Rama Prabha D

Department of Electrical Engineering

School of Electrical Engineering

Vellore Campus

Jayabarathi T

Saranya S

Umamageswari R

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

Sustainable Energy Technologies and Assessments

Fulltext

International Transactions on Electrical Energy Systems

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

International Journal of Ambient Energy

Optimal reconfiguration and renewable distributed generation allocation in electric distribution systems

Renewable energy sector is undergoing rapid expansion as the global focus is shifting towards cleaner, reliable and sustainable resources. As the new installation of these resources are well underway, there is tremendous potential for exploring these to more advanced control algorithms. Model predictive control is gaining immense popularity because of its flexible controllability, its ability to be used in any of application irrespective of its field as well as the availability of fast processors. This paper presents a systematic review on Photo-voltaic (PV) and wind energy systems controlled by Model predictive control approach. The work presented here will help the researchers to further explore the flexibility of this controller for design, analysis and implementation in renewable energy systems. © 2017 Elsevier Ltd

Renewable and Sustainable Energy Reviews

A review on state of art development of model predictive control for renewable energy applications

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

International Journal of Recent Trends in Engineering and Research

Voltage Profile Improvement of Distribution System by Optimal Placement of Distributed Generator

IEEE Transactions on Power Systems

Optimal Placement and Sizing of Distributed Generators in Unbalanced Distribution Systems Using Supervised Big Bang-Big Crunch Method

IET Generation, Transmission & Distribution

Analytical approach for optimal siting and sizing of distributed generation in radial distribution networks

International Journal of Electrical Power & Energy Systems

A MINLP technique for optimal placement of multiple DG units in distribution systems

Optimal location and sizing of distributed generation unit using intelligent water drop algorithm

Journal	Data powered by TypesetSustainable Energy Technologies and Assessments
Publisher	Data powered by TypesetElsevier BV
ISSN	2213-1388
Open Access	0