Power Measurements Research Articles

Security with Wireless Sensor Networks in Smart Grids: A Review

Smart Grids are an area where next-generation technologies, applications, architectures, and approaches are utilized. These grids involve equipping and managing electrical systems with information and communication technologies. Equipping and managing electrical systems with information and communication technologies, developing data-driven solutions, and integrating them with Internet of Things (IoT) applications are among the significant applications of Smart Grids. As dynamic systems, Smart Grids embody symmetrical principles in their utilization of next-generation technologies and approaches. The symmetrical integration of Wireless Sensor Networks (WSNs) and energy harvesting techniques not only enhances the resilience and reliability of Smart Grids but also ensures a balanced and harmonized energy management system. WSNs carry the potential to enhance various aspects of Smart Grids by offering energy efficiency, reliability, and cost-effective solutions. These networks find applications in various domains including power generation, distribution, monitoring, control management, measurement, demand response, pricing, fault detection, and power automation. Smart Grids hold a position among critical infrastructures, and without ensuring their cybersecurity, they can result in national security vulnerabilities, disruption of public order, loss of life, or significant economic damage. Therefore, developing security approaches against cyberattacks in Smart Grids is of paramount importance. This study examines the literature on “Cybersecurity with WSN in Smart Grids,” presenting a systematic review of applications, challenges, and standards. Our goal is to demonstrate how we can enhance cybersecurity in Smart Grids with research collected from various sources. In line with this goal, recommendations for future research in this field are provided, taking into account symmetrical principles.

Iron wool as a heating agent for magnetic catalysis: Experiments and analysis of heating properties under a high-frequency magnetic field

Magnetically induced heterogeneous catalysis has been attracting attention due to its high energy efficiency and flexibility for dynamic reactor control. Iron wool is a commercial, low-cost, and versatile heating agent, which has been used in several magnetic catalysis studies, but its heating properties have never been investigated. Here, the properties of three types of Fe wool were studied using optical and electronic microscopy, x-ray diffraction, and measurements of both heating power and high-frequency hysteresis loops. The effects of strand width, packing, and magnetic field amplitude and frequency were studied. A maximum specific absorption rate (SAR) around 700 W/g under a rms field of 47.4 mT at 93 kHz was measured for the larger width Fe wool. High-frequency hysteresis loops were used to quantify the contribution of hysteresis losses and eddy currents to total heating. Eddy currents contribute 65%–90% to the global heating depending on the strand width. Coating the wool with SiO2 and Ni has negative effects on the SAR but none on hysteresis losses. It is interpreted as originating from the cut-off of inter-wire eddy currents due to the insulating (SiO2, oxidized Ni) nature of the coating. Last, it was found that adding more Fe wool in a given volume mostly decreases the SAR. This effect could be not only due to the absorption and/or screening of the field by surface strands but also due to magnetic interactions. The results described in this work give insights into the magnetic heating of microscale magnetic materials and optimize their use for heterogeneous catalysis.

Empowering energy conservation: A prototype of household energy consumption monitoring based on Internet of Things

Abstract One of the obstacles to control household energy consumption is unavailability electricity instruments/tools to monitor electricity energy consumed by appliances causing a lack of awareness of household energy saving. Energy meter installed on buildings only show electricity consumption in total. This study aims to design and create a prototype system that can monitor and control the electrical appliances usage utilizing the Internet of Things (IoT)-based electronic devices where electricity usage data is stored in Firebase real-time database. The methods carried out are arranged in several stages, starting from data collection, design, configuration, and implementation. The tools used in this research will utilize the ESP8266 as the microcontroller, the PZEM-004T as current sensor and the Blynk as the web server. The tool will send current voltage (Volt (V)) and capacity (Watt (W)) data and then converted to energy and also the costs incurred from electricity usage based on the basic electricity tariff of National Electricity Company (PLN) and the results can be seen directly through IoT (i.e. smartphone, PC, laptop). The accuracy of power measurement by the system is 97.4% compared to measurement used by watt-checker. The results of this study show that an electrical power monitoring system makes people easier to monitor electrical power consumption by appliances used. The pilot measurement shows that a unit system can monitor electricity usage for four units of electronic equipment i.e. water pump, Television, fridge, electrical iron, rice cooker, etc. precisely and succeeded to control and increase energy saving awareness to reduce electricity consumption at the end.

A Comparative Study on Picoammeter Designs as Alternatives for Nuclear Reactor Power Measurement Systems

Abstract The study investigates the picoammeter, a highly sensitive current measurement device capable of measuring currents in the picoampere (pA) range. It discusses the typical amplification technique in picoammeters, utilizing an Op-Amp in a trans-impedance amplifier (TIA) circuit to convert the current into a voltage signal. The paper explores the impact of different IC Op-Amps on the picoammeter’s performance, evaluating AD549, MAX4230, LMC662, TLV272, and MCP6001. The result reveals that AD549 Op-Amp ICs are more suitable for picoammeter design due to their low noise performance and low input bias current. Noise output and AC stability are assessed through numerical analysis and simulations using a circuit simulator. The resulting picoammeter exhibits low noise, high sensitivity, and precise measurement accuracy, making it an optimal choice for precise low-current measurements in CIC detectors.

Measurements of Low Optical Power with Cryostat-Based Predictable Quantum Efficient Detector at Liquid Nitrogen Temperature

Abstract We have validated optical power measurements with a Predictable Quantum Efficient Detector (PQED) at liquid nitrogen temperature (77 K) at low optical power from 130 fW to 3.3 pW. Two laser wavelengths at 514 nm and 785 nm were used. The lowest measured optical power corresponds to a photon flux of 0.5·106 photons per second (785 nm). The PQED’s responsivity is linear within the relative measurement uncertainties of 8% at 0.5·106 ph/s and 1.4% at 10·106 ph/s (95% confidence level), which enables the calibration of other low photon flux detectors directly against a primary standard of optical power.

Current Progress of EUV Spectral Responsivity Calibration for EUV Lithography at CMS/ITRI

Abstract To support the development of advanced EUV lithography for the semiconductor industry in Taiwan, a calibration system for photodiodes’ spectral responsivity was established. The current system utilizes the synchrotron radiation light source and the method is traceable to PTB, Germany. The wavelength range is from 10 nm to 15 nm, including the most often used 13.5 nm. Several techniques were studied to compensate for light source fluctuation and to reduce the measurement uncertainty. The relative expanded uncertainty of the spectral responsivity calibration at 13.5 nm is 4.6 % (k=2). A wafer-type EUV radiant power meter designed to be used in EUV lithography chambers is being developed. Our goal is to develop simple and reliable methods for on-site EUV optical power measurement and dose estimation.

Geopolitical Aspects of Demographic Processes: Development of Scientific Ideas of L. L. Rybakovsky

Demographic processes play a key role in the formation of the geopolitical picture of the world. Population size, its age structure, growth rates and migration flows have a significant impact on the economic power of states, their military potential and their ability to project power in the international arena. This article examines contemporary and historical views on the significance of demographic factors in the geopolitical competition of countries and the measurement of a state's national power. The study covers both contemporary and historical aspects of the issue. The paper provides a systematic review of the evolution of scientific views on the significance of demographic factors in the geopolitical context. Particular attention is paid to modern methodological approaches to measuring the national power of a state considering demographic indicators. The article offers a critical analysis of existing models for assessing geopolitical influence based on demographic factors and considers their applicability in the context of global demographic transformations. The study also addresses topical issues of the impact of demographic trends on the geopolitical strategies of states in the 21st century, including the problems of population aging, migration processes and demographic imbalances between developed and developing countries. Special attention is paid to the analysis of geopolitical aspects of demographic processes in the works of the outstanding Russian demographer L.L.Rybakovsky. The paper considers the key concepts of the scientist, including demographic security, the geopolitical significance of migration processes, the relationship between demography and spatial development of Russia, as well as the role of demographic policy as an instrument of geopolitical influence.

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%.