International Journal of Energy Research最新文献

In this paper, a stochastic multi-objective (MO) modeling for the optimal reconfiguration and placement of photovoltaic (PV) systems in distribution networks (DNs) is presented. The main objectives are to jointly maximize the profit of generating companies (GenCos) as well as to minimize the distribution company’s (DisCo) costs and the expected interruption cost (ECOST). This approach can provide numerous economic and technical advantages for all players in the restructured power system, including GenCos, DisCos, and customers. To attain more practical and accurate results in the simultaneous placement of PVs and reconfiguration, uncertainties are considered in the problem formulation. To cope with the stochastic behavior of PV systems, electricity prices, and demands in the DN, the scenario approach is used. The proposed optimization problem is solved by the dragonfly algorithm (DA) and the best compromise solution is chosen using a fuzzy satisfying criterion. The results are also compared with the particle swarm optimization (PSO) algorithm. To confirm the effectiveness of the proposed MO model, it is implemented on the IEEE 33-bus DN and simulated in various case studies. The model is also applied to a real DN. The results confirm that the proposed model gives a more desired schedule than previous approaches, as all players in the DN including the PV owners, DisCo, and customers are satisfied at the same time.

Solid oxide electrolysis cell (SOEC) systems operating at high current densities (HCD) are emerging as sustainable and efficient solutions for hydrogen production. However, the performance of the HCD SOEC systems in endothermic mode, which requires significant external energy, is underexplored. Existing studies often lack comprehensive exergy analyses and effective energy management strategies. Accordingly, this study bridges these gaps by developing a 10 kW HCD SOEC system using Aspen HYSYS software and analyzing five different cases with varying fuel composition, external steam utilization, and fuel recirculation. The cases were systematically evaluated using energy and exergy models to assess their potential and operational possibilities in endothermic mode. Simulation results indicated that all designed cases achieved a hydrogen production rate of 0.076 g s⁻¹. Systems without external steam and recirculation exhibited low overall performance. However, integrating external steam and recirculation strategies significantly boosted the overall performance (Case 5 (E-DR)), achieving the highest lower heating value LHV-based overall energy and exergy efficiencies of 78.2% and 77.6%, respectively, making it the best configuration under HCD endothermic conditions. In-depth exergy analysis revealed that the SOEC stack and fuel superheater (FS) units experienced the highest energy dissipation in all cases and presented the highest improvement potential. Additionally, parametric analysis showed that Case 5 (E-DR) outperformed all other designed cases when operating with higher external steam temperature, external steam factor, and a recirculation ratio of 0.5. This case maintained superior performance up to 54% steam utilization. Beyond this point, the external steam-supported system without recirculation (Case 3 (NRE-H)) exhibited superior performance, thus offering a simpler design by eliminating the need for recirculation. Overall, these insights pave the way for the advancements in SOEC technology under HCD endothermic conditions.

This paper assesses the separate and simultaneous effects of utilizing cool paints (CPs) and phase change materials (PCMs) in the building envelope of high-rise office buildings on energy demand. Dynamic building energy simulations are used to investigate these impacts. CPs are known to scatter solar radiation, while PCMs are utilized for thermal energy storage in the building envelope. The effects of three CPs with constant thickness and place of application and three PCMs with varying thicknesses on the inner and outer layers of external walls are investigated, resulting in a total of three and twelve conditions for CPs and PCMs, respectively. Additionally, the study considers 36 modes of the combined use of CPs and PCMs. The study envisages that applying a combination of white CP with ATP23 PCM in the inner layer of external walls reduces 10.11 kW·hr/m²·year energy demand in the building (6.49% and 1.29% decrease in gas and electricity demand, respectively). While CPs are most effective in reducing energy demand during hot seasons, PCMs can provide benefits year-round. The economic analysis elucidates that the implementation of white CP yields a payback period of 3 years and an internal rate of return of 55% in the second scenario.

In this study, Khon Kaen and Phuket International Airports are chosen to analyze the glare effect using ForgeSolar and economic viability. Simulation is performed with fixed tilt and orientation as this study aims to provide glare-free solar photovoltaic (PV) sites for stakeholders without negotiating the energy generation. The solar site at Khon Kaen International Airport, a potential for temporary afterimage, occurred on KKC-PV-F1, KKC-PV-G3, KKC-PV-G4, KKC-PV-G5, KKC-PV-G7, KKC-PV-G10 for 3,564 min (flight path receptor (FPR)), 2,206 min (air traffic control (ATC)), 1,199 min (ATC), 438 min (ATC), 8,616 min (FPR), 1,743 min (FPR). Following that, low potential for temporary afterimage occurred on KKC-PV-G4 and KKC-PV-G7 for 2,589 min (ATC) and 5,850 min (FPR), respectively. Apart from these, KKC-PV-F1, KKC-PV-G1, KKC-PV-G2, KKC-PV-G6, KKC-PV-G8, KKC-PV-G9, and KKC-PV-G11 are naturally free from the glare effect for FPR and ATC. The Phuket International Airport, HKT-PV-G2, HKT-PV-G5, HKT-PV-R1, and HKT-PV-R2 solar PV sites are free from the glare effect. Overall, it is concluded that 3,350 kWp (KKC) and 4,300 kWp (HKT) solar PV systems are qualified as per Federal Aviation Administration (FAA) regulations. Further, economic analysis shows that the payback period of the system is 8.34–9.65 years and the overall benefit of 3,462.11 M฿.

Electrospinning enables the rapid and facile production of nanofibers with desired structures and morphologies at room temperature and ambient pressure. These nanofibers are suitable cathode, anode, and separator materials for Li-ion batteries (LIBs) because of their one-dimensional(1-D) structures and mechanical strength as well as their ability to enable rapid Li-ion transport through short diffusion pathways. The use of electrospun nanofibers in LIBs can lead to better battery rechargeability, lifespan, and performance than those of existing LIBs. In this review article, we first discuss the problems associated with the cathode, anode, and separator materials currently used in LIBs. Next, we describe the improvements achieved by incorporating electrospun nanofibers as cathode, anode, and separator materials in LIBs. We believe that electrospun nanofibers can promote the advancement of LIB technology to realize very-high-energy-density energy storage systems.

As a critical component of the energy sector, the high-temperature gas-cooled reactor (HTR) system plays an important role on the road to carbon neutrality. As a flagship of the safety analysis codes, the HTR code package (HCP) has been developed to provide a comprehensive modeling and simulation platform of the HTR system under operational and accidental conditions, especially for pebble bed reactors. A variety of individual legacy HTR computer codes were integrated into a consistent code package using flexible and efficient programing techniques and standards, and the know-how gained over decades in HTR safety studies was preserved. This paper gives a state-of-the-art overview in HTR studies and presents the new flexible curtain-based control rod system that has been recently implemented. This method involves flexible manipulation of isotope concentrations and utilizes C++ object-oriented programing principles while incorporating the legacy codes. Comparative analyses with established codes such as Serpent and ATHLET underscore the precision and reliability of the HCP, thereby enhancing its applicability in HTR design and safety evaluations. Finally, the paper outlines prospective avenues for further advancing the HCP, underscoring its evolving role in shaping the future of HTR development and analysis.

This work introduces a multilayer iterative stochastic dynamic programing (MISDP) framework for optimizing energy management in smart residential settings, incorporating electric vehicles to reduce energy costs while enhancing operational efficiency. The study investigates the complexities of managing residential loads with integrated EV batteries, set against the backdrop of unpredictable charging demands and fluctuating energy prices. The proposed method is designed to optimize charging and discharging schedules, ensuring cost-effective energy consumption without compromising the longevity of EV’s battery operations. The proposed MISDP strategy encompasses multi-iteration processes, both at internal and external levels, that not only highlight the method’s capacity for precise, real-time decision-making but also underscore its adaptability to the dynamic nature of energy systems. The external iteration primarily focuses on adapting to broader operational variables, such as fluctuating prices and demand patterns, setting a framework for optimization. Concurrently, the internal iteration updates the details of EV battery operation, fine-tuning charging and discharging strategies to refine the control law sequence for each operational period, ensuring optimal energy management. Throughout the iteration process, the framework ensures the performance index function remains bounded, adhering strictly to the evolving control law sequence. Through comparative analysis, the MISDP framework is evaluated against different optimization techniques, demonstrating its superior capability in achieving significant energy cost savings and operational effectiveness while ensuring convergence under stochastic conditions.

Triboelectric nanogenerators (TENGs) have become a vital technology in physical health monitoring and rehabilitation applications, enabling continuous, personalized, and convenient monitoring, facilitating early detection and prevention, and offering valuable data-driven insights. On-body wearable triboelectric sensors enable real-time tracking of vital health parameters, promoting accurate and personalized healthcare interventions. In addition to being self-powered, these sensors facilitate early detection and prevention by capturing early warning signs of potential health issues, leading to timely interventions. Furthermore, they play a vital role in rehabilitation monitoring and feedback, helping to assess progress during the recovery process. This continuous monitoring, along with artificial intelligence, provides data-driven insights into patterns, trends, and correlations, facilitating evidence-based healthcare decision-making. In this review, we provide an overview of the recent wearable TENG developments for healthcare applications. We discuss how TENGs work and explore a wide range of self-powered health monitoring and rehabilitation applications. We then summarize recent advancements in healthcare applications, material selection, and unique features to help design highly efficient, accurate, and practical bioapplicable technology. Further, we discuss the challenges and prospects of the TENGs technology for healthcare applications, including miniaturization, moisture resistance, device maintenance, data reliability, and high outpower requirements.

The chemical coupling of molybdenum carbide (Mo₂C) to cobalt (Co) promotes oxygen evolution reaction (OER) kinetics on the Co surface by making the surface more electrophilic. Here, to gain a deeper understanding of the effects of the surface electrophilic properties on the OER kinetics of Co and to obtain high OER activity, Fe and Ni are additionally incorporated into Co nanoparticles that are coupled with Mo₂C nanoparticles (Co-Mo₂C). Considering the oxidation states of Fe (Fe³⁺), Co (Co²⁺/Co³⁺), and Ni (Ni²⁺) ions, Fe and Ni are expected to affect the electronic structure of Co in the opposite direction. Lewis acidic Fe³⁺ doping makes the Co surface oxide more electrophilic, promoting the formation of OER-active CoOOH by strongly attracting hydroxide ions (OH⁻). Thus, the OER kinetics is facilitated on the Co surface of Fe-doped Co-Mo₂C, resulting in a significantly lower overpotential for the OER. On the other hand, the Ni²⁺ doping makes the Co surface oxide less electrophilic, leading to an increase in the overpotential for the OER. Tailoring the electrophilic properties of the Co surface is presented as a key parameter in the design of a Co-based OER catalyst for alkaline water electrolysis.

With the emergence of new technologies, wearable and portable devices become essential tools for various applications, which are flexibly designed. In this situation, flexible supercapacitors with fast charge and discharge cycles are needed as their power source. This study introduces the flexible pseudocapacitor electrode fabricated by electrodeposition of manganese oxide (MnO₂) onto heat-treated hydrophilic buckypaper (BP) molded on polydimethylsiloxane (PDMS). Here, the heat treatment of BP that is optimized by a proper adoption of thermogravimetric analysis is performed to enhance the electrodeposition efficiency of MnO₂. Then, proper hydrophilicity of the heat-treated BP (H-BP) and successful preparation of MnO₂/H-BP@PDMS electrode is well confirmed by electrochemical, spectroscopical, and optical measurements. In their evaluations, it is found that heat treatment of BP is more important factor than electrodeposition time to improve the electrodeposition efficiency of MnO₂ under the same aqueous electrolyte. With that, such optimally prepared MnO₂/H-BP@PDMS electrode shows a high electrical double layer and excellent specific capacitance of 1.31 F/cm² at 1 mA/cm², which are better results than those of other electrodes.