Search Results (121)

To improve the low-carbon economic operation of integrated energy system (IES) with electric–thermal–hydrogen hybrid energy storage (ETH-HES), this paper proposes a low-carbon optimal dispatch strategy that jointly considers the bidirectional interaction between green certificate trading (GCT) and stepwise carbon emission trading (SCET), as well as lifetime degradation of electrolyzers and batteries. A coupled GCT–SCET interaction model is formulated by linking green certificate acquisition with carbon quota transactions, and a triple-incentive mechanism is introduced to monetize the low-carbon value of ETH-HES. In addition, degradation-aware models are established for the electrolyzer and battery to capture long-term operating costs. Case studies show that the proposed strategy reduces system operating cost and carbon emissions, increases wind and PV utilization, and improves the operating profit of ETH-HES. Full article

The integration of solar photovoltaic (PV) systems into smart grids necessitates robust, real-time fault detection mechanisms, particularly in resource-constrained environments like the Solar–Hydrogen AIoT microgrid framework at a university. This study conducts a comparative analysis of four prominent Convolutional Neural Network (CNN) architectures VGG16, ResNet-50, DenseNet121, and EfficientNetB0 to determine the optimal model for low-latency, edge-based fault diagnosis. The models were trained and validated on a dataset of solar panel images featuring multiple fault types. Quantitatively, DenseNet121 achieved the highest classification accuracy at 86.00%, demonstrating superior generalization and feature extraction capabilities. However, when considering the stringent requirements of an AIoT system, computational efficiency became the decisive factor. EfficientNetB0 emerged as the most suitable architecture, delivering an acceptable accuracy of 80.00% while featuring the smallest model size (5.3 M parameters) and a fast inference time (approx. 26 ms/step). This efficiency-to-accuracy balance makes EfficientNetB0 ideal for deployment on edge computing nodes where memory and real-time processing are critical limitations. DenseNet121 achieved 86% accuracy, while EfficientNetB0 achieved 80% accuracy with lowest model size and fastest inference time. This research provides a validated methodology for implementing efficient deep learning solutions in sustainable, intelligent energy management systems. The novelty of this work lies in its deployment-focused comparison of CNN architectures tailored for real-time inference on resource-constrained Solar–Hydrogen AIoT systems. Full article

With the rapid advancement of hydrogen-based direct current microgrid (H₂-DCMG) technology, multi-port converters (MPCs) have emerged as the pivotal interface for integrating renewable power generation, energy storage, and diverse DC loads. This paper systematically reviews the current research status and development trends of isolated and non-isolated MPC topologies within hydrogen-based DC microgrids. Firstly, it analyses the interface requirements for typical distributed energy sources (DER) such as photovoltaics (PV), wind turbines (WT), fuel cells (FC), battery energy storage (BESS), proton exchange membrane electrolyzers (PEMEL), and supercapacitors (SC). Secondly, it classifies and evaluates existing MPC topologies, clarifying the structural characteristics, technical advantages, and challenges faced by each type. Results indicate that non-isolated topologies offer advantages such as structural simplicity, high efficiency, and high power density, making them more suitable for residential and small-scale microgrid applications. Isolated topologies, conversely, provide electrical isolation and modular scalability, rendering them appropriate for high-voltage electrolytic hydrogen production and industrial scenarios with stringent safety requirements. Finally, the paper identifies current research gaps and proposes that future efforts should focus on exploring topology optimization, system integration design, and reliability enhancement. Full article

Stable operating conditions in electrolyzers are crucial for preserving system durability, ensuring highly pure hydrogen production, and enabling the sustainable utilization of surplus renewable electricity. However, in active distribution networks, the output uncertainty of distributed energy resources, such as renewable energy sources (RES) on the generation side and load demand side, can lead to voltage fluctuations that threaten the operational stability of electrolyzers and limit their contribution to a low-carbon energy transition. This paper proposes a novel framework for optimal electrolyzer placement, tailored to their operational requirements and to the planning of sustainable renewable-integrated distribution systems. First, probabilistic scenario generation is carried out for RES and load to capture the characteristics of their inherent uncertainties. Second, based on these scenarios, continuous power-flow-based P–V (power–voltage) curve analysis is conducted to evaluate voltage stability and identify the loadability and load margin for each bus. Finally, the optimal siting of electrolyzers is determined by analyzing the load margins obtained from the voltage stability assessment and deriving a probabilistic electrolyzer hosting capacity. A case study under various uncertainty scenarios examines how applying this method influences the ability to maintain acceptable voltage levels at each bus in the grid. The results indicate that the method can significantly improve the likelihood of stable electrolyzer operation, support the reliable integration of green hydrogen production into distribution networks, and contribute to the sustainable planning of other voltage-sensitive equipment. Full article

This study validates green hydrogen (${\mathrm{H}}_2$) production from a 15 kWe wind–solar PV microplant under real operating conditions and quantifies the renewable diesel (RD) potential from oil hydroprocessing (with palm oil as the base case) via detailed stoichiometric balances. The electric output feeding two electrolyzers was monitored for six months (December 2024–May 2025). Three ${\mathrm{H}}_2$ production models were calibrated against the experimental results; the model with the best fit achieved ${\mathrm{R}}^2$ = 0.9848 and MSE = 130.05. Using the estimated ${\mathrm{H}}_2$ production, monthly balances were established for palm oil TAGs (POP, POO, POL, PLP, and SOS) across various deoxygenation routes—namely decarboxylation (DCX), decarbonylation (DCN), and hydrodeoxygenation (HDO)—with coproduct closure (propane, ${\mathrm{CO}}_2/\mathrm{CO}/{\mathrm{H}}_2\mathrm{O}$). The hybrid plant operated above the electrolyzers’ 2.88 kWe minimum, raising the effective ${\mathrm{H}}_2$ output (which peaked in February–March) and, thereby, the RD potential. The specific ${\mathrm{H}}_2$ demand followed the gradient of HDO > DCN > DCX; for POP, the global demand was 0.30 kg (saturation) + 1.20 kg (cracking) + 2.10 kg (DCN) or 2.55 kg (HDO), highlighting the carbon–hydrogen trade-off. The results indicate that ${\mathrm{green-H}}_2$–HDO integration is technically feasible and scalable in La Guajira; the choice of route (DCX/DCN vs. HDO) should align with local renewable availability to either maximize the liters of RD per kg ${\mathrm{H}}_2$ or conserve carbon. Full article

The integration of renewable energy sources, particularly photovoltaic (PV) solar, is increasingly challenged by the limited flexibility and storage capacity of actual energy systems. Hydrogen produced via renewable-powered electrolysis offers a promising pathway to address these constraints. This paper explores hydrogen blending into the natural gas grid as a systemic solution to enhance power system flexibility and support renewable (PV) expansion. Methodologically, the analysis is based on actual grid flow dynamics rather than static averages, identifying network nodes with stable gas demand as the most suitable for hydrogen injection. The novelty of this study lies in framing power-to-gas coupling as an operational flexibility tool rather than a storage-only option, and in quantifying its potential contribution to PV deployment. The methodology is applied to the Italian energy system, chosen as a representative case of high PV penetration and gas dependency. Analysis indicates that under current regulatory constraints (up to 5% hydrogen blending), the additional PV capacity that could be effectively integrated remains limited, resulting in modest reductions in natural gas consumption (<1%) and CO₂ emissions (~0.3%). However, the approach demonstrates the conceptual and methodological relevance of treating gas networks as dynamic elements of an integrated power-to-gas system. Hydrogen blending thus emerges as a transitional but essential step toward future multi-energy integration under evolving regulatory and economic frameworks. Full article

To achieve optimal performance of renewable hydrogen production systems (RHPS), this study proposes a novel optimization framework for synergistically integrating wind–solar resources with diversified electrolyzers. A comprehensive techno-economic model is developed, incorporating both alkaline electrolyzers (AEL) and proton exchange membrane electrolyzers (PEMEL), and enabling the determination of the optimal wind–solar configuration ratio, electrolyzer types and capacities, and system-level economic performance. The results reveal that the nature of the renewable energy source predominantly influences the selection of electrolyzers. Specifically, pure photovoltaic (PV) systems tend to favor PEMEL, with an optimal PEMEL:AEL capacity ratio of 2:1, whereas pure wind turbine (WT) systems and PV–WT hybrid systems are more suited to AEL, with corresponding AEL:PEMEL ratios of 8:3 and 7:3, respectively. The combined operation of wind–solar complementarity and diversified electrolyzers reduces the levelized cost of hydrogen (LCOH) to USD 4.52/kg, representing a 41.1% reduction compared to standalone PV systems, with a renewable energy utilization rate of 92.26%. Case studies confirm that collaborative AEL–PEMEL operation enhances system stability and efficiency, with PEMEL mitigating power fluctuations and AEL supplying baseload hydrogen production. This synergy improves hydrogen production efficiency, extends equipment lifespan, and provides a viable and theoretically sound solution for RHPS optimization. Full article

The rapid growth of renewable energy integration in modern power systems brings new challenges in terms of stability and quality of electricity supply. Hybrid AC/DC microgrids represent a promising solution to integrate photovoltaic panels (PV), wind turbines, fuel cells, and storage units with flexibility and efficiency. However, maintaining adequate power quality (PQ) under variable conditions of generation, load, and grid connection remains a critical issue. This paper presents the modelling, implementation, and validation of a hybrid AC/DC microgrid equipped with a fuzzy-logic-based energy management system (EMS). The study combines PQ assessment, measurement architecture, and supervisory control for technical compliance and economic efficiency. The microgrid integrates a combination of PV array, wind turbine, proton exchange membrane fuel cell (PEMFC), battery storage system, and heterogeneous AC/DC loads, all modelled in MATLAB/Simulink using a physical-network approach. The fuzzy EMS coordinates distributed energy resources by considering power imbalance, battery state of charge (SOC), and dynamic tariffs. Results demonstrate that the proposed controller maintains PQ indices within IEC/IEEE standards while eliminating short-term continuity events. The proposed EMS prevents harmful deep battery cycles, maintaining SOC within 30–90%, and optimises fuel cell activation, reducing hydrogen consumption by 14%. Economically, daily operating costs decrease by 10–15%, grid imports are reduced by 18%, and renewable self-consumption increases by approximately 16%. These findings confirm that fuzzy logic provides an effective, computationally light, and uncertainty-resilient solution for hybrid AC/DC microgrid EMS, balancing technical reliability with economic optimisation. Future work will extend the framework toward predictive algorithms, reactive power management, and hardware-in-the-loop validation for real-world deployment. Full article

The maritime industry is under increasing pressure to reduce greenhouse gas emissions, especially in countries such as Saudi Arabia that are actively working to transition to cleaner energy. In this paper, a new hybrid shipboard power system, which incorporates wind turbines, solar photovoltaic (PV) panels, proton-exchange membrane fuel cells (PEMFCs), and a battery energy storage system (BESS) together for propulsion and hotel load services, is proposed. A multi-loop Energy Management System (EMS) based on proportional–integral control (PI) is developed to coordinate the interconnections of the power sources in real time. In contrast to the widely reported model predictive or artificial intelligence optimization schemes, the PI-derived EMS achieves similar power stability and hydrogen utilization efficiency with significantly reduced computational overhead and full marine suitability. By taking advantage of the high solar irradiance and coastal wind resources in Saudi Arabia, the proposed configuration provides continuous near-zero-emission operation. Simulation results show that the PEMFC accounts for about 90% of the total energy demand, the BESS (±0.4 MW, 2 MWh) accounts for about 3%, and the stationary renewables account for about 7%, which reduces the demand for hydro-gas to about 160 kg. The DC-bus voltage is kept within ±5% of its nominal value of 750 V, and the battery state of charge (SOC) is kept within 20% to 80%. Sensitivity analyses show that by varying renewable input by ±20%, diesel consumption is ±5%. These results demonstrate the system’s ability to meet International Maritime Organization (IMO) emission targets by delivering stable near-zero-emission operation, while achieving high hydrogen efficiency and grid stability with minimal computational cost. Consequently, the proposed system presents a realistic, certifiable, and regionally optimized roadmap for next-generation hybrid PEMFC–battery–renewable marine power systems in Saudi Arabian coastal operations. Full article

In recent years, advancements in technologies related to hydrogen have facilitated the exploitation of this energy carrier in conjunction with renewable energies to meet the energy demands of diverse applications. This paper describes a pilot plant within the framework of a research and development (R&D) project aimed at utilizing hydrogen in both industrial and domestic sectors. To this end, this facility comprises six subsystems. Initially, a photovoltaic (PV) generator consisting of 48 panels is employed to generate electrical current from solar radiation. This PV array powers a proton exchange membrane (PEM) electrolyzer, which is responsible for producing green hydrogen by means of water electrolysis. The produced hydrogen is subsequently stored in a bottling storage system for later use in a PEM fuel cell that reconverts it into electrical energy. Finally, a programmable electronic load is utilized to simulate the electrical consumption patterns of various profiles. These physical devices exchange operational data with an open source supervisory system integrated by a set of Industry 4.0 (I4.0) and Internet of Things (IoT)-framed environments. Initially, Node-RED acts as middleware, handling communications, and collecting and processing data from the pilot plant equipment. Subsequently, this information is stored in MariaDB, a structured relational database, enabling efficient querying and data management. Ultimately, the Grafana environment serves as a monitoring platform, displaying the stored data by means of graphical dashboards. The system deployed with such I4.0/IoT applications places a strong emphasis on the continuous monitoring of the power inverter that serves as the backbone of the pilot plant, both from an energy flow and communication standpoint. This device ensures the synchronization, conversion, and distribution of electrical energy while simultaneously standing as a primary data source for the supervisory system. The results presented in this article describe the design of the system and provide evidence of its successful implementation. Full article

Algeria’s transition toward sustainable energy requires the exploitation of its abundant solar and wind resources for green hydrogen production. This study assesses the techno-economic feasibility of an off-grid PV/wind hybrid system integrated with a hydrogen subsystem (electrolyzer, fuel cell, and hydrogen storage) to supply both electricity and hydrogen to decentralized sites in Algeria. Using HOMER Pro, five representative Algerian regions were analyzed, accounting for variations in solar irradiation, wind speed, and groundwater availability. A deferrable water-extraction and treatment load was incorporated to model the water requirements of the electrolyzer. In addition, a comprehensive sensitivity analysis was conducted on solar irradiation, wind speed, and the capital costs of PV panels and wind turbines to capture the effects of renewable resource and investment cost fluctuations. The results indicate significant regional variation, with the levelized cost of energy (LCOE) ranging from 0.514 to 0.868 $/kWh, the levelized cost of hydrogen (LCOH) between 8.31 and 12.4 $/kg, and the net present cost (NPC) between 10.28 M$ and 17.7 M$, demonstrating that all cost metrics are highly sensitive to these variations. Full article

While community energy initiatives and pilot projects have demonstrated technical feasibility and economic benefits, their site-specific nature limits transferability to systematic, scalable investment models. This study addresses this gap by proposing a modular framework for Renewable Energy Valleys (REVs), developed from real-world Community Energy Lab (CEL) demonstrations in Crete, Greece, which is an island with pronounced seasonal demand fluctuation, strong renewable potential, and ongoing hydrogen valley initiatives. Four modular business schemes are defined, each representing different sectoral contexts by combining a baseline of 50 residential units with one representative large consumer (hotel, rural households with thermal loads, municipal swimming pool, or hydrogen bus). For each scheme, a mixed-integer linear programming model is applied to optimally size and operate integrated solar PV, wind, battery (BAT) energy storage, and hydrogen systems across three renewable energy penetration (REP) targets: 90%, 95%, and 99.9%. The framework incorporates stochastic demand modeling, sector coupling, and hierarchical dispatch schemes. Results highlight optimal technology configurations that minimize dependency on external sources and curtailment while enhancing reliability and sustainability under Mediterranean conditions. Results demonstrate significant variation in optimal configurations across sectors and targets, with PV capacity ranging from 217 kW to 2840 kW, battery storage from 624 kWh to 2822 kWh, and hydrogen systems scaling from 65.2 kg to 192 kg storage capacity. The modular design of the framework enables replication beyond the specific context of Crete, supporting the scalable development of Renewable Energy Valleys that can adapt to diverse sectoral mixes and regional conditions. Full article

Driven by the growing availability of funding opportunities, electrolyzers have become increasingly accessible, unlocking significant potential for large-scale green hydrogen production. The goal of this investigation is to develop a techno-economic optimization framework for the design of a stand-alone photovoltaic (PV)-driven hydrogen production and refueling station, with the explicit objective of minimizing the levelized cost of hydrogen (LCOH). The system integrates PV generation, a proton-exchange-membrane electrolyzer, battery energy storage, compression, and high-pressure hydrogen storage to meet the daily demand of a fleet of fuel cell buses. Results show that the optimal configuration achieves an LCOH of 11 €/kg when only fleet demand is considered, whereas if surplus hydrogen sales are accounted for, the LCOH reduces to 7.98 €/kg. The analysis highlights that more than 75% of total investment costs are attributable to PV and electrolysis, underscoring the importance of capital incentives. Financial modeling indicates that a subsidy of about 58.4% of initial CAPEX is required to ensure a 10% internal rate of return under EU market conditions. The proposed methodology provides a reproducible decision-support tool for optimizing off-grid hydrogen refueling infrastructure and assessing policy instruments to accelerate hydrogen adoption in heavy-duty transport. Full article

This work develops a replicable method for designing the optimal renewable hydrogen production facility, applicable to any site and based on technical parameters and actual equipment costs. The solution is based on the integration of photovoltaic (PV) energy with lithium-ion battery storage systems, which maximizes electrolyzer operating hours and significantly reduces the Levelized Cost of Hydrogen (LCOH). This study shows that increasing the inclination of the photovoltaic modules reduces the need for storage, optimizing operation and extending the electrolyzer’s annual operating hours. In the Seville case study, with current costs and efficiencies, a minimum LCOH of €4.43/kg was achieved, a value well below market benchmarks, opening the door to a potentially competitive industrial business. The analysis confirms that electrolyzer efficiency—particularly specific power consumption—is the most important factor in reducing costs, while technological progress in photovoltaics, storage, and equipment promises further reductions in the coming years. Overall, the proposed methodology offers a practical and scalable tool to accelerate the economic viability of green hydrogen in a variety of contexts. Full article

This study investigates an integrated solar-powered system for wastewater treatment and hydrogen production, combining solar PV, a humidification–dehumidification (HDH) system, solar thermal collectors, and electrolysis. The objective is to evaluate the feasibility of utilizing industrial wastewater for both clean water production and green hydrogen generation. A transient analysis is conducted using TRNSYS and EES software, modeling a system designed to process 4000 kg of wastewater daily. The results indicate that the HDH system produces 300 kg of clean water per hour, while the electrolyzer generates approximately 66.5 kg of hydrogen per hour. The solar PV system operates under the weather conditions of Kohat, Pakistan. This integrated approach demonstrates significant potential for sustainable wastewater treatment and renewable energy production, offering a promising solution for industrial applications. Full article