Power Distribution Companies Research Articles

Job-Related and Nonjob-Related Gossips Among Low-Ranked Employees in Unionized Service Organization.

Workplace incivility is a common phenomenon that is frequently found across all organizations and cultures. This study was planned to investigate the impact of workplace incivility on job and non-job related gossips through the mediating role of cynicism and psychological contract violation. The perspective of low-ranked unionized employees was explored through a survey method by using stratified sampling in eight strata, which were formulated based on geographical distribution. A total of four hundred questionnaires were distributed among the employees of eight circles, 50 from each, while use able responses remained 301. SmartPLS was used to analyze the data through structural equation modeling. From a theoretical perspective, this study has made several contributions by investigating the impact of workplace incivility in the South Asian context and documenting the impact of incivility from the perspective of individuals belonging to minority socio-cultural status. Besides supporting existing literature, this study provided a unique argument that low-ranked employees in South Asian societies do not spread nonjob-related gossips. This finding is contradictory to the existing literature; and, thus, calls for future research to identify this inconsistency. Limitations and future directions are also discussed.

Toward Identifying Consumer Responsibility on Voltage Distortion and Filtering Based on the Maclaurin Series

Reducing the voltage distortion is an essential concern for consumers and power distribution companies. The distortion voltage due to the distorted current of consumers affects the common coupling point and consequently, other consumers. Nowadays, most of the harmonic-based active filtering initiatives are generic and act to minimize the harmonics independently of their origin, either the distribution companies and consumers. In this context, we propose SRAF (Shared Responsibility in Active Filtering) as a new approach to determine the portion of responsibility for the voltage distortions, which also implies on defining a novel technique to mitigate the disturbance caused only by the consumer. The main contribution of SRAF relies on the combination of the simplicity of the method in terms of physics understanding and the use of MacLaurin series with on-the-fly parameter optimization. Thus, we introduce in the literature a new easy-to-use form to understand energy responsibility on voltage distortion. The results obtained by simulation show encouraging results, even with different input workloads and simulated environments. By using the SRAF approach massively, we expect lower financial costs in filtering systems. Since our approach observes the consumer viewpoint, we emphasize that contingency filtering is also essential in the case of distortions from the power grid.

Probabilistic locational marginal price computation in radial distribution system based on active power loss reduction

This study presents a probabilistic approach to calculate locational marginal price (LMP) at distributed generation (DG) buses in an electric power distribution system to ensure that the network operates at reduced active power losses (APLs). The proportional nucleolus theory-based iterative method is proposed as a deterministic approach to compute LMP based on APLs. Uncertainties in load and market price were captured by using a 2 m + 1 scheme of the point estimation method. To compute the contribution of the reactive and active power of the DG on the APL of the network, loss sensitivity factors have been developed. The proposed method provides an active power price in terms of LMP and reactive power price to each DG as per its contribution to loss reduction. To verify the performance of the proposed method, it was implemented on the Taiwan Power Company distribution system. The proposed method can be utilised by a distribution company to operate the network at reduced APL and improve the benefit of DG owners.

Effect of sectionalizing switches malfunction probability on optimal switches placement in distribution networks

Sectionalizing switches (SSs) are installed in distribution networks to provide ring and maneuver points, thereby increasing service reliability. These switches are either manual switches (MSs) or remote controlled switches (RCSs). The switches are usually assumed to be fully reliable. However, in practice, their performance is not always ideal. Actually, the switches may sometimes experience malfunction, which reduces their ability to enhance system reliability. The present study proposes a model to consider the malfunction possibility of the switches in their optimal placement problem. The model helps to minimize the total costs of SSs as well as the interruption costs incurred by interrupted customers. In order to calculate the malfunction probability of the switches, historical data on operation of the switches and their repair time are obtained from an electric power distribution company in Iran. The discrete Markov chain model is used to obtain the malfunction probability under different modes. The placement problem is then modeled in mixed integer linear programming (MIP) which can be easily solved to obtain the global optimal solution. The effectiveness of the proposed model is revealed by means of multiple case studies and sensitivity analyses. The studies show how the results of the placement problem are affected by the uncertainty caused by the probable malfunction of the switches and how overlooking this uncertainty can lead to deviation of the expected profit from the actual one.

Fraud Detection for Metered Costumers in Power Distribution Companies Using C5.0 Decision Tree Algorithm

Non-technical Losses mainly Electricity theft has been a main concern for power utilities from last many years. Power utilities are estimated to lose billion dollars annually because of illegal usage of electricity by fraudulent consumers. Researchers are trying different methods for proficiently recognizing fraudster costumers. This research suggests a new approach based on C5 algorithm for efficiently identifying consumers involved in electricity theft. The C5.0 algorithm is a modified form of the C4.5 algorithm. It is also one of the decision tree algorithms but with a much-improved classification rate. The C5.0 algorithm relies on monthly energy consumption data to identify any anomaly in consumer energy usage data associated with NTL behavior. There are many types of fraud committed by fraudulent consumers but this research is focused on fraudulent consumers who have a unexpected deviation from their usual load profile. The motivation of this research is to aid Power distribution companies in Pakistan to decrease there NTL’s due to pilfering in energy consumption by fraudulent consumers. The accuracy of the C5.0 algorithm is 94.61% which is much higher when compared to some state of the art machine learning algorithms like Random forest, Support Vector Machine, K-NN and other decision trees.

Risk Factors Affecting Occupational Accidents and Related Causes: Case Study

Background: Electricity is considered as the fifth cause of occupational deaths. Occupational accidents caused by electricity do not form a high percentage of total occupational accidents, but are considered due to the severity of injuries which often result in death. The present study aimed to investigate the factors affecting occupational accidents among employees of a power distribution company in Khuzestan province. Methods: The present study was a descriptive-analytical study which conducted as cross-sectional on the files related to the accidents of the personnel of a company in 2017. Inclusion criteria were a history of accidents during the last 5 years from 2013 to 2017. Thus, all the personnel files of the employees of the company were reviewed and a number of 92 files of the personnel who were injured during the above-mentioned years were extracted. The required information such as demographic information (age, marital status, education level), organizational information of the injured person (employment status, job title), type of injury and place of injury on the body, rate of accidents in different seasons, days, and hours were recorded on a specific worksheet in the files. SPSS software version 22 was used for analyzing the factors affecting occupational accidents using descriptive tests and chi-square test. Significance level was considered as 0.05. Results:The maximum number of accidents occurred in summer during 8 to 10 am and the age group of 25 to 29 years reported the highest number of fatalities. In addition, most accidents occurred in the occupational group having a job experience of 1 to 5 years. Conclusion: Human errors and non- use of personal protective equipment, deficit of equipment and supervision, as well as the failure in implementing technical and safety instructions were the most critical causes of accidents and the actions such as technical and safety training before starting the work were evaluated as effective measures in controlling accidents.

5-Hz Distribution System for Mitigation of Energy Theft by Residential Consumers

Energy theft through meter bypass by residential consumers constitutes significant revenue loss to electric power distribution companies. This unpleasant phenomenon is particularly worrisome in sub-Saharan Africa and some parts of Asia. This paper reports the outcome of a research which attempts to develop a modified distribution and metering system to demotivate energy theft by residential consumers. The project involves modeling and simulating a 5-Hz distribution system in SimPowerSystems. The developed system is then implemented using laboratory-scale power electronics components. The modified distribution system is thereafter interfaced with a modified digital consumer energy meter. The system is subsequently tested by deploying it to power two categories of lighting loads. The test results show that one category of lighting load flickers while the other category is non-operational whenever the proposed system is bypassed, though the power remains available. This is expected to demotivate the practice of energy theft through meter bypass. Thus, it is further expected that the proposed system will mitigate revenue loss by power distribution companies thereby stimulating investments in the sub-sector.

Net Metering and Solar PV Prosumage in Pakistan: Growth and Challenges

In the wake of an on-going energy crisis in Pakistan, National Electric Power Regulatory Authority (NEPRA) issued net metering regulations in 2015 in order to encourage consumers to contribute in power generation. Contrary to the anticipation of attracting large-scale prosumers after the launch of these regulations, the overall capacity installed so far remains insignificant. Moreover, an uneven distribution in terms of issued licenses as well as installed capacity across the power distribution companies (DISCOs), wherein the growth is concentrated in three major cities of Pakistan—Islamabad, Lahore and Karachi—is another challenge. Based on this insight, the study aims to probe the challenges to distributed generation (DG) in Pakistan. Primary data for this paper was collected from three primary stakeholders: the prosumers; the non-prosumers; and the DISCOs or the primary intermediaries. The findings indicate a number of challenges hindering DG growth in Pakistan including cumbersome application process; serious financial barriers; inaction of DISCOs; low trust in technology; absence of awareness programs and absence of fee-for-service (FFS) models. Finally, the paper gives a roadmap to overcome the aforementioned challenges, and catalyzing the prosumage drive.

Electricity prices determinants: India's perspective

A robust trading system is vital to promote competition in the Indian electricity market. In India, the exchange trading market is still at an incipient stage, despite being the best option for innovation, due to the presence of high volatility huge losses are incurred by the power market participants such as power generators and distribution companies. Hence, a descriptive research was conducted to identify the major factors leading to the periods of spikes and jumps in the Indian energy exchange's day-ahead market (DAM) prices of all the regions (north, south, east, west and north east) from August 2008 until June 2017. It was found that the major factors affecting DAMs prices are regulatory, weather, fuel supply, transmission congestion; power plant outages/new plants operational, frequency and reservoir levels. This study will encourage the stakeholders to further model and forecast prices devising profit maximisation techniques thereon.

Design and Implementation of Gsm Enabled Remote Sensor for Monitoring Power Transformer Operation

Transformer is one of the most vital components of power transmission and distribution infrastructure. In a developing country such as Nigeria, majority of the growing population of the people are still grappling with gross inadequate and epileptic power supply. Only about 4000MW of electricity is available for distribution (by load shedding) due to decay in existing infrastructure. The aim of this work is to apply modern technology to prevent further decay of the equipments particularly the transformer which is very expensive. This article involves the design and implementation of a device to monitor and detect the operating condition of a transformer with emphasis on power distribution transformers. A module embedded Global System for Mobile communication (GSM) enabled device is designed to monitor load currents and temperature, using a micro-controller and sensor. The monitored values are processed and recorded in the system memory which is programmed with some predefined instructions to detect any abnormal working condition of the transformer so that the GSM module can send a Small Message Signal (SMS) to designated mobile telephones containing information about the fault, base on the programmed instructions into the micro-controller. This will help the power distribution company respond swiftly to abnormalities that may lead to catastrophic failures and subsequent system short down. It is a fully automated device capable of reducing the risk of transportation and human errors associated with manual transformer inspection and testing. The device was tested and it responded very well to fulfill the set objectives.

SPD in illumination system of HV air insulated substation

The article discusses the distribution of the lightning current between communications of the object as the main aspect determining surge protective devices (SPDs) parameters for applying in substation’s low voltage networks. Wireframe model was designed to compute field-circuit model of earthing device (ED) and define the element potentials and currents using circuit analysis methods. Transients were calculated using operator method. Results of calculation and measurements of the lightning current’s distribution in ED and cables in illumination network of air insulated substation presented. Experimental study results obtained in training ground PJSC «Lenenergo», one of the largest electric power distribution company in Russia. Case of lightning strike in the floodlight mast combined с with lightning rod in 110 kV air insulated substation was studied. Requirements for the parameter "impulse discharge current amplitude" SPD defined. Described general approaches to the illumination network’s lightning surge protection on air insulated substation.

Smart residential electricity distribution system (SREDS) for demand response under smart grid environment

The present research work attempts to develop a Smart Residential Electricity Distribution System (SREDS) for enabling Smart Residences (SR) to participate in Demand Response (DR) schemes of Power Distribution Company (PDC) with either Flat Rate tariff, Time of Use tariff or Real Time Pricing. SREDS includes a Smart Energy Meter (SEM) enabled with Internet of Things, an Intelligent Residential Load Management System (IRLMS) with Wi-Fi connectivity, distributed Wi-Fi enabled Smart Load Nodes (SLN) and Smart Battery Charing/Discharging Controller (SBCDC). The SEM receives the key parameters such as electricity pricing, maximum demand limit, etc. as per the DR schemes from the PDC through Meter Data Management System (MDMS) using Internet. IRLMS receives the required operational timings of the loads as per the desire and comfort of the user either through the user interface or from the SLN connected to the appliances participating in DR. If the SR is equipped with battery storage system, then the battery units are interfaced with the IRLMS through SBCDC. The present status of the battery is communicated to IRLMS by SBCDC. The communication between SEM, IRLMS, SLNs and SBCDC is established through Home Area Network using Wi-Fi. The IRLMS processes the PDC parameters and load requirements, and executes an optimization algorithm to find the best possible scheduling of appliances in order to get minimized electricity bill. The SEM communicates back the energy consumption data to the PDC through MDMS.

Organizational Politics And Workplace Deviance In Unionized Settings: Mediating Role Of Job Stress And Moderating Role Of Resilience.

BackgroundPolitics and political behaviors are a vicious and bitter reality in an organization’s life. Although under investigation for more than three decades, the literature lacks sufficient studies investigating culture-specific potential factors which have the potency to moderate the poisonous consequences of organizational politics. The aim of this study was to investigate the relationship of organizational politics and deviance in unionized settings with the moderating role of resilience in unionized employees in higher power distance culture.MethodsA cross-sectional design was followed for data collection. The population of this study was low-ranked employees having union identity and working in the largest power distribution company of Pakistan. Stratified sampling was applied, and eight strata’s were considered on the basis of geographical distribution, a total of 400 questionnaires were distributed among the employees of eight circles, fifty from each. Smart PLS.3.2.0 was used to analyze data through Structural Equation Modeling (SEM) under measurement and structural models.ConclusionFrom a theoretical perspective, this study confirmed that employees tend to show interpersonal deviance when they experience organizational politics, but organizational politics does not promote organizational deviance. Under stress, the individual also shows a slightly higher level of interpersonal deviance as compared to organizational deviance. However, the moderating role of resilience has not been proved in this study. Research limitations and future directions have also been discussed.

Ensemble Bagged Tree Based Classification for Reducing Non-Technical Losses in Multan Electric Power Company of Pakistan

Non-technical losses (NTLs) have been a major concern for power distribution companies (PDCs). Billions of dollars are lost each year due to fraud in billing, metering, and illegal consumer activities. Various studies have explored different methodologies for efficiently identifying fraudster consumers. This study proposes a new approach for NTL detection in PDCs by using the ensemble bagged tree (EBT) algorithm. The bagged tree is an ensemble of many decision trees which considerably improves the classification performance of many individual decision trees by combining their predictions to reach a final decision. This approach relies on consumer energy usage data to identify any abnormality in consumption which could be associated with NTL behavior. The key motive of the current study is to provide assistance to the Multan Electric Power Company (MEPCO) in Punjab, Pakistan for its campaign against energy stealers. The model developed in this study generates the list of suspicious consumers with irregularities in consumption data to be further examined on-site. The accuracy of the EBT algorithm for NTL detection is found to be 93.1%, which is considerably higher compared to conventional techniques such as support vector machine (SVM), k-th nearest neighbor (KNN), decision trees (DT), and random forest (RF) algorithm.

Automatic restoration of large-scale distribution networks with distributed generators, voltage control devices and heating loads

Energy supply interruption by permanent faults causes economic and social problems, dissatisfaction of customers and penalization to electrical power distribution companies. In the procedure to restore distribution networks, power interruption damages must be minimized by energizing the largest possible number of customer loads in the shortest time interval. The restoration problem of distribution networks can be mathematically formulated as a mixed integer nonlinear programming problem that is non-convex of type NP-complete. The existence of heating loads causes the cold load pickup condition in the distribution network that requires the step-by-step procedure increasing the complexity of the restoration problem. In this work, therefore, it is proposed a methodology to solve the restoration problem of large-scale distribution networks with heating loads where the mathematical model is subjected to intentional islanding of distributed generation and voltage control through optimized adjustments on capacitor banks and voltage regulators. The outcomes are achieved under a testing distribution system with 53 nodes and a real system with 7052 nodes.

Maximizing Usage of Power Supply through Electrical Power Distribution Company or Generator By means of Power Inverter System

Maximizing Usage of Power Supply through Electrical Power Distribution Company or Generator By means of Power Inverter System

Enhancing Power Distribution Feeders Restoration with a Probabilistic Crew Dispatch Method: Case Studies using Historical Data from a Brazilian Power Distribution Company

Abstract This paper proposes a methodology to repair crews dispatch during distribution feeders restoration immediately after remotely controlled actions have been taken. Our method determines the sectors patrol sequence using the expected number of faults for each sector considering a previously calculated fault probability. Next, a road graph mapping of the buses is obtained by associating each bus with its real-world position. The crews’ route inside each sector is determined by the application of the nearest neighbor algorithm on that mapping. The case studies analyzed 24 real faults available in the database of a Brazilian power distribution company, and, a comparison was made between the time spent to locate the failures by simulating both the proposed methodology and the usual greedy strategy. The average time spent in localizing all the failures was from 9.49 % to 41.81 % shorter than in the usual method. Moreover, the speed and distance of repair crews showed weak influence in the crew dispatch methodology efficiency. Such results indicate an enhancement of the power distribution QoS indicators by using the proposed methodology to deal with faults.

Cubic reward penalty structure for power distribution companies

An important significance of restructuring in power industry is the emergence of regulatory performance indices in the power distribution companies. Reward-penalty scheme is a direct control method that regulators use to assure the performance regulatory controls such as system reliability, service efficiency, and customer interruption cost. It is used as a financial tool designed to prevent the service reliability and efficiency deterioration of power distribution companies. Reward penalty scheme rewards the distribution company which provides good reliable power and penalizes those who act otherwise. In this paper, we propose a Cubic Reward-Penalty scheme, to improve the service reliability of power distribution companies. The novel feature of this scheme is the use of cubic reward/penalty formulation which varies in a cubic fashion based on the behavior of the performance-based reliability. In this paper, two methods of implementing Cubic Reward-Penalty scheme are explained: CRPS with no dead band and no reward/penalty capping and CRPS with dead band and reward/penalty capping. These proposed approaches are mainly intended for the regulators who are concerned about the customers affected by the outage duration. The significance of this research, lies in encouraging power distribution companies, to maintain, or even improve, customer service and satisfaction, by developing the Performance Regulatory Reward-Penalty schemes. This paper also provides most of the requirements and design rationale of Cubic Reward-Penalty Structure, its theoretical foundation and its prototype implementation.

A regression spline control chart for monitoring characteristics exhibiting nonlinear profile over time

Purpose The purpose of this paper is to demonstrate the application of the control chart procedure to monitor the characteristics whose profile over time resembles a set of connected line segments. Design/methodology/approach Fit a regression spline model by taking the subgroup average of the characteristic as response variable and time as the explanatory variable. Then monitor the response variable using the regression spline control chart with the fitted model as center line and upper and lower control limits at three standard deviation units of the response variable above and below the center line. Findings The proposed chart is successfully deployed to monitor the daily response time profile of a client server of an application support process. The chart ensured the stability of the process as well as detected the assignable cause leading to the slowing down of the server performance. Practical implications The methodology can be used to monitor any characteristics whose performance profile over time resembles a set of connected line segments. Some of the examples are the consumption profile of utility providers like power distribution companies, usage profiles of telecom networks, loading profile of airline check-in process, e-commerce websites, etc. Originality/value To the best of the author’s knowledge, construction of control charts using regression spline is new. The usage of the control chart to monitor the performance characteristics which exhibits a nonlinear profile over time is also rare.

Energy economy potential estimation of establishment needs objects of power distribution company

This article describes a systematic approach in assessing the potential of energy saving, based on the universal model of technocenosis. A rank analysis of retrospective data on energy consumption was carried out, a mathematical model of power consumption was obtained. The procedures of interval estimation of the rank parametric distribution are carried out and the objects of establishment needs are determined, which power consumption is not included in the boundaries of statistical norms. With the help of cluster procedures, technocenological norms of power consumption are calculated. Based on the theory of structural and topological dynamics of the rank parametric distribution, the predicted power consumption is determined. The energy saving potential has been calculated and the objects of economic needs have been identified, where the implementation of measures aimed at energy saving is first necessary.