Transmission network expansion planning using state-of-art nature inspired algorithms: a survey. (2019)

• Record Type: Journal Article
• Authors: Khandelwal, Ashish; Bhargava, Annapurna; Sharma, Ajay; Sharma, Harish
• Is Part Of: International journal of swarm intelligence. Volume 4:Number 1(2019)
• Page Start: 73
• Page End: 92
• Publication Date: 2019
• Subjects: genetic algorithm -- particle swarm optimisation -- PSO -- differential evolution -- artificial bee colony algorithm -- ABC -- ant colony optimisation -- ACO -- harmony search algorithm -- spider monkey optimisation -- SMO -- grey wolf optimisation -- GWO; Swarm intelligence -- Periodicals; 006.3
• Languages: English
• ISSNs: 2049-4041

Abstract

Transmission network expansion planning (TNEP) problem has been continuously solved for many years still the cost effective, reliable, and optimise solution is always desirable. The TNEP has been solved by various conventional and non conventional strategies. The strategy to find the solution of TNEP by classical mathematical optimisation techniques is tedious, slow and inefficient. In recent years, nature inspired algorithms (NIAs) have proven their importance to provide the solutions of the TNEP problem over classical mathematical optimisation techniques. This paper presents a review on the key contributions of the state-of-art NIAs to solve the TNEP problem. Further, the TNEP system specific significant works presented in the literature are summarised for easy understanding of the readers. The readers can get a brief description of the considered NIAs algorithms which has been applied to solve various systems of TNEP problem and they can also identify the significant NIA which is being applied for specific TNEP system.