Vellore Institute of Technology (VIT) is a private university located in&nbsp;Tamil Nadu, India. Founded in 1984, as Vellore Engineering College, the institution offers 20 undergraduate, 34 postgraduate, four integrated and four research programs. It has campuses in Vellore, Amravati, Bhopal and Chennai.

VIT is one of the top ranked private universities in India according to NIRF, THE and QS Rankings.&nbsp;Govt. of India has recognized&nbsp;VIT, Vellore as an&nbsp;Institution of Eminence. This has allowed VIT to take independent quality initiatives and move up in world ranking.

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VIT University

Optimal size and location of shunt capacitors in the distribution system plays a significant role in minimizing the energy loss and the cost of reactive power compensation. This paper presents a new efficient technique to find optimal size and location of shunt capacitors with the objective of minimizing cost due to energy loss and reactive power compensation of distribution system. A new Shark Smell Optimization (SSO) algorithm is proposed to solve the optimal capacitor placement problem satisfying the operating constraints. The SSO algorithm is a recently developed metaheuristic optimization algorithm conceptualized using the shark's hunting ability. It uses a momentum incorporated gradient search and a rotational movement based local search for optimization. To demonstrate the applicability of proposed method, it is tested on IEEE 34-bus and 118-bus radial distribution systems. The simulation results obtained are compared with previous methods reported in the literature and found to be encouraging. © 2016 Faculty of Engineering, Ain Shams University

World University root node

Electrical

School of Electrical Engineering

Chennai Campus

Fulltext

Ain Shams Engineering Journal

Optimal placement of capacitors in radial distribution system using shark smell optimization algorithm

Nowadays the number of consumers in the distribution system is increasing, the electricity demand and the number of capacitor bank placement is also increasing. Improper placement of capacitor bank leads to decrease the benefits of the system. The objective function of the proposed work is to minimize the total power loss of the system while satisfying all the constraints. The Loss Sensitivity Factor (LSF) has implemented to pre-identify the optimal location of the capacitor. An effective biologically inspired algorithm (Bat Algorithm) is proposed to search the optimal size of the capacitor banks. The proposed method has been tested on IEEE 34-bus distribution system to demonstrate the performance and effectiveness of the technique. © 2015 The Authors. Published by Elsevier Ltd.

VIT Unitversity

Department of Electrical Engineering

Vellore Campus

Energy Procedia

Power Loss Minimization in Radial Distribution System

Optimal location and size of distributed generation (DG) in the distribution system play a significant role in minimizing power losses, operational cost and improving voltage stability. This paper presents a new approach to find the optimal location and size of DG with an objective of minimizing network power losses, operational costs and improving voltage stability. Loss sensitivity factor is used to identify the optimal locations for installation of DG units. Bacterial Foraging Optimization Algorithm (BFOA) is used to find the optimal size of DG. BFOA is a swarm intelligence technique which models the individual and group foraging policies of the Escherichia coli bacteria as a distributed optimization process. The technical constraints of voltage and branch current carrying capacity are included in the assessment of the objective function. The proposed method has been tested on IEEE 33-bus and 69-bus radial distribution systems with various load models at different load levels to demonstrate the performance and effectiveness of the technique. © 2013 Elsevier B.V. © 2014 Elsevier Inc. © 2013ElsevierB.V. Allrightsreserved.

Department of Energy and Power Electronics

Swarm and Evolutionary Computation

Optimal size and siting of multiple distributed generators in distribution system using bacterial foraging optimization

This paper presents a novel integration technique for optimal network reconfiguration and distributed generation (DG) placement in distribution system with an objective of power loss minimization and voltage stability enhancement. Fireworks Algorithm (FWA) is used to simultaneously reconfigure and allocate optimal DG units in a distribution network. FWA is a new swarm intelligence based optimization algorithm which is conceptualized using the fireworks explosion process of searching for a best location of sparks. The radial nature of the network is secured by generating proper parent node-child node path of the network during power flow. Voltage Stability Index (VSI) is used to pre-identify the optimal candidate locations for DG installation. Six different scenarios are considered during DG placement and reconfiguration of network to assess the performance of the proposed technique. Simulations are carried out on well-known IEEE 33- and 69-bus test systems at three different load levels. The simulated results demonstrate well the performance and effectiveness of the proposed method. © 2014 Elsevier Ltd. All rights reserved.

International Journal of Electrical Power & Energy Systems

A novel integration technique for optimal network reconfiguration and distributed generation placement in power distribution networks

In this paper, a new efficient method to solve the network reconfiguration with an objective of improving power loss minimization and voltage profile of the distribution system is presented. A new Meta-heuristics Fireworks Algorithm (FWA) is proposed to optimize the radial distribution network while satisfying the operating constraints. FWA is a recently developed swarm intelligence based optimization algorithm which is conceptualized using the fireworks explosion process of searching for a best location of sparks. Network reconfiguration is formulated as a complex combinatorial optimization problem. The radial nature of the system is secured by generating proper parent node-child node path of the network during power flow. To demonstrate the applicability of the proposed method, it is tested on a standard IEEE 33- and 119-bus system. The simulated results are compared with other methods available in the literature. It is observed that the performance of proposed method is better than the other methods in terms of quality of solutions. Different abnormal cases are also considered during reconfiguration of network to study the effectiveness of the proposed method and the results obtained are found to be encouraging. © 2014 Elsevier Ltd. All rights reserved.

A new power system reconfiguration scheme for power loss minimization and voltage profile enhancement using Fireworks Algorithm

This paper presents a new combined technique for minimizing the power loss in distribution system by optimal Distributed Generation (DG) installation together with capacitor placement. Sensitivity analysis is used to identify the optimal candidate locations of DGs and capacitor placement. Bacterial Foraging Optimization Algorithm (BFOA) is applied to find the optimal size of DGs and capacitors. BFOA is a swarm intelligence technique which models the individual and group foraging policies of the E. coli bacteria as a distributed optimization process. The technical constraints of voltage and branch current carrying capacity are included in the assessment of the objective function. Different cases of DG and capacitor placement are considered to assess the performance of the proposed method. Proposed method has been tested on IEEE 33-bus radial distribution system and the results obtained are encouraging. © 2014 IEEE.