• Energy Research
• 2025-2025close
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Climate crisis mitigation roadmaps, policies and directives have increasingly declared that a key element for the facilitation of sustainable urban development is on-site decentralized renewable energy generation. A technology with enhanced capabilities, able of promoting the integration of renewable energy into buildings, for energy independent and resilient communities, is Photovoltaic Thermal (PVT) systems. Ongoing research has potential yet displays a lack in unified methodology. This limits its influence on future decision-making in building and city planning levels. In this investigation, the often overlooked air-based PVT technology is put on the spotlight and their suitability for integration with energy systems of buildings is assessed. The aim of this study is to highlight vital performance and integration roadblocks in PVT research and offer suggestions for overcoming them. The methodology of reviewed literature is examined in detail with the goal of contributing to a unified approach for more impactful research.

CaO captures CO2 from pyrolysis, forming CaCO3 that activates biochar via decomposition.

Oxy-fuel carbon capture in power plants is a relatively new concept aiming at reducing carbon dioxide emissions from the plants. This is achieved by burning the fossil fuel using oxygen as oxidizer with no nitrogen, thereby rendering the exhaust gases very rich in carbon dioxide (after condensing water vapor by cooling), which facilitates its capture for environmental or commercial purposes. Despite the worldwide interest in oxy-fuel carbon capture, its progress is at risk given the large energy needed to separate oxygen from air in order to provide the oxidizer, thereby hindering further progress of this concept toward large-scale applications. This paper focuses on alleviating this drawback of oxy-fuel combustion by making it more attractive through combining it with another concept, namely magnetohydrodynamic (MHD) power generators. The end product is a power plant operating on a combined cycle composed of a topping MHD ultra-high-temperature cycle with direct electricity extraction from plasma, followed by a bottoming steam cycle with conventional turbo-generators. Different design aspects and simplified technical analysis for the MHD generator are presented.

Abstract Future “net-zero” electricity systems in which all or most generation is renewable may require very high volumes of storage in order to manage the associated variability in the generation-demand balance. The physical and economic characteristics of storage technologies are such that a mixture of technologies is likely to be required. This poses nontrivial problems in storage dimensioning and in real-time management. We develop the mathematics of optimal scheduling for system adequacy, and show that, to a good approximation, the problem to be solved at each successive point in time reduces to a linear programme with a particularly simple solution. We argue that approximately optimal scheduling may be achieved without the need for a running forecast of the future generation-demand balance. We consider an extended application to GB storage needs, where savings of tens of billions of pounds may be achieved, relative to the use of a single technology, and explain why similar savings may be expected elsewhere.

Abstract This paper investigates the forced convection of alumina-water nanofluids within helical tubes, maintaining a constant wall temperature and assuming thermal equilibrium between the nanoparticles and the base fluid. The nanofluid model incorporates the effects of alumina (Al2O3) nanoparticle volume fraction, diameter, and temperature on thermophysical properties. The governing equations are solved using the Forward-Time Central-Space Finite Volume method in conjunction with the simple algorithm. Numerical results are validated against experimental data, demonstrating high accuracy. The study explores the effects of pitch size, curvature ratio, nanoparticle volume fraction, nanoparticle diameter, and Reynolds number on velocity contours, temperature profiles, secondary flow, thermophysical properties, friction coefficient, and heat transfer rate. Additionally, the figure of merit evaluates the impact of these parameters on the thermal performance of the system. The results indicate that an increase in Reynolds number and nanoparticle diameter negatively affects thermal performance, while higher nanoparticle volume fraction, curvature ratio, and pitch size enhance it. Furthermore, incorporating nanoparticles in straight tubes proves to be more advantageous compared to helical tubes. This study tested volumetric ratios of 1%, 2%, and 4%, which resulted in increases in heat transfer coefficients of 21%, 32%, and 43%, respectively, compared to pure water under similar conditions, such as Reynolds number and coil pitch.

Background: Compared with the traditional power system, the large-scale access of distributed energy resources in the new power system has a great impact on the structure and operation mode of the power grid, and it is also more susceptible to device-level and network-level FDI attacks. Objective: In order to improve the accuracy and precision of detecting false data injection attacks in distributed energy resources integration into distribution networks and to further explore time series modeling methods for measurement data, it is helpful for the FDIAs detection method to be widely adopted and applied in new power systems. Methods: To address false data injection attacks on distributed energy resource integration into distribution grids within new power systems, a data-driven time series anomaly detection method is employed. Firstly, time-aware shapelets are extracted from time series data, and then the shapelet evolution graph is constructed to capture the correlation between the shapelets. Finally, time series representation vectors are learned using segment embeddings derived from the shapelet evolution graph through the DeepWalk algorithm. These representation vectors are then input into a BO-XGBoost anomaly detector, facilitating the detection of FDIAs. Results: After multiple rounds of parameter tuning, the parameters of Shapelet quantity (K=40) and segment length (L=4) achieved an accuracy of 92.8% in FDIA detection. Comparative experimental results with different algorithms indicate that, compared to other unsupervised learning methods, this approach exhibits an accuracy improvement of 20-40%. In the case of BOXGBOOST, it achieves a 5% increase in accuracy compared to the unmodified XGBOOST. Conclusion: The experimental results indicate that this method can effectively detect false data injection attacks on the integration of distributed energy resources into distribution grids within new power systems. This model significantly enhances detection accuracy and precision while also imparting physical significance to the dynamic evolution of time series models.

Phase change materials (PCMs) play a pivotal role in various sectors, particularly in automotive engineering, electric vehicles, and building construction. In the automotive sector, phase change materials are crucial for thermal management systems, aiding in temperature regulation of components such as batteries and engines. In electric vehicles, phase change materials are instrumental in enhancing battery performance and lifespan by effectively managing thermal loads during charging and discharging cycles, thus ensuring optimal operating conditions. These materials offer significant energy efficiency benefits by absorbing and releasing large amounts of latent heat during phase transitions, which helps in maintaining stable temperatures and reducing the load on heating and cooling systems. Additionally, PCMs contribute to sustainable building practices by enhancing thermal regulation, thereby lowering energy consumption and associated costs. This study explores the diverse applications and properties of phase change materials for improving thermal management and energy efficiency in vehicles, residences, and buildings. This research provides a comprehensive review of innovative solutions, including PCM-based heat pumps, PCM-integrated cementitious composites, and hybrid active-passive battery thermal management systems.

Agglomeration may cause severe operational problems in fluidized beds for biomass combustion and gasification. Application of external forces is a common way for improving fluidization quality, which may act as a potential countermeasure to mitigate the agglomeration problem. In this work, a pulsed flow is applied to a fluidized bed reactor to examine its effect on mitigating agglomeration in combustion and gasification of wheat straw. The influence of the pulsation parameters, including flow ratio of pulsation/total flow, pulsation frequency and pulsation duty cycle, on the agglomeration tendency were studied in a lab-scale bubbling fluidized bed reactor using silica sand as bed material. The results reveal that application of a pulsed flow to the reactor can reduce the agglomeration tendency in fluidized bed combustor and gasifier. The maximum reduction of agglomeration tendency has been achieved under a condition with pulsation flow ratio of 0.4, pulsation frequency of 1.5 Hz and pulsation duty cycle of 25/75. Among the parameters studied, pulsation duty cycle exhibits the most significant effect on reducing agglomeration tendency, while pulsation frequency in the studied range shows the smallest impact. Moreover, the results show that the combustion performance is not affected by application of the pulsed flow.

In this study, a coupled numerical computation approach integrating aerothermal and thermomechanical effects was employed to investigate the cooling efficiency and thermal stress characteristics of gas turbine stator blades. A comprehensive analysis was conducted considering varying turbulence intensities in the coolant flow (spanning from 0.05 to 0.15) and different coolant media configurations, including pure air, dual-medium mixture of air and steam, and pure steam. The distributional traits of cooling efficiency and thermal stress on the stator blade surface under these conditions were meticulously examined. Furthermore, quantitative assessments were performed to determine the extent to which coolant turbulence intensity and coolant type affect the average cooling efficiency and maximum equivalent thermal stress of turbine stator blades, thereby revealing the influence laws. The results reveal that the minimum cooling efficiency on the stator blade surface predominantly occurs at the position of channel 4 on the pressure surface, while the highest cooling efficiency is generally found near the leading edge of the suction surface. Regions of elevated thermal stress were consistently concentrated around the stator blade tip and root areas. When the coolant turbulence intensity increased from 0.05 to 0.15, the average cooling efficiency on the stator blade surface improved by 2.06%, accompanied by a reduction of 1.12% in the maximum thermal stress. In comparison to pure air cooling, dual-medium (air and steam) cooling and pure steam cooling lead to respective enhancements in the average cooling efficiency of approximately 3.3% and 13.2%, with corresponding decreases in the maximum thermal stress of 2.18% and 10.2%.