Reliable Electric Power Supply Research Articles

Enhancing Fault Detection and Location Identification using GIS-based Techniques: A Case Study of Arba Minch Distribution System

ABSTRACT Fault detection and location in distribution systems are critical for maintaining reliable electric power supply and minimizing outage time. The Arba Minch District distribution department of Ethiopian Electric Utility (EEU) currently employs a manual trial-and-error approach for fault detection and location, which is inefficient, time-consuming, and ineffective in resolving faults. This study evaluates the current approach and proposes an enhanced system utilizing Geographic Information System (GIS) technology to improve fault detection and location in the Arba Minch distribution system, specifically the Shecha feeder. The implementation of GIS-based fault detection and location aims to address the limitations of the manual method and mitigate economic losses associated with feeder faults. ETAP GIS simulations successfully detected and located faults, achieving effective reduction in fault detection and location time compared to the conventional method. By optimizing fault detection and location time, the System Average Interruption Duration Index (SAIDI) for the feeder was significantly reduced. Consequently, the GIS system highly minimizes the economic losses associated with energy not supplied. The results demonstrate the potential of GIS technology in enhancing fault detection and location, ultimately improving the reliability and efficiency of the distribution system.

SHORT-TERM FORECASTING DAILY ELECTRICITY LOADS USING SEASONAL ARIMA PATTERNS OF GENERATION UNITS AT PT. PLN (PERSERO) TARAKAN CITY

Electrical power requirements at load centers tend to change over time, so the State Electricity Company (PLN) as a provider of electrical energy must be able to predict electrical load requirements every day. The city of Tarakan as a reference center in the northern region of Indonesia is developing rapidly. Along with this growth, the need for electric power is of course also increasing, so we must be able to provide an economical and reliable electric power supply system. This research aims to predict the electricity load at PT. PLN (Persero) Tarakan City. The author will carry out short-term forecasting using time series data in the form of daily electrical power usage data using the Autoregressive Integrated Moving Average (ARIMA) method. The ARIMA method or often called the Box-Jenkins technique shows that this method is suitable for predicting a number of variables quickly, simply and cheaply because it only requires variable data to be predicted. Analysis based on the Box-Jenkins time series taking into account the influence of seasonal patterns. The prediction results show that the data contains seasonal elements with the best model being SARIMA with a MAPE of 3 percent.

Analysis of Photovoltaic Systems Through Simulation and Design Using MATLAB

During the operation of photovoltaic systems, a large amount of converted energy, according to various parameters, does not participate in the consumer power supply. As a result, the efficiency of solar installations and the reliability of electric power supply are reduced. This happens for various reasons, but primarily due to the imperfect operation of automatic control systems for photovoltaic installations. These systems are controlled by the information equipment of the entire installation based on software and control algorithms. The imperfection of these algorithms does not allow the full use of solar generation of photovoltaic panels and degrades the quality of operation of all the main and auxiliary equipment of the power generating complex. In the presented work, studies were carried out to improve the operation of the solar power supply system and increase its reliability. The proposed solutions were based on the use of new methods for tracking the maximum power point using high-tech algorithms to control the photovoltaic generating system. In this paper, a generalized Matlab-Simulink solar cell operation model was proposed. The basis of the proposed model is a simple mathematical equation to simulate the operation of a solar photovoltaic cell, since the output characteristics of photovoltaic modules are non-linear. The output I-V and P-V properties of a photovoltaic cell depend on the temperature of the cell and solar radiation. The physical characteristics of a particular solar photovoltaic cell can be modeled as a function of temperature and solar radiation. Numerous models use various software platforms that are available in the literature. This simulation model is very simple and easy to use. Simulation results in Matlab Simulink demonstrate the functionality and dynamic behavior of the provided solar module. Based on the study, it was found that the proposed algorithms can significantly improve the efficiency of photovoltaic installations, taking into account the use of new control methods. The power generated from solar energy converters was used more efficiently, and the photovoltaic system operated at a high conversion rate.

A new methodology for the analysis of fish breeding seasonality

The difficulty to dissect and weigh very tiny gonads and several fish specimens for the purpose of computing gonadosomatic indices (GSIs) due to non-availability of reliable electric power supply under field conditions, necessitated the study. This paper presents the performance of the gonad length indices vis-a-vis the traditional GSIs. The gonad elongation ratio (GER) (i.e. gonad length as a function of fish standard length expressed as a percentage) is here proposed for use in analyzing teleost fish breeding seasonality. The West African amphibious mudskipper, Periophthalmus barbarus (Linneaus, 1766) (Teleostei: Gobiidae) from the Imo River estuary, Nigeria, was used as the trial species. Monthly mean testicular and ovarian elongation ratios were examined vis–a–vis the classical testicular and ovarian gonadosomatic indices. The monthly mean gonad elongation ratios followed similar monthly mean sequences of the corresponding gonadosomatic indices. Mean GSI was 0.192 in males (range 0.097 – 0.347) and 1.197 in females (range 0.512 – 3.398); whereas mean GER was 16.5 for males (varied from 12.9 to 19.2) and 19.5 in females (ranged between 16.8 and 25.3). However, the gonad elongation ratios fluctuated more finely than the gonadosomatic indices. It is 2 - 3 times much easier and faster to determine gonad elongation ratio in the field than the gonadosomatic index. The determination of gonadosomatic indices require the use of sensitive electronic balance and reliable electric power supply while these are not necessities for the determination of gonad elongation ratios. Being a quantitative measure, the gonad elongation ratio can be subjected to statistical reliability estimates such as standard deviation, standard error and confidence intervals. The gonad elongation ratio which is quantitative and has biological interpretation that is analogous to the traditional gonadosomatic index, is recommended for use.

Reliability Assessment of the Configuration of Dynamic Uninterruptible Power Sources: A Case of Data Centers

The number of data centers worldwide is increasing year by year, mostly because of the development of cloud services and applications. In the near future, the rate of construction of data centers will grow, with a corresponding increase in their electrical energy consumption. The requirements of the reliability of the electrical power supply of data centers are one of the highest among industrial power consumers, since uninterrupted power supply is critically important for the continuous functioning of server hardware. The assessment of electrical power supply reliability is one of the most important parts of the design process of data centers. However, the speed of the development of new power equipment does not always make it possible to use classical probabilistic and statistical methods for reliability assessment. Therefore, the development of new methods for reliability assessment based on alternative approaches, which can eliminate the disadvantages of probabilistic and statistical methods, are of great interest. This paper discusses the alternative method for analyzing the reliability of electrical power supply for the case of data centers. The method defines the reliability through the internal information of the system that characterizes the system’s topology, flows of information, energy, and matter in the system.

An Efficient Primal-Dual Interior-Point Algorithm for Volt/VAR Optimization in Rectangular Voltage Coordinates

Security and reliability of electrical power supply has become indispensable to modern society, and the system operator is challenged to manage the increasingly complex modern power system in a manner that ensures the expected reliability and security of system operation. In this context, Volt/VAR optimization (VVO) plays a key role in the efficient delivery of power through the transmission system, contributing significantly to the security, reliability, quality and economy of system operation. This article presents the design and implementation of an efficient primal-dual interior-point algorithm for the solution of the VVO problem. The primal-dual interior-point method combines efficient constraint handling by means of logarithmic barrier functions, Lagrangian theory of optimization, and the Newton method to constitute one of the most efficient deterministic algorithms for large-scale nonlinear optimization. The developed algorithm also incorporates the efficient Newton-Raphson load flow computation, which ensures that the solution is feasible with respect to the power flow balance equations at each iteration of the VVO algorithm. Both the VVO and Newton-Raphson load flow problems are formulated in the rectangular coordinates of system voltages. This is a departure from most researchers, who make use of the polar formulation, and adds considerably to the efficiency of the developed algorithm. The efficiency and effectiveness of the developed algorithm has been demonstrated by means of case studies performed on the 6-bus and IEEE 14-bus, 30-bus and 118-bus test systems, which have been selected to analyse the computational efficiency and scalability of the algorithm as it is applied to systems of various sizes. The extensive analyses that have been conducted reveal the developed primal-dual interior-point algorithm’s effectiveness and efficiency, particularly in being able to successfully solve the VVO problem for systems of widely varying sizes without disproportionate increase in computational cost or deterioration in the quality of the results. The developed algorithm exhibits characteristics of fast convergence, high efficiency, and scalability to large-scale problems.

The Influence of Image on the Acceptance of Mobile Technology

Mobile phones are used to perform various activities in SMEs. The reliance on mobile technology is even more fuelled by the low ICT readiness in the majority of developing nations like poor infrastructures, lack of formal policy frameworks, and lack of reliable electric power supply. While mobile phones are continuously produced and used, some factors influence their usage in various contexts. One of the factors which has not been investigated in the SMEs context is personal image. This research closes this gap by assessing whether Image can potentially be a factor of concern when employees of SMEs use mobile phones for work. This study employs a survey with SEM and AMOS for analysis. The theoretical model was formulated by extending TAM. Among others, the results show that image tends to significantly influence the perceived usefulness of mobile phones in SME settings.

DCPLD-Net: A diffusion coupled convolution neural network for real-time power transmission lines detection from UAV-Borne LiDAR data

The stable and reliable supply of electric power is strongly related to the normal social production. In recent years, power transmission lines inspection based on remote sensing methods has made great progress, especially using the UAV-borne LiDAR system. The extraction and identification of power transmission lines (i.e., conductors) from 3D point clouds are the basis of LiDAR data-based power grid risk management. However, existing rule-based/traditional machine learning extraction approaches have exposed some limitations, such as the lack of timeliness and generalization. Moreover, the potential of deep learning is seriously overlooked in RoW (Right of Way) LiDAR inspection tasks. Thus, we proposed DCPLD-Net: a diffusion coupled convolution neural network for real-time power transmission lines detection from UAV-borne LiDAR data. To implement efficient 2D convolution on 3D point clouds, we proposed a novel point cloud representation, named Cross Section View (CSV), which transforms the discrete point clouds into 3D tensors constructed by voxels with a deformed geometric shape along the flight trajectory. After the CSV feature generation, the encoded features of each voxel are treated as energy (i.e., heat) signals and diffused in space to generate diffusion feature maps. The feature of the power line points are thus enhanced through this simulated physical process (diffusion). Finally, a single-stage detector named PLDNet is proposed for the multiscale detection of conductors on the diffused CSV representations. The experimental results show that the DCPLD-Net achieves an average F1 score of 97.14 % at 8 Hz detection frequency on RoWs inspection LiDAR datasets collected by both mini-UAV LiDAR and large-scale fully autonomous UAV power lines inspection robots, and surpasses compared methods (i.e. PointNet ++, RandLA-Net) in terms of F1 scores and IoU.

Review on Power System Reliability Indices and Evaluation Techniques

Now a day’s most accountable issue in the power industry is Reliability. power systems reliability using Quantitative analysis can be examined with the help of reliability indices. For a long period of time different methods introduced and developed to assess the reliability indices of the power system. In modern society Uninterrupted and Reliable electric power supply is necessary. The wide use of electricity has been lead to a high vulnerability to electric power failures. This is the reason, reliability of electric power has gained spotlight and it’s considered significant role while planning for a electric power system operation.In this paper, a summary is given of the technique of finding out the reliability of a power system. Readers will get an idea about the possibilities of measuring Reliability indices.The inspiration at the back of this paper is to set up a comprehensive general idea about Analytical and simulation technique for reliability assessment and serving for future research and development in the area of electrical power system.

Problems of verification of operating parameters of DC/AC inverters and their integration into the distribution system in the Czech Republic

Operating characteristics of the inverters have great potential to affect the operation of the electric power system in terms of stability, efficiency, quality as well as reliability of electric power supply. Grid support in form of autonomous regulation functions is increasingly required in many countries, even from small sources. The requirements arising from national legislation vary, which raises concerns among distribution system operators about the correct implementation and the required setting of autonomous regulatory functions by inverter manufacturers. Based on the authors' experience with grid-tie and hybrid inverters testing, this paper provides answers to questions that are often associated with the reliability of implementation and the setting of autonomous control functions related to voltage and frequency. The paper describes the test facility assembled within the RESLAB laboratory and the methodology used for inverters testing. It discusses the results acquired by testing of different types from different manufacturers in cooperation with distribution system operators in the Czech Republic as well as the most common deviations from the requirements of current legislation. In addition, the paper contains recommendations for inverter manufacturers and distribution system operators, which are formulated based on presented findings.

Reliability Evaluation of 33/11kV Olunde Injection Substation for Improved Performance

Electric power supply reliability (PSR) is crucial in the present economy to avoid huge economic loss and life discomfort. Thus, there is need to improve PSR. Reliability evaluation of power equipment was carried out on Olunde 33/11kV Injection Substation using extracted and available five years data of Fault Frequency and Downtime of associated power equipment for 2016 to 2020 from the Injection Substation’s log books. Fault Tree Analysis (FTA) Technique was used in this research. The existing Injection Power Substation results shows that the overall injection substation unavailability of power supply was 0.00672; 33kV NBL Feeder alone has the highest percentage of failure contribution 72.97% of the unavailability of the injection substation. The reliability improvement of the Injection Power Substation using doubling maintenance activities method on the NBL 33kV feeder shows that the overall injection substation unavailability improved from 1:1.57; the NBL 33kV feeder failure contribution reduced to 15.63%. Using a redundant feeder, 33kV feeder, the overall unavailability of the injection substation improved from 1:3.6; the NBL 33kV failure contribution reduced to 1.31%. The redundant feeder approach in this work is highly significant since it is better than the doubling maintenance activities method .

Flexible and Wearable Hybrid RF and Solar Energy Harvesting System

In this article, we demonstrate a flexible and wearable hybrid radio frequency (RF) and solar energy harvesting system for powering wearable electronic devices. The system consists of a flexible transparent antenna, a flexible transparent rectifying circuit, and an amorphous silicon solar cell. By utilizing transparent stacked structure, the rectenna and the solar cell can provide more hybrid output power to accommodate more application scenarios. The flexible transparent antenna shows two impedance matching bandwidths of 3.5–3.578 and 4.79–5.09 GHz, covering n78/n79 fifth-generation (5G) communication frequency band and 5-GHz WiFi frequency band. At the frequency of 3.5 GHz, the flexible transparent rectifying circuit achieves a high RF-to-dc conversion efficiency of 54.67% at 13 dBm RF input power. In the room with a light intensity of 210 lux, compared with a single solar cell, the hybrid energy harvesting system can obtain an additional 35.6%–769.5% output power when the RF source power is varied from 4 to 10 dBm. These results demonstrate that the proposed flexible and wearable RF-solar energy harvester can provide reliable electric power supply, which can be a potential candidate for powering wearable electronic devices, distributed sensors and IOT devices.

МАТЕМАТИЧНЕ МОДЕЛЮВАННЯ ПІДВИЩЕННЯ ЕНЕРГОЕФЕКТИВНОСТІ УНІВЕРСИТЕТУ В СИСТЕМІ ЕНЕРГОХАБА ЗНАНЬ

This study attempts to address the issues of enhancing energy efficiency using mathematical modeling methods. The research findings assert that energy saving is a new challenging task of the 21st century, since thermal and electric power consumption is essential to human life and building a favourable living environment. It is observed that boosting the competitiveness, financial stability, energy and environmental security of Ukraine’s economy, as well as improving the living standards and the life quality seem hardly possible without realizing the energy saving potential and increasing energy efficiency through modernization, technological advancements and the transition towards rational and environmentally responsible utilization of energy resources. It is argued that by resolving the above objectives, Ukraine might strengthen its positions among developed economies. The following methods were used to carry out mathematical modeling to enhance the university energy efficiency in the frameworks of the energy knowledge hub: neural network technologies, mean absolute and relative error, mean absolute deviation; statistical comparison of the forecast accuracy based on the mean absolute error, as well as time series forecasting. A model to boost the University energy efficiency has been developed within the knowledge energy hub by implementing neural network patterns based on the experimental data from the Kyiv National University of Technologies and Design for the heating period 2020–2021. In particular, to optimize the operating modes of automatic power supply control for University Building 4, mathematical models with a complex algorithm structure have been employed (offering the increased resource intensity of such tasks). It is argued that making a decision on the feasibility of using an energy hub for University buildings and selecting appropriate equipment should be accomplished with due regard to the structure and the capacity of energy consumers, their types, demands for quality and reliability of electric power supply, their compliance with operating and safety standards, as well as taking into account the results of climate, wind monitoring and monitoring of solar activity. The conclusions resume that to assure the energy quality and the system sustainability, it is considered important to resolve a range of issues related to inconsistency in generation and supply of renewable energy from power plants, ensuring reliability and quality of energy supply through the use of energy storage (batteries) in particular, etc.).

Country-Specific Aspects of Operations of Wholesale Power and Capacity Markets

The modern energy sector, in both the Russian Federation and other countries, features the so-called “finer points,” the challenging issues addressed in many analytical documents as well as in published research. The paper discusses key electric power market developments in different countries, the dynamics of indicators measuring their performance, the results of actions taken to date, as well as the approaches to their regulation and influencing the quality of power supplied. We consider the main features of the adopted regulatory models and the basic principles adhered to by electric utilities as means of successful expansion planning and operation under given conditions. The purpose of this research is to study individual elements of operations of energy markets and the features of regulation as applied to the models originating from abroad and from domestic wholesale electricity and capacity markets. The study also takes into account the technology-related aspects such as the level of reliability of the power system. The study outlines the development vector for the effective operation of generating companies in a given context. The focus is on the areas with the highest potential in terms of contributing to growth. The scope of the paper also covers an overview of key trends of electricity market operations, both as practiced abroad and in this country. We present market models and discuss different approaches to determining the level of quality and reliability of electric power supply.

Electric power supply for spacecrafts using a solid-solid phase change material and its lowtemperature performance.

In this study, we attempted to utilize solid-solid phase change material (PCM) as a new passive thermal control system to realize a low-temperature operable electric power system that can be used for micro/nanosatellites and other space applications. W-doped vanadium dioxide (VWO2) was employed and its solidification and combination with a lithium-ion cell were considered. According to the charge-discharge operation of the lithium-ion cell embedded in VO2-based solid-solid PCM (LiB-1450/VWO2+ER）in a temperature range of 40 to -20°C under vacuum, it was found that the PCM block was effective in holding the suitable temperature around 0°C, resulting stable charging-discharging of LiB-1450/VWO2+ER with relatively low internal resistance. These results reveal the promising potential of the thermal management using a VO2-based solid-solid PCM to construct a highly reliable electric power supply for spacecrafts, especially CubeSats, with minimal assistance, such as a heater.

Droop-Controlled Bidirectional Inverter-Based Microgrid Using Cascade-Forward Neural Networks

The voltage source inverters in microgrids often rely on the droop control method integrated with voltage and inner current control loops in order to provide a reliable electric power supply. This research aims to present a Cascade-Forward Neural Network (CFNN) droop control method that manages inverter-based microgrids under grid-connected/islanded operating modes. The proposed method operates the inverter in a bi-directional technique for a wide range of battery energy storage systems or any other distributed generation systems. The proposed strategy uses the CFNN to learn the inverter’s nonlinear model to achieve accurate demand and reference power tracking under different operating conditions for smart grid applications. Additionally, it reformulates the grid control concept to drive the inverter based on the optimal conditions by considering the power demand, reference power, equipment size, and disturbances. Also, it does not require any tuning procedure. The power tracking and operating performance of the proposed CFNN controller are evaluated through several experimental tests using the power hardware-in-the-loop (PHIL) methodology in different scenarios. All results are matched with the proven conventional strategy to confirm its effectiveness.

Experimental Study on Optimization of Filler Concentration of Silicon Rubber Compound Used in High Voltage Insulators

Abstract: In any power transmission system, insulators are essential for a reliable electrical power supply. The Efficiency of insulators will be decided by their electrical and mechanical properties. Recently in many of the power transmission systems, the conventional porcelain insulators are being replaced by polymeric insulators due to various advantages in their properties. Polymeric insulators have been increasingly popular in recent years as a result of their superior performance in contaminated environments due to their hydrophobic nature. However, research is still being carried out on Polymeric material with regards to ageing condition and feasibility for large scale utilization. Ageing of insulation is due to Environmental, Tracking and Erosion conditions. Ageing leads to immature failures and uncertainty in the performance of the insulators. The constituent materials and their properties have a significant impact on the performance of polymeric insulators. There is a strong need to look into newer filler materials which can be added to the existing polymeric base materials to constitute a composite. Keeping this in mind, in the proposed research uses Silicone rubber as base polymeric material and along with that additives are added to arrive at three different composites. A new filler material will be added to the base material forming a new composite. All these HTV Silicone rubber based composites are then tested the recovery of hydrophobicity, dielectric strength, hardness, specific gravity, tensile strength , ultimate elongation ,tear strength properties based on ASTM standards. Further, Inclined plane Tracking and Erosion studies are also conducted on the polymeric test samples for 6 hours to evaluate the SiR housing material suitability for outdoor insulator applications by subjecting them to AC high voltages under laboratory conditions as per IEC 60587 standards. Keywords: Recovery of hydrophobicity, dielectric strength, hardness, specific gravity, tensile strength, ultimate elongation, tear strength, inclined plane tracking and erosion, ageing, filler material.

Reliability-oriented operation of distribution networks with multi-microgrids considering peer-to-peer energy sharing

This paper aims to propose a comprehensive energy management system (CEMS) to simultaneously enhance the resilience of microgrids (MGs) and distribution network (DN) in a multi-microgrid (MMG) system against unexpected events. It also develops a reliability evaluation framework for the reliability evaluation of MMG distribution systems. In this regard, the proposed CEMS includes two main strategies: (1) networked operation mode (NOM), attributed to the cooperation of independent sub-sections (MGs/DN) in fault-affected portions. Here, each MG must exchange power with the DN and other MGs (may be islanded simultaneously) by participating in peer-to-peer (P2P) energy sharing to enhance resilience and reliability of the whole network, and (2) individual operation mode (IOM), comprising the grid-connected, optional islanding, fully forced islanding, and partial islanding modes for different operational requirements of MGs. Thus, the required information of an outage is identified. A suitable decentralized strategy based on the proposed CEMS and the novel adaptive problem formulation are initially used to operate such systems under different operating conditions. The NOM and IOM together assure the survivability of the whole system during the emergency periods and maintain reliable electric power supply for consumers while guaranteeing system stability indicators and ensuring operating costs of MGs. To substantiate these claims, we use different case studies to demonstrate the efficiency of the proposed CEMS based on a modified reliability test system. • A comprehensive energy management system is proposed for multi-microgrids. • An adaptive problem formulation is used for different operational requirements of microgrids. • The proposed method includes: networked operation mode and individual operation mode. • P2P energy sharing is proposed to enhance the resilience of system in networked operation mode. • Various case studies are conducted to study the system under normal and faulted operation modes.

Usulan Model Pemeliharaan Distribusi Tenaga Listrik Menggunakan Metode TRDX Untuk Meningkatkan Keandalan Pada Pelanggan Industri

Reliability of electricity supply is urgently needed by modern industry because disruptions can directly impact production levels, costs and company profitability. The purpose of this study is to determine the characteristics of the existing maintenance of electric power distribution to industrial customers of PT PLN (Persero) UP3 Karawang and to propose appropriate maintenance methods to improve its performance. The method used is a case study with data collected through observation, interviews, and analysis of relevant documents. The results of the study indicate that the trend of feeder disturbances during 2017-2020 has not met expectations, the realization of the average interruption frequency index (SAIFI) system continues to increase in succession 3.12; 3.85; 5.47; and 6.92 times/customer, as well as the realization of the system average interruption duration index (SAIDI) with an increasing trend, respectively, 182.97; 314.31; 1015.55; and 612 minutes/customer. The three highest causes of disturbances were jointing (39%), followed by third party causes (36%) and cubicle damage (15%). The author proposes the TRDX method to improve the reliability of electric power supply to industrial customers.

A fault location method of distribution network based on XGBoost and SVM algorithm

Nowadays, the reliable supply of electric power is vital in all aspects of social life. With the development and participation of distributed generations, not only does an accurate fault location lets repair of a fault line as quickly as possible, but also it is of great significance to ensure the safe and stable economic operation of the power system. This study proposes a method to determine the fault location in distribution networks, which is a combination of Extreme Gradient Boosting and Support Vector Machine. The effectiveness of the proposed method is validated on an IEEE34-bus distribution network under single-phase-to-ground faults, using voltage measurements available at each node in the distribution network. The comparison in accuracy, precision, recall, F1-score and time-cost of the method in this study with K-Nearest Neighbour and Multi-Layer Perceptron demonstrates the feasibility of applying the proposed method in distribution system fault diagnosis.