Load Profile Research Articles

Impact of turbine availability and wake effect on the application of dynamic thermal rating of wind farm export transformers

Dynamic thermal rating allows transformers to operate beyond the nameplate rating according to the actual weather and loading conditions. This paper proposes a methodology to improve the application of this technology in the design of new transformers or in the operation of existing transformers connected to wind farms by accurately predicting their load profiles, accounting for the influence of wake effect and turbine availability. Specifically, the variation of turbine availability due to the intermittent wind is considered in the load profile estimation. Additionally, a correction method, which can be incorporated into any wake model, is proposed to improve the accuracy of wake loss computation. A case study shows that the wake effect and the changing turbine availability shorten the time that the transformers maintain at full load, thereby reducing the aging rate of the wind farm export transformers. The findings suggest that considering these two factors in the application DTR application can benefit the longevity and efficiency of wind farm exported transformers.

Data-Driven Residential Electric Vehicle Charging Behavior and Load Profile Modeling for Demand Response in the Midcontinent Independent System Operator Region

Data-Driven Residential Electric Vehicle Charging Behavior and Load Profile Modeling for Demand Response in the Midcontinent Independent System Operator Region

Nonlinear Loads Modelling and Harmonics Analysis: A Review

Abstract: In modern life, the applications of nonlinear loads are increasing, especially electronic loads, such as computers, monitors, and battery chargers. Moreover, the usage of semiconductors has increased in modern lighting systems, such as LED lamps and dimmers which are used to control the lighting level. Nonlinear loads may also be in the form of variable speed drive or arc furnace loads. Due to the spread of nonlinear loads, large amounts of harmonics are generated. To study the harmonics of nonlinear loads, it is essential to represent nonlinear loads by their equivalent models in the simulation programs. This paper presents a comprehensive review of modeling methods of nonlinear loads, including time domain methods, frequency domain methods, and state space methods. Equivalent circuits are presented for different types of nonlinear loads, including static loads, dynamic loads and arc furnace loads. The paper also presents the harmonic analysis performed by the Fourier transform of different types of nonlinear loads, including harmonic percentage and its angle. This paper is considered as a comprehensive reference for researchers and engineers to model nonlinear loads and is useful in power system planning for connecting nonlinear loads where mixing nonlinear loads of similar harmonic profiles causes worse situations. Moreover, knowing the nonlinear load profile will help in the suitable mixing of linear loads to achieve lower harmonics levels.

Feasibility study of hybrid renewable energy systems for off-grid electrification in Kuwait’s rural national park reserve

ABSTRACT This study demonstrates the optimal design of a hybrid renewable energy system for the electrification of a potential rural national park reserve. The objective is to evaluate the feasibility of utilising renewable energy sources (RESs) to reduce GHG emissions. The core components studied are photovoltaic solar (PV) panels, wind turbines (WTs), diesel generators (DGs), and battery banks (BBs). The research involves estimating the reserve’s load profile, assessing the potentials of RESs, and designing various system configurations. Each configuration is evaluated to derive the most efficient option. For a building with an energy demand of 832,640 kWh/yr, it is found that PV-WT-BB is the best configuration which comprises of 500-kW PV, 200-kW WT, and 1424-kW BBs and contributes an annual generation of 1,821,732 kWh/year. With a net present cost of $2,206,308 for the lifetime of the project, it saves 757,162 kg/year of total GHG emissions if the reserve operated using DGs.

Towards robust state estimation for LFP batteries: Model-in-the-loop analysis with hysteresis modelling and perspectives for other chemistries

The accurate estimation of a battery’s state of charge (SOC) is critical in battery management systems for various applications. Lithium Iron Phosphate (LFP) batteries, preferred for their long cycle life, cost efficiency, and enhanced safety, have emerged as favourable choices for stationary storage. Yet, they still face challenges in precise SOC estimation due to the flatness and hysteresis of their open circuit voltage. Addressing this, our study integrates a hysteresis model into a third-order battery model for BMS controlling a stationary storage system in frequency containment reserve (FCR) application. We analysed three advanced SOC estimation techniques — extended Kalman filter (EKF), dual unscented Kalman filter (DUKF), and particle filter (PF) — with the hysteresis model using a model-in-the-loop (MiL) toolchain. Performance testing under a 48-hour FCR load profile showed EKF with a 4% error, DUKF achieving the best result with a 1.1% error, and PF’s performance varying between 2.9% and 4% depending on particle count. Robustness tests against initialization and current sensor errors under an 8hr profile revealed DUKF maintained a 2% error boundary irrespective of the error introduced, highlighting the hysteresis model’s effectiveness. Broadening the scope, the study also explores extending the method to other lithium-ion chemistries.

Integrating hybrid PV/wind-based electric vehicles charging stations with green hydrogen production in Kentucky through techno-economic assessment

The study presents a comprehensive analysis of the integration of Photovoltaic (PV)/wind systems with electric vehicle (EV) charging stations, enhanced by green hydrogen production based on existing EV load profiles across Kentucky. It explores the use of excess PV energy to charge Lithium-ion batteries, potentially supplemented by on-grid power during periods of lower electricity costs. The research includes the development of predictive models for hydrogen production and its subsequent use in hydrogen-powered vehicles. The techno-economic assessment reveals that such integration exhibits consistent economic viability, with minimal variations in key financial indicators like the levelized cost of electricity, payback period, and PV/wind energy fraction. The study also highlights green hydrogen production for on-grid PV/wind power charging the electrolyzer leads to the highest production cost (∼13 USD/Kg) compared to off-peak grid and a grid/PV/wind combination (∼6 USD/Kg). The projected hydrogen output is poised to support a significant number of light and heavy-duty vehicles by 2040, indicating promising potential for low-carbon transportation in Kentucky.

Harmonizing the assessment of allostatic load across cycles of the Canadian Health Measures Survey: Variable selection and calculation method.

The availability of measures to operationalize allostatic load - the cumulative toll on the body of responding to stressor demands - in population health surveys may differ across years or surveys, hampering analyses on the entire sampled population. Here, impacts of variable selection and calculation method were evaluated to generate an allostatic load index applicable across all cycles of the Canadian Health Measures Survey (CHMS). Data from CHMS cycles 1 to 4 were used to compare allostatic load scores when replacing the most prevalent risk factor, waist-to-hip ratio - available in cycles 1 to 4 but not 5 and 6 - with body mass index (BMI), waist circumference, waist circumference within BMI groups (classified as normal, overweight, or obese), or waist-to-height ratio. Indexes were generated using clinical or sex-specific empirically defined risk thresholds and as count-based or continuous scores. Logistic regression models that included age and sex were used to relate each potential index to socioeconomic indicators (educational attainment, household income). Of the variables assessed, waist-to-height ratio and waist circumference were closest to waist-to-hip ratio according to an individual's percentile ranking and in classifying "at risk" using either clinical or empirically defined cut-offs. Allostatic load profiles generated using waist-to-height ratios most closely resembled profiles constructed using waist-to-hip ratios. Sex-dependent associations with educational attainment and household income were maintained across constructs whether indexes were count-based or continuous. Allostatic load profiles and associations with socioeconomic indicators were robust to variable substitution and method of calculation, supporting the use of a harmonized index across survey cycles to assess the cumulative toll on health of stressor exposure.

Battery Electrolyte Design for Electric Vertical Takeoff and Landing (eVTOL) Platforms

AbstractThe development of robust and high‐performance battery systems is crucial for the advancement of Electric Vertical Takeoff and Landing (eVTOL) vehicles for urban air mobility. This study evaluates the performance of different lithium‐ion battery chemistries under Electric Vertical Takeoff and Landing (eVTOL) load profiles. The actual flight data coupled with physical models is used to create discharge profiles for testing on developed lithium‐ion cells for eVTOLs. The performance of a standard liquid electrolyte (1.2 M LiPF6 in EC:EMC), labeled Gen‐2, is benchmarked and compared with a fast‐charging electrolyte (1.2 M LiFSI in EC:EMC), labeled XFC. Cell analysis involves the use of various techniques, such as impedance spectroscopy, polarization curves, and capacity retention measurements. Capacity retention is stable for both systems over 500 cycles, but unique discharge capacity trends are observed for different mission segments. During the initial takeoff hover stages, Gen‐2 electrolytes experience substantial voltage fade, while XFC electrolytes maintain consistent behavior. In general, the Gen‐2 electrolyte demonstrated lower discharge overpotentials and higher decay during cycling compared to the XFC electrolyte. This work highlights the complexity of eVTOL battery behavior and provides insights into battery system design, contributing to the advancement of battery energy storage solutions for urban air mobility.

Need a break? The locomotor and tackle pacing profile and loads of women’s rugby league match-play following various between-match turnaround durations

ABSTRACT Objectives The study investigated the locomotor and tackle pacing profile and loads of female rugby league players following various between-match turnaround durations. Specifically, the study examined the (1) pacing of locomotor and tackle loads across the time-course of a match and; (2) whole-match and peak locomotor and tackle loads of match-play. Methods Microtechnology data were collected from elite female rugby league players (n = 172) representing all National Rugby League Women’s teams (n = 6 teams) across two seasons. Players were categorised into backs, adjustables, forwards or interchange players. Data was calculated for the whole-match (m), per minute (m.min−1) and peak (running: m.min−1; acceleration: m.s−2) locomotor and tackle loads (number and efficiency (%)) of match-play. The pacing as well as the locomotor and tackle loads of match-play were examined following short (≤6 days), normal (7 days) or long (≥8 days) turnarounds. Results The pacing profile of playing positions varied across short, normal and long match turnarounds. Trivial to moderate differences existed in the whole-match, per minute and peak locomotor loads across match turnaround durations (effect size ≤ 1.2). Conclusions Following various between-match turnaround durations (i.e., short, normal and long match turnarounds), there were variations in the locomotor and tackle pacing profile and loads whereby, the pacing profile of positional groups was more affected than the load profile. The findings can be used in applied settings to guide the recovery strategies and training plans of female rugby league players to optimise performance and wellbeing across various match turnaround durations.

Frequency and power shaving controller for grid-connected vanadium redox flow batteries for improved energy storage systems

In this research, the performance of vanadium redox flow batteries (VRFBs) in grid-connected energy storage systems centering on frequency and power sharing using voltage source inverters was evaluated. VRFBs are increasingly promising due to their scalability and long lifespan. We explore the impact of voltage source inverters on the frequency of the power supply when there is a change in load and power sharing between the grid and VRFB through MATLAB simulations. The test system demonstrates a storage system at an 11-kV substation and considers a load profile commencing from residential and commercial consumers. The outcome of this study reveals that VRFBs provide the required power to maintain load demand. Due to fast response time, VRFBs also regulate the frequency efficiently during the change in load demand and maintaining current total harmonic distortions (THDs). This research confirms the design and operation of VRFB-based energy storage systems, contributing to resilient grid infrastructure and reliable power distribution systems.

Short-term power load forecasting for integrated energy system based on a residual and attentive LSTM-TCN hybrid network

In the context of Integrated Energy System (IES), accurate short-term power demand forecasting is crucial for ensuring system reliability, optimizing operational efficiency through resource allocation, and supporting effective real-time decision-making in energy management. However, achieving high forecasting accuracy faces significant challenges due to the inherent complexity and stochastic nature of IES’s short-term load profiles, resulting from diverse consumption patterns among end-users and the intricate coupling within the network of interconnected energy sources. To address this issue, a dedicated Short-Term Power Load Forecasting (STPLF) framework for IES is proposed, which relies on a newly developed hybrid deep learning architecture. The framework seamlessly combines Long Short-Term Memory (LSTM) with Temporal Convolutional Network (TCN), enhanced by an attention mechanism module. By merging these methodologies, the network leverages the parallel processing prowess of TCN alongside LSTM’s ability to retain long-range temporal information, thus enabling it to dynamically concentrate on relevant sections of time series data. This synergy leads to improved prediction accuracy and broader applicability. Furthermore, the integration of residual connections within the network structure serves to deepen its learning capabilities and enhance overall performance. Ultimately, results from a real case study of a user-level IES demonstrate that the Mean Absolute Percentage Error (MAPE) of the proposed framework on the test set is 2.35%. This error rate is lower than the averages of traditional methods (3.43%) and uncombined single submodules (2.80%).

Techno-economic assessment of grid-connected residential photovoltaic systems considering overvoltage-induced generation curtailment

Grid-connected residential photovoltaic (PV) systems are continuously installed in worldwide communities, predominantly to reduce electricity bills. However, the rapid growth of distributed PV systems inevitably causes overvoltage in distribution networks. Conventionally, PV curtailment is implemented in a grid-connected inverter to prevent the system from overvoltage. Nevertheless, previous studies have failed to consider PV curtailment caused by overvoltage when conducting techno-economic assessments. Therefore, this study conducts a comprehensive techno-economic assessment of grid-connected residential PV systems, considering overvoltage-induced generation curtailment. A volt-watt curtailment strategy is designed based on a droop characteristic. Simulation studies are conducted using real-world load profiles and electricity tariffs retrieved from the Metropolitan Electricity Authority in Thailand. Furthermore, a typical low-voltage distribution feeder in Bangkok, Thailand, is employed using Thailand’s grid code. Simulation results indicate that the optimal PV size could be reduced by up to 58.33% (depending on the numbers and locations of PV systems) when considering overvoltage-induced generation curtailment, resulting in a profitability reduction of 21.34%. It is concluded that considering overvoltage-induced generation curtailment can accurately determine the PV size, preventing oversizing and overvoltage.

Prediction Analysis of Fault Mode Sets for High Permeability Distributed Energy Distribution Networks Based on Multivariate Data

This technical abstract describes a prediction analysis methodology for fault mode sets in high-permeability distributed energy distribution networks (DEDNs). DEDNs are complex systems composed of multiple interconnected energy sources, storage units, and loads, which are managed and controlled by intelligent devices. These systems have become increasingly important in modern electricity networks due to their ability to integrate a high share of renewable and distributed energy resources. The proposed prediction analysis aims to identify and classify the various fault modes that can occur in high-permeability DEDNs based on multivariate data. It includes information about the system's operational parameters, such as voltage, current, and frequency, as well as data on weather conditions, load profiles, and the state of the network. The methodology involves collecting and pre-processing the data using suitable techniques, such as data filtering and noise removal.

Characterizing residential sector load curves from smart meter datasets

Understanding how and when residential electricity is used throughout the day is integral to the successful implementation of potential residential demand management strategies. Our analysis characterizes the daily hourly load profiles of approximately 160,000 residential electricity customers across the Southern California Edison (SCE) service area during the period spanning 2015 to 2016 and 2018 to 2019 across weekends, weekdays, seasons, and climate zones. We find that total daily electricity usage was highest in the hottest months of the year compared to milder months, particularly for households located in the hottest climate zones. The most energy-consumptive hours occurred during the mid-afternoon during the hottest months, in contrast to early evening high consumption in cooler months. We find that customers with average daily consumption at or above the 80th percentile cumulatively consume over 40% of electricity during the hottest months of the year residential load, while the bottom half of customers cumulatively consume <25% of the total residential load. The disparities in electricity usage across SCE households are higher in the mid-day, especially in milder months across all regions, and in mild climate zones compared to hotter climate zones since loads are not as dependent on high HVAC loads.

Impacts of wireless charging system for electric vehicles on power grid

Electric Vehicles (EVs) have become a viable choice for cutting carbon emissions in the field of road transportation. EVs will be incorporated into the electrical grid at an increasing rate in the near future. EVs themselves are becoming immense power consuming load on the power grid system as a result of the growing number of EVs, mostly light-duty EVs. In addition to posing major technical risks such power quality issues, voltage swings, harmonic injection, battery deterioration, and grid instability, the unplanned installation and rapid adoption of charging stations might impede the smooth functioning of the power distribution system. Therefore, this paper analyzes and summarizes the potential issues and solutions for Fast Wireless Charging (FWC) that allows for the wireless transmission of very high-power levels (>20 kW) from the power grid to explore the impact of EV charging on the power system network. This need can have far-reaching effects on the load profile, operation, and design of the distribution network. In order to avoid exceeding the grid's technical restrictions, it is crucial to find the maximum feasible deployment level before rolling out an FWC network. This study provides a method for assessing how FWC technologies influence distribution networks. Using a realistic model of an Indian MV distribution feeder, the proposed methodology is used, providing both quantitative and qualitative results that serve as potential directions for future research studies.

ETHOS.PeNALPS: A Tool for the Load Profile Simulation of Industrial Processes Based on a Material Flow Simulation

ETHOS.PeNALPS: A Tool for the Load Profile Simulation of Industrial Processes Based on a Material Flow Simulation

Phasing effects on thermo-mechanical fatigue damage investigated via crystal plasticity modeling

Nickel (Ni)-based superalloys have high strength at elevated temperatures, making them ideal candidates for aerospace components exposed to thermo-mechanical loads. Thermo-mechanical fatigue’s (TMF) influence on material failure is highly dependent on the temperature-load phase profile as a consequence of path-dependent thermo-mechanical plasticity. In order to understand the direct influence phasing effects have on TMF performance, a microstructure-based fatigue model has been developed to connect damage mechanisms to crack initiation events. In this work, in-phase (IP) TMF, out-of-phase (OP) TMF, and iso-thermal (ISO) loading profiles are investigated with a temperature-dependent, dislocation density-based crystal plasticity model to pinpoint a relationship between microstructural damage and TMF phasing effects. A crystal plasticity modeling framework with capabilities to isolate phasing (IP, OP, and ISO) effects is presented to locate fatigue damage in a set of statistically equivalent microstructures (SEMs) with an energy-based damage indicative parameter. Local stress, accumulated damage, intragranular misorientiation, grain interactions, and slip alignment activity at the damaged regions are studied under the various temperature-load phase profiles to connect microstructural material damage to TMF performance. Based on the local microstructural material damage, it is postulated the material’s stiffness at maximum load influences OP TMF performance, whereas the hardening/plasticity at maximum load influences IP TMF. The results from the presented framework is consistent with experimental evidence that at high mechanical strain amplitudes IP TMF has a shorter life as a consequence of hardening/plasticity influencing path-dependent thermo-mechanical plasticity, whereas at low strain amplitudes OP TMF has a shorter life due to stiffness influencing path-dependent thermo-mechanical plasticity.

Nodal price-based demand response management via orderly time-of-use strategy for an unbalanced isolated microgrid considering voltage stability constraints

This paper scrutinizes the compatibility of voltage stability criteria with price-based demand response management (DRM) for a large-scale isolated microgrid considering severe dependency of constant-impedance loads (CILs) on nodal voltage magnitude. Meanwhile, a hybrid nodal pricing (HNP) scheme is developed to determine clearing prices for resources and time-of-use (TOU) tariffs for price-responsive loads. The proposed framework is composed of three ingredients including two optimization molds with the objective of actual net profit and recast operation expense sequentially solved in an iterative process together with one pay-off module. The energy schedules, unbalanced voltages and nodal prices are determined considering intermittency of renewable resources, unbalances, circuit limitations, and reactive power requirements. Two bus and line voltage stability indices as well as voltage profile management criterion are used to prevent voltage instability. Thus, load profile is corrected such that voltage stability can be upheld as well. The proposed method is implemented via a modified CIGRE benchmark. The simulation results demonstrate that load factor improves at least 4.30% under desirable stability margins. Moreover, total energy loss and line voltage unbalance rate (LVUR) decrease at least 1.02% and 10.03% respectively.

Twist design of lattice structure fabricated by powder bed fusion to adjust the energy absorption behavior

Additive manufactured lattice structures offer great potential for impact resistance applications. They exhibit excellent energy absorption characteristics during the elasto-plastic deformation process, providing protection to internal devices. However, the mechanical response of lattice structures undergoes substantial variations during the deformation process, thereby imposing limitations on their energy absorption behavior. This study introduces a novel twist design to modify the energy absorption behavior of rectangular and hollow cylindrical lattice structures. Powder bed fusion was used to fabricate the twisted lattice structures. The study employed a combination of compressive simulations and experimental investigations to systematically explore the impact of the twist angle on the peak crushing force, energy absorption, and crash load efficiency of the structures. Adjusting the twist angle results in a reduction of the peak crushing force and a transition towards a stable loading profile during the deformation process. Moreover, the crash load efficiency is also reduced. The twist design concept presented in this paper provides insight into designing and optimizing lattice structures for energy absorption applications.

Comparative analysis of battery energy storage systems’ operation strategies for peak shaving in industries with or without installed photovoltaic capacity

Battery energy storage systems can address energy security and stability challenges during peak loads. This study examines the integration of such systems for peak shaving in industries, whether or not they have photovoltaic capacity. The battery-sizing problem has been analyzed extensively. However, most analyses assume a specific battery operation strategy and ignore the impact of battery-charging schemes on system behavior. In this paper, the authors compare three different operation strategies for charging batteries in an industrial peak-shaving application based on historical demand data from a large electricity consumer in El Salvador. The three strategies are fast charging, time-based charging, and low-power threshold charging. The study analyzes the possible integration of a photovoltaic system with two different sizes for a range of battery sizes (from 250 to 1,500 kWh capacity), examining optimal peak shaving levels, economic savings, and battery degradation. Results indicate that fast-charging reduces monthly billing but degrades batteries faster. The estimated lithium-ion battery lifespan is 10-10.5 years, with a maximum difference of five months. These differences could affect the life cycle economics due to the high costs of battery replacement. The economic savings achieved by the peak shaving operation of the storage system are not enough to compensate the battery investment in this study. However, other case studies with different load profiles or other locations with more expensive electricity tariffs could make the adoption of these systems economically viable.