Abhisek Ukil

Distributed Temperature Sensing: Review of Technology and Applications

Distributed temperature sensors (DTS) measure temperatures by means of optical fibers. Those optoelectronic devices provide a continuous profile of the temperature distribution along the cable. Initiated in the 1980s, DTS systems have undergone significant improvements in the technology and the application scenario over the last decades. The main measuring principles are based on detecting the back-scattering of light, e.g., detecting via Rayleigh, Raman, and Brillouin principles. The application domains span from traditional applications in the distributed temperature or strain sensing in the cables, to the latest “smart grid” initiative in the power systems, etc. In this paper, we present comparative reviews of the different DTS technologies, different applications, standard, and upcoming, different manufacturers.

Development and Implementation of Parameterized FPGA-Based General Purpose Neural Networks for Online Applications

This paper presents the development and implementation of a generalized backpropagation multilayer perceptron (MLP) architecture described in VLSI hardware description language (VHDL). The development of hardware platforms has been complicated by the high hardware cost and quantity of the arithmetic operations required in online artificial neural networks (ANNs), i.e., general purpose ANNs with learning capability. Besides, there remains a dearth of hardware platforms for design space exploration, fast prototyping, and testing of these networks. Our general purpose architecture seeks to fill that gap and at the same time serve as a tool to gain a better understanding of issues unique to ANNs implemented in hardware, particularly using field programmable gate array (FPGA). The challenge is thus to find an architecture that minimizes hardware costs, while maximizing performance, accuracy, and parameterization. This work describes a platform that offers a high degree of parameterization, while maintaining generalized network design with performance comparable to other hardware-based MLP implementations. Application of the hardware implementation of ANN with backpropagation learning algorithm for a realistic application is also presented.

Reconfiguration and Load Balancing in the LV and MV Distribution Networks for Optimal Performance

To get the distribution network to operate at its optimum performance in an automated distribution system reconfiguration was been proposed and researched. Considering, however, that optimum performance implies minimum loss, no overloading of transformers and cables, correct voltage profile, and absence of phase voltage and current imbalances, network reconfiguration alone is insufficient. It has to be complemented with techniques for phase rearrangement between the distribution transformer banks and the specific primary feeder with a radial structure and dynamic phase and load balancing along a feeder with a radial structure. This paper contributes such a technique at the low-voltage and medium-voltage levels of a distribution network simultaneously with reconfiguration at both levels. While the neural network is adopted for the network reconfiguration problem, this paper introduces a heuristic method for the phase balancing/loss minimization problem. A comparison of the heuristic algorithm with that of the neural network shows the former to be more robust. The approach proposed here, therefore for the combined problem, uses the neural network in conjunction with a heuristic method which enables different reconfiguration switches to be turned on/off and connected consumers to be switched between different phases to keep the phases balanced. An application example of the proposed method using real data is presented.

Abrupt change detection in power system fault analysis using adaptive whitening filter and wavelet transform

This paper describes the application of the adaptive whitening filter and the wavelet transform used to detect the abrupt changes in the signals recorded during disturbances in the electrical power network in South Africa. Main focus has been to estimate exactly the time-instants of the changes in the signal model parameters during the pre-fault condition and following events like initiation of fault, circuit-breaker opening, auto-reclosure of the circuit-breakers. The key idea is to decompose the fault signals, de-noised using the adaptive whitening filter, into effective detailed and smoothed version using the multiresolution signal decomposition technique based on discrete wavelet transform. Then we apply the threshold method on the decomposed signals to estimate the change time-instants, segmenting the fault signals into the event-specific sections for further signal processing and analysis. This paper presents application on the recorded signals in the power transmission network of South Africa.

Application of Abrupt Change Detection in Power Systems Disturbance Analysis and Relay Performance Monitoring

This paper describes the application of the abrupt change detection technologies to detect the abrupt changes in the signals recorded during disturbances in the electrical power network of South Africa for disturbance analysis and relay performance monitoring. The aim is to estimate the time instants of the changes in the signal model parameters during the prefault condition, after initiation of fault, after the circuit-breaker opening and autoreclosure, etc. After these event-specific segmentations, the synchronization of the different digital fault recorder recordings are done based on the fault inception timings. The synchronized signals are segmented again. This synchronized segmentation is the first step toward automatic disturbance recognition, facilitating further complex feature vector analysis and pattern recognition. Besides, the synchronized, segmented recordings can be directly used to analyze certain kinds of disturbances and monitor the relay performance. This paper presents many practical examples from the power network in South Africa

Modeling and Validation of Electrical Load Profiling in Residential Buildings in Singapore

The demand of electricity keeps increasing in this modern society and the behavior of customers vary greatly from time to time, city to city, type to type, etc. Generally, buildings are classified into residential, commercial and industrial. This study is aimed to distinguish the types of residential buildings in Singapore and establish a mathematical model to represent and model the load profile of each type. Modeling household energy consumption is the first step in exploring the possible demand response and load reduction opportunities under the smart grid initiative. Residential electricity load profiling includes the details on the electrical appliances, its energy requirement, and consumption pattern. The model is generated with a bottom-up load model. Simulation is performed for daily load profiles of 1 or 2 rooms, 3 rooms, 4 rooms and 5 rooms public housing. The simulated load profile is successfully validated against the measured electricity consumption data, using a web-based Customer Energy Portal (CEP) at the campus housings of Nanyang Technological University, Singapore.

Smart distribution protection using current-only directional overcurrent relay

Overcurrent relays are widely used for power systems protection. Transmission side uses more directional type relays, while distribution systems, e.g., radial and ring-main subtransmission systems use non-directional types. The fault direction may be forward (between relay and grid), or reverse (between relay and source), the normal power flow being from source to the grid. Traditional directional overcurrent relays utilize the reference voltage phasor for estimating the direction of the fault. This requires measurement of both current and voltage using respective sensors. This makes the directional overcurrent relays more costly than the non-directional type. In this paper, a novel current-only directional detection possibility is highlighted along with theoretical and test signal analysis. Possible utilization of the current-only directional relay for intelligent directional protection in the distribution systems are described. Directional protection for distribution systems is a key focus area for enabling the smart grid.

Current-Only Directional Overcurrent Protection for Distribution Automation: Challenges and Solutions

Overcurrent relays are widely used for power systems protection. Transmission side uses more directional type relays, while distribution systems, e.g., radial and ring-main subtransmission systems use nondirectional types. The fault direction may be forward (between relay and grid), or reverse (between relay and source), the normal power flow being from source to the grid. Traditional directional overcurrent relays utilize the reference voltage phasor for estimating the direction of the fault. This requires measurement of both current and voltage using respective sensors. This makes the directional overcurrent relays more costly than the nondirectional type. In this paper, a novel current-only directional detection possibility is highlighted along with theoretical, test signal analysis, challenges and associated solutions. Possible utilizations of the current-only directional relay in the distribution side protection are described, which is a key focus area for enabling the smart grid.

Current-Only Directional Overcurrent Relay

Overcurrent relays are widely used for protection of power systems, directional ones for transmission side, and nondirectional ones for distribution side. The fault direction may be forward (between relay and grid), or reverse (between relay and source), the normal power flow being from source to the grid. Known directional overcurrent relays rely on a reference voltage phasor for estimating the direction of the fault, requiring both current and voltage sensors. This increases the cost of the relays, prohibiting the utilization of such relays in the distribution side protection and automation, which is going to be a key part in the smart grid initiative. In this paper, a novel current-only directional detection possibility is highlighted.

Wavelet based fault analysis in HVDC system

HVDC system has become practically mature over the years but it is still met with some protection issues which should be discussed, for example, the circuit breaker (CB) should be selective to not trip if the transient is temporary, such as overcurrent due to load change. This paper addresses the problem with identifying the type of faults in a HVDC system using wavelet transform (WT). The wavelet transform is proven to be able to capture the distinctive feature of the fault pattern, specifically fault current rising time and oscillation pattern, which are helpful to form a basis for the tripping decision. Three phase-to-ground fault and DC fault are of concern in this paper as their effects are the most detrimental to the system. The point-to-point HVDC system is simulated using PSCAD, and the simulation result is subsequently processed in MATLAB to perform the wavelet transform.