgap and its character of double perovskite materials, with LGBMRegressor and XGBClassifier models identified as the best predictors. These models were further employed to predict the bandgap of novel bismuth-based transition metal oxide double perovskites, showing high accuracy, especially in the range of 1.2-1.8 eV.
Article
Energy & Fuels
Wei Shuai, Haoran Xu, Baoyang Luo, Yihui Huang, Dong Chen, Peiwang Zhu, Gang Xiao
Summary: In this study, a hybrid model based on numerical simulation and deep learning is proposed for the optimization and operation of solar receivers. By applying the model to different application scenarios and considering multiple performance objectives, small errors are achieved and optimal structure parameters and heliostat scales are identified. This approach is not only applicable to gas turbines but also heating systems.
Article
Energy & Fuels
Mubashar Ali, Zunaira Bibi, M. W. Younis, Muhammad Mubashir, Muqaddas Iqbal, Muhammad Usman Ali, Muhammad Asif Iqbal
Summary: This study investigates the structural, mechanical, and optoelectronic properties of the BaCuF3 fluoroperovskite using the first-principles modelling approach. The stability and characteristics of different cubic structures of BaCuF3 are evaluated, and the alpha-BaCuF3 and beta-BaCuF3 compounds are found to be mechanically stable with favorable optical properties for solar cells and high-frequency UV applications.
Article
Energy & Fuels
Dong Le Khac, Shahariar Chowdhury, Asmaa Soheil Najm, Montri Luengchavanon, Araa mebdir Holi, Mohammad Shah Jamal, Chin Hua Chia, Kuaanan Techato, Vidhya Selvanathan
Summary: A novel recycling system is proposed in this study to decompose and reclaim the constituent materials of organic-inorganic perovskite solar cells (PSCs). By utilizing a one-step solution process extraction approach, the chemical composition of each layer is successfully preserved, enabling their potential reuse. The proposed recycling technique helps mitigate pollution risks, minimize waste generation, and reduce recycling costs.
Article
Energy & Fuels
Peijie Lin, Feng Guo, Xiaoyang Lu, Qianying Zheng, Shuying Cheng, Yaohai Lin, Zhicong Chen, Lijun Wu, Zhuang Qian
Summary: This paper proposes an open-set fault diagnosis model for PV arrays based on 1D VoVNet-SVDD. The model accurately diagnoses various types of faults and is capable of identifying unknown fault types.
