Electrical Assets Research Articles

THE KEY SUCCESS FACTOR OF GEOGRAPHIC INFORMATION SYSTEM RE-IMPLEMENTATION IN TENAGA NASIONAL BERHAD DISTRIBUTION, MALAYSIA: A CASE STUDY OF CHERAS TENAGA NASIONAL BERHAD DISTRIBUTION STATION

Tenaga Nasional Berhad (TNB) Distribution has embarked on the development of a Geographical Information System (GIS) since the year 2009. The scope of work is to map and digitize all TNB distribution electrical assets and to systematically establish the customer’s database. In this study, a review on the GIS implementation was carried out at Cheras TNB Distribution station. The low utilization of GIS contributes the most to the need of having the GIS reviewed. The aim of the study is to develop a revised strategy for a successful GIS re-implementation in TNB Distribution electrical network based on the results from the review process. Its objectives are to develop and evaluate strategize plan for the re-implementation based on GIS components after reviewing and analysing the existing implementation. Key success factor (KSF) is introduced to deliver a success GIS project re-implementation. Data from previous implementation, survey, workshop and feedback from user of TNB Cheras staff are used for references when developing the strategies. GIS components are capitalized to establish KSF criteria in order to measure the successfulness of the re-implementation. System Usability Scale (SUS) is used for interpreting the KSF outcome. The study is finally ended with the development and evaluation of the proposed strategize plan for the re-implementation of four GIS components which are System and Tools, Data, Business Process and User. The proposed strategy is used to determine the effectiveness of the re-implementation strategies and KSF in order to drive the future invasion of GIS application to other TNB Distribution stations in Malaysia.

Application of Meta-Heuristic Approaches in the Spectral Power Clustering Technique (SPCT) to Improve the Separation of Partial Discharge and Electrical Noise Sources

In order to achieve an adequate diagnosis of the insulation system in any electrical asset it is necessary to carry out a proper separation process after measuring partial discharges (PD), since during the data acquisition it is very likely that simultaneous PD sources and electrical noise have been measured. Clearly, such separation will simplify the subsequent identification process, because the analysis will be done individually for each of the sources and not over the total of the signals. In this sense, the Spectral Power Clustering Technique (SPCT) has proven to be an effective technique when separating multiple sources acting simultaneously in a monitoring process. The effectiveness of this separation technique is fundamentally based on the proper selection of frequency bands or separation intervals, where the spectral power of the pulses is different for each source. In the case of selecting the wrong bands, the clusters will overlap, hiding the presence of the total number of sources. This research evaluates the performance of different meta-heuristic algorithms when applied to the SPCT for selecting separation intervals. The results obtained from the measurements made in different test objects will allow determining the most appropriate technique for separating PD sources and electrical noise acting simultaneously over an insulation system.

Localization of partial discharge in transformer oil using Fabry-Pérot optical fiber sensor array

Partial discharge is the main reason for insulation deterioration and failure of high voltage electrical asset. Thus, the online detection and localization of partial discharge can provide the information on the equipment degradation characteristics, and moreover, is of great value for improving the safe operation of the power grid and the developing of optimal maintenance. Accounting for the good sensitivity, the high immunity to electromagnetic interference, the compact size with outstanding insulation level, the Fabry-Perot optical fiber sensor is attracting increasing attention as a promising way for online acoustic partial discharge localization. In this study, the partial discharge localization in the transformer oil is realized by an ultrasonic detection system, which is consisting of 2×2 Fabry-Perot optical fiber sensor array with steered response power algorithm. In general, the Fabry-Perot optical fiber acoustic sensor array shows good direction sharpness, and achieves accurate localization. This detection and localization system is further applied to a 35 kV transformer single-phase winding and verified with partial discharges on the outer winding.

City-Friendly Smart Network Technologies and Infrastructures: The Spanish Experience

Efficient, resilient, and sustainable electricity delivery is a key cornerstone in increasingly large and complex urban environments, where citizens expect to keep or rise their living standards. In this context, cost-effective and ubiquitous digital technologies are driving the transformation of existing electrical infrastructures into truly smart systems capable of better providing the services a low-carbon society is demanding. The goal of this paper is twofold: 1) to review the dramatically evolving landscape of power systems, from the old framework based on centralized generation and control, aimed at serving inelastic customers through alternating current (ac) transmission networks and one-way distribution feeders, to a new paradigm centered mainly around two main axes: renewable generation, both centralized and distributed, and active customers (prosumers), interacting with each other through hybrid ac/dc smart grids; 2) to illustrate, through featured success stories, how several smart grid concepts and technologies have been put into practice in Spain over the last few years to optimize the performance of urban electrical assets.

Impact of Demand Side Response on a Commercial Retail Refrigeration System

The UK National Grid has placed increased emphasis on the development of Demand Side Response (DSR) tariff mechanisms to manage load at peak times. Refrigeration systems, along with HVAC, are estimated to consume 14% of the UK’s electricity and could have a significant role for DSR application. However, characterized by relatively low individual electrical loads and massive asset numbers, multiple low power refrigerators need aggregation for inclusion in these tariffs. In this paper, the impact of the Demand Side Response (DSR) control mechanisms on food retailing refrigeration systems is investigated. The experiments are conducted in a test-rig built to resemble a typical small supermarket store. The paper demonstrates how the temperature and pressure profiles of the system, the active power and the drawn current of the compressors are affected following a rapid shut down and subsequent return to normal operation as a response to a DSR event. Moreover, risks and challenges associated with primary and secondary Firm Frequency Response (FFR) mechanisms, where the load is rapidly shed at high speed in response to changes in grid frequency, is considered. For instance, measurements are included that show a significant increase in peak inrush currents of approx. 30% when the system returns to normal operation at the end of a DSR event. Consideration of how high inrush currents after a DSR event can produce voltage fluctuations of the supply and we assess risks to the local power supply system.

Analysis of water use by gated communities in South Africa

Gated communities (hereafter GCs) are popular in many countries, including South Africa, because added security and lifestyle improvements are offered relative to homes built on freestanding properties. One of the key factors for the popularity of GCs is the availability of amenities to support the demands of the residents, such as gymnasia, walkways, golf courses, play parks and polo fields. Further benefits include the improved management of infrastructure such as telecommunication services, roads, water, sewer, electrical and stormwater assets. GCs are often governed by trustees or homeowners’ associations, responsible for the operation and the maintenance functions of the infrastructure, as well as implementing and adhering to legislation that pertains to the GC. As part of this study, the monthly water-use records of 2 888 GCs in 3 different South African cities were analysed. Water use was evaluated for each GC as a whole, and also per household in each case. The average number of homes per GC was 33 households/GC, with the smallest GC in the study sample containing 3 houses and the largest 524 houses. One of the study sites was in the winter rainfall region, while 2 sites were in the summer rainfall region. The average annual water use of individual households in each GC was plotted against current guidelines and was found to be relatively low. The average annual daily demands of all properties in the winter rainfall region was 0.63 kL/d, compared to 0.66 kL/d and 0.49 kL/d for the two study sites in the summer rainfall region. The results highlighted peculiarities in the water use of GCs that have not been reported on before, in particular the relatively low water use and the differences between GC homes’ water use in the various rainfall regions.

Real‐time condition monitoring of substation equipment using thermal cameras

The recent trend of decreasing reliability of the existing power grid due to various kinds of equipment failures at the transmission and distribution level, has led the researchers to develop advanced protection techniques. In distribution systems, the conventional substations are getting transformed to digital substations in the light of upcoming advanced technologies. The key component of such a digital substation is substation monitoring control center (SMCC). This study proposes a novel algorithm for the real-time condition monitoring of substation equipment using thermal images obtained from thermal cameras. The processing of these is done at the remote terminal unit by extracting the speeded-up robust features and passing the same through trained adaptive neuro fuzzy inference system (ANFIS) and support vector machine (SVM) classifier. The information based on the output at the SVM/ANFIS classifier is sent to the SMCC where appropriate actions are taken by the substation engineer. This novel real-time monitoring of substation equipment overcomes the drawbacks of the conventional methodology of manual inspection done at a periodic interval thereby preventing the electrical assets from failure before any catastrophe would happen. Also, a comparative study establishes the superiority of SVM over ANFIS in identifying the critical fault conditions using thermal imaging.

Paesaggi elettrici e nuove economie: valori, patrimoni, responsabilità sociali e management

A fronte di imponenti operazioni di ristrutturazione industriale -in particolare di ripensamento di tutto il processo economico di produzione dell’energia- che coinvolgono molte aree dell’Occidente (e non solo), una questione emergente è quella dei patrimoni “elettrici” dismessi e della riqualificazione dei contesti su cui sono localizzati. Il percorso della valorizzazione –di fatto consolidato disciplinarmente- per questo comparto offre suggestioni di ricerca e di dibattito con alcuni elementi di innovazione: 1) una reinterpretazione della teoria del valore e delle sue componenti classiche; 2) la sinergia tra interventi architettonici e interventi economici strutturali; 3) l’urgenza di operazioni di censimento, di costruzione di conoscenza attraverso banche dati e nuovi flussi di informazioni; 4) il control management dei processi. Il contributo ha l’intento di ripercorrere lo stato dell’arte sul tema e di rileggerlo alla luce dei nuovi approcci di valorizzazione uniti ad un’ottica ambientale e di economia circolare. Fanno da supporto a tale analisi critica, la lettura di casi nazionali italiani (a partire dalle operazioni condotte da Enel) ed internazionali, dove si stanno già generando esternalità, intangibile e benefici attesi oltre che plusvalori economici.

Condition monitoring of electrical assets using digital IRT and AI technique

In this paper, an advancement approach considering an infrared thermography methodology is taken into account for pronouncing and diagnosing the fault persisting in the electrical equipment. This technology is mainly focused on non-contact and non-destructive property. It is a fast and reliable technique to inspect system without any interruption. In the field of the electrified area, maintenance and reliability of transmission and distribution system are one of the most critical issue which mostly suffers from few problems like loose connection, corrosion, and unbalanced loads. The loose connection arise the sag and corrosion on wire produce the more corona loss. In this paper, non-invasive method is employed to monitor the temperature of zinc oxide (ZnO) surge arrester. Surge arrester is utilized to analyze the hot region and exercise the watershed transform for the image segmentation and hot color mapping. Detection of hot regions is resembled through dark red color. Monitoring of surge arrester leakage current (SALC) is the main consideration to solve out the problems through infra-red thermo-gram (IRT) and artificial intelligence (AI) techniques. Artificial neural network (ANN) techniques utilized monitoring the condition of arrester within input constraints; arrester temperature, ambient temperature and humidity. These constraints are implemented to find out leakage current. The proposed method detects the hotness, hot region of the ZnO arrester and a relationship between the thermal characteristic and leakage current of surge arrester for condition monitoring.

Self-healing materials for autonomous cable repair

Self-healing materials are capable, when damaged, of responding to restore the pre-damage properties of an asset. This is of particular interest for high-value electrical assets which cannot be routinely accessed for preventive maintenance or repair, such as underground or offshore cables. The incorporation of self-healing materials would effectively allow these systems to maintain themselves, resulting in enhanced resilience, lower failure rates, and longer operational lifetimes. Here, the authors demonstrate self-repair systems for extruded polymeric cables containing an extruded polymer self-repair layer, and self-healing fluids for legacy fluid-filled circuits. Both self-healing candidates have been formulated for their specific applications and demonstrate excellent efficacy, with ability to move to large-scale trials planned for the near future in advance of routine deployment.

An Ensemble-Boosting Algorithm for Classifying Partial Discharge Defects in Electrical Assets

This paper presents an ensemble-boosting algorithm (EBA) for classifying partial discharge (PD) patterns in the condition monitoring of insulation diagnosis applied for electrical assets. This approach presents an optimization technique for creating a sequence of artificial neural network (ANNs), where the training data for each constituent of the sequence is selected based on the performance of previous ANNs. Four different PD faults scenarios were manufactured in the high-voltage (HV) laboratory to simulate the PD faults of cylindrical voids in methacrylate, point-air-plane configuration, ceramic bushing with contaminated surface and a transformer affected by the internal PD. A PD dataset was collected, pre-processed and prepared for its use in the improved boosting algorithm using statistical techniques. In this paper, the EBA is extensively compared with the widely used single artificial neural network (SNN). Results show that the proposed approach can effectively improve the generalization capability of the PD patterns. The application of the proposed technique for both online and offline practical PD recognition is examined.

The Need for a Whole Life Framework in Electrical Power System Asset Management and the Problems with Individual Silo like Asset Management System Contributions

The asset management of electrical power systems both in industry and academia currently offers up a wide spectrum of engineering practices and guidance to detect, diagnose and to combat asset deterioration. In doing so research largely aims to better enable enhanced decision or prediction making in single engineering applications such as partial discharge or dielectric condition measurements. This paper reviews the current state of the art as related to electrical asset management and sets out how todays engineering and maintenance heavy approaches are insufficient to meet the nature of the complex adaptive (Generation, Transmission & Distribution) systems. Furthermore this paper explains the need for a truly holistic governance framework capable of managing such complexities for power companies by using complex adaptive system science whilst grounded in the engineering, business and socio-technical attributes that applied engineering makes possible. In addition this paper outlines how utilising retroductive case study with hypothesis framework represents the best approach in creating such a fully holistic asset management capability for power companies.

Study on the self-integration of a Rogowski coil used in the measurement of partial discharges pulses

The maintenance of high-voltage power systems requires the determination of the amplitude and waveforms of fast current pulses that commonly occur in electric equipment. These high-frequency pulses may arise from different sources being partial discharges one of the most important events measured to determine the insulation status of electrical assets. This paper is a step forward in the modelling of Rogowski coils, which are commonly used to measure these pulses. This study was performed by means of a simplified model based on lumped electrical parameters. The model was simulated in Simulink and validated by measuring partial discharges (PD) in two different electrical insulation systems. The validation corroborates that the electrical model can be used to study the time and frequency responses of Rogowski coils with different number of turns and dimensions to obtain a configuration that fits the needs of the designer concerning the type of pulses that she/he wishes to measure. The paper also hints that changing the geometric parameters of the coil can be determinant to simplify the integration of pulses, so the Rogowski coil can be used to measure other type of pulses with different frequency spectra, such as lightning strikes, electrical arcs and post-arc phenomena, switching operations of circuit breakers and gas-insulated switchgears and electromagnetic pulses in general.

Integration of GIS with Survey Data for Electrical Asset Mapping in Robertsganj town of India

GIS based consumer indexing and electrical network mapping delivers a tool for consumer, asset and electrical load management for actual decision making in the power sector and its database applications can increase the utility’s efficiency if appropriately integrated with other business developments. In India, the power submission department continuously wishes to update their consumer data and the related electric asset features. The consumer’s data source has to be recorded and show the pertinent linkages with the distribution transformer (DTR), feeder and substation. The present paper mainly focus on the application of geographic information system (GIS) integrated with high resolution remote sensing data and field survey data for mapping of various electrical asset elements of Roberstganj town of Uttar Pradesh, India. The electrical assets like high tension line (HT), low tension lines (LT), distribution transformers (DTRs), various types of electrical poles, feeders, substations etc. of Robertsganj town are extensively surveyed using the high resolution remote sensing data and then updated on GIS platforms using ARC GIS-10.3 software. The exact location of each electrical asset elements of the study area is captured using GPS and same has been plotted on the remote sensing data. In the study area electrification rate is low which approximately 50-60% is and quality power supply is still a faraway. It is identified that the total HT and LT pole in 2011 is 959 and 1421 respectively while it is 1733 and 1899 in 2015. Electric data base prepared though GIS is very useful for decision making, future planning and study such as locations of dangerous poles, load on a specific transformer or location of loose jumpers of HT/LT lines

The Values of Incentive Regulations and Comprehensive Framework for Electrical Asset Management: An Iranian/Tehran Province Perspective

Asset management framework and its incentive economic equations are represented in this paper. To this end, asset management process conducted to realize distribution targets, are considered and a comprehensive framework of these activities is represented. This framework can be utilized in planning and evaluation of distribution system. On the basis of asset management comprehensive framework, economic equations are formulated and regulation indices are determined. Afterwards, method that regulates key indices is described. This method is conformed to distribution targets. At the final step, numerical studies on Tehran Province Regional Electrical Distribution Company (TPREDC) are presented. In TPREDC activities were done with few incentives, therefore productivity and benefit had reduced. After implementation of proposed internal regulation, it can be seen that key indices have been improved.

Performance evaluation of noise reduction method during on-line monitoring of MV switchgear for PD measurements by non-intrusive sensors

• Novel application of a new sensor for PD measurements in air insulated switchgear. • Description of different noise, causing interference during online monitoring. • De-noising of measured PD signals through Discrete Wavelet Transform (DWT). • Performance evaluation of the de-noising method. • Self adaptive de-noising approach through flow chart. Partial Discharge (PD) measurement is a globally accepted method for insulation diagnosis of electrical assets. The consequences of insulation breakdown are well known. The trend is to move from conventional offline testing to online monitoring for insulation life prediction, which results in the inclusion of high frequency noise in the captured signals. Therefore de-noising is of paramount importance in online monitoring to obtain useful information from the signal. In this research, a 20 kV switchgear panel has been subjected to PD faults in the laboratory and measurements have been carried out by using different non-intrusive sensors including a novel sensor, the D -dot sensor and recorded by a high frequency oscilloscope. The measured results show the effective applicability of sensors for switchgear. The Discrete Wavelet Transform (DWT) has been used to de-noise PD signals in this paper. Time domain and frequency domain comparison of original and de-noised PD signals reveals the significance of this technique for online monitoring of Medium Voltage (MV) switchgear. Finally, an adaptive online de-noising concept, based on automatic de-noising is also proposed in this paper.

Design of early fault detection technique for electrical assets using infrared thermograms

Infrared thermography is a non destructive temperature measuring technique, widely used in agriculture, process industries, manufacturing, pharmaceutical industries, and construction industries to detect anomalies, to predict possible faults, or to check the quality of the object. In this paper, two systems, real time and off line, are proposed to monitor the temperature variations and analyze hot regions in the electrical assets using infrared thermograms. This novel technique helps to prevent the electrical assets before any catastrophe would happen in the future. The color based segmentation technique is used to blotch hot regions in the thermograms of electrical systems. A redness area based algorithm is also proposed to analyze the hot regions and also to estimate rate of change of hotness in electrical assets for early detection and prediction of faults.

Envisioning resilient electrical infrastructure: A policy framework for incorporating future climate change into electricity sector planning

Abstract Climate change needs to be incorporated in future designs of the electricity sector. This paper argues for a policy framework in which utilities take the lead by performing an electrical climate change impact assessment that evaluates to what extent utilities’ electrical assets are vulnerable to future climate change. Based on this assessment, electrical climate change adaptation plans should be formulated by the utility in cooperation with utility regulators, municipalities and supralocal governments. A collaborative process is essential, because adaptation measures need to be tailored to the regional circumstances and many types of adaptation measures require governmental approval. In order for the most sustainable and cost-efficient measures to be selected, cooperation between governments, utilities and utility regulators is necessary.

Tailoring the Electrical Properties of Graphene Layers by Molecular Doping

It is an essential issue in graphene-based nanoelectronic and optoelectronic devices to tune the electrical properties of graphene layers, while preserving its unique band structure. Here, we report the tuning of electronic properties of single-, bi-, and trilayer mechanically exfoliated graphenes by p-toluenesulfonic acid (PTSA) molecular doping. Raman spectroscopy and charge transport measurements revealed that PTSA molecule imposes n-doping to single-, bi-, and trilayer graphenes. The shift of G and 2D peak frequencies and intensity ratio of single-, bi-, and trilayer graphenes are analyzed as a function of reaction time. The Dirac point is also analyzed as a function of reaction time indicates the n-type doping effect for all single-, bi-, and trilayer graphenes. Our study demonstrates that chemical modification is a simple approach to tailor the electrical properties of single-, bi-, and trilayer graphenes, while maintaining the important electrical assets.

Partial discharge diagnostics: from apparatus monitoring to smart grid assessment

Partial discharges (PD) are very familiar in the electrical insulation world. A phenomenon able to reveal or cause incipient failure, as well as need of maintenance, of an electrical apparatus must play a fundamental role in the development of electrical asset diagnosis and design.