Custom Power Research Articles

A Game Strategy for Getting Electricity Investment Interface Extension in Adaptation to the Construction of Hainan's High-Level Free Trade Port

This study focuses on the extension of the ' Getting Electricity ' investment interface as its main theme, taking the construction of key parks in the Hainan Free Trade Port ((Hainan Province, China)) as the real-world background. this study constructs an evolutionary model for the cooperative operation mechanism among the power grid company, customers, and government in the extension of the electricity investment interface. It analyzes the strategic interactions among the three parties during the implementation of the interface extension. Furthermore, the study conducts a stability analysis of the equilibrium among the government, power grid enterprises, and park customers under scenarios where value-added services are provided by the power grid enterprises. Different pathways for coordinating the interests of the three parties under various standards of investment interface extension are presented. This provides critical support for formulating targeted policies on ‘Getting Electricity' investment extensions and maximizing the comprehensive efficiency of electric power resources at a broader level.

Research on Broiler Mortality Identification Methods Based on Video and Broiler Historical Movement

The presence of dead broilers within a flock can be significant vectors for disease transmission and negatively impact the overall welfare of the remaining broilers. This study introduced a dead broiler detection method that leverages the fact that dead broilers remain stationary within the flock in videos. Dead broilers were identified through the analysis of the historical movement information of each broiler in the video. Firstly, the frame difference method was utilized to capture key frames in the video. An enhanced segmentation network, YOLOv8-SP, was then developed to obtain the mask coordinates of each broiler, and an optical flow estimation method was employed to generate optical flow maps and evaluate their movement. An average optical flow intensity (AOFI) index of broilers was defined and calculated to evaluate the motion level of each broiler in each key frame. With the AOFI threshold, broilers in the key frames were classified into candidate dead broilers and active live broilers. Ultimately, the identification of dead broilers was achieved by analyzing the frequency of each broiler being judged as a candidate death in all key frames within the video. We incorporated the parallelized patch-aware attention (PPA) module into the backbone network and improved the overlaps function with the custom power transform (PT) function. The box and mask segmentation mAP of the YOLOv8-SP model increased by 1.9% and 1.8%, respectively. The model’s target recognition performance for small targets and partially occluded targets was effectively improved. False and missed detections of dead broilers occurred in 4 of the 30 broiler testing videos, and the accuracy of the dead broiler identification algorithm proposed in this study was 86.7%.

Customer ESG performance and supplier greenwashing behaviour: evidence from China

ABSTRACT Based on a Chinese sample of customer-supplier firm pairs from 2012–2022, we explore the impacts of customer ESG performance on supplier greenwashing behaviour along the supply chain. The results indicate that customer ESG performance can effectively inhibit supplier greenwashing behaviour, and the association is particularly pronounced with lower supplier’s bargaining power or lower customer’s greenwashing tolerance. Our findings offer insights into the development of greenwashing correction mechanisms within the context of China.

System Design of a Customized Solar Photovoltaic Power System for a Microcontroller-based Weather Station in Minna, Nigeria

In atmospheric and meteorological studies, missing values in acquired research data possess serious challenge on the integrity of research output emanating from their use. Missing values or readings may arise due to temporal or permanent failure in power supply to the measuring weather station. In this work, effort was made to address the fundamental issue of remote power at a standalone solar powered weather stations by professionally applying solar photovoltaic power system installation technique and the requisite knowledge of local parameters of the installed location to design a customize power supply pack for the weather station. The protocol involves an elaborate electrical load assessment and analysis of the weather station, followed by an independent component wise design formulation leading to selection of suitable solar module, battery, charge controller and voltage regulator along with their outdoor installation design. It was recommended that the design be validated using solar photovoltaic software followed by physical implementation which should be done in line with the system and installation design.

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.

Performance Evaluation of Battery Swapping Stations for EVs: A Multi-Method Simulation Approach

This study presents an optimisation framework for operating a battery swapping station (BSS) to enhance efficiency and sustainability in electric vehicle (EV) infrastructure. A hybrid modelling approach combines agent-based discrete event simulation and linear programming to model the dynamic behaviour of batteries and operational processes within the BSS. The model considers factors such as charging speed, battery degradation, grid power constraints, customer behaviour, and range anxiety. The agent-based model simulates the interaction between vehicles, batteries, and the station, capturing the stochastic nature of EVs’ arrivals and battery demand with the discrete event simulation. The linear programming component optimises battery state transitions to minimise degradation and ensure that the demand is met while respecting the power limits of the grid. Different battery types are considered based on vehicle category, each with specific capacity and usage patterns, reflecting real-world market conditions. The results demonstrate that the proposed optimisation framework can effectively manage the complex operational needs of a BSS. The proposed framework effectively balances service quality with resource efficiency by employing a strategic mix of charging modes and inventory management, reducing operational and degradation costs. This approach supports a more sustainable EV infrastructure, highlighting BSS as a viable solution to enhance the efficiency and sustainability of EV operations. Furthermore, the analysis highlights the critical role of power limits in determining charging strategies and their impact on operational efficiency. The findings suggest that with optimised operations, BSS can play a critical role in accelerating the adoption of EVs by offering a faster, more reliable, and sustainable alternative.

Power-controllable variable refrigerant flow system with flexibility value for demand response

With the increase of renewable energy sources in the power supply, the issues of balancing power supply and demand are becoming severe. Demand response, by altering the demand-side load state, has been proven as a good method to solve the supply and demand balance problem. Variable refrigerant flow system has great potential in demand-side loads and is poised to become the mainstay of demand response. However, the traditional temperature or compressor state control of variable refrigerant flow systems does not allow for better power regulation for the power system. To address this problem, this paper proposes a power-controllable variable refrigerant flow system with demand response flexibility value for power regulation. The demand response flexibility value is designed as a subjective indicator to satisfy the heterogeneous customer comfort requirement. The predictive mean vote as an objective indicator of customer comfort coordinates with the demand response flexibility value. A fuzzy control strategy for variable refrigerant flow systems is designed to balance power system requirements and customer comfort requirements. The experiment result demonstrates that the power-controllable variable refrigerant flow system can provide power regulation service to the power system with a maximum power regulation deviation of 3.67%. By guaranteeing consumer comfort, the higher the flexibility value, the shorter the consumer’s participation time in demand response. The demand response flexibility values can provide regulation configuration for demand response in practical engineering.

An Analysis of Industry Forces Impacting Apple’s Performance: A Study Using Porter’s Five Forces Framework

The main objective of this study was to identify different electronic industry forces that impact the performance of Apple Inc. using Porter’s five forces framework. The study adopted a desktop methodology. The buyers have moderate power as a result of customers' attraction to the brand. Still, also the availability of alternative products at lower prices gives the customers power to negotiate. There is a moderate power of supplies resulting from a wide industry demand and scarcity of the components. There is a low threat of new entrants in the electronic industry due to high capital investment, high research and development costs, economies of scale and strong brand loyalty. The availability of different products of similar functionalities makes the threat of substitutes to be high in the market like tablets and smartphones. The rivalry of existing competitors is high as the industry is characterized by aggressive price strategies. To maintain its strong position in the market, Apple highly invests in research and development to make its products differentiated and maintains its strong brand loyalty. Apple need to consider the consumers of low incomes as the products of Apple Inc. are regarded as expensive for this group and where the competitors are willing to offer substitute products and services at lower prices.

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.

The Role of AI Leonardo, Discord, and Rytr in Business Enhancement and Digital Economic Growth in Indonesia

Artificial Intelligence (AI) is a series of computing techniques that can perform functions like humans. This technology can have an economic impact on a country. Unfortunately, AI adoption in Indonesia is still low and has not had an impact on the economy. Research This will explore factors that can be a driver of increasing AI adoption in Indonesia, especially in the business sector. This study will also present a comparison of 3 types of AI, namely Leonardo, discord, and Rytr. The method in study This uses a mixed method, namely qualitative and quantitative. The ZMET method is used to analyze qualitative data, and Kruskal Wallis is used for quantitative data. The results of the study show that there are several factors that can encourage the adoption of AI for business actors, one of which is the availability of an AI community, the availability of a digital incubator, and Penta helix collaboration is very necessary. The results also prove that AI Rytr has a greater influence than the 2 types of AI, Leonardo and Discord. Businesses that use AI Rytr own profit term long, availability source Power greater financial, sales growth, business image, and customer loyalty compared to 2 types of AI Leonardo and discord.

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.

Prediksi Biaya Pemakaian Listrik Dengan Metode Logika Fuzzy Mamdani

Understanding the electricity tariff class is needed to predict how much usage costs or electricity bills that must be incurred by customers. Each power capacity has a different basic electricity tariff based on the class, household, business and industry. Fuzzy logic can solve problems with imprecise and heuristic data by producing accurate conclusions. The conclusion obtained from the Fuzzy Logic results is expected to be a consideration for customers in predicting electricity usage costs based on electricity tariff groups and customer electrical power capacity. The proposed research uses the Mamdani Fuzzy Logic Method, the use of this method aims to facilitate customers in predicting the cost of electricity usage based on the electricity tariff class and the customer's electric power capacity. The output of this research is the result of predicting the cost of electricity usage based on the power group in residential homes. The higher the tariff group, the number of kWh, electronic goods, and usage time, the higher the predicted energy consumption used. The results obtained from adjusting the fuzzy input antecedents and fuzzy values, namely [900;850;30;20], then for Type_Tariff Power 900, Total_KWh 850, Electronics 30, and Time_Use 20 is 986. Then the cost that must be incurred in the example case above is 1,333,072 rupiah.

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.