Ravi K

Department of Electrical Engineering

School of Electrical Engineering

Vellore Campus

Devabalaji K.R

Fulltext

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.

&nbsp;

&nbsp;

VIT University

Ain Shams Engineering Journal

International Transactions on Electrical Energy Systems

Loss minimization techniques for optimal operation and planning of distribution systems: A review of different methodologies

Alexandria Engineering Journal

Multi-objective simultaneous DG and DSTATCOM allocation in radial distribution networks using cuckoo searching algorithm

An efficient method for solving the optimal sitting and sizing problem of capacitor banks based on cuckoo search algorithm

Journal of Applied Research and Technology

Multi-objective simultaneous placement of DG and DSTATCOM using novel lightning search algorithm

This paper proposes a new approach to determine the optimal location and sizing of Distributed Generation (DG) and Distribution STATic COMpensator (DSTATCOM) simultaneously in the distribution network. The objective function is formulated to minimize the total power losses of the system subjected to equality and inequality constraints. Loss sensitivity factor (LSF) and Voltage Stability Index (VSI) are used to predetermine the optimal location of DG and DSTATCOM, respectively. Recently developed nature-inspired cuckoo search algorithm (CSA) has been used to determine the optimal size of both DG and DSTATCOM. In the present work, five different cases have been considered during DG and DSTATCOM placement to access the performance of the proposed technique. To check the feasibility, the proposed method is tested on IEEE 12-bus, 34-bus, and 69-bus radial distribution system and the results were compared with other existing techniques.

Modelling and Simulation in Engineering

Optimal Allocation of DG and DSTATCOM in Radial Distribution System Using Cuckoo Search Optimization Algorithm

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.

Swarm and Evolutionary Computation

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

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.

International Journal of Electrical Power & Energy Systems

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

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.

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

Applied Soft Computing

Study impact of various load models on DG placement and sizing using backtracking search algorithm

Optimal allocation of multi-type distributed generators using backtracking search optimization algorithm

Optimal size and siting of multiple DG and DSTATCOM in radial distribution system using Bacterial Foraging Optimization Algorithm

Journal	Data powered by TypesetAin Shams Engineering Journal
Publisher	Data powered by TypesetElsevier BV
ISSN	2090-4479
Open Access	Yes