Lluís Trilla

This paper presents a model predictive control (MPC)-based energy management strategy for hybrid power systems combining a proton-exchange membrane fuel cell (PEMFC) with a lithium iron phosphate (LFP) battery storage unit for renewable energy applications. The proposed framework optimizes power allocation between the two sources while respecting operational constraints, including current limits, power balance requirements, and state-of-charge (SOC) bounds with soft constraints to prevent overcharging and deep discharging. Unlike conventional rule-based approaches, the MPC formulation employs a quadratic cost function with tunable weighting factors that enable flexible prioritization of either fuel cell conservation or battery lifetime extension. Accurate yet computationally efficient models are developed for both components: an equivalent circuit model for the LFP battery and a theoretical electrochemical model for the PEMFC. The performance of the proposed strategy is validated through comprehensive simulations under realistic renewable generation and load profiles. Five case studies are examined, each representing different operational scenarios characterized by varying initial SOC conditions and component prioritization weights. The results demonstrate that the MPC-based approach effectively manages power distribution, maintains SOC within safe operating ranges, and adapts to changing system conditions. Quantitative analysis shows that the tunable weighting strategy successfully limits high-current events, reducing high-current operation and potentially mitigating current-related degradations. The proposed framework offers a scalable and flexible solution for improving the reliability of hybrid energy storage in modern renewable grids.

This paper presents a Model Predictive Control (MPC)-based energy management strategy for hybrid power systems combining a proton-exchange membrane fuel cell (PEMFC) with a lithium iron phosphate (LFP) battery storage unit for renewable energy applications. The proposed framework optimizes power allocation between the two sources while respecting operational constraints, including current limits, power balance requirements, and state-of-charge (SOC) bounds with soft constraints to prevent overcharging and deep discharging. Unlike conventional rule-based approaches, the MPC formulation employs a quadratic cost function with tunable weighting factors that enable flexible prioritization of either fuel cell conservation or battery lifetime extension. Accurate yet computationally efficient models are developed for both components: an equivalent circuit model for the LFP battery and a theoretical electrochemical model for the PEMFC. The performance of the proposed strategy is validated through comprehensive simulations under realistic renewable generation and load profiles. Five case studies are examined, each representing different operational scenarios characterized by varying initial SOC conditions and component prioritization weights. The results demonstrate that the MPC-based approach effectively manages power distribution, maintains SOC within safe operating ranges, and adapts to changing system conditions. Quantitative analysis shows that the tunable weighting strategy successfully limits high-current events, reducing stress on the battery and extending its operational lifetime. The proposed framework offers a scalable and flexible solution for improving the reliability and economic viability of hybrid energy storage in modern renewable grids.

The integration of photovoltaic (PV) and wind turbine (WT) systems into modern power grids demands not only accurate component-level models but also a holistic understanding of their coordinated operation. This review bridges the gap between low-level device physics and high-level system coordination, offering a dual perspective often overlooked in existing surveys that treat generation and management separately. We systematically analyze PV models, from single-diode equivalent circuits to data-driven approaches, and WT models, ranging from aerodynamic and mechanical representations to simplified electrical equivalents suitable for stability studies. Critically, we then shift focus to the system level by examining energy management systems (EMS) that enable hybrid PV–WT coordination. Unlike prior reviews that emphasize either component accuracy or dispatch strategies alone, this paper highlights the emerging synergy between hybrid PV–WT modeling and EMS architectures. By identifying mismatches between model fidelity and EMS requirements, this review maps a pathway towards more integrated hybrid renewable systems. The discussion synthesizes key trade-offs in scalability, uncertainty handling, and real-time feasibility, underscoring that true potential is unlocked only through intelligent integration of component models and control architectures.

The integration of photovoltaic (PV) and wind turbine (WT) systems into modern power grids demands not only accurate component-level models but also a holistic understanding of their coordinated operation. This review bridges the gap between low-level device physics and high-level system coordination, offering a dual perspective often overlooked in existing surveys that treat generation and management separately. We systematically analyze PV models, from single-diode equivalent circuits to data-driven approaches, and WT models, ranging from aerodynamic and mechanical representations to simplified electrical equivalents suitable for stability studies. Critically, we then shift focus to the system level by examining Energy Management Systems (EMS) that enable hybrid PV–WT coordination. Unlike prior reviews that emphasize either component accuracy or dispatch strategies alone, this paper highlights the emerging synergy between hybrid PV–WT modeling and EMS architectures. By identifying mismatches between model fidelity and EMS requirements, this review maps a pathway towards more integrated hybrid renewable systems. The discussion synthesizes key trade-offs in scalability, uncertainty handling, and real-time feasibility, underscoring that true potential is unlocked only through intelligent integration of component models and control architectures.

Desalination is a vital solution to global water scarcity, yet its substantial energy demand persists as a major challenge. As the core energy-consuming components, pumps are fundamental to both membrane and thermal desalination processes. This review provides a comprehensive analysis of renewable energy source (RES)-driven pumping systems for desalination, focusing on the integration of solar photovoltaic and wind technologies. It examines the operational principles and efficiency of key pump types, such as high-pressure feed pumps for reverse osmosis, and underscores the critical role of energy recovery devices (ERDs) in minimizing net energy consumption. Furthermore, the paper highlights the importance of advanced control and energy management systems (EMS) in mitigating the intermittency of renewable sources. It details essential control strategies, including maximum power point tracking (MPPT), motor drive control, and supervisory EMS, that optimize the synergy between pumps, ERDs, and variable power inputs. By synthesizing current technologies and control methodologies, this review aims to identify pathways for designing more resilient, energy-efficient, and cost-effective desalination plants, supporting a sustainable water future.

Desalination is a vital solution to global water scarcity, yet its substantial energy demand persists as a major challenge. As the core energy-consuming components, pumps are fundamental to both membrane and thermal desalination processes. This review pro-vides a comprehensive analysis of renewable energy sources (RES)-driven pumping systems for desalination, focusing on the integration of solar photovoltaic and wind technologies. It examines the operational principles and efficiency of key pump types, such as high-pressure feed pumps for reverse osmosis, and underscores the critical role of energy recovery devices (ERDs) in minimizing net energy consumption. Furthermore, the paper highlights the importance of advanced control and energy management sys-tems (EMS) in overcoming the intermittency of renewable sources. It details essential control strategies, including maximum power point tracking (MPPT), motor drive con-trol, and supervisory EMS, that optimize the synergy between pumps, ERDs, and varia-ble power inputs. By synthesizing current technologies and control methodologies, this review aims to identify pathways for designing more resilient, energy-efficient, and cost-effective desalination plants, supporting a sustainable water future.

The global water crisis, intensified by climate change and population growth, underscores the critical need for sustainable water production. Desalination is a pivotal solution, but its energy-intensive nature demands a transition from fossil fuels to renewable sources. However, the inherent intermittency of solar and wind power poses a fundamental challenge to the stable operation of desalination plants. This review provides a comprehensive analysis of a specifically tailored solution: hybrid energy storage systems (HESS) that synergistically combine batteries and hydrogen fuel cells (FC). Moving beyond a general description of hybridization, this study delves into the strategic complementarity of this pairing, where the high-power density and rapid response of lithium-ion batteries manage short-term fluctuations, while the high-energy density and steady output of fuel cells ensure long-duration, stable baseload power. This operational synergy is crucial for maintaining consistent pressure in processes like reverse osmosis (RO), thereby reducing membrane stress and improving system uptime. A central focus of this review is the critical role of advanced energy management systems (EMS). We synthesize findings on how intelligent control strategies, from fuzzy logic to metaheuristic optimization algorithms, are essential for managing the power split between components. These sophisticated EMS strategies do not merely ensure reliability, they actively optimize the system to minimize hydrogen consumption, reduce operational costs, and extend the lifespan of the hybrid energy storage components. The analysis confirms that a lithium-ion battery-fuel cell HESS, governed by an advanced EMS, effectively mitigates renewable intermittency to significantly enhance freshwater yield and overall system reliability. By integrating component-specific hybridization with smart control, this review establishes a framework for researchers and engineers to achieve significant levels of energy efficiency, economic viability, and sustainability in renewable-powered desalination.