Energies, Volume 16, Issue 14 (July-2 2023) – 345 articles

The energy consumption of buildings is a significant contributor to overall energy consumption in developed countries. Therefore, there is great demand for intelligent buildings in which energy consumption is optimized. Online control is a crucial aspect of such optimization. The implementation of modern algorithms that take advantage of developments in information technology, artificial intelligence, machine learning, sensors, and the Internet of Things (IoT) is used in this context. In this paper, an architecture for testing central heating control algorithms as well as the control algorithms of the heating system of the building is presented. In particular, evaluation metrics, the method for seamless integration, and the mechanism for real-time performance monitoring and control are put forward. The proposed tools have been successfully tested in a residential building, and the conducted tests confirmed the efficiency of the proposed solution. Full article

To promote the adoption of Direct Air Capture (DAC) systems, this paper proposes and tests a photovoltaic-powered DAC system in a generic residential building located in Qatar. The proposed DAC system can efficiently reduce CO₂ concentration in a living space, thus providing an incentive to individuals to adopt it. The ventilation performance of the building is determined using Computational Fluid Dynamics (CFD) simulations, undertaken with ANSYS-CFD. The CFD model was validated using microclimate-air quality dataloggers. The simulated velocity was 1.4 m/s and the measured velocity was 1.35 m/s, which corresponds to a 3.5% error. The system decarbonizes air supplied to the building by natural ventilation or ventilation according to the ASHRAE standards. Furthermore, the performance of the photovoltaic system is analyzed using the ENERGYPLUS package of the Design Builder software. We assume that 75% of CO₂ is captured. In addition, a preliminary characterization of the overall system’s performance is determined. It is determined that the amount of CO₂ captured by the system is 0.112 tones/year per square meter of solar panel area. A solar panel area of 19 m² is required to decarbonize the building with natural ventilation, and 27 m² is required in the case of ventilation according to the ASHRAE standard. Full article

Sediment microbial fuel cell (SMFC) is a type of MFC without a proton exchange membrane. However, SMFC have had problems with low-power production performance. In this paper, the effects of native bacteria (K1) in oily sludge and their electro-oil-induced domestication on the power generation and oil removal performance of SMFC were studied. The results showed that K1 belonged to Ochrobactrum intermedium. During the domestication process, an upward trend was shown in the OD600 and ORP values in the culture medium, and it grown best at 0.7 V. Ochrobactrum intermedium K1 significantly increased the average output voltage, electromotive force, and maximum power density of SMFC and reduced the apparent internal resistance of the battery. The maximum power density was 169.43 mW/m³, which was 8.59 times higher than that of the control group. Ochrobactrum intermedium K1 improved the degradation of crude oil by SMFC. Ochrobactrum intermedium K1 enhanced the degradation of high-carbon alkanes and even-carbon alkanes in n-alkanes. Cyclic voltammetry and chronoamperometry tests showed that after acclimation, Ochrobactrum intermedium K1 improved the extracellular electron transfer efficiency (EET) mediated by c-Cyts and flavin by increasing the surface protein redox potential. Full article

Circuit breakers on the filter bank branches in converter stations are vulnerable to contact wear and mechanical deterioration caused by frequent operations, which can lead to circuit breaker breakdowns and explosions. It is imperative to conduct research on the early detection of abnormal states in circuit breakers. Existing electrical quantity-based detection methods are constrained by a priori assumptions, and their measurement methods are susceptible to interference, leading to misjudgments. To address this issue, this paper examines the influence of changes in critical breakdown field strength and contact spacing on circuit breaker operation states. It also proposes a technical scheme that employs breakdown current values to comprehensively characterize circuit breaker operation states, replacing the use of critical breakdown field strength and contact spacing. An early detection method for abnormal circuit breaker states based on a sequence of breakdown current ratios at different times is proposed, and its effectiveness is verified through simulation and field recording data. Full article

Transcritical carbon dioxide waste heat recovery systems and the construction of scroll expanders have recently been hot topics. The flank clearance, located between the orbiting and fixed scroll, has a vital impact on the scroll expander performance. This paper estimates the effect of the flank clearance on the expander’s thermodynamic performance (first-law efficiency) based on computational fluid dynamics (CFD) simulations. The manufacturing cost of different flank clearances is also considered to enhance the feasibility of the machinery design. The computational cost for different flank clearance cases is significantly reduced with a surrogate-assisted multi-objective optimisation algorithm (SAMOA), which also supports modelling the trade-off relationship between manufacturing cost and machinery efficiency. The results indicated that an increasing flank clearance negatively affects the first-law thermal efficiency. The efficiency decreased from 87.41% to 44.83% moving from 20 to 200 μm flank clearances. The SAMOA successfully reduced the computational cost of the dynamic mesh CFD model from 90 h to 15 s with 0.6% discrepancy. The final Pareto solutions presented a clear trade-off relationship between the first-law efficiency and manufacturing cost and promised a diversity of optimum solutions. The “knee points” for the relationship were 25, 55, and 127 μm, which provided flexible clearance choices based on the importance of either machinery efficiency or manufacturing cost. Full article

The formation of gas hydrates due to temperature and pressure changes during gas storage in the wellbore poses significant danger, necessitating the prediction of temperature and pressure distribution as well as of hydrate formation locations. We establish a temperature model that couples total thermal resistance and temperature in the wellbore-stratum composite medium system. Utilizing the two-phase pressure model alongside the temperature model, we conduct coupling calculations of temperature and pressure. Based on both temperature and pressure distribution within the wellbore and hydrate formation curve, we predict hydrate formation regions during production and analyze factors influencing temperature and pressure distribution. Results indicate that gas production rate and specific gravity of natural gas are major influencers on wellbore temperature and pressure distribution, while production time has minimal impact. Full article

The launch of the national carbon emissions trading (CET) market has resulted in a closer relationship between China’s CET market and its electricity market, making it easy for risks to transfer between markets. This paper utilizes data from China’s CET market and electric power companies between 2017 and 2023 to construct the spillover index model of Diebold and Yilmaz, the frequency-domain spillover approach developed by Barun’ik and Křehl’ik, and a minimum spanning tree model. The comparison is made before and after the launch of the national CET market. Subsequently, this paper examines the market spillover effects, as well as the static and dynamic properties of network structures, considering both the time domain and frequency-domain perspectives. The research findings suggest the following: (1) There is a strong risk spillover effect between China’s CET market and the stock prices of electric power companies; (2) There is asymmetry in the paired spillover effects between carbon trading pilot markets and the national CET market, and differences exist in the impact of risk spillovers from power companies between the two; (3) The results of the MST model indicate that the risk contagion efficiency is higher in the regional CET pilot stage compared to the national CET market launch stage, with significant changes occurring in key nodes before and after the launch of the national CET market; (4) Both the dynamic spillover index and the standardized tree length results demonstrate that crisis events can worsen the risk contagion between markets. Besides offering a theoretical foundation and empirical evidence for the development of China’s CET and electricity markets, the findings of this paper can provide recommendations for financial market participants as well. Full article

In this paper, the performance and emission characteristics of a diesel engine were investigated with varying ratios of tung oil-based biodiesel blends (B10, B20, and B50) and neat diesel under different operating conditions. The experimental results showed that the addition of biodiesel blends had different effects on engine power and torque depending on the blend ratio. B10 displayed a slight increase in power and torque, which increased by 1.9% and 6.6%. At the same time, B20 and B50 showed declines slightly. The fuel consumption rate increased slightly with an increasing percentage of biodiesel added. In general, all the blends exhibited significantly lower emissions of CO, NO_X, HC, and smoke compared to neat diesel. B10 displayed the most notable reduction of CO emissions, with a 42.86% decrease at medium to high loads. NO_X emissions of tung oil-based biodiesel blends were reduced at all load conditions except for B50. In addition, HC emissions were all reduced, especially for B20, which led to a 27.54% reduction at 50% load. Among all the tested blends, B50 showed the greatest decrease in smoke emissions of 38.05% compared to neat diesel at 2000 rpm. The research concluded that using biodiesel fuels from renewable resources, such as tung oil, presents a promising environmentally friendly alternative fuel option. Full article

Renewable distributed generators (RDGs) have made inroads in recent power systems owing to the environmental effect of traditional generators and their high consumption of electric energy. The widespread use of RDGs has been a recent trend in numerous nations. The integration complexity and the intermittent nature of RDGs can undermine the security and stability of microgrids (µGs). In order to guarantee the effectiveness, dependability, and quality of the electricity delivered, appropriate control methods are necessary. RDGs are being included in single-phase microgrids (1Ø-µGs) to generate energy closer to the user. The creation of low-voltage µGs allows for increased energy efficiency and improved electrical supply dependability. Nevertheless, the combined power pumped by DGs might create power quality (PQ) difficulties, especially during off-grid operations. The three biggest problems with PQ are reactive-power swapping, voltage and frequency (VαF) variations, and current and voltage (IαV) harmonic falsification associated with 1Ø-µGs; these conditions may affect the operation of µGs. The designed and implemented (primary–secondary control systems) in RDGs are the prevalent strategy discussed in the literature for mitigating these PQ difficulties. Furthermore, emerging grid innovations like the electrical spring offer viable alternatives that might reduce some problems through decentralized operation. Although several research studies have addressed PQ concerns in 3Ø-µGs, not all of these solutions are immediately applicable to their 1Ø equivalents. In this paper, the state of the art and a performance comparison of several PQ enhancement strategies of µGs is discussed. Additionally, the primary difficulties and several PQ approach tactics are highlighted. All vital features from high-quality published articles and new dimensions in this field are presented for mitigating PQ difficulties in 1Ø-µGs. Full article

This paper presents a comprehensive study of winter temperatures in Norway and northern Sweden, covering a period of 50 to 70 years. The analysis utilizes Singular Spectrum Analysis (SSA) to investigate temperature trends at six selected locations. The results demonstrate an overall long-term rise in temperatures, which can be attributed to global warming. However, when investigating variations in highest, lowest, and average temperatures for December, January, and February, 50% of the cases exhibit a significant decrease in recent years, indicating colder winters, especially in December. The study also explores the variations in Atlantic Meridional Overturning Circulation (AMOC) variations as a crucial climate factor over the last 15 years, estimating a possible 20% decrease/slowdown within the first half of the 21st century. Subsequently, the study investigates potential similarities between winter AMOC and winter temperatures in the mid to high latitudes over the chosen locations. Additionally, the study examines another important climatic index, the North Atlantic Oscillation (NAO), and explores possible similarities between the winter NAO index and winter temperatures. The findings reveal a moderate observed lagged correlation for AMOC-smoothed temperatures, particularly in December, along the coastal areas of Norway. Conversely, a stronger lagged correlation is observed between the winter NAO index and temperatures in northwest Sweden and coastal areas of Norway. Thus, NAO may influence both AMOC and winter temperatures (NAO drives both AMOC and temperatures). Furthermore, the paper investigates the impact of colder winters, whether caused by AMOC, NAO, or other factors like winds or sea ice changes, on electrical power and energy systems, highlighting potential challenges such as reduced electricity generation, increased electricity consumption, and the vulnerability of power grids to winter storms. The study concludes by emphasizing the importance of enhancing the knowledge of electrical engineering researchers regarding important climate indices, AMOC and NAO, the possible associations between them and winter temperatures, and addressing the challenges posed by the likelihood of colder winters in power systems. Full article

The high-frequency modulation method (HFM) for a switched capacitor (SC) inverter often leads to high switching loss since it increases switching frequency. In order to reduce the switching frequency and switching loss in the HFM for SC inverter, this paper proposes a novel hybrid modulation strategy as well as a corresponding demo switched capacitor topology. The hybrid strategy limits the number of high-frequency switches, thus reducing the switching loss significantly. Meanwhile, the demo topology maintains the merits of current switched capacitor inverter such as low switch count, quadruple voltage-boosting ability and self-balancing capacity. The principle of the hybrid modulation method and the circuit configuration of the inverter are analyzed in detail. And comparisons are introduced to demonstrate the advantages of the proposed modulation method and topology. Finally, experimental results have proved the feasibility of the proposed inverter. Full article

The paper presents the results of simulation studies of fluid flow through a standard orifice and two slotted orifices. The research that has been carried out concerns the analysis of the effect of the orifice geometry on the velocity profiles, turbulence kinetic energy and turbulence energy dispersion. The profile studies were conducted at different distances behind the orifice so that the results could be compared with each other. The studied flow included an airflow whose inlet velocity was 15 m/s. The turbulence model k-ε was used for numerical calculations. The tested orifices were characterized by an orifice constriction equal to β = 0.5. The calculations involved flow through a pipeline with a diameter of 160 mm. The results show that for a standard orifice, the maximum velocity of the flow is about 95 m/s and this is recorded at a distance of about 10–20 cm behind the orifice, and then it decreases, and at a distance of about 60 cm, the flow velocity is about 27 m/s. In the case of slotted holes, the maximum velocity is about 30% lower compared to the flow rate through a standard orifice design. The maximum velocity behind slotted orifices occurs directly behind the orifice, and in the cases of slotted orifice 1 and slotted orifice 2, was about 70 m/s and 67 m/s, respectively. For slotted orifice 1, at a distance of 20 cm behind the orifice, the flow assumed a velocity of about 19 m/s, whereas for slotted orifice 2, the flow reached a speed of about 18 m/s, at a distance of about 30 cm behind the orifice. The values of the maximum kinetic energy of turbulence for the tested orifices are about 420 m²/s² for the standard orifice, and about 250 m²/s² and 220 m²/s² for slotted orifices 1 and 2, respectively. The obtained simulation results demonstrated that slotted orifices lead to faster stream homogenization and do not disturb the flow as much as a standard orifice. Slotted orifices exhibit a higher flow coefficient. Full article

PEMFCs, or proton exchange membrane fuel cells, have enormous potential for clean energy and environmentally friendly transportation. PEMFCs’ cost, performance, and durability, however, continue to be major obstacles to their mainstream deployment. This study examines recent developments in PEMFC technology with an emphasis on novel oxygen reduction reaction catalysts, creative flow field designs, methods for reducing degradation processes, and system-level optimization and integration. The results show that innovative studies in these fields have significantly increased the performance and longevity of PEMFCs while lowering expenses. For PEMFC technology to evolve further, be successfully implemented in a variety of applications, and contribute to a more sustainable future, more research and development must be put forward. Full article

In this paper, particular attention is paid to an advanced variant of the plug-in hybrid electric vehicle, known as PHEV, which combines two functionalities: the vehicle’s internal combustion engine (ICE) and the electric motor. The study described herein also presents the influence of factors such as the ambient temperature, vehicle speed and traffic distance on the PHEV’s energy consumption. It has been shown that the vehicle’s range estimated based on its electronic control module (ECU) is about 20% shorter per annum on average for its year-round operation in everyday driving conditions. When analyzing the energy consumption based on the vehicle’s unitary energy consumption model, attention was paid to values that are strongly correlated with traffic and weather conditions. In addition, the authors emphasized that the estimated total energy consumption of a battery electric vehicle (BEV) or hybrid vehicle (PHEV), relative to the normative values arising from the type approval test cycle, deviate from the actual values arising from real driving conditions and often vary substantially. As shown in this paper, the energy consumption intensity of a vehicle is significantly influenced not only by its speed but also by weather conditions, including ambient temperature. In extreme cases, energy consumption intensity can increase by up to 68% relative to a WLTP (Worldwide Harmonized Light Vehicle Test Procedure) cycle. Full article

Indoor environmental parameters are closely related to the energy consumption and indoor thermal comfort of office buildings. Predicting these parameters, especially indoor temperature, can contribute to the management of energy consumption and thermal comfort levels in office buildings. An accurate indoor temperature prediction model is the basis for implementing this process. To this end, this paper first discusses the input and output parameters of the model, and then it compares the prediction effects of mainstream prediction model algorithms based on data mining under the same data conditions. The superiority of the XGBoost integrated learning algorithm is verified, and a further XGBoost-based indoor temperature online prediction method is designed. The effectiveness of the method is validated using actual data from a commercial office building in Haidian District, Beijing. Finally, optimization methods for the prediction method are discussed with regard to the scheduler mechanism proposed in this paper. Overall, this work can assist building operators in optimizing HVAC equipment running strategies, thus improving the indoor thermal comfort and energy efficiency of the building. Full article

A main restriction of renewables from intermittent sources is the mismatch between energy resource availability and energy requirements, especially when extensive power plants are producing at their highest potential causing huge energy surpluses. In these cases, excess power must be stored or curtailed. One alternative is increasing urban solar potential which could be integrated to feed electric buses directly or alternatively through hydrogen (H₂) as an energy vector. H₂ from renewable electricity can be stored and used directly or through fuel cells. This study aims to determine the H₂ capability that could be achieved when integrating large-scale photovoltaic (PV) generation in urban areas. This analysis was carried out by determining the PV energy potentially generated by installing PV in Cuenca City downtown (Ecuador). Cuenca is in the process of adopting renewal of the public transport vehicle fleet, introducing a new model with an electric tram main network combined with “clean type buses”. The conventional diesel urban transport could be replaced, establishing a required vehicle fleet of 475 buses spread over 29 routes, emitting 112 tons of CO2 and burning 11,175 gallons of diesel daily. Between the main findings, we concluded that the electricity that could be produced in the total roof area exceeds the actual demand in the study area by 5.5 times. Taking into account the energy surplus, it was determined that the available PV power will cover from 97% to 127% of the total demand necessary to mobilize the city bus fleet. The novelty of this work is the proposal of a combined methodology to find the potential to feed urban transport with urban solar power in cities, close to the equatorial line. Full article

Combustion instability is a common thermoacoustic coupling problem in combustion systems, and the pressure oscillations generated inevitably damage the combustion system. Studying the mechanism of combustion instability, especially the triggering problem of combustion instability, is particularly important for understanding combustion instability. This article adopts experimental research methods. The flame transfer function and flame describing function governing pressure pulsation were hereby measured to study the effect of heat release rate fluctuation on acoustic disturbance. By triggering combustion instability through ignition, the growth process of combustion instability was also studied. The results showed that flame pulsation amplitude shows a complex curvature when the frequency is lower than 200 Hz, while the growth rate of pulsation amplitude monotonically decreases as frequencies increase above 200 Hz. According to the considerable self−excited combustion instability tests, the oscillation amplitudes in the limit cycle state are generally greater than 0.4, while the pressure amplitudes in the limited state are less than 0.2, thus verifying the concept of a trigger threshold for low−frequency oscillation. In addition, analysis of the growth rate, the pressure and the attractor of the heat release pulsation observed after the triggering of combustion instability reveals that the triggering of combustion instability is a gradual coupling process between oscillation pressure and heat release rate pulsation. Full article

Replacing conventional CO₂ intensive generation with green electricity from RES constitutes an essential prerequisite of sustainable development. Renewables play a vital role in achieving the UN’s goals for clean low-cost energy production and the reverse of climate change process. Based on a comprehensive dataset including observations for 17 European countries between 2003 and 2020, the present research attempts to unveil the fundamental determinants of RES deployment. A panel FMOLS approach was utilized to provide a detailed analysis of the impact of electricity prices, energy taxes and competition level in both power generation and the retail electricity market on each country’s RES percentage participation in electricity production fuel mix. The final econometric outcomes verified the strong statistical significance of all examined variables for the vast majority of the countries, constituting them crucial aspects of national energy strategies. However, both the actual effects as well as the impact size were found to differ significantly across Europe, signifying the complexity of the EU’s task to develop a unified, autonomous and eco-friendly electricity market based on the principals of a fundamental energy strategy. Contributing to state authorities’ and EU’s colossal effort to deal with the crucial challenges of RES power generation, the paper proposes a series of targeted individual and groupwise policy implications. Full article

This paper addresses the optimal stochastic allocation of distributed energy resources in distribution networks. Typically, uncertain problems are analyzed in multistage formulations, including case generation routines, resulting in computationally exhaustive programs. In this article, two probabilistic approaches are proposed–range probability optimization (RPO) and value probability optimization (VPO)–resulting in a single-stage, convex, stochastic optimal power flow problem. RPO maximizes probabilities within a range of uncertainty, whilst VPO optimizes the values of random variables and maximizes their probabilities. Random variables were modeled with hourly measurements fitted to the logistic distribution. These formulations were tested on two systems and compared against the deterministic case built from expected values. The results indicate that assuming deterministic conditions ends in highly underestimated losses. RPO showed that by including ±10% uncertainty, losses can be increased up to 40% with up to −72% photovoltaic capacity, depending on the system, whereas VPO resulted in up to 85% increases in power losses despite PV installations, with 20% greater probabilities on average. By implementing any of the proposed approaches, it was possible to obtain more probable upper envelopes in the objective, avoiding case generation stages and heuristic methods. Full article

The scientific literature acknowledges cascaded H-bridge (CHB) converters as a viable alternative to two-level inverters in electric vehicle (EV) powertrain applications. In the context of an electric vehicle engine connected to a DC charger, this study introduces a state of charge (SOC)-governed method for charging li-ion battery modules using a cascaded H-bridge converter. The key strength of this algorithm lies in its ability to achieve balanced charging of battery modules across all three-phase submodules while simultaneously controlling the DC charger, eliminating the need for an additional intermediate converter. Moreover, the algorithm is highly customizable, allowing adaptation to various configurations involving different numbers of submodules per phase. Simulative and experimental results are presented to demonstrate the effectiveness of the proposed charging algorithm, validating its practical application. Full article

A self-sustained porous burner without a sprayed atomizer was built for diesel oil. It consisted of metal fiber felt as an evaporator upstream and ceramic foam as an emitter downstream. The liquid fuel underwent film boiling in the porous evaporator and was rapidly evaporated by the heat recirculated from the porous emitter to the porous evaporator through intense irradiative heat flux. The effect of the porous structure and its installation location on the performance of the porous burner was investigated. The results indicated that the evaporation and combustion of liquid fuel could be prompted by the radiation of porous media. The position of the flame moved downstream, and the flame temperature decreased when the distance between the metal fiber felt and the ceramic foam was increased. The lowest NOx concentration was obtained when the distance between the foam and the metal fiber felt was 90 mm. When the diameter of the central hole of the ceramic foam was increased, the position of the flame moved towards the burner outlet, and the flame temperature and NOx emission declined. The flame temperature of the divergent configuration as emitter was higher than that of the convergent configuration, and the flame temperature of the C–D configuration was higher than that of the D–C configuration. Different ceramic foam structures had a significant effect on the temperature and emission in the combustion chamber, which showed that the evaporation and radiation performance of inert porous media burners with different structures is quite different. Full article

The complication of the structure, topology and composition of the future electrical networks is characterized by difficult-to-recognize circuit-mode situations and requires modern methods for analyzing information parameters. The growing trend of digitizing signals in substations and the use of the IEC 61850 standard results in a huge amount of new data available at the nodes of the electrical network. The development and analysis of new methods for detecting and recognizing the modes of electrical networks (normal and emergency) are topical research issues. The article explores a new approach to recognizing a faulted section of an electrical network with branches by concurrently analyzing several information features and applying machine learning methods: decision tree, random forest, and gradient boosting. The application of this approach for decision-making by relay protection has not been previously implemented. Simulation modeling and the Monte Carlo method are at the heart of obtaining training samples. The results of testing the studied methods under review showed the required flexibility, the ability to use a large number of information parameters, as well as the best results of fault recognition in comparison with the distance protection relay. Full article

Offshore Wind Power Systems (OWPS) offer great energy and environmental advantages, but also pose significant Operation and Maintenance (O&M) challenges. In this survey, we analyze these challenges and propose some optimization strategies and technologies for OWPS comprehensively. The existing literature review mainly focuses on a certain field of offshore wind power O&M, but lacks a comprehensive introduction to offshore wind power. We consider the energy efficiency, reliability, safety, and economy of OWPS from various aspects, such as offshore wind and wave energy utilization, offshore wind turbine components, and wind power operation parameters, and compare them with onshore wind power systems. We suggest that OWPS can benefit from advanced design optimization, digital twin, monitoring and forecasting, fault diagnosis, and other technologies to enhance their O&M performance. This paper aims to provide theoretical guidance and practical reference for the technological innovation and sustainable development of OWPS. Full article

The article raises issues regarding the consumption of energy from both fossil and renewable sources in households. The research was carried out on the basis of data obtained from the Eurostat database, which covered the period from 1995 to 2021 and concerned the European Union countries. Increasing energy consumption and, thus, increasing household expenses affect their standard of living. The purpose of the analysis was to construct two econometric models for electricity consumption. The first model referred to the consumption of energy from fossil sources and the second from renewable sources. A forecast of energy consumption in households was also constructed on the basis of estimated models. Econometric modelling methods (multiple regression) and time-series forecasting methods (linear regression method, exponential smoothing models) were applied for the study. Research shows that the main factor that models energy consumption in households, both from fossil and renewable sources, is the final consumption expenditure of households (Euro per capita). The set of indicators for the models varies depending on the type of energy source. The forecast shows that the share of energy consumption obtained from fossil sources will decrease systematically, while the share of energy consumption from renewable sources will continue to increase systematically. Full article

At this stage, the inspection of transmission lines is dominated by UAV inspection. Insulators, as essential equipment for transmission line equipment, are susceptible to various factors during UAV detection, and their detection results often lead to leakages and false detection. Combining deep learning detection algorithms with the UAV transmission line inspection system can effectively solve the current sensing problem. To improve the recognition accuracy of insulator detection, the MS-COCO pre-training strategy that combines the FPN module with a cascading R-CNN algorithm based on the ResNeXt-101 network is proposed. The purpose of this paper is to systematically and comprehensively analyze mainstream isolator detection algorithms at the current stage and to verify the effectiveness of the improved Cascade R-CNN X101 model by combining the mAP (mean Average Precision) value and other related evaluation indices. Compared with Faster R-CNN, Retina Net, and other detection algorithms, the model is highly accurate and can effectively deal with the false detection, leakage, and non-recognition of the environment in online special detection. The research in this paper provides a new idea for intelligent fault detection of transmission line insulators and has some reference value for engineering applications. Full article

Difficulty in water injection during the water injection development (water injection production refers to the injection of water into the reservoir from injection wells during the development process of an oil field; due to its good economic efficiency and high feasibility, it has become the main method of oil field development) process of the G block reservoir is an important problem to solve. Three cores of the G block are used as the object of this study, and the laser particle size test is conducted on the target core to obtain the particle size distribution of the core. X-ray diffraction mineral content analysis is used to obtain the proportion of different mineral contents. On this basis, online nuclear magnetic technology is used to carry out the research on the change of reservoir physical properties during the high-magnification water injection process. The experiment shows that three cores (cores 8-2, 16-1, and 9) are identified as medium sandy fine sandstone with silt (the three-level naming method was adopted and the name has been changed to medium sandy fine sandstone containing silt, because the proportion of fine sand is greater than 50%, the content of medium sand is between 25%~50%, and the content of silt is between 10%~25%), medium sandy fin sandstone containing silt, and silt fine sandstone, by laser particle size testing. Their clay mineral contents are 2.47%, 2.51%, and 4.76%, respectively; the permeability (water) of the three cores continues to decrease with the increase in water injection, but the nuclear magnetic porosity and the signal intensity of different fluids in the nuclear magnetic T2 and nuclear magnetic two-dimensional spectrum show different variation patterns with the increase in water injection. The clay minerals of core 8-2 and core 16-1 are relatively small. The nuclear magnetic porosity increases rapidly to the maximum value and then decreases slowly with the increase in water injection. The right peak signal intensity in the T2 spectrum rises first and then drops, while the clay mineral content of core 9 is relatively high. The change trend of nuclear magnetic porosity is firstly decreasing and then increasing, and the signal intensity of the right peak in the T2 spectrum decreases first and then increases. The research concludes that in the early stage of water injection, clay minerals undergo hydration and a small amount of particle migration; in the later stage of water injection, due to the scouring effect of water, the fine silt and clay minerals in the cement easily fall off and migrate to the pore throat to the block. Some damage to the pore throat leads to a decrease in permeability, thus affecting the development effect. Full article

This paper establishes an accurate and reliable study for estimating the lithium-ion battery’s State of Charge (SoC). An accurate state space model is used to determine the parameters of the battery’s nonlinear model. African Vultures Optimizers (AVOA) are used to solve the issue of identifying the battery parameters to accurately estimate SoC. A hybrid approach consists of the Coulomb Counting Method (CCM) with an Adaptive Unscented Kalman Filter (AUKF) to estimate the SoC of the battery. At different temperatures, four approaches are applied to the battery, varying between including load and battery fading or not. Numerical simulations are applied to a 2.6 Ahr Panasonic Li-ion battery to demonstrate the hybrid method’s effectiveness for the State of Charge estimate. In comparison to existing hybrid approaches, the suggested method is very accurate. Compared to other strategies, the proposed hybrid method achieves the least error of different methods. Full article

In order to achieve efficient utilization of solar energy resources, this study combines the trans-critical organic Rankine cycle (ORC) power cycle (TORC) with the trans-critical CO₂ refrigeration cycle (TCO₂). Additionally, a comprehensive three-level index decision evaluation system is developed based on system safety and environmental protection, thermodynamics, and techno-economic performance. The evaluation focuses on typical medium- and high-temperature solar energy applications and considers six organic working gases. The evaluation results demonstrate that the R600 + CO₂ solution outperformed the others. This solution achieved a maximum net output power (P_net) of 1531.31 kW and 2306.43 kW, a maximum coefficient of performance (COP) of 3.16, a predicted payback period of 2.651 years and 2.033 years, and a benefit–investment ratio of 4.533 and 5.773. Full article

Electrochemical impedance is a powerful technique for elucidating the multi-scale polarization process of the proton exchange membrane (PEM) fuel cell from a frequency domain perspective. It is advantageous to acquire frequency impedance depicting dynamic losses from signals measured by the vehicular sensor without resorting to costly impedance measurement devices. Based on this, the impedance data can be leveraged to assess the fuel cell’s internal state and optimize system control. In this paper, a residual network (ResNet) with strong feature extraction capabilities is applied, for the first time, to estimate characteristic frequency impedance based on eight measurable signals of the vehicle fuel cell system. Specifically, the 2500 Hz high-frequency impedance (HFR) representing proton transfer loss and 10 Hz low-frequency impedance (LFR) representing charge transfer loss are selected. Based on the established dataset, the mean absolute percentage errors (MAPEs) of HFR and LFR of ResNet are 0.802% and 1.386%, respectively, representing a superior performance to other commonly used regression and deep learning models. Furthermore, the proposed framework is validated under different noise levels, and the findings demonstrate that ResNet can attain HFR and LFR estimation with MAPEs of 0.911% and 1.610%, respectively, even in 40 dB of noise interference. Finally, the impact of varying operating conditions on impedance estimation is examined. Full article

The objective of this work is to assess the wind resources of the east coast of Maranhão, Brazil. Wind profilers were combined with micrometeorological towers and atmospheric reanalysis to investigate micro- and mesoscale aspects of wind variability. Field campaigns recorded winds in the dry and wet seasons, under the influence of the Intertropical Convergence Zone. The dry season was characterized by strong winds (8 to 12 m s${}^{-1}$) from the northeast. Surface heat fluxes were generally positive (250 to 320 W m${}^{-2}$) at midday and negative (−10 to −20 W m${}^{-2}$) during the night. Convective profiles predominated near the beach, with strongly stable conditions rarely occurring before sunrise. Further inland, convective to strongly convective profiles occurred during the day, and neutral to strongly stable profiles at night. Wind speeds decreased during the rainy season (4 to 8 m s${}^{-1}$), with increasingly easterly and southeasterly components. Cloud cover and precipitation reduced midday heat fluxes (77 W m${}^{-2}$). Profiles were convective during midday and stable to strongly stable at night. Terrain roughness increased with distance from the ocean ranging from smooth surfaces ($z_o$ = 0.95 mm) and rough pastures ($z_o$ = 15.33 mm) to crops and bushes ($z_o$ = 52.68 mm), and trees and small buildings ($z_o$ = 246.46 mm) farther inland. Seasonal variations of the mean flow and sea and land breezes produced distinct diurnal patterns of wind speeds. The strongest (weakest) breeze amplitudes were observed in the dry (rainy) period. Daily changes in heat fluxes and fetch over land controlled the characteristics of wind profiles. During sea breezes, winds approached the coast at right angles, resulting in shorter fetches over land that maintained or enhanced oceanic convective conditions. During land breezes, winds blew from the mainland or with acute angles against the coastline, resulting in large fetches with nighttime surface cooling, generating strongly stable profiles. Coastal observations demonstrated that with increasing monopiles from 100 to 130 m it is possible to obtain similar capacity factors of beachfront turbines. Full article