Energy Science & Engineering最新文献

Investigating the relationship between factors affecting the output power of photovoltaic (PV) cells is crucial for enhancing the efficiency and stability of PV power generation. Traditional PV models have problems such as many parameters, strong nonlinearity, and difficulty in numerical solution. In addition, there is a lack of precise quantitative methods to determine the relationship between different influencing factors. To address this problem, the traditional PV model is simplified and parameters are optimized by taking a single-diode monocrystalline silicon PV cell as an example. The grey correlation theory is introduced to analyze the factors affecting the performance of PV cells, and the correlation between each factor and the maximum output power point is calculated. The results show that the proposed PV model is sensitive to each parameter. The grey correlation method is used to quantitatively calculate the correlation, effectively revealing the relative importance of different factors and the maximum output power, and clarifying the influence of each parameter on the maximum power point. It provides a strong support for the optimization design of large-scale PV power generation systems.

This study focused on the production of hydrocarbon fuels from bio-slurry through an innovative electrolytic process powered by solar energy. The bio-slurry, a byproduct of anaerobic digestion, presents disposal challenges, especially in areas without farmlands for use as organic biofertilizer. To address this issue and contribute to cleaner energy production, the study aimed to catalyze bio-slurry degradation into hydrocarbon fuels using an electrolytic biomass solar cell (EBSC). Powered by a 40 W solar panel, the setup employed a 9000 mL bio-slurry capacity, alongside geo-catalysts and iron oxide catalysts to enhance the efficiency of degradation and gas production. The experiment yielded significant volumes of biofuels, including bio-methane (20.42%), bio-ethane (24.00%), and propane (35.10%), with gas composition analyzed via GC-MS. The use of the “Ebarra” (a geo-catalyst) electrocatalyst significantly increased methane and ethane production. This process could be scaled up for industrial applications with the use of solar panels of higher capacity in large bio-slurry systems, as well as proportionate catalysts to enhance the process. This process presents a sustainable method for converting bio-slurry into valuable hydrocarbon fuels, contributing to environmental conservation and renewable energy development. This method not only converts bio-slurry into valuable hydrocarbon fuels but also minimizes harmful byproducts, contributing to a lower carbon footprint compared to traditional energy production methods, such as the use of water to produce Hydrogen energy, among others.

In today's modern world, people spend most of their time indoors, making indoor air quality (IAQ) a critical concern, particularly in educational buildings, where densely occupied classrooms demand clean and healthy environments. This study enhances the IAQ of an existing college building in West London by aiming to reduce carbon dioxide (CO₂) concentrations and SARS-CoV-2 infection risk, while maintaining or improving energy efficiency and thermal comfort, assessed using the predicted percentage of dissatisfied (PPD). A multi-objective optimisation was conducted using the Non-dominated Sorting Genetic Algorithm II (NSGA-II). A novel approach combining optimisation with EnergyPlus and CONTAM co-simulation was proposed to obtain the final results. Various scenarios were developed, reflecting different priorities. Energy-saving scenarios increased PPD by 15.3% to 17.9%, while IAQ- and comfort-focused scenarios raised energy consumption by 26.95% to 53.91% but maintained or improved comfort. EC45 as a mixed-priority scenario, along with IAQ-priority scenarios, achieved the lowest average SARS-CoV-2 infection risks (9.6%–10.7%). Meanwhile, other mixed-priority (EP45-ECP33) scenarios reduced PPD by 13.9% and maintained a 17% infection risk with only a 29% increase in energy use. This comprehensive approach demonstrates the potential for achieving healthier indoor environments in educational buildings without excessively compromising energy efficiency or occupant comfort.

This study addresses the significant discrepancies in traditional methods for predicting the height of water-conducting fracture zones in deep-mining hard roofs, which can lead to catastrophic water inrush events. The 110,504 working face of Banji Coal Mine was chosen as the research site to systematically investigate the development characteristics of these fracture zones through a combination of theoretical analysis, field measurements, and numerical simulations. A key stratum identification model was proposed, based on the temperature-compensated elliptical stress arch theory, to better account for high ground temperatures in the overlying strata. The theoretical calculations predicted a water-conducting fracture zone height of 61.32 m and a fracture zone height of 21.25 m. The development of the fracture zone exhibited a three-stage evolution: a slow development stage, followed by a rapid expansion stage, and finally a stable penetration stage. The findings suggest that the fracture zone height is primarily governed by the fracturing of key strata within an ellipsoidal stress arch, with overburden failure influenced by mining-induced stress concentration and the structural characteristics of the overlying rock. These results provide both theoretical insights and empirical data for improving predictions of water hazards and enhancing the stability of overburden in deep mining environments.

This paper presents GRATE–DRL–AI, an Artificial Intelligence (AI)–driven algorithm designed to enhance the efficiency and accuracy of distribution system planning. Leveraging advanced AI methodologies, including graph learning, transfer learning, deep reinforcement learning (DRL), and physics-guided neural networks, this model efficiently addresses the growing complexity and uncertainties in modern distribution grids with high penetration of distributed energy resources. Case studies on the Institute of Electrical and Electronics Engineers 33-bus and 123-bus systems show that GRATE–DRL–AI reduces planning cost by up to 8.5%, achieves 99%–100% feasibility, and significantly lowers computation time (e.g., 580 s vs. 1610 s for the 342-bus system). Even under ±30% uncertainty in demand and renewable generation, feasibility remains above 99%. In addition to strong performance gains, the study also highlights limitations, such as data availability, computational requirements, and regulatory considerations, which must be addressed for real-world deployment of AI-driven planning frameworks.

Reducing harmonics in alternating current (AC) input and ripples in direct current (DC) output enhances power quality, achievable through multi-pulse converters (MPCs). This study presents the design, simulation, and analysis (in MATLAB/Simulink) of an autotransformer-based 18-pulse AC-DC converter used with a vector-controlled asynchronous motor drive (VCAMD) to improve power quality at the point of common coupling (PCC). Unlike alternative designs that require three single-phase transformers, the proposed autotransformer only utilizes two, making it a cost-effective replacement for conventional 6-pulse diode bridge rectifiers. The article covers various topologies, simulation outcomes, and comparisons. It also examines load change effects on VCAMD, analyzing total harmonic distortion (THD) and assessing harmonic reduction efficiency. Experimental results from a laboratory prototype further validate the proposed structure's effectiveness.

Hybrid Ocean Thermal Energy Conversion (H-OTEC) systems are characterized by the adoption of both open-loop and closed-loop Rankine cycles. In the closed-loop configuration, a working fluid such as ammonia is evaporated in a heat exchanger, utilizing the heat from water vapor generated in a vacuum chamber by warm surface seawater introduction. The vapor is then expanded through a turbogenerator to produce electricity before being condensed in a cold-water heat exchanger using cold water. In Malaysia, significant advancements are being made in the technology for seawater suction systems, particularly for applications in fish breeding, farming, desalination plants, and power generation. The operation of an H-OTEC Experimental system at UPM I-AQUAS, Port Dickson, Malaysia depends on surface seawater for turbine operation, necessitating the installation of a piping system spanning 336 m from the H-OTEC facility to the suction location. Challenges associated with seawater intake systems include pump cavitation due to high suction head, pipe contamination by organisms such as barnacles and algae, pump placement, strainer size, and pipe diameter intake. The primary objective of this study is to provide valuable insights, conduct field testing, and gather necessary data for the development of the first-of-its-kind surface seawater piping system for H-OTEC in the Asian region. This objective was accomplished through the installation of a centrifugal pump unit with a flow rate of 40 m³/h (600 L/min), the laying of 106 mm inner diameter parallel pipes, installation of strainers, and a booster pump connected to a 125 A HDPE pipe. The collected data provides the necessary input in establishing the layout design and location selection of the seawater intake pipe, introduce a novel helical crossflow self-cleaning suction screen water intake system, facilitate weight structure design, and enable pump sizing and suction pump analysis.

The development of power quality control systems and methods is a credible step for the modernization of the power grid. In this context, this paper presents novel approaches for the control of power quality and voltage of the power grid using power converters connected to photovoltaic battery systems. The photovoltaic system permits to generate the required power to adjust the grid voltage. Indeed, a three-level neutral point clamped (NPC) converter, connecting the PV-batteries to the power grid, plays the function of a static compensator (STATCOM) in the case of a fault causing power grid voltage variation. The NPC converter is controlled by a direct current vector control method based on a hysteresis controller. The amplitude and phase of the NPC converter reference currents are generated based on the irradiation value, the battery state of charge, and the grid voltage. In addition to the NPC converter, the proposed approach uses three DC–DC converters with the aim to extract the maximum power from the PV system and control the charge–discharge of the batteries. The bidirectional converter associated with the batteries and the four-quadrant chopper connected to the NPC converter are controlled by proportional integral (PI) regulators in aim to maintain the voltage and state of charge of the batteries within the acceptable range. To coordinate the different scenarios, a power management system is proposed in this paper to generate adequate control signals for the control of the different power converters. PI closed-loop controllers have been proposed to ensure the highest performance and stability of voltage regulation in the power grid. The different control methods have been implemented and verified in MATLAB-Simulink environment. The results prove the effectiveness of the proposed approach to regulate the voltage and the grid power quality. The results demonstrate that the proposed system is capable of maintaining the grid voltage within ±10% of the nominal value, even under fault conditions, with a voltage regulation efficiency of 98%. Additionally, the power quality improvements are quantified, showing a reduction in total harmonic distortion (THD) of the grid current to below 3%, ensuring compliance with international power quality standards.

The escalating global demand for energy, coupled with pressing environmental anxieties, necessitates the strategic integration of renewable resources with advanced thermodynamic cycles. This paper analyzes the proposed sustainable hybrid power systems combining heliostat-based solar thermal plants, molten salt thermal storage, and supercritical CO₂ Brayton cycles, augmented by green methanol synthesis. This study undertakes a multi-faceted evaluation of the proposed systems, assessing their viability based on energy, exergy, environmental, and economic metrics. This assessment is facilitated by sophisticated, AI-driven multi-objective optimization algorithms. Concurrently, a bibliometric mapping of the research domain was performed using VOSviewer to visualize the scholarly landscape. The results reveal promising configurations with improved thermal performance, enhanced energy storage strategies, and significant emission reductions, offering a viable path toward sustainable industrial-scale energy solutions. The optimized configurations achieved a thermal efficiency of more than 45%, exergy efficiency of more than 40%, and CO₂₂ emission reduction of more than 80% compared to conventional fossil-based systems. These results validate the proposed models technical viability and environmental advantage, offering a promising pathway toward scalable, sustainable energy systems.

Indonesia's considerable geothermal resources present tremendous potential for energy production, yet restricted investor interest hampers development. This study evaluates the economic viability of a proposed 330 MW geothermal power plant in Gunung Kembar to encourage investment and facilitate Indonesia's 2060 Nationally Determined Contributions (NDC). Four scenarios were modeled using RETScreen, each differing in carbon credit pricing and project duration. Scenario I implement a carbon credit price of $2 per metric ton of CO₂ over a 25-year period, resulting in a Net Present Value (NPV) of $22 million and a Levelized Cost of Electricity (LCOE) of 0.091 USD/kWh. Scenario II elevates the credit price to $18, resulting in an NPV of $23.5 million. In Scenario III, prolonging the project lifespan to 30 years yielded a NPV of $30.6 million and a LCOE of 0.088 USD/kWh. Scenario IV, featuring a credit price of $50 and a term of 30 years, attained the highest NPV at $67.9 million and an LCOE of 0.088 USD/kWh. Scenario IV demonstrates the most economic potential, indicating that elevated carbon price may augment project profitability and stimulate renewable investment in Indonesia.