Energies

With the ongoing global drive towards renewable energy, several potential offshore wind energy lease areas worldwide have come into focus. This study aims to estimate the extreme wind and wave conditions across several newly designated offshore wind lease sites spanning six continents that are crucial for risk assessment and the design of offshore wind turbines. Firstly, the raw data of wind speeds and wave heights prevailing in these different lease areas were obtained. Following this, an in-depth extreme value analysis was performed over different return periods. Two principal methodologies were applied for this comparative study: the block-maxima and the peaks-over-threshold (POT) approaches. Various statistical techniques, including the Gumbel method of moments, Gumbel maximum likelihood, Gumbel least-squares, and the three-parameter GEV, were employed under the block-maxima approach to obtain the distribution parameters. The threshold for the POT approach was defined using the mean residual life method, and the distribution parameters were obtained using the maximum likelihood method. The Gumbel least-squares method emerged as the most conservative estimator of extreme values in the majority of cases, while the POT approach generally yielded lower extreme values compared to the block-maxima approach. However, the results from the POT approach showed large variations based on the selected threshold. This comprehensive study’s findings will provide valuable input for the efficient planning, design, and construction of future offshore wind farms. Full article

This paper aims to develop a novel method for the dynamic equivalence of a renewable power plant, ultimately contributing to power system modeling and enhancing the integration of renewable energy sources. In order to address the challenge posed by clusters of renewable generation units during the equivalence process, the paper introduces the degree of similarity to assess similarity features under data. After leveraging the degree of similarity in conjunction with data-driven techniques, the proposed method efficiently entails dividing numerous units in a large-scale plant into distinct clusters. Additionally, the paper adopts practical algorithms to determine the parameters for each aggregated cluster and streamline the intricate collector network within the renewable power plant. The equivalent model of a renewable power plant is thereby conclusively derived. Comprehensive case studies are conducted within a practical offshore wind plant setting. These case studies are accompanied by simulations, highlighting the advantages and effectiveness of the proposed method, offering an accurate representation of the renewable power plant under diverse operating conditions. Full article

This research paper presents an enhanced economic load dispatch (ELD) approach using the Teaching–Learning-Based Optimization (TLBO) algorithm for 10 thermal units, examining the impact of Plug-in Electric Vehicles (PEVs) in different charging scenarios. The TLBO algorithm was utilized to optimize the ELD problem, considering the complexities associated with thermal units. The integration of PEVs in the load dispatch optimization was investigated, and different charging profiles and probability distributions were defined for PEVs in various scenarios, including overall charging profile, off-peak charging, peak charging, and stochastic charging. These tables allow for the modeling and analysis of PEV charging behavior and power requirements within the power system. By incorporating PEVs, additional controllable resources were introduced, enabling more effective load management and grid stability. The comparative analysis showcases the advantages of the TLBO-based ELD model with PEVs, demonstrating the potential of coordinated dispatch strategies leveraging PEV storage and controllability. This paper emphasizes the importance of integrating PEVs into the load dispatch optimization process, utilizing the TLBO algorithm, to achieve economic and reliable power system operation while considering different PEV charging scenarios. Full article

This study describes an investigation of the pyrolysis and combustion of flax straw as biofuel, focusing on the physicochemical properties and kinetic and thermodynamic parameters, and evaluates the type of degradation products using the thermogravimetry analysis–Fourier transform infrared spectroscopy (TGA-FTIR) technique. Pyrolysis and combustion processes were studied via thermogravimetric analysis at different heating rates of 5-10-15 and 20 °C min, one using three isoconversional methods and one using a model-fitting method. The activation energies, frequency factors, and thermodynamic parameters of flax straw biomass were investigated using different models. The obtained activation energy values for pyrolysis varied between 101.0 and 109.6 kJ mol⁻¹ and for combustion were between 203.3 and 239.2 kJ mol⁻¹. The frequency factors were determined to be 1.7 × 109 for pyrolysis and 1.5 × 1017 s⁻¹ for combustion. The change in Gibbs free energy (ΔG) for the pyrolysis of flax straw was calculated to be 162.6 kJ mol⁻¹, whereas for combustion it increased to 203.9 kJ mol⁻¹. A notable contrast between the volatiles produced by pyrolysis and combustion is evident from the real-time analysis of the degradation products. Specifically, carboxylic acids, aromatics, alkanes, and alcohols are the principal degradation products during pyrolysis, while carbon dioxide is the primary component produced during combustion. These encouraging research outcomes regarding flax straw pyrolysis and combustion can broaden its application in bioenergy and biofuel, thus contributing significantly to it for resource recovery. Full article

The paper chronologically describes the results of research on the flow of micro-encapsulated PCM (mPCM) and nano-encapsulated PCM (nPCM) slurry in heat-transfer systems. The focus is on three thematic groups: mPCM (nPCM) slurry flow pressure drop; the friction factor in the laminar, transient, and turbulent flow of slurry in the channels; and the assessment of the effectiveness of using the mPCM (nPCM) slurry in the context of improving heat-transfer coefficients but with increased pumping power. It was found that the number of publications devoted to the above-mentioned topics is very limited compared to the research on the thermal and rheological properties of the mPCM (nPCM) slurry, which has resulted in the lack of systematized knowledge about the influence of slurry concentration, particle size, materials, etc., for example, on the friction factor. It was found that the use of the mPCM (nPCM) slurry in heat-transfer systems may be proper, provided that an appropriate and sufficiently high flow rate is ensured. Full article

In order to achieve more effective online monitoring of distribution cables, a deployment scheme of the distribution cable condition monitoring devices based on a wireless sensor network (WSN) has been proposed. The proposed deployment scheme can improve the coverage rate and extend the lifetime of the sensor network. Moreover, the clustering method, node density, and node deployment method of the wireless sensor routing algorithm are improved, and based on isosceles triangle non-uniform deployment, a routing optimization algorithm has been proposed to achieve the balance of the energy consumption of each node in the network. Firstly, according to the energy consumption model of the network, the energy consumption of each cluster is calculated, and then by taking the minimum energy consumption of data transmission between clusters as the constraint condition, the optimal clustering distance of the network is solved. Then, according to the scale of network nodes, the density of routing nodes in each cluster is calculated, and the routing nodes in the cluster are deployed by an isosceles triangle. Finally, according to the cluster head election formula, the routing cluster head nodes in each cluster are selected, and the network data information is transmitted to the base station in a multi-hop manner through the routing cluster head nodes. The simulation results indicated that, compared with the traditional routing optimization algorithms, the proposed algorithm could keep the routing coverage at more than 200% all the time, and can effectively balance the energy consumption of nodes, improve the energy utilization efficiency of the routing nodes, and at least extend the lifetime of the network by two times. Moreover, the longer the cables, the more cost savings and the better the life cycle optimization effect of the proposed scheme. In addition, the proposed scheme can greatly reduce the economic cost of network investment, compared with using the demodulator to obtain monitoring data. Full article

Ammonia (NH₃) is considered a promising zero-carbon fuel and was extensively studied recently. Mixing high-reactivity oxygenated fuels such as dimethyl ether (DME) or dimethoxymethane (DMM) with ammonia is a realistic approach to overcome the low reactivity of NH₃. To study the combustion characteristics of NH₃/DMM and NH₃/DME mixtures, we constructed a NH₃/DMM chemical mechanism and tested its accuracy using measured laminar burning velocity (LBV) and ignition delay time (IDT) of both NH₃/DMM and NH₃/DME mixtures from the literature. The kinetic analysis of NH₃/DMM flames using this mechanism reveals that the CH₃ radicals generated from the oxidation of DMM substantially affects the oxidation pathway of NH₃ at an early stage of flame propagation. We investigated the formation of nitrogen oxides (NO_x) in NH₃/DMM and NH₃/DME flames and little difference can be found in the NO_x emissions. Using NH₃/DMM flames as an example, the peak NO_x emissions are located at an equivalence ratio ($\phi$) of 0.9 and a DMM fraction of 40% in the conditions studied. Kinetic analysis shows that NO_x emission is dominated by NO, which primarily comes from fuel nitrogen of NH₃. The addition of DMM at 40% significantly promotes the reactive radical pool (e.g., H, O, and OH) while the maintaining a high concentration of NO precursors (e.g., HNO, NO_2, and N₂O), which results in a high reaction rate of NO formation reaction and subsequently generates the highest NO emissions. Full article

Current emission models primarily focus on traditional combustion vehicles and may not accurately represent emissions from the increasingly diverse vehicle fleet. The growing presence of hybrid and electric vehicles requires the development of accurate emission models to measure the emissions and energy consumption of these vehicles. This issue is particularly relevant for low-emission zones within cities, where effective mobility planning relies on simulation models using continuously updated databases. This research presents a two-dimensional emission model for hybrid vehicles, employing artificial neural networks for low-emission zones. The key outcome is the methodology developed to create a CO₂ emission model tailored for hybrid vehicles, which can be used to simulate various road solutions. The CO₂ emission model achieved an R² coefficient of 0.73 and an MSE of 0.91, offering valuable information for further advancements in emission modelling. Full article

This study proposes a new method to accurately evaluate the overall building envelope thermal performance considering the window–wall correlation, providing a new tool for building thermal design. Firstly, a non-stationary room heat transfer model is established based on the Resistance-Capacity Network method. The influence of solar heat gain through the windows on the heat transfer process of the walls in the actual environment is considered, and the room’s integrated thermal resistance and integrated heat capacity indexes describing the overall room thermal resilience performance are proposed. Then, a field research test is conducted around Lhasa to obtain the local dwelling information, climate conditions, and indoor thermal environment. Numerical simulations using EnergyPlus are made to verify the effectiveness of the indexes in describing the overall building (maximum difference within 3.67% MBE and 2.92% CVRMSE) based on the field test results. Finally, the proposed envelope thermal performance index is used to analyze the local residential buildings around Lhasa. The results show that the lack of consideration of window–wall correlation has led to the failure of a local newly built building’s actual envelope performance to meet the design requirements. These findings could help to develop the thermal design method of the building envelope. Full article

Phase-change materials (PCMs) are attractive materials for storing thermal energy thanks to the energy supplied/returned during the change in matter state. The encapsulation of PCMs prevent them from connecting into large clusters, prevents the chemical interaction of the PCM with the walls of the tank and the exchanger material, and allows the phase change to be initiated in parallel in each capsule. The microencapsulation of PCMs (mPCMs) and the nanoencapsulation of PCMs (nPCMs) entail that these particles added to the base liquid can act as a slurry used in heat exchange systems. PCM micro-/nanocapsules or mPCM (nPCM) slurry are subjected to numerous physical, mechanical, and rheological tests. However, flow tests of mPCM (nPCM) slurries are significantly limited. This paper describes the results of detailed adiabatic flow tests of mPCM slurry in a tube with an internal diameter of d = 4 mm and a length of L = 400 mm. The tests were conducted during laminar, transient, and turbulent flows (Re < 11,250) of mPCM aqueous slurries with concentrations of 4.30%, 6.45%, 8.60%, 10.75%, 12.90%, 15.05%, and 17.20%. The mPCM slurry had a temperature of T = 7 °C (the microcapsule PCM was a solid), T = 24 °C (the microcapsule PCM was undergoing a phase change), and T = 44 °C (the microcapsule PCM was a liquid). This work aims to fill the research gap on the effect of the mPCM slurry concentration on the critical Reynolds number. It was found that the concentration of the mPCM has a significant effect on the critical Reynolds number, and the higher the concentration of mPCM in the base liquid, the more difficult it was to keep the laminar flow. Additionally, it was observed that, as yet unknown in the literature, the temperature of the slurry (and perhaps the physical state of the PCM in the microcapsule) may affect the critical Reynolds number. Full article

Many vertical-axis wind turbines (VAWTs) require arms, which generally provide aerodynamic resistance, to connect the main blades to the rotating shaft. Three–dimensional numerical simulations were conducted to clarify the effects of a gap placed at the blade–arm connection portion on VAWT performance. A VAWT with two straight blades (diameter: 0.75 m, height: 0.5 m) was used as the calculation model. Two horizontal arms were assumed to be connected to the blade of the model with or without a gap. A cylindrical rod with a diameter of 1 or 5 mm was installed in the gap, and its length varied from 10 to 30 mm. The arm cross section has the same airfoil shape (NACA 0018) as the main blade; however, the chord length is half (0.04 m) that of the blade. The simulation shows that the power of the VAWT with gaps is higher than that of the gapless VAWT. The longer gap length tends to decrease the power, and increasing the diameter of the connecting rod amplifies this decreasing tendency. Providing a short gap at the blade–arm connection and decreasing the cross–sectional area of the connecting member is effective in increasing VAWT power. Full article

Due to much lower initial and operating costs, as well as a great environmental and energy performance, there has been a growing tendency towards the application of solar still desalination systems to deal with water scarcity issues. By taking advantage of higher investments and providing incentives to policy makers, the application could be even broader. In order to convince the policy makers and investors, it is important to provide a clear and realistic overview of the technical, economic, and environmental viability of solar stills, and several studies have evaluated them from different viewpoints. Nonetheless, the economic and environmental factors have uncertainties, which have not been taken into account. Therefore, this study uses the Monte Carlo approach to consider the effects of the uncertainty of inflation and discount rates, in addition to emission factors, on the system’s techno-enviro-economic viability. The study is performed by covering cost per liter (CPL) and the annual saving of CO₂ (SCO₂) as the most important key techno-economic and environmental indicators of the system. The results show that the best probability distribution functions for inflation, discount, and emission factors are normal, log-normal, and their summation, respectively. Furthermore, both SCO₂ and CPL are found to have considerable uncertainty. The former has a variation ranging from 317.7 to 427.9 g, while the corresponding values for the latter are 0.0212 to 0.0270 $ · L⁻¹, respectively. With the amounts of 0.1716 and 0.1727, the values of 378.9 g and 0.0245 $ · L⁻¹ are the values with the highest chance of occurrence for SCO₂, as well as for CPL, respectively. Full article

This work proposes a centralized data-based orderly charging strategy that considers the user’s charging choices. Three charging choices for different types of users are described. Then, a scheduling model of electric vehicles based on the time dimension is established. In this strategy, the optimization model not only considers the demand of the grid side and the user side, but also takes the driving data of electric vehicles as the driver. The grid-side optimization involves minimizing the equivalent load fluctuation, and the user-side is optimized to minimize the charging cost and maximize the charging electric quantity. The scheduling capabilities of the three charging strategies are analyzed based on a series of driving data of electric vehicles. The results show that the peak-valley difference and equivalent load fluctuation of the power grid in the data-based orderly charging strategy reduced by 22.2% and 22.7%, respectively, and the charging cost of users also reduced much more than the other two charging strategies. Additionally, the effect of users’ charging choices on the charging strategy is analyzed, and the results show that the orderly charging strategy that considers users’ charging choices can effectively decrease the scheduling deviation caused by users’ charging choices. It greatly improves the security and economy of the grid. Full article

A permanent magnet synchronous motor (PMSM) is a nonlinear, strongly coupled, controlled object with time-varying, fractional-order characteristics. It is difficult to achieve the ideal control effect by using the traditional control method when motor parameter changes and load perturbations occur during the operation of the PMSM, so a fractional-order adaptive fuzzy backstepping control method is proposed to improve the system’s fast response and anti-jamming ability in the case of sudden changes in rotational speed, load perturbations and other conditions. Initially, the fractional order theory is introduced, backstepping control is utilized to decompose the system into multiple subsystems, and a fractional order-based Lyapunov function is designed for each subsystem to ensure the system’s stability. Suitable control laws, as well as parameter adaptive laws, are derived through rigorous mathematical derivation. Finally, a fractional order adaptive fuzzy backstepping controller (FOAB-FPID) is designed by combining the advantages of fuzzy control. Then a mechanical simulation model of the PMSM is established to verify the validity of the designed controller, followed by three sets of comparative experiments: PID, fuzzy PID (F-PID), and integer-order adaptive fuzzy backstepping (IOAB-FPID), which are selected to simulate the PMSM under the control of the four controllers. Finally, it is validated on the constructed PMSM experimental platform. Simulation and experimental results show that FOAB-FPID can adaptively adjust system parameters during sudden speed changes, achieve real-time speed tracking, and maintain speed stability under load perturbations and internal parameter uptake. Compared with the three control strategies, reached PMSM system has better acceleration, fast response performance, and better anti-disturbance ability, which proves the rationality and effectiveness of the FOAB-FPID control method. Full article

With the rapid growth of power demand and the advancement of new power system intelligence, smart energy measurement system data quality and security are also facing the influence of diversified factors. To solve the series of problems such as low data prediction efficiency, poor security perception, and “data islands” of the new power system, this paper proposes a federated learning system based on the Improved Hunter–Prey Optimizer Optimized Wavelet Neural Network (IHPO-WNN) for the whole-domain power load prediction. An improved HPO algorithm based on Sine chaotic mapping, dynamic boundaries, and a parallel search mechanism is first proposed to improve the prediction and generalization ability of wavelet neural network models. Further considering the data privacy in each station area and the potential threat of cyber-attacks, a localized differential privacy-based federated learning architecture for load prediction is designed by using the above IHPO-WNN as a base model. In this paper, the actual dataset of a smart energy measurement master station is selected, and simulation experiments are carried out through MATLAB software to test and examine the performance of IHPO-WNN and the federal learning system, respectively, and the results show that the method proposed in this paper has high prediction accuracy and excellent practical performance. Full article

In 2013, the Mexican Constitution was amended to allow private firms to participate in the energy sector market. Consequently, the energy reform opened the energy market to private investors, ending the state monopoly of PEMEX and CFE. This article aims to assess the impact of the 2013 Mexican Energy Reform on energy household consumption and, if proven effective, explore its potential to help achieve SDG 7. This longitudinal study gathered data before and after the energy bill reform, from 2012 to 2018, with a non-experimental design. Data analysis to determine the effect of the price variance was estimated through price elasticities of demand, and a logarithmic model was used to determine the relationship between the price and cost of electricity, gas, and fuel. Findings suggest that the 2013 Mexican Energy Reform led to an increase in energy prices that, on the one hand, reduced the consumption of energy generated using fossil hydrocarbons but, on the other hand, affected the portion of the population with less income. Consequently, it is possible to conclude that the 2013 Mexican Energy Reform is irreconcilable with SDG 7 unless substantial additional efforts are made to leave no one behind. Full article

The growing use of gas-fired power generators and electricity-driven gas compressors and storage has increased the interdependence between electric power infrastructure and natural gas infrastructure. However, the increasing interdependence may spread the failures from one system to the other, causing subsequent failures in an integrated power and gas system (IPGS). This paper investigates the structural vulnerability of a realistic IPGS based on complex network theory. Different from the existing works with a focus on the static vulnerability analysis for an IPGS, this paper considers both static and dynamic vulnerability analysis. The former focuses on vulnerability analysis under random and selective failures without flow redistribution, while the latter concentrates on vulnerability analysis under cascading failures caused by flow redistribution. Also, different from the existing works with a focus on the IPGS as a whole, we not only analyze the vulnerability of the IPGS but also analyze the vulnerability of the power subsystem (PS) and gas subsystem (GS), in order to understand how the vulnerability of the IPGS is affected by its PS and GS. The analysis results show that (1) if the PS and GS are more susceptible to cascading failures than selective and random failures, the IPGS as a whole is also more vulnerable to cascading failures. (2) There are different dominant factors affecting the IPGS vulnerability under cascading failures and selective failures. Under cascading failures, the GS has a more significant impact on the IPGS vulnerability; under selective failures, the PS has a more important impact on the IPGS vulnerability. (3) The IPGS is more vulnerable to failures on the critical nodes, which are identified from the IPGS as a whole rather than from the individual PS or GS. The results provide insights into the design and planning of IPGSs to improve their overall reliability. Full article

Understanding cycle-to-cycle variations (CCV) is of practical importance for the combustion of fossil and renewable fuels, as increasingly stringent emission regulations require reductions in the negative effects of such variations. The subject of this study is the flow around inlet valves, since oscillations of such inlet flows affect the flow structure in the cylinder and are thus one of the causes of CCV. To this end, a parametric analysis of the influences of the mass flow rate and valve lift of two parallel engine intake valves on the flow structures is performed. This follows on from an earlier similar study where the flow around a single intake valve was investigated. To analyse the flow behaviour and, in particular, the interactions of the flow leaving these two valves, an optical test rig for 2D particle image velocimetry (PIV) and a large eddy simulation (LES) are used. Proper orthogonal decomposition (POD), together with a quadruple decomposition and the Reynolds stress transport equations, are used to study the turbulence phenomena. The PIV and LES results are in good agreement with each other. The detailed LES analysis of the flow structures shows that, for small valve lifts, the flow separates along the whole perimeter of the intake valve, and for larger valve lifts, the flow escapes only to one side. This is, for combustion engines with the tumble concept, the stage at which the tumble movement develops. Moreover, the flow structures are strongly influenced by the valve lift, while they are unaffected by the variation in the mass flow. The turbulent kinetic energy in the flow field increases quadratically with a decreasing valve lift and increasing mass flow. The large, high-energetic flow structures are particularly dominant near the jet, and the small, low-energetic structures are homogeneously distributed within the flow field. The specific Reynolds stress transport equation shows the limitations of two-dimensionality and large timesteps in the PIV results and the limitations of the LES model. Full article