Optimal Power Flow Using a Hybrid Optimization Algorithm of Particle Swarm Optimization and Gravitational Search Algorithm
Published 2015 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Optimal Power Flow Using a Hybrid Optimization Algorithm of Particle Swarm Optimization and Gravitational Search Algorithm
Authors
Keywords
-
Journal
ELECTRIC POWER COMPONENTS AND SYSTEMS
Volume 43, Issue 17, Pages 1958-1970
Publisher
Informa UK Limited
Online
2015-08-26
DOI
10.1080/15325008.2015.1061620
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Optimal power flow using Teaching-Learning-Based Optimization technique
- (2014) H.R.E.H. Bouchekara et al. ELECTRIC POWER SYSTEMS RESEARCH
- Multi-objective optimal power flow considering the cost, emission, voltage deviation and power losses using multi-objective modified imperialist competitive algorithm
- (2014) Mojtaba Ghasemi et al. ENERGY
- Hybrid optimisation method for optimal power flow using flexible AC transmission system devices
- (2014) Chao-Ming Huang et al. IET Generation Transmission & Distribution
- Spiral Optimization Algorithm for solving Combined Economic and Emission Dispatch
- (2014) Lahouaria Benasla et al. INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
- Adaptive biogeography based predator–prey optimization technique for optimal power flow
- (2014) A. Ananthi Christy et al. INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
- Optimal power flow using krill herd algorithm
- (2014) Provas Kumar Roy et al. International Transactions on Electrical Energy Systems
- A novel hybrid algorithm of imperialist competitive algorithm and teaching learning algorithm for optimal power flow problem with non-smooth cost functions
- (2013) Mojtaba Ghasemi et al. ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
- Artificial bee colony algorithm for solving multi-objective optimal power flow problem
- (2013) M. Rezaei Adaryani et al. INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
- Training feedforward neural networks using hybrid particle swarm optimization and gravitational search algorithm
- (2012) SeyedAli Mirjalili et al. APPLIED MATHEMATICS AND COMPUTATION
- Optimal Power Flow Using Adapted Genetic Algorithm with Adjusting Population Size
- (2012) Abdel-Fattah Attia et al. ELECTRIC POWER COMPONENTS AND SYSTEMS
- A novel approach to multi-objective optimal power flow by a new hybrid optimization algorithm considering generator constraints and multi-fuel type
- (2012) Mohammad Rasoul Narimani et al. ENERGY
- A new hybrid algorithm for optimal power flow considering prohibited zones and valve point effect
- (2012) Taher Niknam et al. ENERGY CONVERSION AND MANAGEMENT
- Optimal power flow using gravitational search algorithm
- (2012) Serhat Duman et al. ENERGY CONVERSION AND MANAGEMENT
- Optimal power flow using differential evolution algorithm
- (2010) A.A. Abou El Ela et al. ELECTRIC POWER SYSTEMS RESEARCH
- Multi-objective optimal power flow with FACTS devices
- (2010) M. Basu ENERGY CONVERSION AND MANAGEMENT
- Application of biogeography-based optimisation to solve different optimal power flow problems
- (2010) A. Bhattacharya et al. IET Generation Transmission & Distribution
- Enhanced Genetic Algorithm based computation technique for multi-objective Optimal Power Flow solution
- (2010) M. Sailaja Kumari et al. INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
- Optimal power flow using differential evolution algorithm
- (2009) A. A. Abou El Ela et al. ELECTRICAL ENGINEERING
- GSA: A Gravitational Search Algorithm
- (2009) Esmat Rashedi et al. INFORMATION SCIENCES
Become a Peeref-certified reviewer
The Peeref Institute provides free reviewer training that teaches the core competencies of the academic peer review process.
Get StartedAsk a Question. Answer a Question.
Quickly pose questions to the entire community. Debate answers and get clarity on the most important issues facing researchers.
Get Started