High Electrical Load Research Articles

A Systematic Empirical Evaluation of Machine Learning Algorithm on Energy Prediction

The energy crisis has alerted all scientists and researchers in every field. The evident increase in the usage of electronic items causes high electricity consumption. Especially in residential households and high-rise apartments, buildings show high electrical loads. This study is designed to forecast the energy need using AI prediction models and find the most efficient model to predict the future loads of any household considering its surroundings, like weather, air pressure, room temperature and others. This is a comprehensive comparative study that provides a comprehensive comparison between regression models. The finding of the study is that by using the optimum model, we can achieve the best results in predicting electricity load.

A multi-objective artificial hummingbird algorithm for dynamic optimal volt-var controls for high electric vehicle load penetration in a photovoltaic distribution network

Renewable energy systems (RESs) and electric vehicles (EVs) have become global necessities to meet the sustainable development goals (SDGs). Because they are intermittent and stochastic, these two technologies have caused power grid operation and regulation challenges despite their environmental benefits. A new combined dynamic optimal network reconfiguration (DONR) and capacitor bank switching (CBS) optimization technique reduces solar and multi-type load effects on the distribution network performance. Considering substantial EV load penetrations, ONR and CBS should coordinate to reduce energy loss, improve the voltage profile, and save money during 24 h operation. The artificial hummingbird algorithm (AHA) solves this difficult optimization problem for the first time. An enhanced IEEE 33-bus benchmark test system was used to simulate various instances to evaluate the computational characteristics of the AHA and compare it with other similar algorithms. The obtained results demonstrate the superiority of the combined DONR and CBS for real-time scenarios over any individual approach.

Performance Enhancement of Flux Switching Motor for Electric Vehicle Applications: An Overview

As the reduction of greenhouse gas emissions becomes crucial, electric vehicles (EVs) are expected to enter the market extensively in the coming years. The efficiency of the electrical motor used in EVs plays a significant role in their overall performance. This paper explores the flux switching motor (FSM) and its applications in EVs. The FSM is compared to other electrical motors, highlighting its potential as a suitable choice for EV traction. Various configurations and techniques are reviewed to enhance the performance of FSMs, including magnetic materials, torque ripple alleviation, and magnetic flux weakening. The advantages and disadvantages of these methods are discussed, providing valuable insights for designing FSMs for EVs. Generally, EV traction requires high torque density and high power density electrical motor. To achieve these goals, high electric and magnetic loading must be considered in design stage of the motor. Application of the FSM may be one of the appropriate option. For many reasons, three-phase FSM is preferred. Considering the base speed of machine in the EV and high electric loading, the FSM with 12 stator teeth and 10 rotor teeth may be the most appropriate choice in which the stator core is oriented and rotor core is nonoriented iron. To enhance the torque density and applied flux weakening method, combination of Nd and Al–Ni–Co magnets is preferred.

A multi-model probabilistic framework to evaluate seismic resilience of UHV converter stations

Ultra-high voltage converter stations are significant electric power infrastructures with a high electric energy load. To quantitatively evaluate the seismic and recovery capability of a UHV converter station, this paper proposes a multi-model probabilistic resilience assessment framework divided into four analysis modules for hierarchical evaluation. The conditional probability set of the functional state between network nodes is determined using a matrix-based approach. Taking connectivity and power transmission capacity into account, the functional reliability model was built through the improved Bayesian network. A multi-parameter quantification of the post-earthquake recovery process was carried out by constructing the stepped functional recovery function as well as the time-varying seismic resilience function. The economic loss assessment model was built from multiple aspects. Taking a typical ± 800 kV UHV converter station as a case study for seismic resilience analysis, the probabilistic resilience assessment was realized, and variation trends of the multi-parameter expected value were obtained by mathematical expectation. This article shows that taking measures to postpone the sensitive interval of the system helps to avoid the seismic active area. This avoidance of seismic activity is the objective of optimization. The proposed framework can serve as a reference for the operation and optimization of power systems.

Cost-inclusive heuristic power management of hybrid power generation plant with ANN-regulated biogas plant

To mitigate the negative effects of fossil fuels, renewable energy sources are being promoted for power generation. Biomass, a renewable energy source, is also being promoted to reduce the negative impact of organic waste generated in societies and industries. Waste biomass is used to produce biogas fuel in a biogas plant via an anaerobic digestion process, which is typically used to generate electricity as well as fuel for cooking and vehicles. However, the high local electrical load in biogas plants reduces profit for plant owner. Biogas-based power generation is hybridised with Photovoltaics (PV) and Battery energy storage systems (BESS), to meet power demand, to increase profit and power generation capacity while reducing the burden of local electrical load on biogas plants. A Proton-exchange membrane fuel cell (PEMFC) stack has been used for power generation from the hydrogen produced from the biogas obtained from the anaerobic digestion process. A cost-inclusive heuristic power management system has been designed for power management in hybrid power generation, considering the availability of sources and their dynamic tariffs. An artificial neural network (ANN) has also been designed to determine the digester operating temperature according to methane yield requirements. The designed system has been investigated for hydrogen consumption, carbon emission, power generation cost, operating cost, power factor, frequency, distortion, efficiency, and voltage regulation. The proposed system effectively meets the load demand at a lesser cost in different scenarios. Cost saving of 28.42%, carbon emission reduction by 96% and 4.53% Total harmonic distortion (THD) at a power factor of 0.99 has been observed. The complete proposed hybrid power plant is ideal for implementation in societies and industries.

Thermometry of AlGaN/GaN 2D Channels at High Electric Fields Using Electrical and Optical Methods

AbstractThe active channels in AlGaN/GaN‐based heterostructures are studied under different applied electrical fields to identify the Joule heating factors affecting the temperature values in the channels. The temperature in active channels of two different lengths (30 and 180 µm) is characterized using optical methods, and electrical methods are used as a reference. The technique of optical thermometry is based on the data of micro‐photoluminescence and micro‐Raman experiments. The electrical method is based on the measurements of current–voltage characteristics for comparison. It is shown that photoluminescence‐ and electrical‐based temperature values demonstrate similar behavior and good correlation. The Raman‐based method, exploiting the temperature dependence of the frequency position of E2high vibrational band in GaN, shows a significant deviation compared with electrical‐ and luminescence‐based methods. This deviation is shown to be related to the residual mechanical strain in the layered structure and the formation of hot phonons. The influence of hot phonons and mechanical strain effects increases at high electrical load (>5 kV cm−1) and at high temperatures (>400 °C), respectively.

Advances in HVdc Bushing Using Nonlinear Materials: Theory, Materials, Structure, and Realization

Bushings are the key equipment in a high-voltage dc (HVdc) project. HVdc bushings not only provide the insulating medium between the HV conductor and the ground electrode but also physically fix the HV conductor in the transformer or in the feedthrough assembly. In operation, HVdc bushings always experience high electric field and load current. When a fault occurs, the bushing will inevitably face instantaneous overvoltage and overcurrent conditions. This harsh operating condition poses a serious threat to the long-term performance and reliability of HVdc bushings. However, the construction of extra-HVdc projects, ultra-HVdc projects, and flexible dc transmission projects is in full swing. The market demand for HVdc bushings is growing rapidly. Take China, for example: from 2013 to 2020, about 2,600 transformer bushings for ultra-HVdc converter transformers and 400 wall bushings for valve halls were needed. The annual demand for HVdc bushings is about 375, and the cost is more than 1.7 billion CNY per year. Considering the construction of extra-HVdc and flexible dc projects, the market scale of an HVdc bushing will increase in the future.

Airgap Length Analysis of a 350 kw PM-Assisted Syn-Rel Machine for Heavy Duty EV Traction

Synchronous reluctance (Syn-Rel) machines with embedded permanent magnets (PMs) are research hotspots in variable speed motor drives due to their robust rotor structure and wide constant power speed range (CPSR). In this article, the potential of PM-assisted Syn-Rel machine to be next generation heavy duty traction motor solution has been investigated, with special attention put on one key geometric parameter, i.e., airgap length. Careful machine design and optimization has been conducted based on geometric parametrization including airgap length variation, for 15000 rpm peak speed and 350 kW peak power output. In low speed operations, the influence of airgap length on different torque components has been analyzed in detail based on the frozen permeability method. In field weakening region, the variation trend of several key parameters such as output power, torque ripple, and power losses have been investigated along with airgap length. It is found that with high electric and magnetic loading, reducing the electromagnetic airgap length is not always beneficial. There exists a suitable airgap length value to comprehensively balance torque/power density, cooling capability, efficiency and reliability. Numerical FEA and experimental tests of the prototype are combined to verify the conclusions.

Surface-governed deformation mechanisms in sub-20-nm metallic crystals stimulated by electrical loading

Metal nanocrystals have been shown to present two sorts of antithetical mechanical behaviors during mechanical tests, that is, “smaller is stronger” and “smaller is weaker”. Dislocation-starvation induced strengthening and surface diffusion induced softening are revealed as two main mechanisms that govern such behaviors. However, the competition between these two mechanisms, as well as their relationship with temperature, is still unclear. To probe into this issue, we here perform an investigation on sub-20-nm Au and Co nanocrystals using an electrical loading-coupled transmission electron microscopy, as the electrical loading can create an adjustable local heating effect, providing variable conditions for testing temperature-related competitions between displacive and diffusional events. It is found that surface diffusion is much more sensitive to temperature than dislocation activities. Apparent transitions of deformation mechanisms are observed when surface diffusion is energetically activated or inhibited. Surface curvature acts as a stimulus or mediator to atom diffusion, generating double-edged impacts on the nucleation of dislocation slip. At elevated temperatures (i.e. high electrical loading), the metal nanocrystals present liquid-like behaviors. Their surfaces can consecutively reshape when surface diffusion dominates; otherwise, shape transformations take place in a collapse-and-reconstruction manner.

Modeling Probabilistic Driving and Charging Profiles of Commercial Electric Vehicles

The electrification of road transport requires a massive integration of charging infrastructure into the electrical distribution grids. In order to investigate their impact on the grid expansion demand or to develop optimization methods for charging management, it is necessary to model the uncertainties of the driving and charging behavior of electric vehicles in the form of probabilistic time series but also as a simultaneity factor. Most scientific papers focus on modeling privately owned electric vehicles. However, the influence of commercial electric vehicles has hardly been considered so far, even though high electric loads are to be expected here as well in the future. In this paper we present our method for modeling the driving and charging behavior of commercially owned electric passenger cars and light commercial vehicles. In our evaluation, we show the plausibility for a fleet of 5000 vehicles in terms of average annual mileage, weekday-dependent trips, and seasonal energy demand, among others. Finally, we determine the maximum simultaneity of the charging power.

Feasible and Optimal Design of an Airborne High-Temperature Superconducting Generator Using Taguchi Method

Aircraft electrification has become a tendency with demands for low carbon emissions and high electrical load capacity nowadays. Aircraft are especially strict with onboard weight; as a result, high-temperature superconducting (HTS) electrical machines are drawing attention for airborne applications due to their potential for a significant increase in power density. In this study, a feasible scheme of a hybrid-HTS airborne synchronous generator was proposed to fulfill the requirements of a small aircraft (with fewer than eight seats and a maximum range of about 1000 km). The full design from top to bottom is described. The output characteristics and metallic and superconducting AC losses were calculated based on the finite element method. The power grade of 1 MW was obtained, with a power density of 9.27 kW/kg and an efficiency of 98.73%. Furthermore, the performance of the machine was optimized using the Taguchi method. The preliminary design demonstrated the possibility and benefits of hybrid-HTS machines for airborne applications.

UPS Design for Increased Flexibility of Use and More Economic with PWM Controlled Inverter Based on ATmega 328 Microcontroller

As the high electrical load increases, power outages can occur suddenly while using electronics and often will cause damage to both software and hardware from the electronic load. To solve this problem, can use an UPS. but UPS also still has weaknesses that become the basis for consideration of its use not yet widespread, such as the price is still expensive and the backup time is short, Therefore, the design of a single-phase ac power supply with a PWM Inverter controller based on the Atmega 328 Microcontroller was carried out to increase the flexibility of the UPS using a current flow pattern according to a bidirectional ac power supply and simplified in this study to make it more economical with fewer diodes and MOSFETs. Total harmonic distortion (THD) voltage is 5.24%, output frequency is 49.56 Hz, output voltage and voltage drop meet the standard with the UPS device consisting of a transformer, adapter and inverter with adjustable switching frequency and filters.

FEM implementation of the nonlinear damage evolution model for piezoelectric material under bipolar electrical fatigue load

The service life of piezoelectric actuator is significantly affected by the high electric fatigue load. Predicting damage evolution in piezoelectric materials under high electric load is essential for the reliability and life prediction of piezoelectric structures and devices. In this paper, a nonlinear damage evolution FE model and its acceleration program are proposed which are capable of modeling nonlinear damage evolution of piezoelectric material and structure under high electric fatigue load. The simulation results of degraded piezoelectric constant varying with the number of cycles are compared with the experimental results, and a well agreement verifies the validity of the nonlinear damage evolution FE model. Moreover, the damage distribution evolution of piezoelectric multi-layer actuator with standard double comb electrode is studied by the proposed nonlinear damage evolution model. The driving performance of piezoelectric multi-layer actuator decreases rapidly under the high electric fatigue load, where the damage area starts from the tip of the electrode and gradually spreads to the area between the electrodes. Based on the nonlinear damage evolution and its FEM implementation, the damage distribution and evolution for piezoelectric structures with variable amplitude bipolar electrical fatigue load can be obtained. This provides a reliable reference for the life prediction and application of the piezoelectric actuator.

Karakterisasi Performa Genset Diesel 5 kW menggunakan Syngas Sekam Padi dengan Variasi Pembebanan

With the decrease in world oil reserves, energy savings have begun to be launched in almost all countries of the world. Indonesia has now become one of the crude oil importing countries, so efforts are needed to reduce dependence on oil and gas fuels. The sustainability of biomass gasification technology, especially in Indonesia, is highly guaranteed because of the abundant availability of biomass in Indonesia. The purpose of this study is to determine the performance of a 5 kW diesel generator against variations in loading with diesel fuel. The second is to know the performance of a 5 kW diesel generator against variations in loading with diesel fuel and rice husk syngas. Data collection on the performance characterization of the 5 Kw diesel generator set from syngas rice husks against variations in loading was carried out at the New Renewable Energy Engineering Laboratory. The loading carried out in this study was using a 5200 Watt halogen lamp. The power used in this study is only up to a maximum of 3200 Watt. The test result shows that the power generated by the generator is greater when using diesel fuel compared to using a mixture of diesel fuel with syngas. The value of the generator power for each loading variable increased when using low electrical load and decreasing when using high electrical load.

Variable Speed Diesel Generators: Performance and Characteristic Comparison

Diesel generators (DGs) are set to work as a backup during power outages or support the load in remote areas not connected to the national grid. These DGs are working at a constant speed to produce reliable AC power, while electrical energy demand fluctuates according to instantaneous needs. High electric loads occur only for a few hours a day in remote areas, resulting in oversizing DGs. During a low load operation, DGs face poor fuel efficiency and condensation of fuel residues on the walls of engine cylinders that increase friction and premature wear. One solution to increase combustion efficiency at low electric loads is to reduce diesel engine (DE) speed to its ideal regime according to the mechanical torque required by the electrical generator. Therefore, Variable Speed Diesel Generators (VSDGs) allow the operation of the diesel engine at an optimal speed according to the electrical load but require additional electrical equipment and control to maintain the power output to electrical standards. Variable speed technology has shown a significant reduction of up to 40% fuel consumption, resulting in low GHG emissions and operating costs compared to a conventional diesel generator. This technology also eliminates engine idle time during a low load regime to have a longer engine lifetime. The main objective of this survey paper is to present the state of the art of the VSDG technologies and compare their performance in terms of fuel savings, increased engine lifetime, and reduced greenhouse gases (GHG) emissions. Various concepts and the latest VSDG technologies have been evaluated in this paper based on their performance appraisal and degree of innovation.

Energy recovery from shock absorbers through a novel compact electro-hydraulic system architecture

Riding a road vehicle involves only 10-16% of the fuel energy to overcome the resistance from friction and air drag, while the rest contributes to a massive ecological and economic damage. From an energy balance point of view, a great amount of energy is dissipated as vibrations at the shock absorbers level. In this paper, a hydraulic regenerative shock absorber, able to recover and convert the vibration energy caused by road profiles is designed and manufactured by exploiting off-the-shelf components to reduce R&D costs, and its overall maximum efficiency is measured. The prototype is composed of a twin tube electronically controlled shock absorber and of an electro-hydraulic unit (also called regenerative valve) rigidly connected to it. The main relations ruling the dynamics of a regenerative damper are discussed and the main features of the regenerative valve are designed to comply with size, performance, and safety requirements. Parametric relations are illustrated and properly managed to justify the choice of a dedicated electric motor. Performances are assessed through simulations and experimental tests, while reliability is confirmed through a thermal analysis that reveals no thermal issues. The prototype reaches a maximum overall harvesting efficiency of 11.7% for an intermediate value of the external electric load at a 500mm/s rod speed and a maximum electric power in output of 75W for a high external electric load at 1000mm/s rod speed. Efficiency is strongly hindered at low values of rod speed because of predominant friction effects. It is also demonstrated the possibility to modify the damping curve by varying the electrical characteristics of the circuit connected to the electric machine. The compact design of the RSA, with a mass of only 5.8kg, allows its installation into the suspension of a B-class SUV with a minimum impact on the current damper structure.

Nonstoichiometric effect of A-site complex ions on structural, dielectric, ferroelectric, and electrostrain properties of bismuth sodium titanate ceramics

To investigate the nonstoichiometric effect of (Bi0.5Na0.5)TiO3 (BNT) ceramics on their properties, we propose a novel chemical expression, (Bi0.5+xNa0.5−3x)TiO3. The nonstoichiometric effect of BNT can be explored in compounds with this composition without being hampered by the charge imbalance problem. With x ranging from −0.02 to 0.02, we find that the morphological, dielectric, ferroelectric, and electrostrain properties differ considerably between Na-rich and Bi-rich ceramic samples. The average grain size (AGS) increased significantly in Na-rich samples compared to that in stoichiometric BNT, while it decreased slightly in Bi-rich samples. The dielectric characteristics measured from 30 °C to 500 °C indicate that conductivity is activated in Na-rich nonstoichiometric samples but is effectively suppressed in Bi-rich nonstoichiometric samples. The ferroelectric properties also show the same trend. In Na-rich samples, elliptical polarization against electric field (P-E) hysteresis loops were detected, indicating a conductive character induced by high electric field loading. However, saturated P-E loops are observed in Bi-rich samples with well-inhibited conductivity. Furthermore, compared to stoichiometric BNT and nonstoichiometric x = 0.02 Bi-rich samples, (Bi0.5+xNa0.5−3x)TiO3 samples with x = 0.01 exhibit higher electrostrain from 30 °C to 150 °C. Based on the assumption of charge balance, our findings indicated that the presence of 1 mol% excess Bi would facilitate significant improvement in the dielectric, ferroelectric, and electrostrain properties of BNT and BNT-based systems.

Characterizing patterns and variability of building electric load profiles in time and frequency domains

The rapid development of advanced metering infrastructure provides a new data source—building electrical load profiles with high temporal resolution. Electric load profile characterization can generate useful information to enhance building energy modeling and provide metrics to represent patterns and variability of load profiles. Such characterizations can be used to identify changes to building electricity demand due to operations or faulty equipment and controls. In this study, we proposed a two-path approach to analyze high temporal resolution building electrical load profiles: (1) time-domain analysis and (2) frequency-domain analysis. The commonly adopted time-domain analysis can extract and quantify the distribution of key parameters characterizing load shape such as peak-base load ratio and morning rise time, while a frequency-domain analysis can identify major periodic fluctuations and quantify load variability. We implemented and evaluated both paths using whole-year 15-minute interval smart meter data of 188 commercial office building in Northern California. The results from these two paths are consistent with each other and complementary to represent full dynamics of load profiles. The time- and frequency-domain analyses can be used to enhance building energy modeling by: (1) providing more realistic assumptions about building operation schedules, and (2) validating the simulated electric load profiles using the developed variability metrics against the real building load data.

Network overloading management by exploiting the in‐system batteries of electric vehicles

SummaryNetwork overloading and electric power shortfalls occur due to large variations in anticipated renewable electric power and electric loads, which may cause system overheating or network failure. A large portion of residential loads (RLs) comprises of electric vehicles (EVs); therefore, by using in‐system electric vehicle batteries (EVBs), above mentioned issues can be resolved. A lot of research has been done in this domain but the stochastic nature of this system has not been fully explored yet. In this article, an intelligent charging mechanism of EVs has been proposed for RLs. EVBs are charged during off‐peak hours and then batteries are utilized as an independent power source during peak hours to decrease stress on the power network. Vehicle‐to‐grid charging and discharging scenarios are considered, to optimize the rate of charging. A novel stochastic model predictive control (SMPC) framework, based on smart charging/discharging of EVBs has been proposed in this article. SMPC deals with the uncertain variations in the projected generation and demand of electric power, due to variable renewable energy and high electric loads, respectively. It deals with the discrepancy of supply, demand, and energy prices. Using SMPC, complex stochastic problems can be transformed into a simpler optimization problem, making it computation efficient and suitable for real‐time applications. To relax constraints on power demand, a worst case scenario technique has been used which reduces the computational cost of the system. Simulation results depict that controlled charging and discharging of EVBs in power grid network help reduce overshoots and undershoots of electric power demand in a smart community. Comparison of the proposed strategy has been done with benchmark algorithms, to show the competency of the proposed strategy. This study provides insight of a smart community microgrid operation and resultant trade‐offs to manage the demand and supply of electricity.

Improving electrical properties and toughening of PZT-based piezoelectric ceramics for high-power applications via doping rare-earth oxides

Ceramics show brittle nature because of ionic and covalent bondings. However, the need for reliable high-power applications with vibrational displacements under high electric fields and stress loadings demands robust piezoelectric ceramics. In this work, three series of Lead Zirconium Titanate-based piezoelectric ceramics for high-power applications are synthesized via solid solution reaction technique. The microstructures and phases are manipulated by doping different rare-earth oxides Nd2O3, Dy2O3 and Yb2O3. Although all as-sintered piezoelectric ceramics show a perovskite structure with a coexistence of rhombohedral and tetragonal phases, phase fraction, grain size distribution and attendant electrical and mechanical properties vary depending on the doping species and contents. The comprehensive properties of optimized piezoelectric ceramics for high-power applications are: d33 = 292–308 pC/N, kp = 54.2–57.0%, Qm = 320–400, ε33T/ε0 = 1140–1210 and KIC = 1.55–1.60 MPa m1/2. These properties are improved by 19.0%–27.0% compared to the original composition without doping. The toughening mechanism by doping rare-earth oxides is discussed. Nd3+, Dy3+ and Yb3+ substitution and compensation at A-sites of perovskite unit cells generate extrinsic vacancies besides the intrinsic vacancies caused due to PbO evaporation during sintering, which make the domain wall highly mobile and result in softened ferroelectrics. Our results show an efficient route to toughen the PZT-based piezoelectric ceramics and enhance electrical properties synergistically via doping appropriate amounts of rare-earth oxides.