Hasil untuk "Energy conservation"

Xiaodong GUO, Shicheng ZHANG, Jingchen ZHANG et al.

Objectives and MethodsDeep coalbed methane (CBM) reservoirs commonly exhibit well-developed beddings, strong mechanical heterogeneity, and high in-situ stress gradients. These characteristics result in pronounced nonlinear fracture propagation and strong multi-field coupling effects during hydraulic fracturing. Consequently, it is challenging to accurately describe the mechanisms governing fracture complexity in deep coal reservoirs using conventional mechanical models for fractures. Using a super-large true triaxial system with dimensions of 2.0 m × 2.0 m × 1.0 m, this study conducted physical simulation experiments on hydraulic fracturing under varying injection rates and viscosities of fracturing fluids. In combination with fracture mechanics and energy conservation theory, this study established an energy balance equation for fracture propagation, a convection-diffusion equation for proppant transport and settling, and a model for the coupling relationships among fracture complexity and the injection rate and viscosity of fracturing fluids. Accordingly, both the dynamic mechanisms behind fracture evolution and the pattern governing the fracture network complexity were systematically elucidated.Results The results indicate that fracture propagation is jointly controlled by the in-situ stress field, fluid pressure field, and bedding structures, representing a unsteady energy conversion process. The fracture propagation rate exhibits a power-law relationship with the energy release rate. The injection rate of fracturing fluids primarily determines the energy input rate and fracture propagation velocity. A high injection rate results in energy concentration in the front of the primary fracture, promoting fracture interconnectivity while suppressing branch development. Accordingly, fracture complexity is reduced. In contrast, a low injection rate corresponds to a more uniform energy distribution, enhancing the accumulation and lateral diffusion of energy. This facilitates multi-point initial cracking and fracture branching, increasing fracture complexity by approximately 25%–35%. Fracturing fluid viscosity significantly influences the energy transfer between fluids and solids, as well as proppant settling behavior. A high viscosity (45 mPa·s) is associated with a significant decrease in the proppant settling velocity. Compared to a low viscosity of 15 mPa·s, the high viscosity increases the proppant transport capacity by approximately 40%, promoting more uniform proppant placement in far-wellbore zones and creating favorable conditions for the formation of continuous hydraulically conductive pathways.ConclusionsEmpirical relationships derived from experiments and fitting indicate that the fracture complexity exhibits power-law coupling relationships with the injection rate and viscosity of fracturing fluids. Notably, the low-injection-rate and high-viscosity combination is more favorable for the development of 3D fracture networks, with a fractal dimension reaching up to 1.46. The proposed theoretical-experimental coupling framework reveals the energy transfer mechanisms governing fracture propagation and proppant transport in deep coal reservoirs, providing a quantitative theoretical basis for optimizing hydraulic fracturing parameters and predicting fracture complexity in deep unconventional reservoirs.

Akeem Babatunde Akinwola, Abdulaziz Alkuhayli

The rapid integration of photovoltaic (PV) generation into modern power networks introduces significant operational challenges, including intermittent power production, uneven charge distribution, and reduced system reliability in multi-battery energy storage systems. Addressing these challenges requires intelligent, adaptive, and physically consistent control strategies capable of operating under uncertain environmental and load conditions. This study proposes a Physics-Informed Neural Network (PINN)-based charge allocation framework that explicitly embeds physical constraints—namely charge conservation and State-of-Charge (SoC) equalization—directly into the learning process, enabling real-time adaptive control under varying irradiance and load conditions. The proposed controller exploits real-time measurements of PV voltage, current, and irradiance to achieve optimal charge distribution while ensuring converter stability and balanced battery operation. The framework is implemented and validated in MATLAB/Simulink under Standard Test Conditions of 1000 W·m⁻² irradiance and 25 °C ambient temperature. Simulation results demonstrate stable PV voltage regulation within the 230–250 V range, an average PV power output of approximately 95 kW, and effective duty-cycle control within the range of 0.35–0.45. The system maintains balanced three-phase grid voltages and currents with stable sinusoidal waveforms, indicating high power quality during steady-state operation. Compared with conventional Proportional–Integral–Derivative (PID) and Model Predictive Control (MPC) methods, the PINN-based approach achieves faster SoC equalization, reduced transient fluctuations, and more than 6% improvement in overall system efficiency. These results confirm the strong potential of physics-informed intelligent control as a scalable and reliable solution for smart PV–battery energy systems, with direct relevance to renewable microgrids and electric vehicle charging infrastructures.

Rebeca Cabral Gonçalves, Geovana Carvalho Silva, Fernando Lage Araújo Schweizer et al.

This work aims to qualify the use of porous zones for representing fuel assemblies of a proposed SMR reactor in numerical models in other to reduce the computational demand required to study these structures. It employs computational fluid dynamics (CFD) methods to calculate the conservation equations of mass, momentum, and energy within a control volume. Initially, a detailed geometry of the fuel assembly was created and used for isothermal simulations. Based on the results of pressure drop and velocity, equations were used to calculate the coefficients of porosity and pressure drop of the system. These were then utilized to configure a second geometry, consisting of hexahedros divided into thirteen sub-regions according to their cross-sectional area, each having different porosities and pressure drop coefficents. Finally, the results of the two simulations were compared to verify their convergence to allow the use of the porous geometry. The outcomes suggests that, for models with a control volume significantly larger than a single fuel assembly, such as a complete nuclear reactor vessel, the use of porous zones is advantageous, as the variations in average velocity and pressure drop along the length of the structure are small, with the maximum axial velocity variation of -10.99%. However, if the objective is to conduct a more detailed analysis of the entire assembly, this strategy is not recommended, since some specific aspects of fluid behavior are not well capturated, such as radial velocity differences. 

Chuanshuai Dong, Lei Chen, Weiquan Lin et al.

Abstract Interfacial solar evaporation, which captures solar energy and localizes the absorbed heat for water evaporation, is considered a promising technology for seawater desalination and solar energy conversion. However, it is currently limited by its low photothermal conversion efficiency, salt accumulation, and poor reliability. Herein, inspired by human intestinal villi structure, we design and fabricate a novel intestinal villi‐like nitrogen‐doped carbon nanotubes solar steam generator (N‐CNTs SSG) consisting of three‐dimensional (3D) hierarchical carbon nanotube matrices for ultrahigh solar evaporation efficiency. The 3D matrices with radial direction nitrogen‐doped carbon nanotube clusters achieve ultrahigh surface area, photothermal efficiency, and hydrophilicity, which significantly intensifies the whole interfacial solar evaporation process. The new solar evaporation efficiency reaches as high as 96.8%. Furthermore, our ab initio molecular dynamics simulation reveals that N‐doped carbon nanotubes exhibit a greater number of electronic states in close proximity to the Fermi level when compared to pristine carbon nanotubes. The outstanding absorptivity in the full solar spectrum and high solar altitude angles of the 3D hierarchical carbon nanotube matrices offer great potential to enable ultrahigh photothermal conversion under all‐day and all‐season circumstances.

Sagar Wankhede, Ajay D. Pingale, Atharva Kale

The increasing adoption of electric vehicles (EVs) has driven extensive research and development efforts to optimize the performance and safety of their energy-storage systems, particularly lithium-ion battery packs (LIBPs). Elevated temperatures in EV batteries primarily result from thermal instability during various operating, traveling, and charging conditions. In formula student electric vehicle (FSEV) competitions, where efficiency and reliability are critical, effective cooling of the battery pack (BP) is essential. This study analyzed the cooling performance of an air-cooled thermal management system using relevant system parameters and precise thermal modeling through CFD simulations. Various cooling parameters, such as coolant flow rate, fan speed, and cooling channel geometry, were systematically adjusted to evaluate their effects on BP temperature distribution, thermal equilibrium, and overall performance. Key metrics, including maximum temperature and temperature distribution within the battery module, were used to compare simulation results and optimize outcomes for future applications. Experiments validated the simulations of the optimal solution. The results of this investigation provide valuable insights for designing and improving active cooling systems for LIBPs in FSEVs. The average variance of the obtained temperature data was 4.256% based on simulation results. At an air velocity of 17 m·s−1, the BP temperature remained within the ideal range of 30–40 °C. Enhanced cooling strategies can improve the thermal stability of BPs, extend their lifespan, and reduce the risk of thermal runaway.

Qin Zhou, Changgao Cheng, Zhou Fang et al.

Urbanization develops with the goal of establishing improved and more sustainable habitats for residents. Environmental and social performance must be simultaneously monitored to ascertain whether regions are progressing towards or deviating from the safe and just space (SJS) in urbanization. Despite relevant studies, the absence of indicators that bridge ecological preservation and human well-beings renders dual monitoring challenging. This study bridged the gap by exploring the interactions between urbanization, ecosystem services (ESs), and basic water, energy, and food (WEF) needs within the SJS framework across China and its provinces. By quantifying the minimum and actual demands for freshwater withdrawal, carbon emissions, phosphorus emissions, and land use, as well as the supply of ESs into unified biophysical indicators, we found that: (1) China can meet the basic WEF needs for all from 2000 to 2020, but only water and land provisioning ESs can operate within the SJS. Carbon emissions surpassed the sequestration capacity in 2010, while phosphorus purification ES has consistently been unsafe. (2) The SJS performance in terms of ecological and social fulfilment exhibited scale differences and undergone changes with urbanization. Overall, no province in China can consistently operate within all SJSs. (3) In the process of urbanization, improvements in ecological protection and production practices in most provinces expanded the size of SJS, but the continuous increase in total demand failed to steer regions toward safer spaces. Our framework emphasized the common but differentiated pathways that regions at varying stages of urbanization navigate to achieve safety and justice. It also provides an applicable solution for regions aiming to pursue urban growth while maintaining ecological conservation and social justice, ultimately achieving sustainable development.

Remo Luan Marinho Costa Pereira, Cesar Mösso, Luci Cajueiro Carneiro Pereira

Erosion represents a significant global threat to coastal zones, especially beaches, which are among the most valuable coastal landforms. This study evaluates the vulnerability to coastal erosion along the Brazilian Amazon coast, focusing on eight recreational beaches. The research is based on an assessment of geological, physical, ecological, and anthropogenic indicators. Some of these indicators were proposed in this study to enhance the evaluation of vulnerability in Amazonian beaches. The analysis reveals that most of the beaches studied are highly vulnerable to erosion due to a combination of natural factors and human activities. The barrier–beach ridge, composed of unconsolidated sediments, exhibits the highest vulnerability, while low cliffs present a moderate level of risk. The study highlights that semi-urban beaches with significant infrastructure development are particularly susceptible to erosion, a problem exacerbated by unplanned land use. Conversely, rural beaches, especially those located in protected areas, show lower vulnerability due to reduced human impact and better conservation of natural ecosystems. Furthermore, the study underscores the effects of extreme climatic events, such as prolonged rainfall and high-energy waves, which can intensify erosion risks. The findings suggest that anthropogenic changes, combined with extreme climate events, significantly influence the dynamics of coastal erosion. This research emphasizes the importance of targeted management strategies that address both natural and human-induced vulnerabilities, aiming to enhance coastal resilience and sustainability for Amazonian beaches.

A.M. Al-Khreisat, Q. Abdelal, M.R. Al-Kilani et al.

BACKGROUND AND OBJECTIVES: Open irrigation ponds are commonly used for agricultural water storage but lose significant water amounts to evaporation. The energy and environmental implications of these losses in water-scarce regions, where conservation is a priority, can reveal important insights. The study objectives were to examine water, energy, and environmental impacts of evaporation losses in the Jordanian Badia to identify insights for sustainable agricultural practices.METHODS: Field surveys were conducted at 20 farm sites in the northern Jordanian Badia to assess pond usage and water management practices. The study utilized novel methods including open-access meteorological data and sensor-based validation to record dynamic changes during the irrigation season. The study also explored the environmental implications by using the carbon equivalent factor with water and energy consumption information, which has not been addressed before in the region.FINDINGS: Drip irrigation was the most common choice in the study area due to water scarcity, followed by soilless systems and sprinkler irrigation. On-farm storage systems were widely used (70 percent) in the region due water supply issues, but only 20 percent of farmers used closed tank systems. Evaporation reached over 220 millimeters per month during the summer, with annual water losses exceeding 4500 cubic meters per pond. These losses required an estimated 1635 kilowatt hours of energy per 1000 cubic meters of water pumped. Annual energy consumption per pond reached approximately 2000 kilowatt hours, resulting in up to 1200 kilograms of carbon dioxide equivalent per year. This accounted for almost 1 million cubic meters in water losses, 100,000 dollars in costs, and over 200 tons of equivalent carbon emissions to replace evaporation losses every year.CONCLUSION: Evaporation losses from irrigation ponds significantly reduce water use efficiency and increase energy and environmental costs. This was despite the various water conservation techniques in the region. These losses can be slightly reduced through low-cost measures such as reducing pond water levels. They can also be significantly reduced by applying more robust methods like floating solar panels, but at a large investment. Implementing such practices supports sustainable agriculture and aligns with national water conservation priorities, but requires sound policy interventions.

Sydney Erickson, Martin Millon, Padmavathi Venkatraman et al.

Strongly lensed Active Galactic Nuclei (AGN) with an observable time delay can be used to constrain the expansion history of the Universe through time-delay cosmography (TDC). As the sample of time-delay lenses grows to statistical size, with $\mathcal{O}$(1000) lensed AGN forecast to be observed by the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST), there is an emerging opportunity to use TDC as an independent probe of dark energy. To take advantage of this statistical sample, we implement a scalable hierarchical inference tool which computes the cosmological likelihood for hundreds of strong lenses simultaneously. With this new technique, we investigate the cosmological constraining power from a simulation of the full LSST sample. We start from individual lenses, and emulate the full joint hierarchical TDC analysis, including image-based modeling, time-delay measurement, velocity dispersion measurement, and external convergence prediction. We fully account for the mass-sheet and mass-anisotropy degeneracies. We assume a sample of 800 lenses, with varying levels of follow-up fidelity based on existing campaigns. With our baseline assumptions, within a flexible $w_0w_a$CDM cosmology, we simultaneously forecast a $\sim$2.5% constraint on H0 and a dark energy figure of merit (DE FOM) of 6.7. We show that by expanding the sample from 50 lenses to include an additional 750 lenses with plausible LSST time-delay measurements, we improve the forecasted DE FOM by nearly a factor of 3, demonstrating the value of incorporating this portion of the sample. We also investigate different follow-up campaign strategies, and find significant improvements in the DE FOM with additional stellar kinematics measurements and higher-precision time-delay measurements. We also demonstrate how the redshift configuration of time-delay lenses impacts constraining power in $w_0w_a$CDM.

Yong YANG, Jiajia CHEN, Songyan LIU et al.

Objectives: With the development of modern processing technology, heat accumulation has become an urgent processing problem that needs to be solved. A heat pipe is a heat exchange element that efficiently transfers heat through the gas-liquid phase change of the working fluid inside the pipe. Gravity heat pipe have advantages such as simple structure, stable operation, and low cost, and are widely used in various heat exchange scenarios in industrial production. They have played a significant role in energy conservation, the development and utilization of new energy, and in strengthening heat exchange during processing. This article prensents experimental research on diamond nanofluids, exploring the influence of different parameters on the heat transfer performance of diamond nanofluid gravity heat pipes, laying a foundation for the research and application of heat pipe technology in heat dissipation during machining processes such as drilling, milling, and grinding. Methods: The evaporation section is heated using a DC power supply and thermal resistance wire. K-type thermocouples and temperature acquisition cards are used to record the temperature of the evaporation and condensation sections of the gravity heat pipe. The influence of heating power, filling rate, nanofluid concentration, and nanoparticle size on the heat transfer performance of the gravity heat pipe is analyzed using thermal resistance R as an indicator. Results: The heat transfer performance of gravity heat pipes is investigated under a power range of 3-18 W, while maintaining a filling rate of 20% and a nanoparticle concentration of 1%. The results show that as the heating power increases, the temperatures of the evaporation and the condensation sections gradually increase, while the rise time gradually shortenes. The temperature difference between the evaporation and condensation sections shows a decreasing trend. When the heating power increases for the same concentration and filling rate of nanoparticles, the total thermal resistance shows a decreasing trend, but the magnitude of the decrease continues to decrease. Keeping the concentration of nanoparticles at 2% and the heating power at 6 W, the heat transfer performance of gravity heat pipes is investigated under conditions of filling rates of 8%, 14%, 20%, and 26%. The results show that the overall temperature of the 20 nm diamond nanofluid is higher than those of other filling rates at a 20% filling rate, while the overall temperature at a 26% filling rate is lower than at other filling rates. The overall temperature at a 26% filling rate is higher than at other filling rates. With the same mass fraction and heating power, as the filling rate increases, the total thermal resistance shows a trend of first decreasing and then increasing, with the minimum value of the total thermal resistance appearing at a filling rate of 14%. By maintaining a filling rate of 26% and a heating power of 12 W, the heat transfer performance of gravity heat pipes under 0.5%, 1.0%, 1.5%, and 2.0% mass fraction conditions is investigated. The results show that the overall temperature of 20 nm diamond nanofluid heat pipes is the highest at a 1% mass fraction, while the overall temperature is lower at a 2.0% mass fraction. The hot-end temperature of 50 nm diamond nanofluid heat pipes is the highest at a 1.5% mass fraction, and the cold-end temperature is the lowest. At a mass fraction of 2.0%, there is a situation where the hot-end temperature is lower and the cold-end temperature is higher. With the same filling rate and heating power, as the mass fraction increases, the total thermal resistance first increases and then decreases. At a mass fraction of 2.0%, the minimum total thermal resistance will appears. In addition, for diamond nanofluids with different particle sizes, there is a trend of heat transfer capacity decreasing first and then improving with increasing mass fraction. Maintaining a filling rate of 14% and a mass fraction of 2.0%, the heat transfer performance of gravity heat pipes with particle sizes of 20 nm and 50 nm was investigated. The total thermal resistance of 50 nm diamond nanofluid gravity heat pipes was always lower than that of 20 nm diamond nanofluid gravity heat pipes. However, as the heating power increases, the advantage of 50 nm diamond nanofluid gravity heat pipes tends to weaken. Maintaining a liquid filling rate of 14% and a mass fraction of 2.0%, the heat transfer performance of gravity heat pipes with and without a liquid absorbing core was investigated. The total thermal resistance of gravity heat pipes with suction cores is lower than that of heat pipes without suction cores, but as the heating power increases, the advantage tends to weaken. Conclusions: When the mass fraction is 2.0%, gravity heat pipes have the best heat transfer performance, with a total thermal resistance increase of approximately 28.4%-64.7% compared to the maximum value. When the filling rate is 14%, the heat transfer performance is the best, and the total thermal resistance decreases by about 6.1%-8.5% compared to the maximum value. When using diamond nanofluids with a particle size of 50 nm, the overall heat transfer performance of gravity heat pipes is better than that of 20 nm. When the heating power of the power supply increases, the heat exchange performance also improves. When using a gravity heat pipe with a liquid absorbing core, its overall heat transfer performance is better than that of a gravity heat pipe without a liquid absorbing core.

Valery Nkemeni, Fabien Mieyeville, Godlove Suila Kuaban et al.

Battery-powered sensor nodes encounter substantial energy constraints, especially in linear wireless sensor network (LWSN) applications like border surveillance and road, bridge, railway, powerline, and pipeline monitoring, where inaccessible locations exacerbate battery replacement challenges. Addressing these issues is crucial for extending a network’s lifetime and reducing operational costs. This paper presents a comprehensive analysis of the factors affecting WSN energy consumption at the node and network levels, alongside effective energy management strategies for prolonging the WSN’s lifetime. By categorizing existing strategies into node energy reduction, network energy balancing, and energy replenishment, this study assesses their effectiveness when implemented in LWSN applications, providing valuable insights to assist engineers during the design of green and energy-efficient LWSN monitoring systems.

Timo Gerres, José Pablo Chaves, Pedro Linares

Basic materials such as steel, cement, aluminium, and (petro)chemicals are the building blocks of industrialised societies. However, their production is extremely energy and emission intensive, and these industries need to decarbonise their emissions over the next decades to keep global warming at least below 2 °C. Low-emission industrial-scale production processes are not commercially available for any of these basic materials and require policy support to ensure their large-scale diffusion over the upcoming decades. The novel transition to industry decarbonisation (TRANSid) model analyses the framework conditions that enable large-scale investment decisions in climate-friendly basic material options. We present a simplified case study of the cement sector to demonstrate the process by which the model optimises investment and operational costs in carbon capture technology by 2050. Furthermore, we demonstrate that extending the model to other sectors allows for the analysis of industry- and sector-specific policy options.

Victor Atanasov

The interrelationship between energy and probability conservation is explored from the point of view of statistical physics and non-relativistic quantum mechanics. The simultaneous validity of the law of conservation of energy and the continuity equation (probability conservation) breaks for an interacting dynamical system. A separate and independent description of a physical system can be obtained by requiring that the law of conservation of probability is at the heart of the derivation of the ''equations of motion''. In effect, The Schrodinger equation can be viewed as an appropriate factorization of the continuity equation instead of an energy conservation relation per se.

Kai Xiao, Daoxing Li, Xiaohui Wang et al.

Integrating marketing and distribution businesses is crucial for improving the coordination of equipment and the efficient management of multi-energy systems. New energy sources are continuously being connected to distribution grids; this, however, increases the complexity of the information structure of marketing and distribution businesses. The existing unified data model and the coordinated application of marketing and distribution suffer from various drawbacks. As a solution, this paper presents a data model of “one graph of marketing and distribution” and a framework for graph computing, by analyzing the current trends of business and data in the marketing and distribution fields and using graph data theory. Specifically, this work aims to determine the correlation between distribution transformers and marketing users, which is crucial for elucidating the connection between marketing and distribution. In this manner, a novel identification algorithm is proposed based on the collected data for marketing and distribution. Lastly, a forecasting application is developed based on the proposed algorithm to realize the coordinated prediction and consumption of distributed photovoltaic power generation and distribution loads. Furthermore, an operation and maintenance (O&M) knowledge graph reasoning application is developed to improve the intelligent O&M ability of marketing and distribution equipment.

Bin Hu, Jiawei Wu, Peng Li et al.

The front-row shading reduction coefficient is a key parameter used to calculate the system efficiency of a photovoltaic (PV) power station. Based on the Hay anisotropic sky scattering model, the variation rule of solar radiation intensity on the surface of the PV array during the shaded period is simulated, combined with the voltage–current characteristics of the PV modules, and the shadow occlusion operating mode of the PV array is modeled. A method for calculating the loss coefficient of front shadow occlusion based on the division of the PV cell string unit and Hay anisotropic sky scattering model is proposed. This algorithm can accurately evaluate the degree of influence of the PV array layout, wiring mode, array spacing, PV module specifications, and solar radiation on PV power station system efficiency. It provides a basis for optimizing the PV array layout, reducing system loss, and improving PV system efficiency.

Su Yin Chee, Louise B. Firth, Amy Yee-Hui Then et al.

Nature-based Solutions (NbS) have been advocated to protect, sustainably manage, and restore natural or modified ecosystems, simultaneously providing human well-being and biodiversity benefits. The uptake of NbS differs regionally with some countries exhibiting greater uptake than others. The success of NbS also differs regionally with varying environmental conditions and social-ecological processes. In many regions, the body of knowledge, particularly around the efficacy of such efforts, remains fragmented. Having an “inventory” or “tool box” of regionally-trialed methods, outcomes and lessons learnt can improve the evidence base, inform adaptive management, and ultimately support the uptake of NbS. Using Malaysia as a case study, we provide a comprehensive overview of trialed and tested NbS efforts that used nature to address societal challenges in marine and coastal environments (here referring to mangroves, seagrass, coral reefs), and detailed these efforts according to their objectives, as well as their anticipated and actual outcomes. The NbS efforts were categorized according to the IUCN NbS approach typology and mapped to provide a spatial overview of IUCN NbS effort types. A total of 229 NbS efforts were collated, representing various levels of implementation success. From the assessment of these efforts, several key actions were identified as a way forward to enhance the uptake of Nature-based Solutions for informing coastal sustainable development policy and planning. These include increasing education, training, and knowledge sharing; rationalizing cooperation across jurisdictions, laws, and regulations; enhancing environmental monitoring; leveraging on existing policies; enabling collaboration and communication; and implementing sustainable finance instruments. These findings can be used to inform the improved application and uptake of NbS, globally.

Ruey-Lung Hwang, Bi-Lian Chen, Wei-An Chen

Strategies to reduce energy consumption are presently experiencing vigorous development. Phase change materials (PCMs) are novel materials that can reduce indoor temperatures via the change in material phase. Regarding the situation in Taiwan, there is no practical utilization of PCMs in school buildings at present, especially in combination with rooftops. In this paper, we discuss the feasibility and utilization potential of installing PCMs in the rooftops of school buildings. School buildings located in northern and southern Taiwan (Taipei and Kaohsiung) were selected to analyze the energy-saving potential and optimization of indoor thermal comfort by installing PCMs with different properties in rooftops over two time periods, including the air conditioning (AC) and natural ventilation (NV) seasons. Based on the simulation results, the feasible patterns of PCM simultaneity are found to be appropriate for improved indoor comfort and energy saving during the different seasons. Specifically, the efficient phase change temperature (PCT) for different PCM thicknesses is clarified to be 29 °C. The economic thickness of PCM was clarified to be 20 mm for Taipei and Kaohsiung. Through the recommendations proposed in this study, it is expected that the PCMs may be efficiently implemented in school buildings to realize the goal of energy conservation and improve thermal comfort.

Cheng Zhong, Huayi Li, Yang Zhou et al.

In autonomous microgrids frequency regulation (FR) is a critical issue, especially with a high level of penetration of the photovoltaic (PV) generation. In this study, a novel virtual synchronous generator (VSG) control for PV generation was introduced to provide frequency support without energy storage. PV generation reserve a part of the active power in accordance with the pre-defined power versus voltage curve. Based on the similarities of the synchronous generator power-angle characteristic curve and the PV array characteristic curve, PV voltage Vpv can be analogized to the power angle δ. An emulated governor (droop control) and the swing equation control is designed and applied to the DC-DC converter. PV voltage deviation is subsequently generated and the pre-defined power versus voltage curve is modified to provide the primary frequency and inertia support. A simulation model of an autonomous microgrid with PV, storage, and diesel generator was built. The feasibility and effectiveness of the proposed VSG strategy are examined under different operating conditions.

Katir Ziouche, Ibrahim Bel-Hadj, Zahia Bougrioua

Jia-Wei Zhao, Cheng-Fei Li, Zi-Xiao Shi et al.

In the process of oxygen evolution reaction (OER) on perovskite, it is of great significance to accelerate the hindered lattice oxygen oxidation process to promote the slow kinetics of water oxidation. In this paper, a facile surface modification strategy of nanometer-scale iron oxyhydroxide (FeOOH) clusters depositing on the surface of LaNiO3 (LNO) perovskite is reported, and it can obviously promote hydroxyl adsorption and weaken Ni-O bond of LNO. The above relevant evidences are well demonstrated by the experimental results and DFT calculations. The excellent hydroxyl adsorption ability of FeOOH-LaNiO3 (Fe-LNO) can obviously optimize OH- filling barriers to promote lattice oxygen-participated OER (LOER), and the weakened Ni-O bond of LNO perovskite can obviously reduce the reaction barrier of the lattice oxygen participation mechanism (LOM). Based on the above synergistic catalysis effect, the Fe-LNO catalyst exhibits a maximum factor of 5 catalytic activity increases for OER relative to the pristine perovskite and demonstrates the fast reaction kinetics (low Tafel slope of 42 mV dec-1) and superior intrinsic activity (TOFs of ~40 O2 S-1 at 1.60 V vs. RHE).