Open AccessVoltage Profile Assessment in Distribution Substation using Generalized Regression Neural Network
Author(s) -
A. Shiny Pradeepa,
C. Vaithilingam
Publication year - 2019
Publication title -
international journal of recent technology and engineering
Language(s) - English
Resource type - Journals
ISSN - 2277-3878
DOI - 10.35940/ijrte.b3249.078219
Subject(s) - electric power system , artificial neural network , computer science , voltage , convergence (economics) , stability (learning theory) , power flow study , ac power , power (physics) , control theory (sociology) , iterative method , mathematical optimization , engineering , algorithm , mathematics , artificial intelligence , machine learning , electrical engineering , physics , control (management) , quantum mechanics , economic growth , economics
Power system stability is one of the major factors for the reliable operation of electric utilities. Factors resulting power system instability are the sudden increase in load or insufficient reactive power support. Efficient Voltage regulation methods enable the system to operate in a stable operating condition. Many methods reported in the literature for voltage stability assessment of the power system such as optimization method, continuation power flow method, Indices based method and Artificial Intelligence based methods. Several iterative methods are used for the solution of load flow problems. The major disadvantages of iterative methods are larger iteration and increase in convergence time which depends on size of the power system. This paper proposes new method for voltage profile assessment on distribution system using Generalized Regression Neural Network. The Power System Analysis Toolbox (PSAT) is used for Distribution power flow solution. The proposed method is tested using 52 buses, distribution system of Tirunelveli, Tamil Nadu India. The technical feasibility of the proposed method is verified by comparing the results of proposed method and PSAT