Custom Power Research Articles

Creating a Quasi-Resonant Induction Cooktop Integrating Zero-Voltage Switching (ZVS) and Load Management

This study aims to elucidate the development and construction of a durable induction cooktop, with key considerations including efficiency, power customization, and safety features. The intricate processes involved in crafting a 3.5 kW induction burner are thoroughly examined, encompassing simulations for quasi-resonant inverters, the meticulous selection of induction coils and capacitors, the implementation of practical Analog-to-Digital Converter (ADC) filtration, pulse width modulation (PWM) driving techniques, and the integration of protection mechanisms. Leveraging an ARM-based microcontroller enabled the attainment of diverse objectives such as Zero-Voltage Switching (ZVS), safeguarding IGBTs, facilitating user interaction through a user-friendly interface, and enabling load detection capabilities. Furthermore, the capability to gauge and adjust output power based on user preferences was incorporated. Subsequently, rigorous testing was conducted to evaluate the functionality and applicability of the device in real-world scenarios.

Performance Evaluation of Solar PV Integrated with Custom Power Device under Various Load Conditions

The non-linear properties and rapid switching of power electronic equipment are the primary causes of power quality issues in power systems, particularly in the power distribution systems. The widespread use of delicate equipment, which continuously pollutes the environment, is making power quality problems worse. The increasing integration of renewable energy sources into the generation mix and the decarburization of the economy have created new challenges for smart grid technology, requiring creative solutions such as energy storage systems and smart transformers. This article describes a solar photovoltaic integrated unified power quality conditioner (UPQC) that uses a deep learning method based on neural networks and a novel compensating technique. Here, two Deep Neural Network algorithms are used, one in the solar PV system to obtain the maximum power under various irradiance situations, and the other to manage the UPQC under various load conditions. When compared to the conventional UPQC based on PQ Theory, DNN-UPQC produces superior results in terms of reducing total harmonic distortion. This iterative strategy, which is focused on soft computing, provides faster convergence to the target condition while maintaining the updating weight within a predetermined limit. PV-based UPQC has been connected individually to reduce voltage sag, swell, and unbalance in variable load conditions. The system's dynamic and steady state performance are assessed by modelling it with a MATLAB-Simulink in different load condition.

Power consumption state evaluation of important power customers based on AHP‐TOPSIS algorithm

AbstractIn the construction of a new power system, the identification and evaluation of power consumption status of power customers will become an important basis for them to participate in the emerging businesses such as demand response and virtual power plants. In order to ensure the power safety of important power customers, a new evaluation of power consumption status of important power customers based on the AHP (analytic hierarchy process)‐TOPSIS (technique for order preference by similarity to an ideal solution) algorithm is proposed by fully mining and applying the power big data. Firstly, a power consumption big data analysis platform based on the Hadoop architecture is built to provide a high‐performance platform support for big data analysis. Secondly, nine evaluation indexes are constructed from the three dimensions of voltage, load and synthesis, which objectively and scientifically describes the power consumption status of important power customers. Finally, the AHP‐TOPSIS algorithm is used to evaluate and analyse the voltage, load and comprehensive indicators respectively, thus, obtaining the evaluation values of three kinds of indicators. The power consumption status scores of important power customers are determined by the variable weight weighted summation. The rationality and feasibility of the method and algorithm are proved by example analysis and field verification. This method helps to promote the transformation from post fault emergency repair to warning beforehand. It has the multiple effects of ensuring safe power consumption, supporting accurate patrolling and active emergency repair serving.

Investment Research of China Medical Device Industry under the Concept of Corporate Finance — Take Yuyue Medical Co., Ltd. as Example

With the optimization of China’s healthcare policy, the rise of the aging population, the increasing health awareness of society, and the impact of the global epidemic, China’s medical device industry has become a key market for investors. However, compared with the mature and well-funded medical device companies in overseas developed countries, China’s local medical device companies have apparent disadvantages and jumping battles. Yuyue Medical Co., Ltd. is a prominent player in the medical device industry in China, having sustained a significant profit margin over an extended period. Its profitability has changed over the post-epidemic period, in any case. Given Yuyue Medical Co., Ltd.’s exceptional standing in the medical equipment sector, an analysis of the company as an industry investment case makes sense. Based on Yuyue Medical Co., Ltd. as the industry investment benchmark, the study analyses the industry’s competitive development situation, financial performance, and impact on the external environment by adopting Porter’s Five Forces, ratio analysis, and PESTEL. The study found that China’s medical device industry has growth potential due to the low bargaining power of customers and suppliers, high technological barriers, and low threat of substitution by new entrants. Yuyue Medical Co., Ltd. has healthy financial performance and several advantages from the external environment, so Yuyue Medical Co., Ltd. is worthy of investment.

English

English

Evaluating conventional and renewable energy systems for green buildings: A case study on energy efficiency and cost optimization

This study explores two primary categories of power generation: conventional methods reliant on fossil fuels and renewable energy methods. Fossil fuel-based approaches, including natural gas and heavy fuel oil, contribute to environmental concerns due to their carbon dioxide (CO2) emissions, which are responsible for the greenhouse effect and global warming. Many nations, particularly in Europe, have implemented stringent measures to restrict CO2 emissions, imposing fines on industries that exceed emission limits. In response to these concerns, this study focuses on a green building project that aims to meet its power requirements through renewable energy sources. Various renewable energy resources will be evaluated, considering the merits and drawbacks of each technology, to identify the most suitable option for the building under investigation. Additionally, a comprehensive thermodynamic analysis will be conducted, including calculations of electrical needs such as cooling load, lighting load, and equipment load. A customized power calculator will also be developed for application in similar projects. The ultimate objective of this study is to achieve complete autonomy from the electric grid by utilizing renewable energy resources, transforming the building into a green building. The results indicate that at an outside temperature of 22 °C, the total heat gain decreases from 157.3 to 39 kW, reducing the total cost of electricity from 20,000 to 5100 AED/year. Conversely, at an outside temperature of 50 °C, the total heat gain increases from 157.3 to 196 kW, raising the total cost of electricity from 20,000 to 26,000 AED/year. These findings demonstrate the significant influence of outside temperature on the building's energy requirements and costs, underscoring the importance of considering temperature variations in energy efficiency and cost optimization strategies.

Design and Testing of a Multi-Cylinder Piezopump for Hydraulic Actuation

Hydraulic actuation systems are widely used in industries such as aerospace, the marine industry, off-highway vehicles, and manufacturing. There has been a shift from the hydraulic distribution of power from a centralized supply to electrical power distribution, to reduce the maintenance requirements and weight and improve the efficiency. However, hydraulic actuators have many advantages, such as power density, durability, and controllability, so the ability to convert electrical to hydraulic power locally to drive an actuator is important. Traditional hydraulic pumps are inefficient and unsuitable for low-power applications, making piezopumps a promising alternative for the conversion of electrical to hydraulic power in the sub-100 W range. Currently, the use of piezopumps is limited by their maximum power (typically a few watts or less) and low flows. This paper details the design, simulation, and testing of a multi-cylinder piezopump designed to push the envelope of the power output. The simulation results demonstrate that pumps with two or three cylinders show increasing benefits in terms of hydraulic and electrical performance due to the reduced flow and current ripple compared to a single-cylinder pump. The experimental results from a two-cylinder pump confirm this, and the effect of the phase relationship between the drive signals is investigated in detail. The experimental pump has fast-acting disc-style reed non-return valves, allowing piezostack drive frequencies of up to 1.4 kHz to be used. Custom power electronics tailored to the pump are developed. These features are critical in demonstrating the potential for multi-cylinder piezopumps to play an important role as a future actuation solution.

Shoprite Holdings LtdCase Study: Challenges for Expansion in Africa

This study investigates the obstacles faced by the African expansion efforts of Shoprite Holdings Ltd., a South African retailer. Shoprite pursued mergers and acquisitions within its native country but established wholly owned subsidiaries as its preferred entry route for expanding into other African states. As a result, Shoprite significantly increased its operations by expanding to 16 nations by 2020. However, Shoprite currently focuses its operation in ten countries, exclusively in southern African countries and its home country. This study seeks to comprehend the reasons behind Shoprite's rapid withdrawal from multiple African countries and shed insight into the challenges of conducting business in Africa's demanding business climate. The analysis revealed a combination of economic variables, such as reduced purchasing power of customers, currency volatility, increased operational costs, and the economic shocks caused by the COVID-19 outbreak. Additionally, high customer preference for informal markets and social factors were also identified. The findings indicate that Shoprite should prioritize strategic location selection, adopt a lower entry mode, and consider the potential for developing e-commerce as feasible measures. The report proposes that African retail businesses should comprehend the intricacies of the African market and employ strategies for international expansion, entrance techniques, and the significance of adjusting operations to local conditions and regulatory environments. These discussions offer insights to organizations considering international expansion, seeking to mitigate risks, and aiming to optimize their market entry strategy in various locations, specifically Africa.

Design and Control of DVR Based on Adaptive Bateman Polynomial for Power Quality Improvement

ABSTRACTPower quality issues encompass a spectrum of disturbances that affect the stability and reliability of the power supply. This study explores voltage‐related anomalies, including sags, surges, flickers, unbalances, harmonics, interruptions, and swells, examining their origins, characteristics, and repercussions. These issues arise from a myriad of sources, such as load fluctuations, equipment malfunctions, and grid dynamics. The ramifications of these disturbances extend to equipment malfunctions, reduced operational efficiency, and financial losses. Dynamic voltage restorer (DVRs) are series custom power devices for mitigating these voltage‐related anomalies and use real‐time monitoring and control to quickly inject exact voltages into the grid during disruptions, restoring voltage levels to acceptable levels. This study demonstrates the capacity of DVRs to successfully alleviate power quality concerns, hence improving equipment dependability and system stability by analyzing case studies and simulation findings. The control system used to supply switching signals to the voltage source converter (VSC) of the DVR is based on adaptive Bateman polynomial (ABMP). Traditional DVR control techniques often rely on fixed or linear control strategies, which may not adequately handle varying load conditions and disturbances. ABMP offers an adaptive approach where the control parameters can adjust dynamically based on real‐time system conditions. This adaptive capability enhances the accuracy of voltage restoration, ensuring that the DVR responds optimally to varying loads and disturbances. During voltage sag and swell conditions at the grid side, the VSC injects the compensating voltage in series with the feeder with a constant switching frequency. A battery energy‐supported system (BESS) based DVR is considered for the proposed system. The supply is connected to the critical and sensitive loads. The proposed control scheme is validated through extensive simulation and experimental results.

Behavioral analysis of electricity consumption characteristics for customer groups using the k-means algorithm

In the fierce competition of the electricity market, how to consolidate and develop customers is particularly important. Aiming to analyze the electricity consumption characteristics of customer groups, this paper used a k-means algorithm and optimized it. The number of clusters was determined by the Davies-Bouldin index (DBI). An improved Harris Hawks optimization (IHHO) algorithm was designed to realize the initial cluster center selection. Based on data such as electricity purchase and average electricity price, electricity customer groups were clustered using the IHHO-k-means algorithm. The IHHO-k-means algorithm achieved the best clustering effect on Iris, Wine, and Glass datasets compared with the traditional k-means and PSO-k-means algorithms. Taking Iris as an example, the optimal value of the IHHO-k-means algorithm was 96.538, with an accuracy rate of 0.932, precision and recall rates of 0.941 and 0.793, respectively, an F-measure of 0.861, and an area under the curve (AUC) value of 0.851. In the customer dataset, the number of clusters determined by DBI was 4. The power customers were divided into four groups with different characteristics of electricity consumption, and their electricity consumption behaviors were analyzed. The results prove the reliability of the IHHO-k-means algorithm in analyzing electricity consumption characteristics of customer groups, and it can be applied in practice.

A dynamic reference voltage adjustment strategy for Open-UPQC to increase hosting capacity of electrical distribution networks

Future electrical grids, particularly the distribution networks, may face more severe voltage rises/drops, and in general, more power quality problems in the presence of new loads such as electric vehicle chargers and renewable energy generation units like photovoltaic systems. This necessitates investing in additional high-cost infrastructure to increase the capability of the feeder in hosting higher levels of loads and generation units while the existing capacity is not utilized effectively. In the stated condition, effective voltage stabilization strategies in electrical distribution networks can contribute to hosting capacity improvement and the better utilization of the existing infrastructure. Accordingly, in this paper, the application of Open-UPQC in voltage profile improvement and hosting capacity enhancement is evaluated in low-voltage distribution networks. Furthermore, a dynamic reference voltage adjustment strategy is applied to the device to improve its capabilities in power quality improvement and hosting capacity enhancement. Simulation studies have been implemented to evaluate the capability of Open-UPQC either with static reference voltage or the dynamically-adjusted one in low-voltage networks with real measured data while different cases are assessed regarding the topology and the length of the feeder. The simulation results approved the capability of Open-UPQC especially with the dynamic reference voltage in hosting capacity enhancement while providing the highest level of voltage profile improvement among all the assessed custom power devices in the studied low-voltage networks.

Penny Wise and Pound Foolish: Does Striving to Meet Earnings Expectations by Manipulating Real Activities Trigger Product Recalls?

We examine whether managers’ activities in striving to reach earnings targets through real earnings manipulation affect their firms’ product recalls. Our evidence implies that firms suspected of manipulating real activities in trying to meet earnings benchmarks exhibit a higher likelihood and frequency of product recalls. In cross-sectional results consistent with expectations, we find that the impact of exploiting real activities to attain earnings benchmarks on product recalls intensifies for firms whose managers have stronger incentives to manage earnings and subsides for firms subject to greater customer power and firms with more growth opportunities. Additional analysis shows that lowering product quality to meet or beat earnings expectations undermines firms’ future performance. This paper was accepted by Ranjani Krishnan, accounting. Funding: Y. Chen acknowledges the General Research Fund of the Research Grants Council of Hong Kong [Project 15504219] for financial support. L. Ma acknowledges financial support from the Ministry of Education Project of Humanities and Social Sciences [Project 22YJC630099] and the Young Scholars Grant Program of the University of International Business and Economics [Project 20YQ06]. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2021.04035 .

Design and testing of a high power piezo pump for hydraulic actuation

Traditional valve-controlled hydraulic cylinders are usually very inefficient due to power loss through the control valve. An efficient alternative architecture is to distribute power electrically rather than hydraulically to a group of cylinders and drive each cylinder via individual servomotor-driven pumps. This arrangement is called electrohydrostatic actuation. Such actuators are currently available for power ratings of several hundred watts or greater, but not in the sub-100 W range. This paper details the design, simulation and testing of a piezopump which is intended to address this gap. The motivation is for aerospace applications, and in particular accessory actuators used in the landing gear system. The 10–100 W range is a high-power output for a piezopump, and to achieve this a novel design using disc-style reed valves was developed to allow pumping frequencies above 1 kHz. These high frequencies necessitated the development of custom power electronics capable of delivering 950 V peak-peak sine wave excitation to a largely capacitive load. Experimental results show that the piezopump is capable of delivering over 30 W of hydraulic power, and at no-load can deliver up to 2 L/min of flow at 1250 Hz. Future development includes a transition to multi-cylinder pumps, and improved reed-valve modelling to improve the accuracy of simulated performance.

How to mitigate the negative effect of PDB on DIY preference

PurposeThis paper aims to explore the negative effect of power distance belief (PDB) on do-it-yourself (DIY) preference. It extends previous studies by delving into the underlying mechanism and identifying three theoretically driven moderators that could mitigate this negative effect.Design/methodology/approachThe paper uses secondary data at the country level and conducts three experiments involving participants from the USA and Germany.FindingsThe results suggest that the adverse impact of PDB on DIY preference exists through the underlying mechanism of attitude toward customer power. This negative effect can be mitigated when individuals with high PDB focus on status, find themselves in a position of low power or engage in activities within a private consumption setting.Practical implicationsFor DIY companies, this study offers crucial insights into the impact of cultural values on consumers’ DIY preferences. By customizing their marketing communications, companies can resonate with high PDB customers more effectively.Originality/valueThis research enhances DIY literature by introducing novel moderators within a theoretical framework, explaining why DIY preference might be low among individuals with high PDB and suggests ways to attenuate this effect.

Enhancing Day-Ahead Electricity Market Planning with a Novel Probabilistic Strategy for Wind Power and Uncertain Customers

Enhancing Day-Ahead Electricity Market Planning with a Novel Probabilistic Strategy for Wind Power and Uncertain Customers

Mitigation of Ethiopian industry sector power quality problems using ultra-capacitor based dynamic voltage restorer

Nowadays, power quality issues; specifically, voltage sag, swell, harmonics, and interruptions have become significant challenges for customers in Ethiopia. These problems can lead to equipment damage, production losses, reduced trust, and increased unsold energy for utility providers. To address these issues, the implementation of Flexible Alternating Current Transmission Systems (FACTS) and Custom Power Devices (CPD) is crucial. In this study, we focus on Desta Garment PLC, an Ethiopian garment industry. Due to faults in a nearby substation, the factory's feeder line frequently experiences voltage sag, swell, and interruptions. As a result, the factory faces partial shutdowns and occasional hours-long interruptions. To mitigate these voltage quality problems, we propose the use of an Ultra Capacitor-based Dynamic Voltage Restorer (DVR). The DVR has been carefully selected and implemented with advanced control strategy which is adaptive fuzzy proportional integral controller. We collected one year of data from the factory and conducted simulations using MATLAB, comparing scenarios with and without the DVR. The simulation results demonstrate that the proposed mitigation technique significantly enhances voltage sag and swell conditions. Importantly, the performance aligns with both IEEE 1250–1995 and IEEE 519–1992 standards. This study highlights the effectiveness of the Ultra Capacitor-based DVR in improving power quality and ensuring stable operations for Desta Garment PLC. By addressing voltage fluctuations, the factory can maintain productivity and minimize disruptions.

Covert-channels in FPGA-enabled SmartSSDs

Cloud computing providers today offer access to a variety of devices, which users can rent and access remotely in a shared setting. Among these devices are SmartSSDs, which are solid-state disks (SSD) augmented with an FPGA, enabling users to instantiate custom circuits within the FPGA, including potentially malicious circuits for power and temperature measurement. Normally, cloud users have no remote access to power and temperature data, but with SmartSSDs they could abuse the FPGA component to instantiate circuits to learn this information. Additionally, custom power waster circuits can be instantiated within the FPGA. This paper shows for the first time that by leveraging ring oscillator sensors and power wasters, numerous covert-channels in FPGA-enabled SmartSSDs could be used to transmit information. This work presents two channels in single-tenant setting (SmartSSD is used by one user at a time) and two channels in multi-tenant setting (FPGA and SSD inside SmartSSD is shared by different users). The presented covert channels can reach close to 100% accuracy. Meanwhile, bandwidth of the channels can be easily scaled by cloud users renting more SmartSSDs as the bandwidth of the covert channels is proportional to number of SmartSSD used.

PERLINDUNGAN HUKUM BAGI KONSUMEN PADA TRANSAKSI JUAL BELI HEWAN KURBAN MENURUT HUKUM ISLAM

This article aims to examine the legal protection for consumers in the sale and purchase of qurban animals provided by Kutaraja Aqiqah as a business actor to its customers (consumers) according to Islamic law. The research method used is qualitative research, namely solving problems by collecting, compiling, analysing, and interpreting the data that has been obtained. The phenomenon that occurs about consumer protection in Kutaraja Aqiqah demands descriptive analysis and answers. This can be fulfilled by describing the conditions and situations, as well as answers related to the problems in the phenomenon. The results of this study conclude that first, the mechanism of buying and selling transactions in kutaraja aqiqah follows the teachings of Islamic law, several types of livestock buying and selling transactions in kutaraja aqiqah such as cash, salam contracts, down payments, and qurban arisan. Second, the form of protection provided by kutaraja aqiqah according to Islamic law is in accordance with sharia which is also beneficial for business actors in attracting the attention and interest of purchasing power of customers

Research on Power Equipment Fault Diagnosis Based on Improved SVM Algorithm

Recently, Data collected from safety relays and circuit breakers has been used in fault diagnostics to identify power system components that are either failing or have tripped. A tiny percentage of heating zones may cause problems when identifying faults, although the chance of aberrant heat production in power equipment is modest. The power transformer is one of the most crucial components of any electrical system. Discovering any concealed defects in power equipment is essential to ensuring a continuous supply of electrical power for customers. The challenging characteristic of such fault diagnosis in power equipment is the greater potential for harm and a great deal of time invested in testing and training. Hence, in this research, Smart Support Vector Machine enabled Artificial Neural Network (SVM-ANN) technologies have been improved for fault diagnosis in power equipment for industry. The Genetic Algorithm (GA) process the power equipment for industrial data processing and monitoring in that fault diagnosis. The classification of strategies used and their relationships to power equipment processes to identify significant trends and research problems related to intelligent fault diagnosis systems for industry. The experimental analysis of SVM-ANN outperforms fault diagnosis using the power equipment industry in terms of performance, accuracy, prediction ratio, efficiency, and error rate.

High-throughput quantification of quasistatic, dynamic and spall strength of materials across 10 orders of strain rates

Abstract The response of metals and their microstructures under extreme dynamic conditions can be markedly different from that under quasistatic conditions. Traditionally, high strain rates and shock stresses are achieved using cumbersome and expensive methods such as the Kolsky bar or large spall experiments. These methods are low throughput and do not facilitate high-fidelity microstructure–property linkages. In this work, we combine two powerful small-scale testing methods, custom nanoindentation, and laser-driven microflyer (LDMF) shock, to measure the dynamic and spall strength of metals. The nanoindentation system is configured to test samples from quasistatic to dynamic strain-rate regimes. The LDMF shock system can test samples through impact loading, triggering spall failure. The model material used for testing is magnesium alloys, which are lightweight, possess high-specific strengths, and have historically been challenging to design and strengthen due to their mechanical anisotropy. We adopt two distinct microstructures, solutionized (no precipitates) and peak-aged (with precipitates) to demonstrate interesting upticks in strain-rate sensitivity and evolution of dynamic strength. At high shock-loading rates, we unravel an interesting paradigm where the spall strength vs. strain rate of these materials converges, but the failure mechanisms are markedly different. Peak aging, considered to be a standard method to strengthen metallic alloys, causes catastrophic failure, faring much worse than solutionized alloys. Our high-throughput testing framework not only quantifies strength but also teases out unexplored failure mechanisms at extreme strain rates, providing valuable insights for the rapid design and improvement of materials for extreme environments.