Renewable Energy Systems Research Articles

Under the background of “dual-carbon”, the development of energy internet is an inevitable trend for China’s low-carbon energy transition. This paper proposes a hydrogen-coupled electrothermal integrated energy system (HCEH-IES) operation mode and optimizes the source-side structure of the system from the level of carbon trading policy combined with low-carbon technology, taps the carbon reduction potential, and improves the renewable energy consumption rate and system decarbonization level; in addition, for the operation optimization problem of this electric–gas–heat integrated energy system, a flexible energy system based on electric–gas–heat is proposed. Furthermore, to address the operation optimization problem of the HCEH-IES, a deep reinforcement learning method based on Soft Actor–Critic (SAC) is proposed. This method can adaptively learn control strategies through interactions between the intelligent agent and the energy system, enabling continuous action control of the multi-energy flow system while solving the uncertainties associated with source-load fluctuations from wind power, photovoltaics, and multi-energy loads. Finally, historical data are used to train the intelligent body and compare the scheduling strategies obtained by SAC and DDPG algorithms. The results show that the SAC-based algorithm has better economics, is close to the CPLEX day-ahead optimal scheduling method, and is more suitable for solving the dynamic optimal scheduling problem of integrated energy systems in real scenarios.

In recent years, as the cost of renewable energy generating technology has decreased, there has been an increase in research devoted to the appropriate scale of renewable off-grid systems. Many of these studies use daily load profiles to predict electricity consumption, which are occasionally supplemented with seasonal or random components. Such techniques often neglect the existing possible case-specific association between renewable energy supply and energy demand, particularly the load's inherent variability in terms of extreme values or ramp rates. The Cost of Energy and Net Present Cost of a Lithium-Ion battery-based system are determined to be 30% and 35% lower than those of a Lead Acid battery-based system, respectively. The research is further expanded to include sensitivity analysis for a variety of input factors, including discount rate, photovoltaic cost, battery cost, fuel cost, wind speed, and design flow rate. To define the final energy dynamic and estimate -effective arrangement for the examined region, several groups of wind turbines, PV solar systems, and biomass generators are simulated, modelled, and optimised. The HOMER computer programme was used to assess the techno-economic viability of the proposed projects, taking into account the Net Present Cost (NPC) and the Levelized Cost of Energy (LCOE) as cost factors

Neodymium-based permanent magnets are fundamental to modern technologies, underpinning high-performance applications in electronics, renewable energy, and advanced medical systems. Among emerging neodymium compounds, neodymium nitride (NdN) has attracted significant attention due to its unique electronic structure, where strongly localized 4f orbitals and strong spin-orbit coupling are anticipated to drive exceptional magnetic behavior. Here, we show conclusive experimental evidence of orbital angular momentum-driven ferromagnetic ordering and prominent magnetic anisotropy in epitaxial, near-stoichiometric NdN thin films synthesized using ultrahigh vacuum deposition techniques. Magnetization and X-ray magnetic circular dichroism measurements reveal a dominant 4f orbital moment of 5.14 μB, contributing to a total magnetic moment of 2.43 μB per formula unit at 4 K, close to the first-principles density functional theory calculated values. Complementary synchrotron-radiation photoelectron spectroscopy, along with the theoretical calculations, uncovers occupied 4f states ∼6.4 eV below the Fermi level, contributing to the orbital-driven ferromagnetism in NdN. Moreover, the high crystalline quality of the NdN films is further supported by the structural characterization and vibrational properties. The intrinsic orbital angular momentum-driven magnetism of NdN positions it as a promising platform for next-generation orbitronic devices beyond conventional spintronics.

Research on water wave metamaterials based on local resonance has advanced rapidly. However, their application to floating structures for controlling surface gravity waves remains underexplored. In this work, we introduce the floating metaplate, a periodic array of resonators on a floating plate that leverages locally resonant bandgaps to effectively manipulate surface gravity waves. We employ the eigenfunction matching method combined with Bloch’s theorem to solve the wave–structure interaction problem and obtain the band structure of the floating metaplate. An effective model based on averaging is developed, which agrees well with the results of numerical simulation, elucidating the mechanism of bandgap formation. Both frequency- and time-domain simulations demonstrate the floating metaplate’s strong wave attenuation capabilities. Furthermore, by incorporating a gradient in the resonant frequencies of the resonators, we achieve the rainbow trapping effect, where waves of different frequencies are reflected at distinct locations. This enables the design of a broadband wave reflector with a tuneable operation frequency range. Our findings may lead to promising applications in coastal protection, wave energy harvesting and the design of resilient offshore renewable energy systems.

The research will focus on the assessment, feasibility, and hydropower potential estimation in the Gedeo zone Dilla Ethiopia with an analysis of the viability of the systems for rural community electrification. Waleme River Catchment is located in the Rift Valley basin, covering an area of around 80 km2 and It extends up to 30 km with a river basin This hydropower plant considers the reliability, sustainability, and environmental protections of supplying electricity to the village, particularly for remote communities where grid extension is not suitable. The hydropower renewable energy system will be the best solution for the off-grid areas. Due to international policy and the reduction of carbon dioxide emissions, the generation of electricity using renewable energy sources has become more significant. Currently, it is among the most intriguing and eco-friendly technology solutions. The hydropower potential of the site will be analyzed by measuring the gross head with the help of a Geographical Position System (GPS) and stream flow data analysis. The proposed research will be completed within two years with a total estimated budget of 363,075 ETB, by site surveying, data collection, and estimating the hydropower potential of Waleme River and finally the paper will be prepared for publication.

This study presents a novel integrative review of 329 review articles on sustainable buildings from 2015 to 2025, combining quantitative bibliometrics with qualitative insights to map the field’s evolution and pinpoint critical future pathways. Seven core research themes were identified in this study: (1) material and advanced construction technologies, (2) energy efficiency and renewable energy systems, (3) digitalization and smart technologies, (4) policy, standards, and certification, (5) sustainable design and optimization, (6) stakeholder and socio-economic factors, (7) other (cross-cutting) topics. Key findings reveal a surge in publications post-2020, driven by global net-zero commitments, with China, Australia, and Hong Kong leading research output. Innovations in low-carbon materials (e.g., hemp concrete, geopolymers), artificial intelligent (AI)-driven energy optimization, and digital tools (e.g., building information modeling (BIM), internet of things (IoT)) dominate recent advancements. However, challenges persist, including policy fragmentation, scalability barriers for sustainable materials, and socio-economic disparities in green building adoption. The study proposes a unique future research framework emphasizing nanotechnology-enhanced materials, interpretable AI models, harmonized global standards, and inclusive stakeholder engagement. This review provides actionable recommendations to bridge gaps between technological innovation, policy frameworks, and practical implementation in sustainable construction.

The ongoing energy transition and decarbonization efforts have prompted the development of Hybrid Renewable Energy Systems (HRES) capable of integrating multiple generation and storage technologies to enhance energy autonomy. Among the available options, hydrogen has emerged as a versatile energy carrier, yet most studies have focused either on stationary applications or on mobility, seldom addressing their integration withing a single framework. In particular, the potential of Metal Hydride (MH) tanks remains largely underexplored in the context of sector coupling, where the same storage unit can simultaneously sustain household demand and provide in-house refueling for light-duty fuel-cell vehicles. This study presents the design and analysis of a residential-scale HRES that combines photovoltaic generation, a PEM electrolyzer, a lithium-ion battery and MH storage intended for direct integration with a fuel-cell electric microcar. A fully dynamic numerical model was developed to evaluate system interactions and quantify the conditions under which low-pressure MH tanks can be effectively integrated into HRES, with particular attention to thermal management and seasonal variability. Two simulation campaigns were carried out to provide both component-level and system-level insights. The first focused on thermal management during hydrogen absorption in the MH tank, comparing passive and active cooling strategies. Forced convection reduced absorption time by 44% compared to natural convection, while avoiding the additional energy demand associated with thermostatic baths. The second campaign assessed seasonal operation: even under winter irradiance conditions, the system ensured continuous household supply and enabled full recharge of two MH tanks every six days, in line with the hydrogen requirements of the light vehicle daily commuting profile. Battery support further reduced grid reliance, achieving a Grid Dependency Factor as low as 28.8% and enhancing system autonomy during cold periods.

Urban areas are increasingly challenged by the combined effects of climate change, rapid population growth, and high energy demand. The integration of renewable energy systems, such as photovoltaic (PV) panels, and nature-based solutions, such as green roofs, represents a key strategy for sustainable urban development. This study evaluates the spatial potential for PV and green roof implementation in Iași, Romania, using moderate to high-resolution geospatial datasets, including the ALOS AW3D30 Digital Surface Model (DSM) and the Copernicus Urban Atlas 2018, processed in ArcMap 10.8.1 and ArcGIS Pro 2.6.0. Solar radiation was computed using the Area Solar Radiation tool for the average year 2023, while roof typology (flat vs. pitched) was derived from slope analysis. Results show significant spatial heterogeneity. The Copou neighborhood has the highest PV-suitable roof share (73.6%) and also leads in green roof potential (46.6%). Integrating PV and green roofs can provide synergistic benefits, improving energy performance, mitigating urban heat islands, managing stormwater, and enhancing biodiversity. These findings provide actionable insights for urban planners and policymakers aiming to prioritize green infrastructure investments and accelerate the local energy transition.

This paper presents a novel Hybrid Beluga Whale Optimization (HBWO) algorithm enhanced with multi-strategy mechanisms for Maximum Power Point Tracking (MPPT) in photovoltaic (PV) systems integrated with an Open-End Winding Induction Motor (OEWIM) drive. The HBWO algorithm is developed to ensure fast and accurate maximum power extraction under dynamic irradiance, partial shading, and varying load conditions. The motor drive is governed by an improved Direct Torque Control (DTC) scheme featuring a five-level torque hysteresis controller and an optimized switching table, resulting in reduced torque ripple and enhanced system stability. Simulation-based performance analysis, conducted in MATLAB/SIMULINK, benchmarks the proposed method against traditional MPPT algorithms including Perturb & Observe (P&O), Particle Swarm Optimization (PSO), Chimp Optimization Algorithm (COA), and Giza Pyramid Construction (GPC). Quantitative results demonstrate that HBWO achieves a DC link voltage rise time of 0.11s, overshoot of 0.382%, settling time of 0.17s, steady-state ripple of 0.50%, and steady-state error of only 0.04%. In terms of motor speed control, the system delivers a rise time of 0.1s, overshoot of 0.37%, settling time of 0.18s, and steady-state error of 0.03%. Furthermore, the torque ripple is minimized to just 0.5%, significantly outperforming conventional algorithms such as P&O (5.6%) and COA (2.2%). These improvements confirm the HBWO algorithm's superiority in terms of convergence speed, control accuracy, and system robustness. The integration of advanced hybrid optimization with refined motor control architecture offers a comprehensive and efficient solution for renewable energy systems. This work contributes to the development of intelligent PV-driven motor systems capable of maintaining high performance and stability under real-world, variable conditions.

Abstract This work aims at designing and developing a hybrid renewable energy system (HRES) that can accommodate rural sustainability by utilizing locally accessible biomass resources, wind speeds, and solar radiation within concrete communities. An important consequence is that it will enable the best energy‐generating arrangement to be recognized in order to further increase per capita energy availability (EPC) and the standard of life as a whole. The difficulties tackled in the research include which energy sources to choose and which optimization of the system component sizes to determine with the help of a hybrid optimization model where energy balances are based on priorities. System performance was analyzed with multi‐objective Moth Swarm Optimization (MOMSA). The given HRES showed that the share of renewable energy in the system grew by 30% in comparison with the current system and the energy exported into the grid increased by 14%. Feasibility analysis also indicated great gains, such as a System Net Present Cost (NPC) of 53.8 million Indian rupees, a 35/kWh Cost of Energy (COE), maximum Renewable Resource Penetration (RRP), and minimum Power Loss Probability (PLP). These findings demonstrate the possibilities of the system to improve the energy sustainability of the rural areas and meet national energy delivery objectives.

This study presents a techno-economic assessment of hybrid renewable energy systems for Perhentian and Tioman Islands, Malaysia, with the goal of reducing diesel dependency and supporting sustainable electrification. Using HOMER Pro simulation software, various configurations combining solar photovoltaic (PV), wind, and mini-hydropower sources with energy storage systems (ESS) were analyzed. For Perhentian, the optimal configuration consists of a 177.24 MW solar PV system and 23 ESS units, resulting in a Net Present Cost (NPC) of RM51.1 million and a Levelized Cost of Energy (LCOE) of RM0.839/kWh. For Tioman Island, the optimal system integrates 1.19 GW solar PV, 533 kW mini-hydro, and 293 ESS units, achieving an NPC of RM451 million and LCOE of RM0.803/kWh. Comparative analysis with diesel-based systems shows significant cost advantages and environmental benefits in favor of renewable-based configurations. These findings demonstrate the viability of hybrid renewable systems for remote island electrification and offer policy-relevant insights for Malaysia's National Energy Transition Roadmap (NETR) and rural decarbonization efforts.

Solar Chimney Power Plants (SCPPs) are a promising technology in the advancement of renewable energy systems. Among the various important design parameters, the geometry of the absorber surface plays a pivotal role in determining system performance. This study was conducted to evaluate the impact of the absorber surface geometry and height on the thermal and aerodynamic behavior of SCPPs. Five absorber configurations were investigated: standard, 3-square, 4-square, 5-square, and 6-square arrangements. Additionally, the effect of varying absorber surface heights was examined to identify optimal design parameters. The simulation results demonstrate that the 5-square configuration delivered the highest performance relative to the standard flat-absorber system, particularly at an absorber height of H₀ = 7.5 cm, where the maximum airflow velocity reached 24.45 m/s and the power output peaked at 258.38 W. The 3-square configuration also showed notable performance at H₀ = 5 cm, generating up to 156.82 W and achieving the lowest internal atmospheric pressure, indicative of improved convective flow. Overall, the findings emphasize the substantial influence of absorber surface design on SCPP efficiency, confirming that multi-square absorber configurations can significantly enhance power generation through improved thermal and fluid dynamic behavior.

This study investigates the optimization of a two-degree-of-freedom PID (2DOF-PID) controller using the Ant Lion Optimizer (ALO) for enhanced frequency regulation in a hybrid Photovoltaic (PV)–Reheat Thermal Power System under sudden load disturbances. To benchmark performance, conventional PID and PI controllers were also tested to assess their ability to minimize the frequency fluctuations and manage the inter-area power exchanges. Simulations were carried out in MATLAB/Simulink using a dual-area dynamic model, and the performance was evaluated based on standard control metrics, including the settling time, overshoot/undershoot, and the Integral of Absolute Error (IAE). The results indicate that the ALO-optimized 2DOF-PID controller reduced the average settling time by nearly 40% and IAE by 12.6%, compared to the best-performing PID controller in the benchmark group. These findings highlight the advantages of combining the 2DOF-PID architecture with an evolutionary optimization strategy, offering improved dynamic and nonlinear control performance. The proposed approach shows strong potential for application in next-generation renewable energy systems and smart grids.

Abstract Integrating renewable energy sources into modern power networks presents challenges like reduced grid inertia and low-frequency oscillations. The displacement of conventional synchronous generators weakens system inertia, making grids more susceptible to disturbances. Additionally, variable output from renewables can trigger low-frequency oscillations, threaten overall stability and require advanced control strategies for mitigation. Promising alternatives include pumped storage hydro power generation and advanced control algorithms like fuzzy logic, neural networks, and hybrid optimization techniques, though these still require further research and development. This research suggests a coordinated control approach that combines wind, Solar Photovoltaic (SPV), and pumped storage hydro generators with a turbine governor and unified power flow controller to efficiently mitigate issues. The primary goals are to: (a) Optimize the coordination between the unified power flow controller and the pumped storage governor in order to generate an efficient damping torque for problems during changeable solar and wind inputs. (b) To increase the pumped storage governor’s controllability while making sure it offers sufficient dampening for power system problems. The control systems aim to minimize deviations from desired operating points, focusing on both speed and real power deviations. This is accomplished by combining Linear Quadratic Regulator (LQR) and Proportional Derivative (PD) controllers, which increase the hybrid system’s efficacy. To fine-tune the suggested controller, a novel optimization technique: the Dynamic Opposite Learning-based Enhanced Osprey Optimization Algorithm (DOLOA) is proposed. This approach enhances the coordinated control strategy, enabling it to effectively mitigate low-frequency oscillations and maintain power system stability, even under significant disturbances, such as sudden fluctuations in solar photovoltaic and wind energy penetration. Simulations on the MATLAB/Simulink platform are used to test the performance of the suggested technique and compared to Tilt Integral Derivative (TID) and Fractional Order Proportional Integral Derivative (FOPID). The proposed control strategy achieves optimal performance, reducing frequency variations to within ±0.0001 p.u. over 15 s, outperforming TID and FOPID controllers.

This study presents a comprehensive design and performance validation of a three-phase, 900-watt Inner-Rotor Radial Flux Surface-Mounted Permanent Magnet Synchronous Generator (IR-RF-SPMSG). The proposed generator, featuring 10 poles and 30 slots with a 0.9 pole arc ratio, is designed analytically and simulated using 3D finite element modeling. The key contributions include the validation of the air-gap flux density using leakage and reluctance correction factors, the detailed modeling of the leakage inductance components, and an accurate three-phase winding configuration. The comparison between the analytical and simulation results yields errors below 1% for the air-gap flux density (Bg), back-EMF (Eph), phase current (Iph), terminal voltage (Vph), and three-phase output power (Sout). The methodology significantly improves the terminal voltage prediction under load and ensures waveform integrity, offering a reliable design reference for low-speed renewable energy systems.

Floating photovoltaic installations (FPV) are among the promising emerging marine renewable energy systems contributing to future global energy transition strategies. FPVs can be integrated within existing offshore wind farms, contributing to more efficient use of marine space. This complementarity has gained increasing attention as a sustainable approach to enhance green energy production while reducing offshore grid infrastructure costs, particularly in the North Sea. This study presents a first assessment to quantify the mid- and far-field hydrodynamic effects of FPVs (elevated design) deployed within an existing offshore wind farm (OWF) in the Belgian part of the North Sea. A subgrid-scale parameterization was adopted into the 3D hydrodynamic model COHERENS to assess impacts on four key hydrodynamic metrics: surface irradiance reduction due to shading, changes in current velocity fields, turbulent kinetic energy production, and variations in current-induced bottom shear stress. Four scenarios were compared: a baseline without structures, a scenario with only offshore wind turbines and two combined wind and photovoltaic configurations (sparse and dense). At farm scale, simulations showed small effects of FPV shading on sea surface temperature (< 0.1°C), but significant reductions in current speed, increased turbulent kinetic energy mainly beneath the floaters, and a noticeable impact on bottom shear stress. This hydrodynamic modeling study constitutes a first step toward a comprehensive environmental impact assessment of FPVs, particularly in relation to their biogeochemical effects on the water column and benthic habitats. The findings provide valuable insights to support sustainable marine spatial planning, environmental assessments, and industrial design strategies in the North Sea and beyond.

The transition toward sustainable energy systems necessitates innovations that overcome the limitations of conventional electrochemical systems. Redox-mediated flow cell systems emerge as a transformative paradigm by decoupling energy storage, conversion, and chemical processes from traditional electrode-bound reactions. These systems employ soluble redox mediators to shuttle electrons between electrodes and spatially separated reactive phases (solid, liquid, or gas), thereby enabling unprecedented operational flexibility and scalability. This standpoint underscores the adaptability of redox-mediated electrified systems across a range of applications, encompassing high-energy-density redox targeting-based flow batteries, fuel cells, electrified CO2 capture, sustainable chemical synthesis, waste recycling, etc. The rational design of redox-active materials is central to their success, with precise alignment of redox potentials, enhanced electron-transfer kinetics, and robust stability underpinning performance. The challenges of new materials development, system durability, and cost-effectiveness can be addressed through advances in experimental measurement, computational modeling, operando characterization, and interdisciplinary collaboration. Moving forward, the integration of redox-mediated technologies with renewable energy systems and industrial processes is predicted to transform energy and chemical landscapes. The integration of laboratory innovations with real-world deployment facilitates a pathway to decarbonization, resource efficiency, and the circular economy. This perspective emphasizes the pivotal functions of redox-mediated architectures in fostering a robust, electrified future, where the convergence of energy storage, environmental stewardship, and sustainable chemical production is pivotal in addressing global challenges.

Abstract Energy storage technologies have become increasingly essential in addressing the global transition toward renewable energy systems. The rapid global shift toward renewable energy has made efficient and reliable energy storage technologies (ESTs) essential for addressing the intermittency of solar, wind, and other clean energy sources. Recent research highlights significant advancements in battery chemistries, supercapacitors, hydrogen storage, and thermal energy systems; however, persistent challenges such as high manufacturing costs, limited cycle life, low energy density, and environmental impacts continue to hinder large-scale implementation. Despite the growing number of studies, there is a lack of integrated knowledge that systematically maps recent trends, material innovations, and application specific challenges. This review aims to bridge that gap by comprehensively analyzing advancements in energy storage technologies over the past decade, evaluating key performance indicators such as energy and power density, efficiency, and lifecycle sustainability. By synthesizing findings from peer-reviewed literatures this study identifies critical barriers and emerging strategies such as nanostructured materials, hybrid systems, and circular economy approaches that could redefine future energy storage landscapes. The conclusions underscore the urgent need for interdisciplinary research, material optimization, and cost-effective designs to accelerate the development and deployment of next-generation storage technologies.

This study investigates the integrated impact of high penetration renewable energy sources specifically photovoltaic (PV) farms and wind turbine generators (WTGs) based on Doubly-Fed Induction Generators (DFIG), Squirrel Cage Induction Generators (SCIG), and Permanent Magnet Synchronous Generators (PMSG) on power grid performance under both normal and fault conditions. A hybrid renewable energy system architecture is developed and simulated using MATLAB/Simulink to analyze its dynamic behavior, fault ride-through capability, reactive power demand, and harmonic distortion. The methodology includes detailed modeling of PV arrays, WTGs, and associated power electronic converters, enabling the assessment of system performance during symmetrical (LLLG) and asymmetrical (LG) faults. Results reveal that while DFIGs and PMSGs deliver efficient active power generation, SCIGs exhibit higher reactive power consumption and lower dynamic stability. The study also evaluates total harmonic distortion (THD) and short-circuit ratio (SCR) for each generator type, showing that PMSGs achieve the lowest THD and maintain operational resilience under weak grid conditions (low SCR). These findings offer practical guidance for enhancing grid compliance, stability, and performance in future multi-source renewable energy systems.

This study presents a comparative analysis of efficiency and harmonic generation in Triple Active Bridge (TAB) converters under two operating configurations: Case I, with one input source and two loads, and Case II, with two input sources and one load. Two modulation strategies, Single-Phase Shift (SPS) and Dual-Phase Shift (DPS), are evaluated through frequency-domain modeling and simulations performed in MATLAB/Simulink. The analysis is complemented by experimental validation on a laboratory prototype. The results show that DPS reduces harmonic amplitudes, decreases conduction losses, and improves output waveform quality, leading to higher efficiency compared to SPS. Harmonic current spectra and total harmonic distortion (THD) are analyzed to quantify the impact of each modulation method. The findings highlight that DPS is more suitable for applications requiring stable power transfer and improved efficiency, such as renewable energy systems, electric vehicles, and multi-source DC microgrids.