P. Venkatesh

Siddhartha Medical College

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Co-Authors

S. Charles Raja

Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology

J. Jeslin Drusila Nesamalar

Tamil Nadu Government Dental College and Hospital

B.V. Manikandan

Vellore Institute of Technology University

P. Chitra

Sri Eshwar College of Engineering

M. K. Kavitha Devi

SRM Institute of Science and Technology

S. Arockia Edwin Xavier

Madurai Medical College

Narayana Prasad Padhy

Indian Institute of Technology Roorkee

Aravind Srinivasan

Thiagarajar College of Engineering

R. Rajaram

Thiagarajar College of Engineering

S. Balamurugan

Jain University

Cooperative Institutions

Madurai Medical College

Thiagarajar College of Engineering

Anna University, Chennai

Vellore Institute of Technology University

Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology

SRM Institute of Science and Technology

Sathyabama Institute of Science and Technology

PSG INSTITUTE OF TECHNOLOGY AND APPLIED RESEARCH

Sri Venkateswara University

Dr. N.G.P. Institute of Technology

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Application of Multi Objective Evolutionary Programming to Combined Economic Emission Dispatch Problem

IEEE International Conference on Neural Networks/IEEE ... International Conference on Neural Networks (2007)

D.N. Jeyakumar P. Venkatesh Kwang Y. Lee

This paper describes a new multi-objective evolutionary programming (MOEP) method to solve the combined economic emission dispatch (CEED) problem. CEED is a multi-objective optimization problem by considering the fuel cost and emission as the objectives. It is converted into single objective optimization problem using weighted sum method. Hence the MOEP is proposed by employing the non-dominated solution ranking as selection mechanism for the bi-objective CEED problem. The developed algorithm is tested for a three-unit and a six-unit system. The results demonstrate the capabilities of the proposed approach to generate well-distributed Pareto optimal solutions of the multi-objective CEED problem in a single run.

Economic Dispatch

10.1109/ijcnn.2007.4371122

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Citations (30)

Smoothing approach to alleviate the meager rating problem in collaborative recommender systems

Future Generation Computer Systems (2011)

M. K. Kavitha Devi P. Venkatesh

MovieLens

Benchmark (surveying)

Smoothing

Kernel (algebra)

Backpropagation

Multilayer perceptron

10.1016/j.future.2011.05.011

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Citations (16)

Multi-Objective Evolutionary Programming for Economic Emission Dispatch problem

P. Venkatesh Kwang Y. Lee

This paper describes a new multi-objective evolutionary programming (MOEP) method to solve the combined economic emission dispatch (CEED) and economic emission dispatch (EED) problems. The CEED is a bi-objective optimization problem that considers two objectives such as fuel cost and NO _x emission. It is converted into a single objective optimization problem using weighted sum method. The EED is a three-objective optimization problem that considers the fuel cost, NO _x and SO ₂ emissions as objectives. Non-dominated solution ranking is employed as selection mechanism in the proposed MOEP for the CEED and EED problems. The developed algorithm is tested for a three-unit and a six-unit systems, and six and 30 bus systems. The results demonstrate the capabilities of the proposed approach to generate well-distributed Pareto optimal solutions of the multi-objective problems in a single run.

Economic Dispatch

10.1109/pes.2008.4596896

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Citations (42)

Comparative Study of Two Congestion Management Methods for the Restructured Power Systems

Journal of Electrical Engineering and Technology (2011)

B.V. Manikandan S. Charles Raja P. Venkatesh Manasarani Mandala

Congestion management

Transmission system

10.5370/jeet.2011.6.3.302

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Citations (8)

Kernel based collaborative recommender system for e-purchasing

Sadhana (2010)

M. K. Kavitha Devi P. Venkatesh

Relevance

Empirical Research

10.1007/s12046-010-0035-8

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Citations (8)

Transaction cost allocation in deregulated power system using an analytical method

International Conference on Energy Efficient Technologies for Sustainability (2013)

S. Jeyasankari J. Jeslin Drusila Nesamalar S. Charles Raja P. Venkatesh

In the new deregulated environment, transmission cost allocation is one of the major challenges due to the increase of power transactions in transmission open access faced by the electric power sector. In this paper, Transaction Impact Factors (TIFs) are developed with respect to each transaction and used for the allocation of usage based transmission transaction costs. These factors relate the real power flow in the lines with the transacted power. This analytical method provides the impact of line flows without running power flow solution when the amount of transacted power changes in real time. The proposed method is evaluated by considering bilateral and multilateral transactions, and compared with Megawatt Modulus (MM) method on sample six bus and IEEE 30 bus systems.

Power transmission

Sample (material)

10.1109/iceets.2013.6533539

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Citations (1)

Document Content Analysis Based on Random Forest Algorithm

Lecture notes in networks and systems (2020)

N. Sardar Basha K Manjunath Mohan Kumar Naik P. S. Ashok Kumar P. Venkatesh

Intension

Ridiculous

10.1007/978-981-15-3284-9_55

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Citations (1)

Silicone Rubber MgO Nanocomposite for High Voltage Outdoor Insulation Application

R. Rajan Prakash P. Venkatesh M. Kottaisamy S. Arockia Edwin Xavier

This paper deals with the experimental studies of the Electrical properties of silicone rubber filled with Magnesium Oxide (MgO) nanofillers at low filler concentration by weight (1% - 3%). The silicone rubber nanocomposite samples are prepared by mastication process. The structure and morphology studies of the composites are studied using X – Ray Diffraction and scanning electron microscopy techniques. The thermogravimetric analysis shows that the thermal stability of the silicone rubber is enhanced on addition of the nanofillers. The frequency dependence of the dielectric properties like ac conductivity, relative permittivity and loss tangent are studied. The ac dielectric strength, the arc resistance properties and the mechanical properties are also studied as a function of filler concentration. The results show that even at low filler concentrations, the nanocomposite demonstrates a remarkable enhancement in dielectric constant, arc resistance and mechanical strength which can be applied for many existing electrical systems.

Silicone rubber

Thermogravimetric analysis

Dissipation factor

Thermal Stability

Dielectric loss

Filler (materials)

10.15866/iree.v8i5.2122

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Citations (1)

Multiobjective evolutionary computation algorithms for solving task scheduling problem on heterogeneous systems

International Journal of Knowledge-based and Intelligent Engineering Systems (2010)

P. Chitra P. Venkatesh

The task scheduling problem in heterogeneous systems (TSPHS) is a NP-complete problem. It is a multiobjective optimization problem (MOP). The objectives such as makespan, average flow time, robustness and reliability of the schedule are con

10.3233/kes-2010-0187

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Citations (4)

A Perfomance study of Ann and Anfis Controller for Statcom in dSpace Environment

Journal of Electrical Engineering (2013)

S. Arockia Edwin Xavier P. Venkatesh M. Saravanan

Reactive power compensation is an important issue in the control of electric power system. Reactive power from the source increases the transmission losses and reduces the power transmission capability of the transmission lines. Moreover, reactive power should not be transmitted through the transmission line to a longer distance. Hence Flexible AC Transmission Systems (FACTS) devices such as static compensator (STATCOM) unified power flow controller (UPFC) and static volt-ampere compensator (SVC) are used to alleviate these problems. In this paper, a voltage source converter (VSC) based STATCOM is developed with Artificial Neural Network Controller (ANNC) and Adaptive Neuro Fuzzy Inference System(ANFIS) controllers. The conventional PI controller has more tuning difficulties while the system parameter changes, whereas a trained neural network and ANFIS controllers requires less computation time. They have the ability to generalize and can interpolate in between the training data. The ANNC and ANFIS controllers designed were tested on a 75 V, 100 VA STATCOM in real time environment via state-of-the-art of digital signal processor advanced control engineering (dSPACE) DS1104 board and it was found that ANFIS controller was producing better results than the ANNC.

Static VAR compensator

10.2478/jee-2013-0023

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Citations (0)