Search Results (161)

This study proposes a new air treatment system that integrates dehumidification, cooling, and water recovery using a Horizontal Air–Ground Heat Exchanger (HAGHE) combined with Peltier cells. The airflow generated by a fan flows through an HAGHE until it meets a septum on which Peltier cells are placed, and then separates into two distinct streams that lap the two surfaces of the Peltier cells: one stream passes through the cold surfaces, undergoing both sensible and latent cooling with dehumidification; the other stream passes through the hot surfaces, increasing its temperature. The two treated air streams may then pass through a mixing chamber, where they are combined in the appropriate proportions to achieve the desired air supply conditions and ensure thermal comfort in the indoor environment. A Computational Fluid Dynamics (CFD) analysis was carried out to simulate the thermal interaction between the HAGHE and the surrounding soil. The simulation focused on a system installed under the subtropical climate conditions of Nairobi, Africa. The simulation results demonstrate that the HAGHE system is capable of reducing the air temperature by several degrees under typical summer conditions, with enhanced performance observed when the soil is moist. Condensation phenomena were triggered when the relative humidity of the inlet air exceeded 60%, contributing additional cooling through latent heat extraction. The proposed HAGHE–Peltier system can be easily powered by renewable energy sources and configured for stand-alone operation, making it particularly suitable for off-grid applications. Full article

This study presents the design and techno-economic comparison of two standalone photovoltaic (PV) systems, each supplying a 1 kW critical load with 100% reliability under Cairo’s climatic conditions. These systems are modeled for both the constant and the night load scenarios, accounting for the worst-case weather conditions involving 3.5 consecutive cloudy days. The primary comparison focuses on traditional lead-acid battery storage versus green hydrogen storage via electrolysis, compression, and fuel cell reconversion. Both the configurations are simulated using a Python-based tool that calculates hourly energy balance, component sizing, and economic performance over a 21-year project lifetime. The results show that the PV/H₂ system significantly outperforms the PV/lead-acid battery system in both the cost and the reliability. For the constant load, the Levelized Cost of Electricity (LCOE) drops from 0.52 USD/kWh to 0.23 USD/kWh (a 56% reduction), and the payback period is shortened from 16 to 7 years. For the night load, the LCOE improves from 0.67 to 0.36 USD/kWh (a 46% reduction). A supplementary cost analysis using lithium-ion batteries was also conducted. While Li-ion improves the economics compared to lead-acid (LCOE of 0.41 USD/kWh for the constant load and 0.49 USD/kWh for the night load), this represents a 21% and a 27% reduction, respectively. However, the green hydrogen system remains the most cost-effective and scalable storage solution for achieving 100% reliability in critical off-grid applications. These findings highlight the potential of green hydrogen as a sustainable and economically viable energy storage pathway, capable of reducing energy costs while ensuring long-term resilience. Full article

Off-grid and isolated rural communities in developing countries with limited resources require energy supplies for daily residential use and social, economic, and commercial activities. The use of data from space assets and space-based solar power is a feasible solution for addressing ground-based energy insecurity when harnessed in a hybrid manner. Advances in space solar power systems are recognized to be feasible sources of renewable energy. Their usefulness arises due to advances in satellite and space technology, making valuable space data available for smart grid design in these remote areas. In this case study, an isolated village in Namibia, characterized by high levels of solar irradiation and limited wind availability, is identified. Using NASA data, an autonomous hybrid system incorporating a solar photovoltaic array, a wind turbine, storage batteries, and a backup generator is designed. The local load profile, solar irradiation, and wind speed data were employed to ensure an accurate system model. Using HOMER Pro software V 3.14.2 for system simulation, a more advanced AI optimization was performed utilizing Grey Wolf Optimization and Harris Hawks Optimization, which are two metaheuristic algorithms. The results obtained show that the best performance was obtained with the Grey Wolf Optimization algorithm. This method achieved a minimum energy cost of USD 0.268/kWh. This paper presents the results obtained and demonstrates that advanced optimization techniques can enhance both the hybrid system’s financial cost and energy production efficiency, contributing to a sustainable electricity supply regime in this isolated rural community. Full article

For a new distribution network with energy storage and a flexible multi-state switch (FMSS), several problems of multi-mode operation and switching, such as the unbalance of feeder loads and feeder faults, among others, should be considered. This paper forwards a coordination control strategy to address the above challenges faced by the FMSS under grid-connected operations. To tackle the multi-mode operation problem, the system’s operational state is divided into multiple working modes according to the operation states of the system, the positions and number of fault feeders, the working states of the transformers, and the battery’s state of charge. To boost the system’s operational reliability and load balance and extend the power supply time for the fault load, the appropriate control objectives in the coordination control layer and control strategies in the equipment layer for different working modes are established for realizing the above multi-directional control objectives. To resolve the phase asynchrony issue among the fault load and other normal working loads caused by the feeder fault, the off-grid phase-locked control based on the V/f control strategy is applied. To mitigate the bus voltage fluctuation caused by the feeder fault switching, the switching control sequence for the planned off-grid is designed, and the power feed-forward control strategy of the battery is proposed for the unplanned off-grid. The simulation results show that the proposed control strategy can ensure the system’s power balance and yield a high-quality flexible power supply during the grid-connected operational state. Full article

To explore the feasibility of renewable hybrid energy systems for expressway infrastructure, this study proposes a scenario-based design methodology integrating solar, wind, and hydropower resources within the expressway corridor. A case study was conducted on a highway service area located in southern China, where a solar/wind/hydro hybrid energy system was developed based on the proposed approach. Using the HOMER Pro 3.14 software platform, the system was simulated and optimized under off-grid conditions, and a sensitivity analysis was conducted to evaluate performance variability. The results demonstrate that the strategic integration of corridor-based natural resources—solar irradiance, wind energy, and hydrodynamic potential—enables the construction of a technically and economically viable hybrid energy system. The system includes 382 kW of PV, 210 kW of wind, 80 kW of hydrokinetic power, a 500 kW diesel generator, and 180 kWh of battery storage, forming a hybrid configuration for a stable and reliable energy supply. The optimized configuration can supply up to 1,095,920 kWh of electricity annually at a minimum levelized cost of energy of USD 0.22/kWh. This system reduces CO₂ emissions by 23.2 tons/year and NO_x emissions by 23 kg/year. demonstrating strong environmental performance and long-term sustainability potential. Full article

Off-grid renewable energy hydrogen production is a crucial approach to enhancing renewable energy utilization and improving power system stability. However, the strong stochastic fluctuations of wind and solar power pose significant challenges to electrolyzer reliability. While hybrid energy storage systems (HESS) can mitigate power fluctuations, traditional power allocation rules based solely on electrolyzer power limits and HESS state of charge (SOC) boundaries result in insufficient energy supply capacity and unstable electrolyzer operation. To address this, this paper proposes a two-stage power optimization method integrating rule-based allocation with algorithmic optimization for wind–solar hydrogen production systems, considering reserved energy storage. In Stage I, hydrogen production power and HESS initial allocation are determined through the deep coupling of real-time electrolyzer operating conditions with reserved energy. Stage II employs an improved multi-objective particle swarm optimization (IMOPSO) algorithm to optimize HESS power allocation, minimizing unit hydrogen production cost and reducing average battery charge–discharge depth. The proposed method enhances hydrogen production stability and HESS supply capacity while reducing renewable curtailment rates and average production costs. Case studies demonstrate its superiority over three conventional rule-based power allocation methods. Full article

The adoption of wind energy is pivotal for advancing sustainable power systems, particularly in off-grid microgrids where infrastructure limitations hinder conventional energy solutions. The inherent variability of wind generation, however, challenges grid reliability and demand–supply balance, necessitating accurate forecasting models. This study proposes a hybrid framework for short-term wind speed prediction, integrating deep learning (Long Short-Term Memory, LSTM) and ensemble methods (random forest, Extra Trees) to exploit their complementary strengths in modeling temporal dependencies. A multivariate approach is adopted using meteorological data (including wind speed, temperature, humidity, and pressure) to capture complex weather interactions through a structured time-series design. The framework also includes a feature selection stage to identify the most relevant predictors and a hyperparameter optimization process to improve model generalization. Three wind speed variables, maximum, average, and minimum, are forecasted independently to reflect intra-day variability and enhance practical usability. Validated with real-world data from Cuenca, Ecuador, the LSTM model achieves superior accuracy across all targets, demonstrating robust performance for real-world deployment. Comparative results highlight its advantage over tree-based ensemble techniques, offering actionable strategies to optimize wind energy integration, enhance grid stability, and streamline renewable resource management. These insights support the development of resilient energy systems in regions reliant on sustainable microgrid solutions. Full article

The use of solar photovoltaic systems for power generation requires efficient battery energy storage systems to ensure a steady and constant supply for self-sufficient power generation and off-grid areas. “Vision 2030” is Saudi Arabia’s strategy for reducing the country’s dependence on oil by 50% through investment in clean, renewable resources by 2030. This paper reviews the latest advancements in battery technologies designed for solar photovoltaic panels through a detailed comparative analysis of performance, energy storage capacity, efficiency, lifespan, cost, safety, and environmental impact for residential applications in the Kingdom of Saudi Arabia and those available in the United States of America. The performance of the advanced lithium-ion battery technology available in the USA surpasses that in the Kingdom of Saudi Arabia. The findings underscore the need for investments by the Kingdom of Saudi Arabia in advanced battery manufacturing technologies to improve the availability of different battery types and capacities and achieve the objectives outlined in the Kingdom of Saudi Arabia’s Vision 2030. Full article

The reduction of harmful emissions is shaping trends across many industries, including architecture and building. With rising ecological awareness and the threat of climate change, architects, construction engineers, and developers are focusing on innovative solutions to minimize the construction sector’s environmental impact. This paper presents a technical and management approach system using renewable energy sources, based on an existing single-family house with known energy consumption. The aim is to achieve energy independence by relying solely on on-site electricity generation and storage, while remaining connected to water and sewage infrastructure. Utilizing renewable energy sources enhances self-sufficiency and investment profitability. The study evaluates the house’s energy consumption to optimally select electricity supply solutions, including a small wind farm and photovoltaic installation integrated with appropriate electricity storage. This is crucial due to the air heat pump used for heating and domestic hot water, which requires electricity. An hourly simulation of the system’s operation over a year verified the adequacy of the selected devices. Additionally, two different locations were analyzed to assess how varying climate and wind conditions influence the design and performance of off-grid energy systems. The analysis showed that solar and wind systems can meet annual energy demand, but limited storage capacity prevents full autonomy. Replacing the heat pump with a biomass boiler reduces electricity use by about 25% and battery needs by 40%, though seasonal energy surpluses remain a challenge. This concept aligns with the goal of achieving climate neutrality by 2050. Full article

Transitioning to clean energy in off-grid remote locations is essential to reducing fossil-fuel-generated greenhouse gas emissions and supporting renewable energy growth. While hybrid renewable energy systems (HRES), including multiple renewable energy (RE) sources and energy storage systems are instrumental, it requires technical reliability with economic efficiency. This study examines the feasibility of an HRES incorporating solar, wind, hydrogen, and biofuel energy at a remote location in Australia. An electric vehicle charging load alongside a residential load is considered to lower transportation-based emissions. Additionally, the input data (load profile and solar data) is validated through statistical analysis, ensuring data reliability. HOMER Pro software is used to assess the techno-economic and environmental performance of the hybrid systems. Results indicate that the optimal HRES comprising of photovoltaic, wind turbines, fuel cell, battery, and biodiesel generators provides a net present cost of AUD 9.46 million and a cost of energy of AUD 0.183, outperforming diesel generator-inclusive systems. Hydrogen energy-based FC offered the major backup supply, indicating the potential role of hydrogen energy in maintaining reliability in off-grid hybrid systems. Sensitivity analysis observes the effect of variations in biodiesel price and electric load on the system performance. Environmentally, the proposed system is highly beneficial, offering zero carbon dioxide and sulfur dioxide emissions, contributing to the global net-zero target. The implications of this research highlight the necessity of a regional clean energy policy facilitating energy planning and implementation, skill development to nurture technology-intensive energy projects, and active community engagement for a smooth energy transition. Potentially, the research outcome advances the understanding of HRES feasibility for remote locations and offers a practical roadmap for sustainable energy solutions. Full article

Standalone wind–solar–diesel–storage microgrids serve as a crucial solution for achieving energy self-sufficiency in remote and off-grid areas, such as rural regions and islands, where conventional power grids are unavailable. Addressing scheduling optimization challenges arising from the intermittent nature of renewable energy generation and the uncertainty of load demand, this paper proposes an adaptive optimization scheduling method (DQN-PSO) that integrates Deep Q-Network (DQN) with Particle Swarm Optimization (PSO). The proposed approach leverages DQN to assess the operational state of the microgrid and dynamically adjust the key parameters of PSO. Additionally, a multi-strategy switching mechanism, incorporating global search, local adjustment, and reliability enhancement, is introduced to jointly optimize both clean energy utilization and power supply reliability. Simulation results demonstrate that, under typical daily, high-volatility, and low-load scenarios, the proposed method improves clean energy utilization by 3.2%, 4.5%, and 10.9%, respectively, compared to conventional PSO algorithms while reducing power supply reliability risks to 0.70%, 1.04%, and 0.30%, respectively. These findings validate the strong adaptability of the proposed algorithm to dynamic environments. Further, a parameter sensitivity analysis underscores the significance of the dynamic adjustment mechanism. Full article

This study investigates a widely recognized ninth-order numerical technique within the explicit two-step family of methods (a.k.a. hybrid Numerov-type methods). To boost its performance, we incorporate an economical step-size control algorithm that, after each iteration, either preserves the current step length, reduces it by half, or doubles it. Any additional off-grid points needed by this strategy are computed using a local interpolation routine. Indicative numerical experiments confirm the substantial efficiency gains realized by this method. It is particularly adept at resolving differential equations with oscillatory dynamics, delivering high precision with fewer function evaluations. Furthermore, a detailed Mathematica implementation is supplied, enhancing usability and fostering further research in the field. By simultaneously improving computational efficiency and accuracy, this work offers a significant contribution to the numerical analysis community. Full article

A three-leg full-bridge inverter is conventionally used to generate split-phase AC voltage. If the neutral phase of such an inverter is grounded, then parasitic currents of significant magnitude appear in the ground circuit. This issue arises primarily due to the presence of high-frequency common-mode voltage between the output AC terminals and the DC-bus terminals. In this paper, split DC-bus capacitors are introduced in the conventional inverter circuit to attenuate the common-mode switching voltage. The addition of the capacitive filter forms a second-order low-pass filter for common-mode voltage and attenuates the magnitude of the switching-frequency component of common-mode voltage by around 40 dB. The proposed inverter is thereby able to generate a transformer-less neutral grounded split-phase AC voltage supply for an off-grid application. The simulation and experimental results of a 12 kW lab prototype are presented for verifying the proposed converter circuit topology. Full article

Nanogrids are becoming an essential part of modern home power systems, offering sustainable solutions for residential areas. These medium-to-low voltage, small-scale grids, operating at medium-to-low voltage, enable the integration of distributed energy resources such as wind turbines, solar photovoltaics, and battery energy storage systems. However, ensuring power quality, stability, and effective energy management remains a challenge due to the variability of renewable energy sources and evolving customer demands, including the increasing charging load of electric vehicles. This paper reviews the current research on nanogrid architecture, functionality in low-voltage distribution systems, energy management, and control systems. It also explores power-sharing strategies among nanogrids within a microgrid framework, focusing on their potential for supplying off-grid areas. Additionally, the application of blockchain technology in providing secure and decentralized energy trading transactions is explored. Potential challenges in future developments of nanogrids are also discussed. Full article

The effects of global warming are severely recognizable and, according to the OECD, 47% of the world’s population will soon live in regions with insufficient drinking water. Already, many countries depend on desalination for fresh water supply, but such facilities are often powered by fossil fuels. This paper presents an energy self-sufficient desalination system that runs entirely on solar power. Sunlight is harvested using parabolic trough collectors with an effective aperture area of 1.5 m × 0.98 m and a theoretical concentration ratio of 150 suns, in which a concentrator photovoltaic thermal (CPV-T) hybrid-absorber converts the radiation to electricity and heat. This co-generated energy runs a multi-effect distillation (MED) plant, whereby the waste heat of multi-junction concentrator solar cells is used in the desalination process. This concept also takes advantage of synergy effects of optical elements (i.e., mirrors), resulting in a cost reduction of solar co-generation compared to the state of the art, while at the same time increasing the overall efficiency to ~75% (consisting of an electrical efficiency of 26.8% with a concurrent thermal efficiency of 48.8%). Key components such as the parabolic trough hybrid absorber were built and characterized by real-world tests. Finally, results of system simulations, including fresh water output depending on different weather conditions, degree of autonomy, required energy storage for off-grid operation etc. are presented. Simulation results revealed that it is possible to desalinate around 2,000,000 L of seawater per year with a 260 m² plant and 75 m³ of thermal storage. Full article