Power Measurements Research Articles

Economic outcomes and evaluation of market power of enterprises

Equitable distribution of society's resources is impossible without controlling monopolies. This is especially true of state-owned enterprises, which, in addition to inflated prices, often have the ability to use the resources received inefficiently. In order to control the market power of enterprises, scientists have already developed many approaches to analysing the market structure and assessing the level of its concentration. At the same time, the problem of formal numerical assessment of the degree of market power of enterprises remains insufficiently resolved. One of the most important areas of assessing the market power of an enterprise is the analysis of its economic results. The essence of this assumption is quite simple: the higher the level of market power an enterprise has, the more independent it is in setting higher prices, which lead to excessive profits. This paper does not consider possible sources and causes of market power related to product uniqueness, cross elasticity of demand or market structure. The purpose of the paper is to find a way to assess market power according to performance indicators that are derived from and result from the use of market power by an enterprise. However, a study of the existing methods of assessing the level of market power of an enterprise has shown that there is no single approach to determining the degree of market power of an enterprise, despite the unambiguous dependence. Most methods propose to use profitability as a basis, but there is a variety of views on how to calculate this indicator. While the first component of profit, revenue or the price of goods, is a fairly objective indicator, the greatest difficulties are found in understanding and applying cost elements to calculate profitability as a measure of market power.

Smart home power management algorithm using real-time model predictive control for a stand-alone PV system with battery energy storage

A smart home power management system is critical for stand-alone home-photovoltaic (HPV) with battery energy storage. Existing approaches often focus on maximizing power extraction from PV systems without considering real-time power adjustments or battery state of charge (SoC), which can lead to over-current or over-voltage issues that damage the battery. To address these limitations, this paper proposes a home power management algorithm that dynamically adjusts the power flow between the PV system, home loads, and the battery based on real-time system power measurements and battery SoC. This dynamic adjustment ensures an uninterrupted power supply to the home loads while maintaining battery safety. The proposed home manager algorithm features multiple operating modes: Maximum power point (MPP) charging, partial charging, fast charging, float charging, and partial discharging. Each mode is integrated with its dedicated model predictive controller (MPC) to achieve its specific control objective. Finally, through a semi-experimental simulation using a process-in-the-loop (PIL) test approach with the embedded board eZdsp TMS320F28335, testing under various irradiance levels shows that the home manager achieves significant improvement over conventional approaches. For instance, over the MPP mode it achieve a power efficiency of 99.36% with a 2.05% SoC increase, while fast charging mode resulted in 87.44% efficiency with an 11.2% SoC increase. However, float charging mode maintained an 87.27% efficiency with a 2.6% SoC increase, and partial discharging led to a 1.3% SoC decrease. The overall battery efficiency reached 96.45%, demonstrating the algorithm’s ability to optimize power flow, ensure a reliable energy supply, and maintain battery safety under varying weather conditions.

The effectiveness of duty cycling technique on air conditioning system during break period for comfort, energy and cost savings: A real case study in health center

This paper investigates the potential of duty cycling techniques for air conditioning (AC) systems in producing energy and cost savings and the impact on the indoor thermal environment, air quality, and environmental sustainability. The real case study concentrated on energy consumption practice during the break period between 13:00 to 14:00 in a lobby area of a Health Center. Site data measurements of electrical input power, energy, indoor air temperature and humidity, and indoor carbon dioxide (CO2) concentration were conducted. Two zero-cost strategies were studied and results were compared to baseline conditions. In general, the results show that all strategies can meet the indoor thermal environment and air quality requirements, except room temperature for Strategy 2 which ranges on average between 26.71 to 26.82C. In addition to the instant payback period (0 years), the results also indicate that as compared to baseline condition, Strategies 1 and 2 led to annual energy and cost savings of around 759.2 kWh (USD 64.40) and 1250.6 kWh (USD 106.08), respectively. In terms of environmental sustainability, Strategies 1 and 2 can avoid environmental CO2 emissions by 444.13 and 731.60 kg of CO2 per year, respectively. Due to these reasons and if the sensitivity of occupant comfort to room temperature during the break period can be tolerated, it is proposed that Strategy 2 is the best option for the AC system operation during the break period. Considering other buildings also adopted the same strategy, this small action can lead to a high impact, not only on energy and cost savings but also on environmental sustainability in the future.

Predicting costs of local public bus transport services through machine learning methods

The present study developed several machine learning-based cost models to predict an efficient total economic cost per vehicle revenue-mile of urban public bus transport. The models were trained on a built-in dataset from 269 transit agencies providing urban services in the United States from 2015 to 2019. A feature selection strategy was implemented, finding that, for each proposed model, a subset of features determined a large impact on unit cost. These “core” features included commercial speed, average salary expenses per employee, vehicle productivity, and fleet ownership cost per vehicle. Machine learning techniques outperformed the linear regression method in terms of predictive power and robustness (understood as the dispersion of predictive power measures over the training sets). Based on SHAP values, the sensitivity analyses showed that the proposed models could be used to predict the impact of changes in some critical features on corresponding unit costs. The results may be useful for: (i) introducing regulatory constraints to the allocation of national public resources to local public bus transport services, aimed at minimizing the resources needed to provide a given level of service; (ii) defining the maximum economic compensation required by firms involved in competitive tendering for the allotment of service concessions, or firms with monopoly rights (by political choice and/or local public ownership); and (iii) improving service contract management and design by identifying key cost drivers of transit services.

Feelings of Empowerment Scale for Family Caregivers: Development, Exploratory, and Confirmative Analysis

ABSTRACT Objectives This study aimed to validate a measure of feelings of empowerment among family caregivers of persons with life limiting illnesses. Methods Family caregivers (N = 295) completed a survey on their feelings of empowerment and psychosocial constructs. Results Utilizing exploratory and confirmatory factor analyses, the study validated the Empowerment in the Context of Caregiving scale, revealing a two-factor structure related to influencing the care recipient and controlling personal outcomes, with high reliability and validity. Convergent validity was supported by a strong association with an established measure of power. Discriminant validity was demonstrated through weak associations with theoretically less relevant constructs, confirming the scale’s validity. Conclusions This scale provides a reliable tool to identify feelings of disempowerment among caregivers, with implications for theory and practice. Future research should explore predictive validity and consider cultural factors to enhance its applicability in diverse caregiving contexts. Clinical Implications This study provides a reliable tool to identify feelings of empowerment among family caregivers of persons with life limiting illnesses for clinicians. It also allows future studies to reliably investigate a theory-driven intervention target, feelings of power, and allows clinicians to tailor this into theory-driven intervention for family caregivers of persons with life limiting illnesses.

New, Optimized Skin Calorimeter Version for Measuring Thermal Responses of Localized Skin Areas during Physical Activity.

We present an optimized version of the skin calorimeter for measuring localized skin thermal responses during physical activity. Enhancements include a new holding system, more sensitive thermopiles, and an upgraded spiked heat sink for improved efficiency. In addition, we used a new, improved calorimetric model that takes into account all the variables that influence the measurement process. Resolution in power measurement is 1 mW. Performance tests under air currents and movement disturbances showed that the device maintains high accuracy; the deviation produced by these significant disturbances is less than 5%. Human subject tests, both at rest and during exercise, confirmed its ability to accurately measure localized skin heat flux, heat capacity, and thermal resistance (less than 5% uncertainty). These findings highlight the calorimeter's potential for applications in sports medicine and physiological studies.

Restoration of abnormal sleep EEG power in patients with insomnia disorder after 1Hz rTMS over left DLPFC.

Hyperarousal has been a significant pathophysiological theory related to insomnia disorder (ID), characterized by excessive cortical activation and abnormal electroencephalogram (EEG) power during daytime or sleep. However, there is currently insufficient attention to the EEG power during rapid eye movement (REM) sleep and different stages of non-rapid eye movement (NREM) sleep. Additionally, whether the abnormal sleep EEG power in ID patients can be restored by repetitive transcranial magnetic stimulation (rTMS) remains unclear. Data of 26 ID patients and 26 healthy controls (HCs) were included in the current observational study. The comparisons of relative power between patients and HCs at baseline in each band of each sleep stage and the changes in patients before and after rTMS treatment were performed. The correlations between relative power and behavioral measures of the patients were also investigated. Abnormalities in sleep EEG relative power in the delta, beta and gamma bands of the patients were observed in NREM2, NREM3 and REM sleep. Correlations were identified between relative power and behavioral measures in ID group, primarily encompassing sleep efficiency, sleep onset latency and depression scores. Post-treatment improvements in relative power of the delta and beta band were observed in NREM2 sleep. The relative power of sleep EEG exhibited a significant correlation with sleep measures in ID patients, and demonstrated notable differences from HCs across the delta, beta, and gamma frequency bands. Furthermore, our findings suggest that rTMS treatment may partially ameliorate relative power abnormalities in patients with ID.

On generating functions to compute some power measures for weighted majority games

AbstractIn this paper we introduce new procedures, based on generating functions, for calculating some power measures for weighted majority games. In particular, we present methods for computing the Johnston index and the Colomer–Martínez measure. Besides, we introduce a new power measure that combines the principles underlying the Johnston index and Colomer–Martínez measure as well as a procedure for computing it using generating functions. Finally, we introduce the new R package and describe its capabilities to compute some power measures by means of generating functions. We illustrate its performance with a real example.

Traceable characterisation of fibre-coupled single-photon detectors

Abstract The detection of single photons plays an essential role in advancing single-photon science and technologies. Yet, within the visible/near-infrared spectral region, accurate fibre-based optical power measurements at the few-photon level are not yet well-established. In this study, we report on a fibre-based setup, enabling traceable optical power measurements at the few-photon level in this spectral region. The setup was used to calibrate the detection efficiency (DE) of four single-photon avalanche diode (SPAD) detectors. The relative standard uncertainties on the mean DE values obtained from repeat fibre-to-detector couplings ranged from 0.67% to 0.81% (k = 2). However, the relative standard deviation of DE values, which ranged from 1.38% to 3.20% (k = 2), poses a challenge for the metrology of these devices and applications that require high accuracy and repeatability. We investigated the source of these variations by spatially mapping the response of a detector’s fibre connector port, using a focused free-space beam, allowing us to estimate the detector’s spatial non-uniformity. In addition, we realise a novel calibration approach for fibre-coupled SPADs in a free-space configuration, enabling a direct comparison between the fibre-based setup and the National Physical Laboratory’s established free-space facility using a single SPAD. Finally, we investigated alternative coupling methods, testing the repeatability of different fibre-to-fibre connectors in addition to direct fibre-to-detector couplings: SPADs from three manufacturers were tested, with both single-mode and multi-mode fibre.

Testing Algorithms for Controlling the Distributed Power Supply System of a Railway Signal Box

Trends in the use of renewable energy sources to power buildings do not bypass objects for which maintaining a power supply is critical. This also applies to railway signal boxes. The aim of the research work was to test the multisource power supply system for a railway signal box with power electronic converter systems and a DC bus, built as part of the research project. The assumption for powering the railway signal box building was to use renewable sources, energy storage devices, and a 3 kV DC traction network as the second required power supply grid. Both power grids were connected by power electronic converters, and the power values of the converters were set based on the calculated power balance values using the values measured at the system nodes and the set constraints. The tests primarily tested the response of the power supply system to changes in load power and power generated by the photovoltaic source, as well as the charge level of the energy storage devices. The correctness of the control algorithm’s operation was assessed based on the recorded power values in the power supply system nodes. The tests were carried out for 60 scenarios that covered all normal and emergency operating conditions. During the tests, delays in response to changes in the power supplied to the converters and the values of circular power flow between the power grid connections were recorded. The recorded delays ranged from 2 to about 50 s and the circular power flows did not exceed 1500 W. Based on the results of the tests, it was found necessary to improve the power measurement system in the power supply system nodes and to improve the quality of communication and the transmission time of measurement data transmission time.

UNCERTAINTY EVALUATION USING LAW OF PROPAGATION AND MONTE CARLO SIMULATION METHODS WITH THE AUTORFPOWER MEASUREMENT SOFTWARE

RF power measurement is essential in RF and microwave metrology. For reliable and accurate power measurement, automatic measurement is preferred. A software application in C#, named AutoRFPower, was developed for automatic RF power measurement and uncertainty calculations at this study. According to the GUM document, this application is enhanced for uncertainty calculations by utilizing the Law of Propagation method and the Monte Carlo Simulation method. Trial measurements were performed at different RF power levels and frequencies between 50 MHz and 18 GHz using the AutoRFPower software. Law of Propagation and Monte Carlo Simulation uncertainty calculations were carried out by AutoRFPower based on the trial measurements and by the Oracle Crystal Ball simulation application. All measurements and their uncertainty calculations were compared with each other, and this study validated the uncertainty calculation of AutoRFPower. In addition, it was observed that in the Monte Carlo Simulation, uncertainty calculation results were non-symmetrical normal distribution, contrary to the assumption of symmetrical normal distribution according to the Low of Propagation method. Moreover, it has been observed that the statistical distribution of uncertainty changes depending on the dominant component of the parameters in the model function used for the uncertainty calculation with the Monte Carlo Simulation method.

Wire-to-two-drop plasma thruster: Experimental and numerical investigation of electroaerodynamic jet flow for micro aerial vehicle propulsion

Conventional micro aerial vehicles (MAVs) have primarily relied on complex, flapping-wing mechanisms for propulsion, often exhibiting limitations in terms of reliability and efficiency. To overcome these challenges, this study explores the potential of electroaerodynamic (EAD) thrusters as a novel propulsion system. By accelerating air molecules through ion collisions, EAD jet flow generates thrust, offering advantages such as noiseless operation and zero emissions due to its moving-part-free design. This research presents a comprehensive experimental and numerical investigation of a wire-to-two-drop thruster configuration to elucidate its electromechanical performance, plasma flow dynamics, and EAD jet characteristics. Experimental measurements of key parameters, including current, thrust, power, and effectiveness, were correlated with numerical simulations, demonstrating excellent agreement with a maximum error below 5%. These findings align strongly with established theoretical frameworks, revealing an inverse square root relationship between effectiveness and thrust. To optimize thruster performance, optimal operating voltages were identified at approximately 8.2, 9.4, and 11.6 kV for inter-electrode gap distances of 10, 15, and 20 mm, respectively, achieving a balanced trade-off between thrust and effectiveness. Detailed numerical visualizations of the plasma flow field, including velocity distribution, jet morphology, potential distribution, and electric field lines, provided valuable insights into the thruster's operation. Building upon these insights, a proof-of-concept EAD flier was constructed and tested, incorporating a serrated emitter electrode and lightweight materials. This flier achieved a mass of 0.5 g and generated a thrust of 0.77 g at 15 kV, resulting in a thrust-to-weight ratio of 1.54 and successful liftoff. This demonstration highlights the potential of EAD propulsion for practical MAV applications.

A hybrid fuzzy logic-based MPPT algorithm for PMSG-based variable speed wind energy conversion system on a smart grid

Recently, wind power has gained popularity as a sustainable energy source. Wind energy conversion systems (WECSs) can accept fixed speed and variable speed (VS) operations. VS-WECSs are preferable to conventional WECSs because of their higher electricity collection capacity. Maximum power point tracking systems (MPPTs) are essential for maximizing the efficiency of wind energy generation in wind turbine installations linked to power grids. This study introduces a hybrid fuzzy logic controller-based MPPT (FLC-MPPT) for wind turbines (WTs) connected to permanent magnet synchronous generators (PMSGs) to accurately determine the maximum power output of WTs. This study employs a three-phase back-to-back converter to link a PMSG to a utility grid. The reference signals for pulse width modulation controllers comprise two-phase system currents. It constructs a converter that can transfer electrical energy in both directions using insulated-gate bipolar transistor technology and is powered by a battery. The machine-side converter uses model predictive control for the present control loop. Given the generator's susceptibility to changes in wind conditions, this factor is of the utmost importance. A WT simulation was conducted using MATLAB/Simulink and an FLC methodology was employed. The model used a PMSG. Measurements of rotor speed, power, induced voltage, and current were taken in relation to variations in wind speed. The simulation results show that the FLC-MPPT can maximize the output power over a wide range of wind speeds with a higher efficiency of 92.6% and performance of 95.7%.

Evaluation of Measurement Uncertainty Using the Monte Carlo Method in Steady-State Power Measurement of Household Refrigerator Based on IEC 62552:2015

Evaluation of Measurement Uncertainty Using the Monte Carlo Method in Steady-State Power Measurement of Household Refrigerator Based on IEC 62552:2015

Intelligent Reflecting Surfaces for Visible Light Positioning Based on Received Power Measurements

Intelligent Reflecting Surfaces for Visible Light Positioning Based on Received Power Measurements

Spatiotemporal landscape pattern changes and their effects on land surface temperature in greenbelt with semi-arid climate: A case study of the Erbil City, Iraq

Urban expansion of cities has caused changes in land use and land cover (LULC) in addition to transformations in the spatial characteristics of landscape structure. These alterations have generated heat islands and rise of land surface temperature (LST), which consequently have caused a variety of environmental issues and threated the sustainable development of urban areas. Greenbelts are employed as an urban planning containment policy to regulate urban expansion, safeguard natural open spaces, and serve adaptation and mitigation functions. And they are regarded as a powerful measure for enhancing urban environmental sustainability. Despite the fact that, the relation between landscape structure change and variation of LST has been examined thoroughly in many studies, but there is a limitation concerning this relation in semi-arid climate and in greenbelts as well, with the lacking of comprehensive research combing both aspects. Accordingly, this study investigated the spatiotemporal changes of landscape pattern of LULC and their relationship with variation of LST within an inner greenbelt in the semi-arid Erbil City of northern Iraq. The study utilized remote sensing data to retrieve LST, classified LULC, and calculated landscape metrics for analyzing spatial changes during the study period. The results indicated that both composition and configuration of LULC had an impact on the variation of LST in the study area. The Pearson’s correlation showed the significant effect of Vegetation 1 type (VH), cultivated land (CU), and bare soil (BS) on LST, as increase of LST was related to the decrease of VH and the increases of CU and BS, while, neither Vegetation 2 type (VL) nor built-up (BU) had any effects. Additionally, the spatial distribution of LULC also exhibited significant effects on LST, as LST was strongly correlated with landscape indices for VH, CU, and BS. However, for BU, only aggregation index metric affected LST, while none of VL metrics had a relation. The study provides insights for landscape planners and policymakers to not only develop more green spaces in greenbelt but also optimize the spatial landscape patterns to reduce the influence of LST on the urban environment, and further promote sustainable development and enhance well-being in the cities with semi-arid climate.

The data recovery strategy on machine learning against false data injection attacks in power cyber physical systems

During the transmission of power measurement data through communication networks from remote terminal unit (RTU) to the state estimator in Supervisory Control and Data Acquisition (SCADA), power cyber-physical systems (PCPSs) are more susceptible to cyber-attacks. To mitigate that threat, this paper is concerned with a new data recovery strategy on machine learning against false data injection attacks (FDIAs) in PCPSs. Firstly, in view of the limited resources (such as limited energy) of adversaries and system protections, a sparse target false data injection attack (FDIA) is constructed. Then, the FDIA detection problem is transformed into a tripartite separation problem, and the alternating direction method of multipliers on proximal exchange (ADMM-PE) is adopted to complete the intrusion detection of FDIAs. In addition, with the help of reliable mask information and real incomplete measurement data provided by the FDIA detection, a similar supervised generative adversarial imputation networks (GAIN) is proposed to complete the measurement data recovery after FDIAs. Specifically, the pseudo labels generated by data analysis methods such as k-means clustering and support vector machine (SVM) to improve the accuracy of measurement data recovery. Finally, the experimental results of PCPSs show the effectiveness and superiority of the proposed data recovery strategy against FDIAs.

Goodness-of-fit tests based on Kullback-Leibler divergence for bladder cancer survival analysis: Applications to exponentiated exponential distribution

Bladder cancer is among the ten most common types of cancer worldwide, with approximately 550,000 new cases occurring each year. It accounts for comprehensively compared to 3% of all newly diagnosed cancer cases and contributes to 2.1% of cancer-related deaths globally. This article introduces goodness-of-fit tests that aim to fit the exponentialized exponential distribution. These tests are based on the Kullback-Leibler difference and have been applied to censored and complete samples of Bladder Cancer Patients. We calculated critical values and statistical power measurements, considering the best and worst bandwidth scenarios. We then comprehensively compared essential values and power across various parameters, accounting for optimal and suboptimal bandwidth choices derived from the Kullback–Leibler difference. In the final phase of our study, we used a dataset of individuals diagnosed with bladder cancer to demonstrate the practical applicability of our proposed research. Finally, this modeling type can benefit researchers and healthcare professionals through time-to-event analysis (survival analysis), investigation of events, medical decision-making, and risk prediction.

Uncertainty Calculation as a Service: Integrating Cloud-Based Microservices for Enhanced Calibration and DCC Generation.

The calibration industry is renowned for its diverse and sophisticated equipment and complex processes, which necessitate innovative solutions to keep pace with rapidly advancing technology. This paper introduces an enhancement to an existing microservice-based cloud architecture, aimed at effectively managing the inherent complexity within this field. The enhanced architecture seamlessly integrates various equipment types and communication technologies, aligning diverse stakeholder expectations into a unified system that ensures efficient and accurate calibration processes. It highlights the integration of microservices to facilitate various methods of uncertainty calculation and the generation of digital calibration certificates (DCCs). A case study on RF power measurement illustrates the practical application and benefits of the enhanced architecture. Although initially focused on RF power measurement, the flexible architecture allows for future expansions to accommodate new standards and measurement techniques. The enhanced system offers a comprehensive approach to managing data flow from calibration equipment to the final generation of DCCs, utilizing cloud-based services for efficient data processing. As a future direction, this extension sets the groundwork for broader applicability across multiple measurement types, ensuring readiness for upcoming advancements in metrology.

A comparative study between the two vertical jump tests of stability and the platform jumping device in measuring the explosive power of the two legs in female volleyball players

The research aims to: - To identify the differences between the two tests of the vertical jump of stability and the platform of the jumping platform in measuring the explosive power of the two legs of the female volleyball players. - Identifying the relationship between the two vertical jump tests of stability and the platform jumping device in measuring the explosive power of the two legs in female volleyball players. As for the research hypothesis:- -There are statistically significant differences between the standing vertical jump tests and the jumping platform device in measuring the explosive power of the legs in female volleyball players. - There is a significant correlation between the two standing vertical jump tests and the jumping platform device in measuring the explosive strength of the legs in female volleyball players. The research community was determined by the intentional method of the players of the first degree of volleyball in the Kurdistan Region / Iraq.The research sample was determined by the random method from the research community, which consisted of players from these clubs (Hajiaoa, Rania, and Tactac,koya University Team) which in total were 37 players, One female player was excluded from the Hajiao Club due to not attending the test day, and (6) female players from the Koya University team were excluded because of their participation in the reconnaissance experiment. Thus, the size of the final sample reached 30 players out of 30 players, with a rate of 81.01%. The researchers used the descriptive approach in a comparative study method. And the correlations, and after obtaining the results, they were discussed in a scientific manner supported by the sources to achieve the research goals. In light of the research results, the researchers reached the following Conclusions: - There is a correlation between the springboard mat test and the standing vertical jump test in their measurement of the explosive strength of the legs in female volleyball players. - There are differences between the springboard mat test and the vertical stability jump test in their measurement of the explosive power of the legs in female volleyball players, and in favor of the springboard mat test.