Energies, Volume 17, Issue 4 (February-2 2024) – 212 articles

With the ongoing expansion and interconnection of electrical power systems, alongside the rapid proliferation of renewable distributed generations (DGs), the short-circuit extent in the power grid is experiencing a significant rise. Fault current limiters (FCLs) have been introduced in an effort to address this issue, ensuring the robustness and sustainability of expensive power system components when confronted with short-circuit faults. Among the various types of FCLs, bridge-type DC reactor fault current limiters (BDCR-FCLs) have emerged as one of the most promising options. While BDCR-FCLs have shown excellent properties in limiting harmful short-circuit currents, they are also advantageous in other respects. This paper investigates the supplementary functionalities of BDCR-FCLs as a multifaceted device towards the enhancement of the quality of supplied energy in terms of total harmonic distortion (THD) reduction, power factor (PF) correction, peak current reduction for nonlinear loads, and soft load variation effects, as well as their capability to limit fault current. To this aim, the capabilities of BDCR-FCLs have been studied through various simulated case studies in PSCAD/EMTDC software V5.0.1, in addition to experimental tests considering an AC microgrid connected to a DC system. The experimental and simulation investigations verify the superior multifaceted functionalities BDCR-FCLs introduce in addition to their excellent fault current-limiting capabilities. The results show that PF improved by 6.7% and 7%, respectively, in simulation and experimental tests. Furthermore, the current THD decreased by 20% and 18% in the simulation and experiment, respectively. Full article

Dark fermentation (DF) of kitchen waste (KW) is a promising technology for the production of renewable biohydrogen. It can be both a method of obtaining clean energy and a sustainable waste management. Despite its potential, this process requires further research to improve efficiency. The aim of the research was to test the effect of thermal pretreatment of the inoculum on H₂ and volatile fatty acids (VFAs) production in the DF process. The process was carried out at 37 °C, in batch mode. The digested sludge from the Group Wastewater Treatment Plant in Lodz was used as inoculum. KW from households was used as substrate. The inoculum was pre-treated at 70 °C for 15 and 30 min. Two control reference experiments were also used. The first without the inoculum, and the second without heating the inoculum. The thermal pretreatment inhibited methane production and increased hydrogen production. After the thermal pretreatment, the amount of CO₂ produced during the process decreased compared to the bioreactor without inoculum pretreatment. Additionally, the main VFAs in the samples with pretreated inoculum were acetic and butyric acids, which are associated with hydrogen production in the biochemical pathways of the DF process. However, the time of thermal pretreatment had no significant effect on H₂ production. Full article

Battery electric trucks (BETs) represent a well-suited option for decarbonizing road freight transport to achieve climate targets in the European Union. However, lower ranges than the daily distance of up to 700 km make charging stops mandatory. This paper presents an online algorithm for optimal dynamic charging strategies for long-haul BET based on a dynamic programming approach. In several case studies, we investigate the advantages optimal strategies can bring compared to driver decisions. We further show which charging infrastructure characteristics in terms of charging power, density, and charging station availability should be achieved for BETs in long-haul applications to keep the additional time required for charging stops low. In doing so, we consider the dynamic handling of occupied charging stations for the first time in the context of BET. Our findings show that, compared to driver decisions, optimal charging strategies can reduce the time loss by half compared to diesel trucks. To keep the time loss compared to a diesel truck below 30 min a day, a BET with a 500 kWh battery would need a charging point every 50 km on average, a distributed charging power between 700 and 1500 kW, and an average charger availability above 75%. The presented method and the case studies’ results’ plausibility are interpreted within a comprehensive sensitivity analysis and subsequently discussed in detail. Finally, we transformed our findings into concrete recommendations for action for the efficient rollout of BETs in long-haul applications. Full article

In this work, hemp (Cannabis sativa L.) stalks were pretreated with pyrrolidinium acetate [Pyrr][AC] to increase the availability of cellulose for cellulolytic enzymes and thus improve the production of 2G ethanol from reducing sugars. The process was carried out under different temperature and time conditions: The control sample was raw material and deionized water, and the second sample was kept at 21 °C for 24 h. The third sample was kept at 90 °C for 30 min, and the fourth sample was kept at the same temperature for 24 h. For each pretreatment, the extraction of lignin and hemicellulose was determined, as well as the change in biomass composition before and after pretreatment. The stalks of hemp seed contained 41.54% cellulose, 18.08% lignin and 28. 87% hemicellulose. [Pyrr][AC] used to dissolve seed hemp at 90 °C for 24 h was most effective in the extraction of this biopolymer, extracting 3.1% content. After enzymatic hydrolysis, the highest content of reducing sugars was found for samples of hemp stalks that were first pretreated with proton ionic liquid (PIL) and stirred at 90 °C for 24 h. On the other hand, the highest ethanol content (5.6 g/L) after fermentation and yeast viability (56.7%) after 72 h were obtained in samples pretreated at 90 °C and for 24 h. Full article

The article analyses the evolution of the social dimension in energy security transition in Lithuania. It contributes to an emerging attempt in the literature to broaden the horizons of our understanding of societal transformation and energy transitions. The analysis reveals the interdependence of changing Lithuanian society and its developing energy security concerns throughout the Independence period, from the importance of material threats (ecological, economic, and political) to post-material values (such as climate change concerns) in the context of energy security. Accordingly, the energy sector undergoes a vivid transition from a totally dependent “Energy Island” to a diversified, interconnected, and self-sustainable system. Such a journey inevitably resulted in the highlight of the social dimension in energy security and provoked certain socio-economic implications, like changing public awareness and participation, social equity and justice, and socio-economic resilience and vulnerability. The research is based on case study principles (applying sociological discourse analysis through scientific articles’ qualitative content analysis method as well as energy security policy analysis reviewing all national strategies throughout the Independence period) and is focused on a unique Lithuanian context. Full article

An investigation into the non-premixed combustion characteristics of methane in a planar micro-combustor with a splitter was performed. The impact of blending methane with hydrogen on these characteristics was also analyzed. Additionally, the effects of inlet velocity and global equivalence ratio on flame location, flame temperature, combustion efficiency and outer wall temperature were studied for three different fuel compositions: pure methane (MH0), 60% methane with 40% hydrogen (MH40), and 40% methane with 60% hydrogen (MH60)). A heat recirculation analysis of the combustor wall was conducted to determine the amount of heat recirculated into the unburnt gas at various inlet velocities for all three fuel compositions. The results demonstrated that the stability limit of methane in terms of inlet velocity (1–2 m/s) and global equivalence ratio (1.0–1.2) was significantly enhanced to 1–3 m/s and 0.8–1.2, respectively, with the addition of hydrogen. At an inlet velocity of 2 m/s, the flame location of 3.6 mm for MH0 was significantly improved to 2.2 mm for MH60. Additionally, outer wall temperature exhibited a rise of 100 K for MH60 compared to MH0. Furthermore, from heat recirculation analysis, when the ratio of heat recirculated to heat loss exceeded unity, the flame started exhibiting the lift-off phenomenon for all the fuel compositions. Full article

In the context of global value chains (GVCs), the impact of the Belt and Road Initiative (BRI) on China’s bilateral trade with Belt and Road countries (BRCs) is controversial. This study constructed a GVC accounting framework based on a multiregional input–output model, aiming to clarify the trends and transfer characteristics of the value added (VA) and the embodied carbon emissions (ECEs) in China–BRCs bilateral trade from 2000 to 2018 at the overall country, Belt and Road region (BRR), and typical country levels. The relevant results are threefold. (1) At the overall country level, the BRCs VA and ECEs imports and exports have shown overall increasing trends. (2) Most BRRs are net ECE exporters to China. Southeast Asia and Northeast Asia are the main ECEs destinations and sources. (3) In China–typical BRCs bilateral trade, China is a net ECEs exporter to most typical BRCs, and the net ECE transfers through route 1 (onefold value chain) are all positive, implying that route 1 can reduce ECEs in BRCs. These findings can help formulate policies and measures to reduce carbon emissions and provide a scientific basis for realizing the coordinated development of carbon emission reduction and economy in China and BRCs. Full article

This paper proposes a long short-term memory (LSTM) network to predict the power degradation of proton exchange membrane fuel cells (PEMFCs), and in order to promote the performance of the LSTM network, the ant colony algorithm (ACO) is introduced to optimize the hyperparameters of the LSTM network. First, the degradation mechanism of PEMFCs is analyzed. Second, the ACO algorithm is used to set the learning rate and dropout probability of the LSTM network combined with partial aging data, which can show the characteristics of the dataset. After that, the aging prediction model is built by using the LSTM and ACO (ACO-LSTM) method. Moreover, the convergence of the method is verified with previous studies. Finally, the fuel cell aging data provided by the Xiangyang Da’an Automotive Testing Center are used for verification. The results show that, compared with the traditional LSTM network, ACO-LSTM can predict the aging process of PEMFCs more accurately, and its prediction accuracy is improved by about 35%, especially when the training data are less. At the same time, the performance of the model trained by ACO-LSTM is also excellent under other operating conditions of the same fuel cell, and it has strong versatility. Full article

The most general purpose of the current paper is to trace and discuss the history and state of the art of studies on vehicle motion (dynamics) in a transition curve above the critical velocity, with the aim of potentially increasing the circle of researchers involved in studying this issue and strengthening the will of the authors to continue their studies. This general goal is achieved in two ways: first, through a profiled literature analysis, showing the historical progress and current state of the research; and second, through reference to the history of stability studies as an example of selected studies’ development. In addition, this work has two more specific goals. Together, they consist of collecting the literature in a related field in one place and analyzing it on site to accomplish the review. Both specific goals are attained by dividing the literature into two corresponding parts. In the first part, the current issues of rail vehicle stability are analyzed and divided into four problems. The second part includes works that deal with the subject of the motion and dynamics of a rail vehicle on a transition curve section. Here, the works are divided into five groups and discussed. They are put in order from the closest to the furthest from this paper’s main subject; however, the last group includes the most recent references. In addition, information on the authors’ approach to the problem is provided, including the methods and models used, as well as example results. Based on the analysis of the literature and the state of the art, a summary of the analysis is presented at this paper’s end. It highlights the small number of works on the subject of interest, and based on the review of stability studies, it seeks to encourage present and potential authors to study this field and share their results with society. Full article

Agricultural emissions can be significantly reduced with smart farming, which includes moving away from large conventional tractors to fleets of compact wheeled electric robots. This paper presents a novel simulation modeling approach for an ATV-sized wheeled electric agricultural robot pulling an implement on deformable terrain. The 2D model features a semiempirical tire–soil interaction model as well as a powertrain model. Rear-wheel drive (RWD), front-wheel drive (FWD), and all-wheel drive (AWD) versions were developed. Simulations were carried out on two different soils to examine the energy consumption and tractive performance of the powertrain options. The results showed that energy consumption varies the least with AWD. However, RWD could provide lower energy consumption than AWD with light workloads due to lower curb weight. However, with the heaviest workload, AWD had 7.5% lower energy consumption than RWD. FWD was also found to be capable of lower energy consumption than AWD on light workloads, but it was unsuited for heavy workloads due to traction limitations. Overall, the results demonstrated the importance of taking the terrain characteristics and workload into account when designing electric agricultural robots. The developed modeling approach can prove useful for designing such machines and their fleet management. Full article

The studies of the rheology of digested pulp from agricultural biogas plants have often been fragmentary and non-standardised due to their complexity and time-consuming nature. As a result of measurements, it was possible to develop a procedure and range of measurements for the correct determination of the parameters of the carrier substance. The applicability of the coaxial cylinder measurement system was demonstrated for assessing the rheological parameters of digested pulp from a fermenter that utilises agricultural biomass. To determine the characteristics of solid particles, the Zingg diagram was used, inter alia, allowing the comparison of particles from each fraction. The analysis of the shape and size of solid particles may help to describe the onset of motion of this phase, flow type, or sedimentation type. The authors propose a completely new research approach to obtain an appropriate, repeatable test conditions of medium, which is the carrier liquid from the biogas plant reactor. The proposed methodology and the scenario of the entire study make it possible to achieve scalable and comparable test results in any laboratory. The proposed solution eliminates the influence of most external factors on the sample and rheological measurements, and the effectiveness of the presented procedure was confirmed in tests. Full article

The muddy limestone in the Lei₃² sub-member of the Middle Triassic Leikoupo Formation in the well Chongtan 1 (CT1) of the Sichuan Basin has yielded promising industrial oil and gas production. This discovery has the potential to become a significant strategic reservoir in the future for oil and gas exploration in the Sichuan Basin. However, the understanding of hydrocarbon accumulation in the muddy limestone of the Lei₃² sub-member remains insufficient, which poses limitations on further exploration selection and deployment strategies. This study focuses on the analysis of core samples and laboratory data in the wells CT1 and Jianyang 1 (JY1), aiming to investigate the source rock and reservoir characteristics of the muddy limestone in the Lei₃² sub-member, as well as the primary controlling factors influencing the development of the source rock and reservoir. The results show that the Lei₃² sub-member in the Central Sichuan Basin is an evaporated lagoon deposition; the tight argillaceous limestone and limy mudstone exhibit the characteristic of source–reservoir integration, belonging to a new type of unconventional oil and gas reservoir. The reservoir space of the argillaceous limestone and limy mudstone in the Lei₃² sub-member primarily consists of inorganic and organic micro–nanopores and microfractures. The average porosity and permeability are 2.7% and 0.19 mD, indicating a low-porosity and low-permeability unconventional reservoir. The clay minerals and gypsum content are the important factors influencing reservoir porosity, and the fractures are key factors influencing permeability. This study will elucidate the specific features of hydrocarbon accumulation in the muddy limestone reservoirs of the Lei₃² sub-member and provide insights into its exploration potential. Full article

The reliability and stability of differential protection in power transformers could be threatened by several types of inferences, including magnetizing inrush currents, current transformer saturation, and overexcitation from external faults. The robustness of deep learning applications employed for power system protection in recent years has offered solutions to deal with several disturbances. This paper presents a method for detecting internal faults in power transformers occurring simultaneously with inrush currents. It involves utilizing a data window (DW) and stacked denoising autoencoders. Unlike the conventional method, the proposed scheme requires no thresholds to discriminate internal faults and inrush currents. The performance of the algorithm was verified using fault data from a typical Korean 154 kV distribution substation. Inrush current variation and internal faults were simulated and generated in PSCAD/EMTDC, considering various parameters that affect an inrush current. The results indicate that the proposed scheme can detect the appearance of internal faults occurring simultaneously with an inrush current. Moreover, it shows promising results compared to the prevailing methods, ensuring the superiority of the proposed method. From sample N–3, the proposed DNN demonstrates accurate discrimination between internal faults and inrush currents, achieving accuracy, sensitivity, and precision values of 100%. Full article

The heterogeneity, sedimentary characteristics, and distribution of fine-grained sediments of millimeter-scale laminae were studied in alkaline lacustrine strata in the lower Permian Fengcheng Formation (P₁f₂) in the Mahu Sag to provide a sound theoretical basis for shale oil exploration and development. They were investigated by using core and thin-section observation, geochemical and elemental analysis, mineral identification, and pore examination. Five types of laminae were distinguished, with different mineral compositions, pore characteristics, and distributions. These laminae occur in four distinct combinations. The pore systems predominantly consist of intercrystalline pores, intragranular pores, and dissolution pores of feldspar and dolomite and also contain imporous alkaline mineral particles. Influenced by variations in salinity, the influx of volcanic–hydrothermal material, and the participation of both endogenous and exogenous materials, the formation has gone through five stages of sedimentary evolution. Furthermore, felsic laminae (FQL), dolomite laminae (DOL)/reedmergnerite laminae (RL)/shortite laminae (SL), and chert laminae (CL) developed in single-terrestrial-source still water deposition, hybrid-source still water deposition, and single-intrasource deposition, respectively. Vertically, the FQL-DOL combination shows favorable reservoir characteristics and is the most extensively developed lamina combination in the Fengcheng Formation that primarily developed in the period of the late Feng 1 Member (P₁f₁), the early Feng 2 Member (P₁f₂), the late Feng 2 Member (P₁f₂), and the early Feng 3 Member (P₁f₃). The FQL-RL/SL combination primarily developed in the period of the middle P₁f₂, and the DOL-CL combination is the counterpart in the period of the early P₁f₂ and the late P₁f₂ stages. Considering this in conjunction with the longitudinal distribution of lamina combinations, a model is proposed for the distribution of fine-grained sediments in alkaline lacustrine strata. Full article

The EU has planned the phase-out of new vehicles based on internal combustion engines in favor of high-efficiency battery electric vehicles (BEV) by 2035 (Fit for 55 package). However, many doubts remain about the effectiveness of this choice for each country of the Union in terms of CO₂ emissions reduction, as each State is characterized by a different carbon intensity related to the production of electricity needed to manufacture and recharge vehicles. This study seeks to explore the Italian case. To this aim, carbon intensities related to electricity production were calculated considering both the Italian electricity mix production in 2022 and those envisaged in 2035, considering two energy scenarios based on different introductions of renewable energy sources (RES). Afterward, the values obtained were adopted for determining the CO₂ emissions related to the whole production process of battery systems in Italy (emissions from mining and refining, scrap materials, and final assembly included) by comparing some of the most up-to-date Life-Cycle Assessment (LCA) analyses related to the manufacturing cycle of the batteries. Finally, the results were adopted to calculate the starting carbon debit for A, B, C, and M car segments for Mild Hybrid, Full Hybrid, and Full Electric powertrains. At the same time, statistical road fuel/electricity consumption data were collected and overall CO₂ emissions were calculated for the same vehicles adopting a dynamic approach and plotted for a defined distance, so as to determine break-even points with respect to the cumulative (i.e., from battery and road) carbon emissions. The results showed that advantages related to electric vehicles are significant only if a low carbon intensity related to electricity production is reached by means of a very high introduction of RES, thus keeping the door open for innovative hybrid powertrain technologies, if fed with low carbon fuels. Full article

Given the inherent volatility and intermittency of photovoltaic power generation, enhancing the precision of photovoltaic power predictions becomes imperative to ensure the stability of power systems and to elevate power quality. This article introduces an intelligent photovoltaic power prediction model based on the Extreme Learning Machine (ELM) with the Adaptive Spiral Dung Beetle Optimization (ASDBO) algorithm. The model aims to accurately predict photovoltaic power generation under multi-factor correlation conditions, including environmental temperature and solar irradiance. The computational efficiency in high-dimensional data feature conditions is enhanced by using the Pearson correlation analysis to determine the state input of the ELM. To address local optimization challenges in traditional Dung Beetle Optimization (DBO) algorithms, a spiral search strategy is implemented during the dung beetle reproduction and foraging stages, expanding the exploration capabilities. Additionally, during the dung beetle theft stage, dynamic adaptive weights update the optimal food competition position, and the levy flight strategy ensures search randomness. By balancing convergence accuracy and search diversity, the proposed algorithm achieves global optimization. Furthermore, eight benchmark functions are chosen for performance testing to validate the effectiveness of the ASDBO algorithm. By optimizing the input weights and implicit thresholds of the ELM through the ASDBO algorithm, a prediction model is established. Short-term prediction experiments for photovoltaic power generation are conducted under different weather conditions. The selected experimental results demonstrate an average prediction accuracy exceeding 93%, highlighting the effectiveness and superiority of the proposed methodology for photovoltaic power prediction. Full article

Photovoltaic (PV) modules have emerged as a promising technology in the realm of sustainable energy solutions, specifically in the harnessing of solar energy. Photovoltaic modules, which use solar energy to generate electricity, are often used on terrestrial platforms. In recent years, there has been an increasing inclination towards the installation of photovoltaic (PV) modules over water surfaces, including lakes, reservoirs, and even oceans. The novel methodology introduces distinct benefits and complexities, specifically pertaining to the thermal characteristics of the modules. In order to accomplish this objective, a photovoltaic (PV) module system with a capacity of 1 MW was developed as a scenario in the PVsyst Program. The scenario simulation was conducted on the Mamasın Dam, situated in the Gökçe village within the Aksaray province. To conduct the efficiency analysis, a comparative evaluation was conducted between bifacial and monofacial modules, which were installed from above the water at 1 m. The comparison was made considering two different types of modules. Additionally, the albedo effect, water saving amount, and CO₂ emissions of the system were also investigated. Albedo measurements were made in summer when the PV power plant will operate most efficiently. As a result of the simulations, it was found that bifacial modules produce 12.4% more energy annually than monofacial modules due to the albedo effect. It is estimated that PV power plant installation will save 19,562.695 and 17,253.475 tons of CO₂ emissions in bifacial and monofacial systems, respectively. Full article

Galloping-based piezoelectric energy harvesting systems are being used to supply renewable electricity for low-power wireless sensor network nodes. In this paper, a W-shaped bluff body is proposed as the core component of a piezoelectric wind energy harvester. Experiments and simulations have shown that the W-shaped bluff body can improve harvesting efficiency at low wind speeds. For the W-shaped structure, the finite element simulation results indicate that the structure can help improve the aerodynamic performance to obtain high aerodynamic force. The experimental results demonstrate that compared with the traditional bluff bodies, the piezoelectric wind energy harvester with the W-shaped bluff body (WEHW) can generate higher output voltages and has a lower cut-in speed. When the length L is 30 mm and the rear groove angle β is 30°, the W-shaped structure can induce the best harvesting performance. When an external load resistance of 820 KΩ is connected and the wind speed is 5 m/s, the WEHW generates an average output power of 0.28 mW. Full article

Permanent magnet (PM) motors are gaining prominence in subsea applications such as drilling, pumping, and boosting for oil and natural gas extraction. These motors are gradually replacing traditional induction motors. However, starting and operating PM motors at low speeds under heavy loads poses significant challenges. This is because of unknown initial rotor positions and resistive voltage drops due to the presence of a sinewave filter, transformer, and long cable. An unknown rotor position may result in temporary reverse speed, which may cause a loss of synchronism; therefore, initial rotor position estimation is preferable. Additionally, addressing the voltage drop issue requires careful voltage compensation to avoid transformer core saturation. In this paper, an enhanced $V/Hz$ starting of a PM motor is proposed with initial position detection (IPD) and voltage compensation to start the motor reliably with a heavy load. The proposed control method is verified with controller hardware in the loop (C-HIL) real-time simulation using a Typhoon HIL-604 emulator and a Texas Instruments TMS320F28335 digital signal processor (DSP) control card. Full article

The deployment of proppant to fracture shear is a promising approach to stimulating hydraulic permeability in fractured reservoirs. However, the interactive effects of proppant and surface roughness have not been clearly revealed. To better understand this concern, direct shear tests (DSTs) are implemented on 2D rough fractures with a joint roughness coefficient (JRC) varying from 4 to 6 and 18 to 20 under propped conditions. The results show that peak shear strength is positively proportional to asperity amplitude. The highest peak shear strength is determined with a JRC of 14–16 due to it having the highest asperity of 6.34 mm. The peak shear load was decreased significantly by deploying the proppant. Shear damage only occurs in the localized zone where the upper–lower asperities contact. The shear dilatancy was attributed to both the “shear climbing” effects and the shear damage that caused the frictional slip. The proppants weaken the climbing effect but also prevent the shear damage that in turn promotes shear dilatancy. Full article

Given the growing shares of renewable energy sources in the grids, the interest in energy storage systems has increased. The role of pumped hydro energy storage systems as flexible solutions for managing peak and off-peak prices from nuclear and fossil power plants in previous systems is now revitalized in the liberalized systems, with a volatile generation of wind and solar energy. Thus, understanding of the patterns behind the economics of energy storage is crucial for the further integration of energy storage in the grids. In this paper, the factors that impact the economic viability of energy storage in electricity markets are analyzed. The method of approach used in this study considers the electricity market price distribution, full load hours, the total costs of energy storage, and linear regression analysis. Using revenues from arbitraging a 10-megawatt (MW) pumped hydro storage system in the Western Balkans, resulting from the electricity market price distribution and the analysis of the total costs of storage, an econometric model is created. This model shows the impacting factors of energy storage development in the context of the rising renewables sector. Research shows that the previous hypothesis about the integration of energy storage systems in proportion to the increase in shares of renewables in the grids is incorrect. There is a significant correlation between energy storage revenues, the dependent variable, and the independent variables of hydro, wind, and solar generation. The conducted analysis indicates the future arbitraging opportunities of pumped hydro energy storage systems and provides useful insights for energy storage investors and policymakers. During the transitional period, until the deployment of renewables changes the effects of fossil power plants, energy storage price arbitrage is profitable and desirable for 500, 1000, and 2000 full load hours in the Western Balkan region. Despite the need for flexibility, with more renewables in the grids, large-scale energy storage systems will not be economically viable in the long run because of “revenue cannibalization”. Full article

In low-voltage AC distribution systems, when a series arc fault occurs in a branch with multiple loads operating in parallel, it will be significantly more difficult to identify. Existing arc fault detection methods make it difficult to effectively detect faults occurring in the lower-level branch. This study introduces a novel series arc fault detection approach based on the improved northern goshawk optimization adaptive base class LogitBoost (INGO-ABCLogitBoost) algorithm. Considering the zero-rest, intermittent, and random fluctuation and high-frequency features of the arc current, the zero-rest coefficient, discrete coefficient, harmonic amplitude, and wavelet entropy are proposed to establish the high-dimensional feature matrix of the arc current. The ReliefF feature selection algorithm is used to optimize feature quality and decrease feature dimensionality. Subsequently, the ABCLogitBoost fault detection model is proposed, with the INGO algorithm applied to optimize the model parameters, thus enhancing the model’s diagnostic capabilities. The efficacy of the proposed diagnostic model is validated through the construction of a multi-load arc simulation system. The simulation results show that the overall fault diagnosis accuracy of the proposed method reaches 99.01% and can effectively identify the fault load types, which helps to locate the fault location. Full article

This study focuses on the renovation and construction of compressed air energy storage chambers within abandoned coal mine roadways. The transient mechanical responses of underground gas storage chambers under a cycle are analyzed through thermal-solid coupling simulations. These simulations highlight changes in key parameters such as displacement, stress, and temperature within the chamber group during the loading and unloading processes of compressed air energy storage. It is found that within a cycle, the small circular chamber experiences the most significant deformation, with an average peak displacement of 0.24 mm, followed by the large circular chamber and horseshoe-shaped tunnels. The small circular chamber exhibits maximum tensile and compressive stresses. Therefore, special attention in engineering practice should be paid to the long-term safety and stability of small circular tunnels, and the stability of horseshoe-shaped tunnels should be also carefully considered. The findings from this study offer some insights for theoretical support and practical implementation in the planning, design, construction, and operation of high-pressure underground gas storage chambers for compressed air energy storage. Full article

In this research, we propose a fixed-time sliding mode controller using a prescribed performance control approach to address the speed tracking problem in linear motor traction systems, which are powered by high-power permanent magnet linear synchronous motors (PMLSMs). Initially, to tackle the issue of the convergence time and dynamic response associated with traditional finite-time sliding mode controllers, we introduce a fixed-time sliding mode controller. This controller guarantees that the system state converges to the origin within a specified upper time limit. Subsequently, to enhance the dynamic response of the PMLSM and minimize speed errors, we integrate the prescribed performance control strategy with a fixed-time sliding mode controller. This effectively limits the motor’s speed error within the predefined function boundaries, reduces system overshoo, and mitigates system jitter to a certain degree. Finally, simulation results are presented to validate that the proposed control strategy significantly enhances precision of speed tracking in PMLSMs. Full article

The electrification of process industries is one of the main challenges when building a low-carbon society since they consume huge amounts of fossil fuels, generating different emissions. Heat pumps are some of the key players in the industrial sector of the carbon-neutral market. This study proposes an approach to improve the economic feasibility of heat pumps within process plants. Initial energy targeting with grand composite curves was used and supplemented with the detailed design of an evaporator and a compressor for different condensation and evaporation pressures. The trade-off between the capital cost of the heat pump and the electricity cost was investigated, and optimal configurations were selected. This case study investigates the gas fractioning unit of a polymer plant, where three heat pumps are integrated into distillation columns. The results demonstrate that the heat recovery is 174 MW and requires an additional 37.9 MW of electricity to reduce the hot utility by 212 MW. The selection of the evaporation and condensation pressures of heat pumps allows 21.5 M EUR/y to be saved for 7 years of plant operation. The emission-saving potential is estimated at 1.89 ktCO₂/y. Full article

In order to improve the performance of an arc suppression coil grounding system in handling cross-line two-point successive grounding faults (CTSGs), the applicability of the transient quantity method and the steady-state quantity method for assessing CTSGs is analyzed. Then, a novel method for line selection for CTSGs was proposed, which comprehensively utilizes transient and steady-state information. Specifically, this method adopts a continuous line selection process, with priority given to the transient quantity method, and a supplementary line selection process, with priority given to the steady-state quantity method. After accurately selecting some faulty lines, such lines are tripped, and then, the process proceeds with continuous line selection again. When the number of cycles exceeds the set value, and the fault line cannot be completely cut off, they are tripped one by one according to the degree to which they are approaching the steady-state method criterion, from large to small. Furthermore, in response to the dramatic increase in computing volume that is caused by the continuous application of the transient method in on-site applications and the impact of current transformer accuracy on the steady-state method, this paper proposes corresponding solutions. PSCAD simulation, full-scale tests, and field recording data tests verify that this paper’s method can accurately detect a CTSG. Full article

The quality of the intermediate point temperature control of a supercritical unit is directly related to the quality of the coal–water ratio and main steam temperature control of the supercritical unit, which is also related to the economy and safety of the unit. In order to improve the accuracy of short-term predictions of the intermediate point temperature, a short-term prediction model of the intermediate point temperature based on the EEMD (Ensemble Empirical Mode Decomposition)-LSTM (Long Short-Term Memory) model is proposed. This model uses the data of a 600 MW thermal power station in 2022 as a sample. The EEMD method is used to decompose the historical data into IMF components and residual components, and the correlation between each component and the original data is calculated. The relevant components are sent to the LSTM neural network, and all the sub-components are superimposed to obtain the final intermediate point temperature prediction results. At the same time, the BP and LSTM models are built to compare the errors with the proposed model. The results show that the single model will produce large errors when predicting the factors of large data fluctuations. The EEMD–LSTM coupling model can fully extract the detailed features and the prediction effect is obvious. The prediction accuracy of the EEMD–LSTM prediction model built in this paper is significantly better than that of the other two models. It has certain application value in the research field of intermediate point temperature prediction and can meet the requirements of short-term predictions of the intermediate point temperature. Full article

In this paper, a user thermal comfort criterion based on predicted mean vote (PMV) values is introduced to realize the optimal operation of an improved energy hub (IEH) while considering thermal inertia and user thermal behavior. A three-layer optimization model based on user thermal comfort is constructed which fully considers user thermal comfort demand, IEH operating costs, and energy network constraints. Moreover, since IEH optimization considering user thermal comfort is a multi-objective bilevel optimization (MNBO) problem, this paper proposes an improved multilayer nested quantum genetic algorithm (IMNQGA) to solve it. Finally, the effectiveness of the proposed optimization model and algorithm is verified through the analysis of the four modes. The examples show that the proposed optimal control method can reduce the system’s operating costs and improve energy efficiency while satisfying user thermal comfort demand. Full article

The global energy crisis, which began in 2021 due to the extraordinary economic recovery after the pandemic and intensified after Russia’s invasion of Ukraine in February 2022, has changed the conditions of energy management, paying more attention to energy efficiency. Natural gas prices have reached record levels and, consequently, so have electricity prices in some markets. Oil prices have reached their highest level since 2008. Higher energy prices have contributed to sharply increased inflation. Households are again becoming interested in buying coal as a source of heat. High energy and gas prices have pushed many families into poverty and forced some factories to cut production or even close. They have also slowed economic growth to the point where some countries are heading for a serious recession. Paradoxically, the negative effects of the energy crisis may accelerate the introduction of cleaner, sustainable, renewable energy such as wind and solar energy. The energy crisis is comparable to the oil crisis of the 1970s, when it contributed to significant advances in energy efficiency. The current crisis has highlighted the importance of investments in renewable energy resources and initiated the process of integrating regional markets, developing energy efficiency and promoting renewable energies. The aim of this article is to comprehensively explore the complex relationship between energy awareness, consumption patterns, and energy efficiency, with a focus on both individual consumers and industries, during the global energy crisis. This paper is based on a literature review, overarching policy documents, energy reports, and other secondary documents. The primary research method was the systematic literature review method, based on which the impact of the global energy crisis on energy efficiency was evaluated. This study emphasizes the diverse influences on energy awareness, ranging from economic factors to consumer preferences and environmental consciousness. The findings of the paper underscore the significant responsibility of industries in contributing to energy-saving efforts and the active role of consumers in the energy market. The responsibility of industries in contributing to energy efficiency is highlighted, with a call for a comprehensive approach that integrates energy-saving criteria into product development and corporate social responsibility. Full article

Shutdowns of photovoltaic installations are a problem that has been increasingly affecting private investors who have built home installations of several to a dozen kWp over the last few years. This problem, most often caused by outdated infrastructure, appears in many countries and impacts energy production. This work focuses on three aspects of the problem. The first one answers the question of how shutdowns of the photovoltaic installation affect production, and how significant the energy loss happens when the PV inverter is not working or is in the restart phase. The second aspect proposes an original, low-cost method that reduces the number of shutdowns. This method relates to the auto-consumption mechanism associated with domestic water heaters and the system for measuring voltage and energy consumption from the electrical network. The solution is based on constant monitoring of the network voltage and the switching of heaters based on a dedicated algorithm. Additionally, continuous analysis also allows for reporting observed irregularities to the electricity supplier. The third and final factor corresponds to the real impact of shutdowns on the long-term aspect of the investment and the extension of its payback period, and to what extent the proposed solution shortens this period. Through a detailed analysis on the issue of shutdowns, the proposed solution allows for a reduction in the number of shutdowns by over 40%. However, due to the fact that it discusses a specific case, this solution requires a calibration and adjustment process, which is discussed in the article. Full article