Transmission lines forms the backbone of the transmission and distribution networks which powers the nation. No modern society can imagine its existence without power supplies which runs everything ranging from consumer electronics to bullet trains. Electrical power systems suffer from unexpected failures due to various random causes. Unpredicted faults that occur in power systems are required to prevent from propagation to other area in the protective system. The functions of the protective systems are to detect, then classify and finally determine the location of the faulty line of voltage and/or current line magnitudes. Then at last, for isolation of the faulty line the protective relay have to send a signal to the circuit breaker. The ability to learn, generalize and parallel processing, pattern classifiers is powerful applications of machine learning used as an intelligent means for detection. This research paper focuses on detecting, classifying and locating faults on electric power transmission lines. Fault detection and fault classification have been achieved by using support vector machines. The SVM based classifier is trained on the fault database to classify transient single phase to ground faults. Simulation results have been provided to demonstrate that Support Vector Machine based methods are efficient in locating faults on transmission lines and achieve satisfactory performances. Simulation of three phase transmission line is done in MATLAB and results are compared in context of the fault classification and fault location.

http://www.ijirst.org/articles/IJIRSTV1I12057.pdf

Fault Classification in Electric Power Transmission Lines using Support Vector Machine

The use of DC distribution networks has several advantages, especially for energy saving and integration of energy storage system and renewable energies. In this regard, DC nano-grids are a very interesting solution when distributing electrical power in households. In this paper, an analysis about the possible bidirectional capability of this DC nano-grid is presented. The end-user can freely connect either a passive load (demanding power) or an active one (able to sink current to the grid). The analysis is divided into three different parts. First, a discussion about the most promising power architecture is addressed, taking into consideration the loads in a house. Second, a standard for voltage regulation in a bidirectional DC nano-grid is proposed. Finally, a possible bus provider for this particular bidirectional DC nano-grid is also addressed. This power converter is based on a Dual Active Bridge cascaded with five synchronous buck converters. The key design aspects of the proposed topology are analyzed to emphasize the particular constraints imposed by the standard and the power architecture. A 500 W, 380 V to 24 V bidirectional bus provider has been built in order to experimentally validate the standard proposal and the design aspects.

https://www.mdpi.com/1996-1073/12/19/3715/pdf

On Bidirectional DC Nano-Grids: Design Considerations and an Architecture Proposal

The impact of new technologies within and across industries is only felt through their widespread diffusion, yet studies of technology diffusion are scarce compared to other aspects of the innovation process. The electric power industry is one industry that is currently undergoing substantial change as a result of both technological and institutional innovations. In this dissertation I examine the economic rationale for the adoption of smart meters by electric power utilities and the relationship between smart meters and the evolving electric power industry. I contribute to empirical research on technology diffusion by studying the early diffusion of smart meters in the US electric power industry. Using a panel dataset and econometric models, I analyze the determinants of both the interfirm and intrafirm diffusion of smart meters in the United States. The empirical findings suggest multiple drivers of smart meter diffusion. Policy and regulatory support have had a significant, positive impact on adoption but have not been the only relevant determinants. The findings also suggest that utility characteristics and some combination of learning, cost reductions, and technology standards have been important determinants affecting smart meter diffusion. I also explore the policy implications resulting from this analysis for enhancing the diffusion of smart meters. The costs and benefits of adopting smart meters have been more uncertain than initially thought, suggesting that some policy support for adoption was premature. The coordination of policies is also necessary to achieve the full benefits of using smart meters.

The early diffusion of smart meters in the US electric power industry

The paper begins by outlining the difficulties which faced the early electrical entrepreneurs when they tried to devise methods of charging for electricity supply which were fair, accurate and economic. It discusses the alternatives to fully metered supplies, and also the arguments about the relative merits of energy and quantity meters. The major part of the paper describes the most important types of electricity supply meter and how they developed over a period of about ten years from the opening in 1882 of Edison's Holborn Viaduct electricity supply system, where meters were first used. Detailed technical descriptions of the meters are not given, but references to this information are quoted where possible. An attempt is made to show how widely the different designs of meter were used and to give the opinions of contemporary engineers about them.

C.N. Brown

Papers

Charging for electricity in the early years of electricity supply