Energies, Volume 16, Issue 15 (August-1 2023) – 268 articles

The quest for sustainable and environmentally friendly fuel feedstocks has led to the exploration of green solvents for the extraction of bio-oil from various biomass sources. This review paper provides a comprehensive analysis of the challenges and future research outlooks for different categories of green extraction solvents, including bio-based solvents, water-based solvents, supercritical fluids, and deep eutectic solvents (DES). The background of each solvent category is discussed, highlighting their potential advantages and limitations. Challenges such as biomass feedstock sourcing, cost fluctuations, solvent properties variability, limited compatibility, solute solubility, high costs, and potential toxicity are identified and examined in detail. To overcome these challenges, future research should focus on alternative and abundant feedstock sources, the development of improved solubility and separation techniques, optimization of process parameters, cost-effective equipment design, standardization of DES compositions, and comprehensive toxicological studies. By addressing these challenges and advancing research in these areas, the potential of green extraction solvents can be further enhanced, promoting their widespread adoption and contributing to more sustainable and environmentally friendly industrial processes. Full article

Improvement of the principles of the implementation of a hybrid solar-wind system equipped with a battery for self-consumption of a local object, with the control of power consumed from the grid, is considered. The aim is to increase the degree of energy use from renewable energy sources for consumption while limiting the degree of battery discharge, taking into account deviations in the load schedule and generation of energy sources relative to the calculated (forecast) values. The possibility of compensating for deviations in the load schedule and renewable energy sources generation relative to the calculated (forecast) values is shown when electricity consumption decreases and the degree of energy use increases. Compliance of the schedule of the battery state of charge with the calculated schedule is achieved by correcting the consumption of active power according to the deviation of the state of charge with a given discreteness of time. The algorithm of the control was improved by taking into account the measured value of the load power with an increase in the degree of energy use. Also, the use of correction allows you to limit the depth of discharge of the battery at the accepted value. A mathematical 24 h model of energy processes was developed, taking into account the error in estimating the state of charge. The results of the modeling using archival data on renewable sources generation confirm that the proposed solutions are effective. For the considered application with average monthly generation in February, the correction allows reducing electricity consumption by 16–21% and payment costs at three tariffs by 24–27%. Full article

In this study, a method is proposed to expand the utilization of an existing calculation model for a floor heat exchanger (HX) from room scale to small district scale. The model, namely Trnsys Type 653, is typically employed for the simulation of single or simultaneously controlled parallel heating circuits. It uses a simplified approach to calculate the heat exchange between fluid and screed, taking the HX effectiveness as an input. In order to calculate the effectiveness based on the HX design, fluid properties and mass flow rate, a Python model is developed to be coupled with Type 653. The results are compared to a reference finite element model set up in COMSOL^® and depend on the HX design. The highest deviations range from over 1 K for 35 min to over 2 K for 175 min, while the lowest deviations range from below 0.5 K to below 1 K. Furthermore, the simplification of the floor HX model is analyzed by summarizing heating circuits from single rooms to a whole flat and from single flats to a whole floor. This approach results in deviations of approximately 2 and 4%, respectively, in the overall transferred heat over longer periods of time, while the switch-on frequency of the controller in an exemplary day is halved. While further analysis is required, the described simplifications seem promising for detailed district simulations with relatively low computational effort. Full article

Due to the reduction in pollutant emissions, the number of electric vehicles has experienced rapid growth in worldwide traffic. Vehicles equipped with batteries represent a greater danger of explosion and fire in the case of traffic accidents, which is why new protective systems and devices have been designed to improve impact safety. Through their design and construction, auxetic structures can ensure the efficient dissipation of impact energy, reducing the risk of battery damage and maintaining the safety of vehicle occupants. In this paper, we analyze the crashworthiness performance of a battery case equipped with an energy absorber with a particular shape based on a re-entrant auxetic model. Simulations were performed at a velocity of 10 m/s and applied to the battery case with a rigid impact pole, a configuration justified by most accidents occurring at a low velocity. The results highlight that by using auxetic structures in the construction of the battery case, the impact can be mitigated by the improved energy absorber placed around the battery case, which leads to a decrease in the number of damaged cells by up to 35.2%. In addition, the mass of the improved energy absorbers is lower than that of the base structure. Full article

This article addresses the problem of the contact voltage increase caused by the low-frequency oscillation of the train-grid system in the phase-separation process of EMUs. The article establishes the EMU-contact line-traction substation model, reveals the mechanism of low-frequency oscillation, and ascertains the relationship between the phase angle when the pantograph leaves the line, and low-frequency oscillations. Methods to suppress overvoltage during the low-frequency oscillation are proposed. The research indicated that a significant voltage amplitude was observed in the neutral zone, when the phase angle of the pantograph to the contact line separation power supply fell within the range of 60–90° and 240–270°. The maximum voltage amplitude reached 69.75 kV, and there was an occurrence of low-frequency oscillation in the neutral zone, where electrical phase separation takes place. During this oscillation, the voltage of the contact network in the neutral zone mainly operated at one-third of the power frequency (16.7 Hz). However, after installing an RC suppression device in the neutral zone, when low-frequency oscillation occurred, the absolute value of the peak voltage dropped below 37 kV as soon as the EMU entered electric phase separation. Furthermore, compared to situations without a connected suppression device, there was nearly a 30% reduction in the absolute value of the peak voltage. The study provides a basis for the design of the neutral zone of the contact line, and the selection of high-voltage equipment for the EMU. Full article

ZnO is a commonly used material for hydrogen gas sensors. In this study, a ZnO nanofiber film with a diameter of approximately 60 nm was synthesized by the electrospinning method. Compared to previously reported ZnO hydrogen gas sensors, an abnormal phenomenon was observed here, where the resistance of the ZnO nanofiber film increased upon exposure to hydrogen gas in the temperature range from 210 °C to 330 °C. The physical mechanism of this phenomenon was explored through microstructure analysis and DFT simulation calculations that showed a total charge transfer of 0.65 e for the hydrogen molecule. This study can push forward the understanding of ZnO hydrogen sensing. Full article

Undertaking various activities aimed at sustainable development, especially energy conservation, is becoming one of the challenges of modern economies, including developing urban areas. One of the most widely promoted activities is designing and implementing energy-conserving solutions for urban mobility. People play a vital role in this regard, especially young people, represented here by Generation Z. Their attitudes and behaviours regarding sustainability can significantly impact the effectiveness of energy-efficient technological solutions. The purpose of this article is to examine the nature of the relationship between the assessment of the importance of energy-efficient transportation solutions available in the city and the attitudes and behaviours of representatives of Generation Z relating to the idea of sustainability, broken down into two categories, i.e., energy-conserving behaviour and mobility. In this study, a diagnostic survey method was used. Based on the literature review, we designed a research tool in the form of a questionnaire. Four hundred and ninety representatives of Generation Z participated in the study. To verify the hypotheses, first, a qualitative analysis was carried out for the three study areas using measures of central tendency; then, a correlation analysis was performed based on Pearson’s chi-square independence test, and to determine the strength of the relationship, the following symmetric measures were used: Cramer’s V and the Contingency Coefficient. The normalisation of the data, giving them a quantitative character, allowed the possibility of examining the correlation using Pearson’s test and the directionality of the analysed relationships based on simple and multiple linear regression results. Ananalys is of the obtained results allows us to conclude that energy-related sustainable behaviours in the acquisition of electrical appliances, their use and disposal, and mobility-related energy-conserving behaviours, resulting from the choice of means of transportation for moving in the city, influence the assessment of the importance of available energy-efficient mobility solutions. City administrations could use the study results as a guideline for the implementation of energy-conserving solutions in urban transportation, as well as the planning and promotion of appropriate activities related to the mobility of Generation Z, that are adequate to the attitudes and behaviours of young people. Full article

As the sustainability of the environment is a very much concerning issue for developed countries, the drive of the paper is to reveal the effects of nuclear, environment-friendly, and non-friendly energy, population, and GDP on CO₂ emission for Italy, a developed country. Using the extended Stochastic Regression on Population, Affluence, and Technology (STIRPAT) framework, the yearly data from 1972 to 2021 are analyzed in this paper through an Autoregressive Distributed Lag (ARDL) framework. The reliability of the study is also examined by employing Fully Modified Ordinary Least Square (FMOLS), Dynamic Ordinary Least Square (DOLS), and Canonical Cointegration Regression (CCR) estimators and also the Granger causality method which is used to see the directional relationship among the indicators. The investigation confirms the findings of previous studies by showing that in the longer period, rising Italian GDP and non-green energy by 1% can lead to higher CO₂ emissions by 8.08% and 1.505%, respectively, while rising alternative and nuclear energy by 1% can lead to falling in CO₂ emission by 0.624%. Although population and green energy adversely influence the upsurge of CO₂, they seem insignificant. Robustness tests confirm these longer-period impacts. This analysis may be helpful in planning and developing strategies for future financial funding in the energy sector in Italy, which is essential if the country is to achieve its goals of sustainable development. Full article

Supplementation with iron oxide nanoparticles has been suggested as a potential method for improving energy generation through anaerobic digestion, specifically by enhancing the rate of methane production. This investigation examined the effects of iron oxide (Fe₃O₄) nanoparticles (NPs) on anaerobic co-digestion of cow manure (CM) and sewage sludge (SS) through batch testing conducted under mesophilic conditions (35 °C) using a RESPIROMETRIC Sensor System 6 Maxi—BMP (RSS-BMP). The use of Fe₃O₄ nanoparticles at doses of 40, 80, 120, and 160 mg/L (batches M1, M2, M3, and M5) was studied. The use of 160 mg/L Fe₃O₄ nanoparticles in combination with mixtures of different ratios (M4, M5, and M6) was further investigated. The findings indicate that the addition of Fe₃O₄ nanoparticles at a concentration of 40 mg/L to anaerobic batches did not significantly impact the hydrolysis process and subsequent methane production. Exposing the samples to Fe₃O₄ NPs at concentrations of 80, 120, and 160 mg/L resulted in a similar positive effect, as evidenced by hydrolysis percentages of approximately 94%, compared to 60% for the control (C2). Furthermore, methane production also increased. The use of Fe₃O₄ nanoparticles at a concentration of 160 mg/L resulted in biodegradability of 97.3%, compared to 51.4% for the control incubation (C2). Moreover, the findings demonstrate that supplementing anaerobic batches with 160 mg/L Fe₃O₄ NPs at varying mixture ratios (M4, M5, and M6) had a significant impact on both hydrolysis and methane production. Specifically, hydrolysis percentages of 94.24, 98.74, and 96.78% were achieved for M4, M5, and M6, respectively, whereas the percentages for the control incubation (C1, C2, and C3) were only 56.78, 60.21, and 58.74%. Additionally, the use of 160 mg/L Fe₃O₄ NPs in mixtures M4, M5, and M6 resulted in biodegradability percentages of 78.4, 97.3, and 88.3%, respectively. In contrast, for the control incubation (C1, C2, and C3) biodegradability was only 44.24, 51.4, and 49.1%. Full article

In track-oriented road cars with electric powertrains, the ability to recuperate energy during track driving is significantly affected by the frequent interventions of the antilock braking system (ABS), which usually severely limits the regenerative torque level because of functional safety considerations. In high-performance vehicles, when controlling an active rear wing to maximize brake regeneration, it is unclear whether it is preferable to maximize drag by positioning the wing into its stall position, to maximize downforce, or to impose an intermediate aerodynamic setup. To maximize energy recuperation during braking from high speeds, this paper presents a novel integrated open-loop strategy to control: (i) the orientation of an active rear wing; (ii) the front-to-total brake force distribution; and (iii) the blending between regenerative and friction braking. For the case study wing and vehicle setup, the results show that the optimal wing positions for maximum regeneration and maximum deceleration coincide for most of the vehicle operating envelope. In fact, the wing position that maximizes drag by causing stall brings up to 37% increased energy recuperation over a passive wing during a braking maneuver from 300 km/h to 50 km/h by preventing the ABS intervention, despite achieving higher deceleration and a 2% shorter stopping distance. Furthermore, the maximum drag position also reduces the longitudinal tire slip power losses, which, for example, results in a 0.4% recuperated energy increase when braking from 300 km/h to 50 km/h in high tire–road friction conditions at a deceleration close to the limit of the vehicle with passive aerodynamics, i.e., without ABS interventions. Full article

This study presents a genetic algorithm integrated with dynamic programming to address the challenges of the hydropower unit commitment problem, which is a nonlinear, nonconvex, and discrete optimization, involving the hourly scheduling of generators in a hydropower system to maximize benefits and meet various constraints. The introduction of a progressive generating discharge allocation enhances the performance of dynamic programming in fitness evaluations, allowing for the fulfillment of various constraints, such as unit start-up times, shutdown/operating durations, and output ranges, thereby reducing complexity and improving the efficiency of the genetic algorithm. The application of the genetic algorithm with dynamic programming and progressive generating discharge allocation at the Manwan Hydropower Plant in Yunnan Province, China, showcases increased flexibility in outflow allocation, reducing spillages by 79%, and expanding high-efficiency zones by 43%. Full article

Policymakers regularly implement stricter building energy-efficiency codes towards curtailing building energy use. Inevitably, super-insulating materials such as Vacuum Insulation Panels (VIPs) are essential to satisfy such codes. VIPs have been applied to buildings for over two decades now, with many lessons learned. Generally, the thermal conductivity values of VIPs often reported in the literature are the center-of-panel thermal conductivity (λ_cop) and effective thermal conductivity (λ_eff), factoring thermal bridges. However, there are other indexes, such as λ_90/90 (declared value in the 90% percentile with a confidence of 90%) and λ_{cop,90/90,aged} (factoring aging), that increase consistently and reliably in the declared thermal conductivity value for VIPs. These indexes are scarcely computed and hardly reported. The main aim of this study was to examine the different declared thermal conductivity values of VIP-based guidelines, such as draft ISO DIS 16478, and evaluate their implications on annual building energy consumption. The main study constitutes four parts: (1) experimental evaluation of the thermal properties of pristine and aged VIP samples, (2) computation of thermal conductivity indexes, (3) numerical investigation of thermal conductivity indexes based on a reference building, and (4) related building energy implications. The mean λ_cop for 10 VIP samples was 0.0042 W/(mK) and increased to 0.0073 W/(mK) for ${\lambda }_{90/90}$, bridge, aged. Results show a significant bearing on building energy performance of as much as 2.1 GJ. Full article

The inherent randomness, fluctuation, and intermittence of photovoltaic power generation make it difficult to track the scheduling plan. To improve the ability to track the photovoltaic plan to a greater extent, a real-time charge and discharge power control method based on deep reinforcement learning is proposed. Firstly, the photovoltaic and energy storage hybrid system and the mathematical model of the hybrid system are briefly introduced, and the tracking control problem is defined. Then, power generation plans on different days are clustered into four scenarios by the K-means clustering algorithm. The mean, standard deviation, and kurtosis of the power generation plant are used as the features. Based on the clustered results, the state, action, and reward required for reinforcement learning are set. In the constraint conditions of various variables, to increase the accuracy of the hybrid system for tracking the new generation schedule, the proximal policy optimization (PPO) algorithm is used to optimize the charging/discharging power of the energy storage system (ESS). Finally, the proposed control method is applied to a photovoltaic power station. The results of several valid experiments indicate that the average errors of tracking using the Proportion Integral Differential (PID), model predictive control (MPC) method, and the PPO algorithm in the same condition are 0.374 MW, 0.609 MW, and 0.104 MW, respectively, and the computing time is 1.134 s, 2.760 s, and 0.053 s, respectively. The consequence of these indicates that the proposed deep reinforcement learning-based control strategy is more competitive than the traditional methods in terms of generalization and computation time. Full article

Analyzing and investigating the impact of implementing an environmental policy mix on carbon emission from private cars and social welfare holds significant reference value. Firstly, based on vehicle trajectory big data, this paper employs reverse geocoding and artificial neural network models to predict carbon emissions from private cars in various provinces and cities in China. Secondly, by simulating different scenarios of carbon tax, carbon trading, and their policy mix, the propensity score matching model is constructed to explore the effects of the policy mix on carbon emission reduction from private cars and social welfare while conducting regional heterogeneity analysis. Finally, policy proposals are proposed to promote carbon emission reduction from private cars and enhance social welfare in China. The results indicate that the environmental policy mix has a significant positive impact on carbon emission reduction from private cars and social welfare. Furthermore, in the regional heterogeneity analysis, the implementation of the policy mix in eastern regions has a significant positive effect on both carbon emission reduction from private cars and social welfare, while in central and western regions, it shows a significant positive impact on social welfare but has no significant effect on carbon emission reduction in the private car sector. Full article

Biomass and renewable resources are becoming substitutes for fossil-based resources, providing opportunities for more sustainable environmental management and reductions in environmental damage. This paper studies the prospects for wood pellet production in Kazakhstan through the lens of business model adjustment in a microenterprise in Kazakhstan. This study focuses on answering the following questions: (1) How do microenterprises propose, create, deliver and capture value through business models in the wood industry? (2) What are the opportunities and challenges relating to these business models in the context of wood pellet production in Kazakhstan? Kazakhstan has a high potential for biomass production, providing a particularly interesting case for analysing how microenterprises can tap into this potential to create value. This paper combines an analysis of bioenergy and forestry trends with a qualitative case study. The analysis of the business model is based on Osterwalder’s business model canvas. The value proposition of the enterprise studied herein is to provide a local biomass-based alternative to fossil fuels. The overall growth of wood-based industries in Kazakhstan and the national movement towards renewable energy create favourable prospects for microenterprises engaged in the production of wood pellets; however, these industries are also characterised by high institutional and regulatory dependencies. Full article

Caloric cooling systems are potentially more efficient than systems based on vapour compression. Electrocaloric cooling systems use a phase transformation from the paraelectric to the ferroelectric state by applying or removing an electric field to pump heat. Lead scandium tantalate (PST) materials show a first-order phase transition and are one of the most promising candidates for electrocaloric cooling. To model caloric cooling systems, accurate and thermodynamically consistent material models are required. In this study, we use a phenomenological model based on an analytical equation for the specific heat capacity to describe the material behaviour of bulk PST material. This model is fitted to the experimental data, showing a very good agreement. Based on this model, essential material properties such as the adiabatic temperature change and isothermal entropy change of this material can be calculated. Full article

Backflashover rate (BFR) is strongly dependent on the cumulative peak current distribution (CCD) adopted in the calculations. An original aspect of the present work is that such dependence is simultaneously assessed in estimating the probability of the critical current being exceeded as well as in the annual number of flashes to the line. An IEEE brochure recommends that the distribution values that characterize the atmospheric characteristic of the region under study as accurately as possible be used. The objective of this article is to evaluate the impact of the use of different CCDs, related to several measurements carried out around the world, in the estimation of the lightning performance of transmission lines (TLs). Structures of 138, 230 and 500 kV were analyzed. In the simulations, representative curves of lightning associated with measurements taken at Monte San Salvatore (MSS), Morro do Cachimbo (MCS) and TLs in Japan (TLJ) were considered. The distributions recommended by the IEEE and by the CIGRE and the distributions of Berger obtained from MSS, MCS and TLJ were considered. The presented results indicate differences of up to 100% between the considered work distributions and the IEEE one for certain values of tower footing impedance. Full article

This study examines the sustainable decomposition reactions of benzene using non-thermal plasma (NTP) in a dielectric barrier discharge (DBD) reactor. The aim is to investigate the factors influencing benzene decomposition process, including input power, concentration, and residence time, through kinetic modeling, reactor performance assessment, and machine learning techniques. To further enhance the understanding and modeling of the decomposition process, the researchers determine the apparent decomposition rate constant, which is incorporated into a kinetic model using a novel theoretical plug flow reactor analogy model. The resulting reactor model is simulated using the ODE45 solver in MATLAB, with advanced machine learning algorithms and performance metrics such as RMSE, MSE, and MAE employed to improve accuracy. The analysis reveals that higher input discharge power and longer residence time result in increased tar analogue compound (TAC) decomposition. The results indicate that higher input discharge power leads to a significant improvement in the TAC decomposition rate, reaching 82.9%. The machine learning model achieved very good agreement with the experiments, showing a decomposition rate of 83.01%. The model flagged potential hotspots at 15% and 25% of the reactor’s length, which is important in terms of engineering design of scaled-up reactors. Full article

Recent years have seen a rapid uptake in distributed energy resources (DER). Such technologies pose a number of challenges to network operators, which ultimately can limit the amount of rooftop solar photovoltaic (PV) systems that can be connected to a network. The objective of this industry-based research was to determine the potential network effects of forecast levels of customer-owned rooftop solar PV on Energy Queensland’s distribution network and formulate functions that can be used to determine such effects without the requirement for detailed network modeling and analysis. In this research, many of Energy Queensland’s distribution feeders were modeled using DIgSILENT PowerFactory and analyzed with forecast levels of solar PV and customer load. Python scripts were used to automate this process, and quasi-dynamic simulation (QDSL) models were used to represent the dynamic volt–watt and volt–var response of inverters, as mandated by the Australian Standard AS/NZS 4777. In analyzing the results, linear relationships were revealed between the number of PV systems on a feeder and various network characteristics. Regression was used to form trend equations that represent the linear relationships for each scenario analyzed. The trend equations provide a way of approximating network characteristics for other feeders under various levels of customer-owned rooftop solar PV without the need for detailed modeling. Full article

The emission reduction of global greenhouse gases is one of the key steps towards sustainable development. Demand response utilizes the resources of the demand side as an alternative of power supply which is very important for the power network balance, and the virtual power plant (VPP) could overcome barriers to participate in the electricity market. In this paper, the optimal scheduling of a VPP with a flexibility margin considering demand response and uncertainties is proposed. Compared with a conventional power plant, the cost models of VPPs considering the impact of uncertainty and the operation constraints considering demand response and flexibility margin characteristics are constructed. The orderly charging and discharging strategy for electric vehicles considering user demands and interests is introduced in the demand response. The research results show that the method can reduce the charging cost for users participating in reverse power supply using a VPP. The optimizing strategy could prevent overload, complete load transfer, and realize peak shifting and valley filling, solving the problems of the new peak caused by disorderly power utilization. Full article

A periodic pigging operation performed to clean off sediment and provide operators with detailed health information for a pipeline is mandatorily required. The research on pigging-induced issues for the steel catenary riser (SCR), one of the key parts in offshore hydrocarbon recovery pipelines between the floating production system and the seabed, has been scarce until now. As a result, there is an urgent need for theories to guide the pigging operation to ensure safe pigging is achieved in deepwater risers. In this paper, a study aiming to determine the effects of the pigging impact load and the pigging-induced slugging load on the dynamic response of the riser is reported. A SCR pigging model was established and proposed based on the finite element analysis (FEA) method. The stress distribution and displacement of the SCR were investigated under the pigging conditions, with the consideration of the effects of waves, currents, and floating platform movements. It was found that the pigging load has large effects on the stress and displacement of the touchdown zone (TDZ), especially the touchdown point (TDP). The displacement of the TDZ in the Y (vertical) direction is more significant than that in the X (horizontal) direction under pigging conditions, and the maximum displacement of the TDZ in the Y direction is proportional to the weight of the pig, as well as the length of the pigging-induced slugging. Full article

In this work, the thermodynamics and kinetics of hydrate formation in 9.01 wt% tetra butyl ammonium bromide (TBAB) mixed with water-soluble hydroxylated multi-wall carbon nanotube (MWCNTol) systems were characterized by measuring hydrate formation conditions, induction time, and final gas consumption. The results showed that MWCNTols had little effect on the phase equilibrium of CO₂ hydrate formation. Nanoparticles (graphene nanoribbons (GNs) and MWCNTols) could significantly shorten the induction time. When the concentration was ≤0.06 wt%, MWCNTols had a better effect on the induction time than the GN system, and the maximum reduction in induction time reached 44.22%. The large surface area of MWCNTols could provide sites for heterogeneous nucleation, thus shortening the induction time of hydrate formation. Furthermore, adding different concentrations of nanoparticles to the 9.01 wt% TBAB solution effectively increased the final gas consumption, and the maximum increase was 10.44% of the 9.01 wt% TBAB + 0.08 wt% GN system. Meanwhile, the suitable initial pressure and experimental temperature could also promote the hydrate formation and increase the motivation in hydrate formation. The 9.01 wt% TBAB + 0.02 wt% MWCNTol system had the best effect at 3.5 MPa and 277.15 K. The induction time was reduced by 66.67% and the final gas consumption was increased by 284.11% compared to those of the same system but at a different initial pressure and experimental temperature. This work helps to promote the industrial application of hydrate technology in CO₂ capture and storage. Full article

This research paper presents a comprehensive study on the optimal planning and design of hybrid renewable energy systems for microgrid (MG) applications at Oakland University. The HOMER Pro platform analyzes the technical, economic, and environmental aspects of integrating renewable energy technologies. The research also focuses on the importance of addressing unmet load in the MG system design to ensure the university’s electricity demand is always met. By optimizing the integration of various renewable energy technologies, such as solar photovoltaic (PV), energy storage system (ESS), combined heat and power (CHP), and wind turbine energy (WT), the study aims to fulfill the energy requirements while reducing reliance on traditional grid sources and achieving significant reductions in greenhouse gas emissions. The proposed MG configurations are designed to be scalable and flexible, accommodating future expansions, load demands changes, and technological advancements without costly modifications or disruptions. By conducting a comprehensive analysis of technical, economic, and environmental factors and addressing unmet load, this research contributes to advancing renewable energy integration within MG systems. It offers a complete guide for Oakland University and other institutions to effectively plan, design, and implement hybrid renewable energy solutions, fostering a greener and more resilient campus environment. The findings demonstrate the potential for cost-effective and sustainable energy solutions, providing valuable guidance for Oakland University’s search for energy resilience and environmental surveillance, which has a total peak load of 9.958 MW. The HOMER simulation results indicate that utilizing all renewable resources, the estimated net present cost (NPC) is a minimum of USD 30 M, with a levelized energy cost (LCOE) of 0.00274 USD/kWh. In addition, the minimum desired load will be unmetered on some days in September. Full article

Flutter is an instability phenomenon that can occur in wind turbine blades due to fluid–structure interaction, particularly for longer and more flexible blades. Aeroelastic tailoring through bend–twist coupling is an effective method to enhance the aeroelastic performance of blades. In this study, we investigate the impact of bend–twist coupling on the structural performance and flutter limit of the IEA 15 MW blade, which is currently the longest reference wind turbine blade, and determine the optimal layup configuration that maximizes the flutter speed. The blade is modeled by NuMAD and iVABS, and the cross-section properties are obtained by PreComb and VABS. The accuracy of the blade model is verified in terms of stiffness and frequency. The bend–twist coupling is implemented by changing the fiber angle of the skin and spar cap considering symmetric and asymmetric layups. The flutter limits of both the baseline and the bend–twist coupled blade are evaluated based on HAWC2. The results show that the angle of spar cap carbon fiber has a greater effect on the blade’s structural properties and flutter speed than the skin fiber. Varying the spar cap carbon fiber angle increases the flutter speed, with the effect being more significant for the symmetric layup, up to 9.66% at a fiber angle of 25 degrees. In contrast, the variation in skin fiber angle has a relatively small impact on flutter speed—within ±3%. Full article

Current electric vehicle solutions offer the possibility of a fully electrified bus fleet, although due to financial constraints, most cities cannot afford it. Therefore, the possibility of battery replacement is a needed alternative to the electrification process of a city’s bus fleet. The aim of this study is to investigate the needs of cities and present the concept of battery replacement in an electric bus. The research was based on two groups of selected Polish cities: (1) up to 150,000 inhabitants, and (2) up to 1 million inhabitants. The research part includes an analysis of the means of transport in provincial cities in Poland, an analysis of the kilometers covered by the city fleet, the average distances covered by buses per day, and an estimate of the number of battery replacements. The concept is based on current technological solutions. The description of the concept includes the proposed battery and the technology used, the placement of the battery in the vehicle, and the replacement scheme. Research indicates that the concept can be used with existing technology but will be more justifiable for a larger city due to the higher fleet load. The paper shows the importance of researching bus electrification solutions and that modern solutions can improve existing urban networks in cities. Full article

A Permanent Magnet Linear Alternator (PMLA) works seamlessly with a Free Piston Stirling Engine (FPSE) to convert short-stroke and high-frequency linear motion to electric power. Cogging force is an unavoidable opposition force acting on the translator, limiting the linear motion from the driving force, which shortens the lifespan of the machine, causing oscillatory power output and increased maintenance costs. This research focuses on the methods to reduce the cogging force acting on the translator of a slot-spaced PMLA by making geometrical changes to the structure of the machine. The profile of the cogging force is made to be in line with the displacement profile of the translator to avoid unnecessary vibrations and damaging the piston of the FPSE. The changes made also influence the induced voltage. Bringing a balance between reduced voltage and cogging force with minor geometrical changes and a sinusoidal cogging force profile is the outcome of this work. Full article

The ironless linear permanent magnet synchronous motor (ILPMSM) is highly compact, easy to control, and exhibits minimal thrust fluctuations, making it an ideal choice for direct loading applications requiring precise positioning accuracy in linear motor test rigs. To address the issue of temperature rise resulting from increased primary winding current and to simultaneously enhance thrust density while minimizing thrust fluctuations, this paper introduces a bilateral-type ILPMSM with a cooling water jacket integrated between the dual-layer windings of the primary movers. The primary winding of the motor adopts a dual-layer coreless structure where the upper and lower windings are closely spaced and cooled by a non-conductive metal cooling water jacket, while the dual-sided secondary employs a Halbach permanent magnet array. The motor’s overall braking force is a combination of the electromagnetic braking force generated by the energized windings and the eddy current braking force induced on the cooling water jacket. This paper specifically focuses on the analysis of the eddy current braking force. Initially, the motor’s geometry and working principle are presented. Subsequently, the equivalent magnetization intensity method is employed to determine the no-load air gap magnetic density resulting from the Halbach array. An analytical model is then developed to derive expressions for the eddy current density and braking force induced in the water-cooling jacket. The accuracy of the analytical method is validated through finite element analysis. Then, a comparative analysis of the braking forces in two primary cooling structures, namely the inter-cooled type and the two-side cooled type ILPMSM, is conducted. Moreover, the characteristics of the eddy current braking force are thoroughly examined concerning motor size parameters and operating conditions. This paper provides a solid theoretical foundation for the subsequent optimization design of the proposed motor. Full article

Accurately predicting power load is a pressing concern that requires immediate attention. Short-term load prediction plays a crucial role in ensuring the secure operation and analysis of power systems. However, existing research studies have limited capability in extracting the mutual relationships of multivariate features in multivariate time series data. To address these limitations, we propose a multi-dimensional time series forecasting framework called TS2ARCformer. The TS2ARCformer framework incorporates the TS2Vec layer for contextual encoding and utilizes the Transformer model for prediction. This combination effectively captures the multi-dimensional features of the data. Additionally, TS2ARCformer introduces a Cross-Dimensional-Self-Attention module, which leverages interactions across channels and temporal dimensions to enhance the extraction of multivariate features. Furthermore, TS2ARCformer leverage a traditional autoregressive component to overcome the issue of deep learning models being insensitive to input scale. This also enhances the model’s ability to extract linear features. Experimental results on two publicly available power load datasets demonstrate significant improvements in prediction accuracy compared to baseline models, with reductions of 43.2% and 37.8% in the aspect of mean absolute percentage error (MAPE) for dataset area1 and area2, respectively. These findings have important implications for the accurate prediction of power load and the optimization of power system operation and analysis. Full article

The present study introduces a novel approach employing weightless neural networks (WNN) for the detection and diagnosis of visual faults in photovoltaic (PV) modules. WNN leverages random access memory (RAM) devices to simulate the functionality of neurons. The network is trained using a flexible and efficient algorithm designed to produce consistent and precise outputs. The primary advantage of adopting WNN lies in its capacity to obviate the need for network retraining and residual generation, making it highly promising in classification and pattern recognition domains. In this study, visible faults in PV modules were captured using an unmanned aerial vehicle (UAV) equipped with a digital camera capable of capturing RGB images. The collected images underwent preprocessing and resizing before being fed as input into a pre-trained deep learning network, specifically, DenseNet-201, which performed feature extraction. Subsequently, a decision tree algorithm (J48) was employed to select the most significant features for classification. The selected features were divided into training and testing datasets that were further utilized to determine the training, test and validation accuracies of the WNN (WiSARD classifier). Hyperparameter tuning enhances WNN’s performance by achieving optimal values, maximizing classification accuracy while minimizing computational time. The obtained results indicate that the WiSARD classifier achieved a classification accuracy of 100.00% within a testing time of 1.44 s, utilizing the optimal hyperparameter settings. This study underscores the potential of WNN in efficiently and accurately diagnosing visual faults in PV modules, with implications for enhancing the reliability and performance of photovoltaic systems. Full article

Understanding the electrochemical and mechanical degradations inside the electrodes of lithium-ion battery is crucial for the design of robust electrodes. A typical lithium-ion battery electrode consists of active particles enclosed with conductive binder and an electrolyte. During the charging and discharging process, these adjacent materials create a mechanical confinement which suppresses the expansion and contraction of the particles and affects overall performance. The electrochemical and mechanical response mutually affect each other. The particle level expansion/contraction alters the electrochemical response at the electrode level. In return, the electrode level kinetics affect the stress at the particle level. In this paper, we developed a multiphysics–multiscale model to analyze the electrochemical and mechanical responses at both the particle and cell level. The 1D Li-ion battery model is fully coupled with 2D representative volume element (RVE) model, where the particles are covered in binder layers and bridged through the binder. The simulation results show that when the binder constraint is incorporated, the particles achieve a lower surface state of charge during charging. Further, the cell charging time increases by 7.4% and the discharge capacity reduces by 1.4% for 1 C-rate charge/discharge. In addition, mechanical interaction creates inhomogeneous stress inside the particle, which results in particle fracture and particle–binder debonding. The developed model will provide insights into the mechanisms of battery degradation for improving the performance of Li-ion batteries. Full article