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PID controller for automatic voltage regulator using teaching-learning based optimization technique

INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2016年第May期77卷 418-429页

作者： Chatterjee, Shamik Mukherjee, V. Indian Sch Mines Dept Elect Engn Dhanbad 826004 Jharkhand India

The present work presents teaching-learning based optimization (TLBO) algorithm as an optimization technique in the area of tuning of the classical controller installed in automatic voltage regulator (AVR). The proposed TLBO algorithm is applied with an aim to find out the optimum value of proportional integral derivative (PID) controller gains with first order low pass filter installed in the AVR The voltage response of the AVR system, as obtained by using the proposed TLBO based PID controller with first order low pass filter, is compared to those offered by the other algorithms reported in the recent state-of-the-art literatures. The advantage of using this control strategy may be noted by providing good dynamic responses over a wide range of system parametric variations. For on-line, off-nominal operating conditions, fast acting Sugeno fuzzy logic technique is applied to obtain the on-line dynamic responses of the studied model. Furthermore, robustness analysis is also carried out to check the performance of the designed TLBO based PID controller. An analysis, based on voltage response profile, has been investigated with the variations of the model parameters. The simulation results show that the proposed TLBO based PID controller is a significant optimization tool in the subject area of the AVR system. The essence of the present work signifies that the proposed TLBO technique maybe, successfully, applied for the AVR of power system. (C) 2015 Elsevier Ltd. All rights reserved.

关键词： Automatic voltage regulator figure of demerit Sugeno fuzzy logic (SFL) Teaching-learning based algorithm

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Performance Evaluation of Evolutionary Programming and Hybrid Evolutionary Programming for LMP Determination at Spot Electricity Market

Performance Evaluation of Evolutionary Programming and Hybri...

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IEEE International Conference on Power and Energy (PECon)

作者： Tambe, Varada Jayant Roy, Ranjit Sardar Vallabhbhai Natl Inst Technol Dept Elect Engn Surat India

ISBN: (纸本)9781467350198

The paper evaluates performance of Evolutionary Programming (EP) and Hybrid Evolutionary Programming (HEP) algorithm to find optimum Locational Marginal Price (LMP) at various buses of an IEEE-9 bus test system for load variation of 24 hours duration. Based on the figure of demerit, it is found that Hybrid Evolutionary Program yields superior results compared to Evolutionary Program.

关键词： Evolutionary Programming figure of demerit Hybrid Evolutionary Programming Locational Marginal Price

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