Search

This paper introduces a new motor design for traction applications that achieves high power density and meets the power density target of 50kW/L target set by the US Department of Energy. The proposed motor has a doubly salient structure with concentrated toroidal 3-phase windings and permanent magnets (PMs) in the stator and a reluctance rotor, improves torque capability and operating speed compared to traditional designs. A design optimization process was conducted to balance efficiency, power density, and power factor. An equivalent circuit in the DQ reference frame is introduced to enable vector control for the proposed special double salient machine. The resulting design was validated through the creation of an open frame lab prototype (OFLP) and an experimental dyno test bench was developed. The prototype was tested through open circuit tests, static torque tests, and unity power factor tests. This paper also discusses the use of synchronous reference frame theory and per-phase diagrams to calculate electric machine parameters. In addition to experimentation, 3D and 2D electromagnetic FEA simulations have been performed for unity power factor operation as a generator to numerically separate the power loss components.

Significant opportunity for savings in energy and investment through improved performance of power distribution systems exists in the optimal placement and rating of capacitors, a conventionally cost-effective and popular reactive power compensating technology. A novel optimal capacitor planning (OCP) procedure is proposed for large-scale utility power distribution systems, which is exemplified on an existing utility circuit of approximately 4,000 buses. An initial sensitivity analysis is employed to intelligently reduce OCP computation time and maintain quality of optimal configurations. Three optimization objectives are considered, including the minimization of total system active power losses, standard deviation of node voltages, and investment in total capacitor power rating. Eight multi-objective optimization methods that employ the non-dominated sorting algorithm III (NSGA-III) concept are compared to determine individual merits. Differences between the methods include the incorporation of a penalty constraint for voltage violations and the automatic readjustment of load-tap-changing (LTC) transformer tap settings for proposed capacitor re-configurations concurrently within the optimizer, which ensures peak system performance and fair comparison to the reference case. A multi-step model conversion process was developed with OpenDSS to enable the OCP procedure to be generally applicable to real large-scale utility circuits. OCP is performed for three example sub-circuits served by a substation with a 48MW, 9Mvar peak load, which represents the most extreme case and offers the best opportunity for savings. Example configurations from the resulting Pareto sets through a pseudo-weight vector approach are also analyzed through a systematic procedure of comparison between the most extreme configuration types to inform configuration selection.

Domestic load profiles in the residential sectors are being modified with the adoption of smart home management systems and solar generation. In addition, houses with rooftop PV behave like local generators, contributing to the growth of the penetration of PV energy. Hence, the demand for power is declining day by day. However, the increasing PV penetration causes technical challenges for the power system, such as the “duck curve”. This can be addressed through home energy management (HEM) techniques including peak shaving, load shifting with smart home devices. In this regard, electric water heaters (EWH), with high thermal mass and being ubiquitous, are attractive and low-cost energy storage systems. In this article, a case study for one of the largest rural field smart energy technology demonstrators involving business, industries, and more than 5,000 residences, located in Glasgow, KY, US, is presented. Furthermore, a HEM system, which aims to minimize the total energy usage and peak demand by regulating the heating, ventilation, and air-conditioning (HVAC) systems, water heaters, and batteries, thereby benefiting both the utility and the consumer is proposed. This work also demonstrates the ability of EWH to provide ancillary services while maintaining customer comfort. The minimum participation rates for EWH and batteries are calculated and compared with respect to different peak reduction targets. Long term load prediction by considering different fractions of smart homes for the utility is also provided.

Advanced control techniques may be used to establish a virtual power plant to regulate the operation of electric water heaters, which may be regarded as a “uni-directional battery” and a major component of a hybrid residential energy storage system. In order to estimate the potential of regulating water heaters at the aggregated level, factors including user behavior, number of water heaters, and types of water heaters must be considered. This study develops generic water heater load curves based on the data retrieved from large experimental projects for resistive electric water heaters (EWHs) and heat pump water heaters (HPWHs). A community-level digital twin with scalability has been developed to capture the aggregated hot water flow and average hot temperature in the tank. The results in this paper also include the “energy take” in line with the CTA-2045 standard and Energy Star specification. The data from the experiments demonstrated that changing from an EWH to an HPWH reduces electricity usage by approximately 70%. The case study showed that daily electricity usage could be shifted by approximately 14% and 17% by EWH and HPWHs, respectively, compared to their corresponding average power. Another case study showed that both EHWs and HPWHs, coordinated with PV to reduce morning and evening peaks, could shift approximately 22% of the daily electricity.

Separating the HVAC energy use from the total residential load can be used to improve energy usage monitoring and to enhance the house energy management systems (HEMS) for existing houses that do not have dedicated HVAC circuits. In this paper, a novel method is proposed to separate the HVAC dominant load component from the house load. The proposed method utilizes deep learning techniques and the physical relationship between HVAC energy use and weather. It employs novel long short-term memory (LSTM) encoder-decoder machine learning (ML) models, which are developed based on future weather data input in place of weather forecasts. In addition to being used in the proposed HVAC separation method, the LSTM models are employed also for accurate day-ahead HVAC and solar photovoltaic (PV) energy forecasts. To test and validate the proposed method, the SHINES dataset, a publicly available dataset spanning three years at 15-minute time resolution from a large-scale DOE experimental project, is used. Two computational case studies are constructed with a test HEMS to investigate the power regulating capability of smart home virtual operation as dispatchable loads or generators. Prediction results obtained with the proposed method show hourly and daily CV(RMSE) of 29.4% and 11.1%, respectively. These results are well within the bounds of error established by academia and the ASHRAE building model and calibration standards.

The equivalent circuit model for utility-scale battery energy storage systems (BESS) is beneficial for multiple applications including performance evaluation, safety assessments, and the development of accurate models for simulation studies. This paper evaluates and compares the performance of utility-scale equivalent circuit models developed at multiple sub-component levels, i.e. at the rack, module, and cell levels. This type of modeling is used to demonstrate that the equivalent circuit model for a reference cell, module, or rack of a BESS can be scaled to represent the entire battery system provided that the battery management system (BMS) is active and functional. Contrary to the rapid pulse discharge cycles employed in conventional cell parameter estimation approaches, the study proposes a new charge/discharge cycle for identifying the equivalent circuit parameters for utility-scale battery systems using equipment readily available at installation sites without the need for laboratory setups. Furthermore, a sensitivity analysis for classifying and quantifying the effect of each equivalent circuit parameter on the performance of the proposed battery system model was executed. The measurements and simulations are conducted for a 1MW/2MWh BESS testing facility located at the Louisville Gas and Electric and Kentucky Utilities (LG&E and KU) E.W. Brown generating plant. The results indicate that for the example utility-scale battery setup with an active BMS, the equivalent circuit model of either the cell, module, or rack can be scaled to represent the battery system with less than 1% average voltage error.

The Multilevel inverters (MLIs) are a new breed of power electronics converters. They are primarily used for the conversion of dc power to ac power. The two-level inverters are conventionally used to obtain ac power, but it requires operating the switches under very high switching frequency. Besides, the two-level inverter necessitates the use of LC filters with the switches operating under high dv/dt stress. The MLIs offer the advantage of utilizing several dc voltage sources to generate a stepped ac waveform with the proper arrangement of switches. Investigation of a Transistor Clamped T Type H-Bridge Multilevel Inverter (TC-TT-HB-MLI) with Inverted Double Reference Single Carrier PWM Technique (IDRSCPWM) for Renewable Energy Applications are discussed in this paper. A PV source is taken as an input to the TC-TT-HB-MLI. For different modulation indices like 0.85, 1 and 1.25, the FFT analysis is performed and presented, which corresponds to the variations in the irradiations from solar energy. A single unit of the TC-TT-HB-MLI is extended to a generalized MLI structure named Generalized Transistor Clamped T-Type H-Bridge Multilevel Inverter (GTC-TT-HB-MLI). The significant benefits of GTC-TT-HB-MLI are the multiple numbers of reductions in the switch count, and driver circuit counts for a higher number of MLI levels. Fast Fourier Transform (FFT) analysis is carried out on the MLI output to calculate the total harmonics distortion (THD). The experimental verification is performed using SPARTAN 3E-XCS250E; the gate signals are generated and provided to the switches.

In significant cases, the generated voltage needs to be step-up with high conversion ratio by using the DC-DC converter as per the requirement of the load. The drawbacks of traditional boost converter are it required high rating semiconductor devices and have high input current ripple, low efficiency, and reverse recovery voltage of the diodes. Recently, the family of Multilevel Boost Converter suggested and suitable configuration to overcome the above drawbacks. In this article, hybrid DC-DC non-isolated and non-inverting Nx Interleaved Multilevel Boost Converter (Nx-IMBC) is analyzed in Continuous Conduction Mode (CCM) and Discontinuous Conduction Mode (DCM) with boundary condition and investigated in detail. The Nx-IMBC circuit combined the features of traditional Interleaved Boost Converter (IBC) and Nx Multilevel Boost Converter (Nx-MBC). The modes of operation, design of Nx-IMBC and the effect of the internal resistance of components are presented. The comparison study with various recent DC-DC converters is presented. The experimental and simulation results are presented with or without perturbation in input voltage, output power and output reference voltage which validates the design, feasibility, and working of the converter.

The automobile companies are focusing on recent technologies such as growing Hydrogen (H2) and Fuel Cell (FC) Vehicular Power Train (VPT) to improve the Tank-To-Wheel (TTW) efficiency. Benefits, the lower cost, `Eco' friendly, zero-emission and high-power capacity, etc. In the power train of fuel cell vehicles, the DC-DC power converters play a vital role to boost the fuel cell stack voltage. Hence, satisfy the demand of the motor and transmission in the vehicles. Several DC-DC converter topologies have proposed for various vehicular applications like fuel cell, battery, and renewable energy fed hybrid vehicles etc. Most cases, the DC-DC power converters are viable and cost-effective solutions for FC-VPT with reduced size and increased efficiency. This article describes the state-of-the-art in unidirectional non-isolated DC-DC Multistage Power Converter (MPC) topologies for FC-VPT application. The paper presented the comprehensive review, comparison of different topologies and stated the suitability for different vehicular applications. This article also discusses the DC-DC MPC applications more specific to the power train of a small vehicle to large vehicles (bus, trucks etc.). Further, the advantages and disadvantages pointed out with the prominent features for converters. Finally, the classification of the DC-DC converters, its challenges, and applications for FC technology is presented in the review article as state-of-the-art in research.

Forthcoming capacity scaling requirements of optical networks and advances in optical fiber communications beyond the omnipresent single-mode fiber operating over the conventional band introduces new opportunities and challenges for exploiting the expanded spectral and spatial resources available for fiber-optic network designs. The spectral and spatial degrees of freedom introduce utilization tradeoffs that can be leveraged under different applications. After briefly reviewing the supporting network building elements (emerging fiber types, multiplexers, optical switches, and amplifiers), we consider networking scenarios such as intra/inter datacenter, terrestrial, undersea, and wireless 5G/6G hauling networks and identify the best utilization plan and key attributes that can be harnessed by the offered spectral and spatial degrees of freedom for each scenario and how optical switching can be employed therein for traffic management. Networks supporting these scenarios are experiencing tremendous traffic growth pushing their existing implementations to their physical capacity-distance limits. New network builds must offer significant capacity multipliers in an efficient and cost-effective manner, requiring new switching solutions for supporting the unabated traffic growths foreseen in the years to come. We discuss how space-division multiplexed networks can help address this challenge in key communication scenarios. [ABSTRACT FROM AUTHOR]