Nature inspired algorithms for transmission network expansion planning problems: a review. (17th March 2023)

• Record Type: Journal Article
• Authors: Rajoria, Divya; Sharma, Ajay
• Is Part Of: International journal of intelligent engineering informatics. Volume 10:Number 6(2022)
• Page Start: 435
• Page End: 463
• Publication Date: 2023-03-17
• Subjects: TNEP -- transmission network expansion planning -- swarm intelligence -- NIAs -- nature-inspired algorithms -- metaheuristic -- optimisation; Artificial intelligence -- Engineering applications -- Periodicals; Engineering -- Computer programs -- Periodicals; Knowledge management -- Periodicals; 620.0028563
• Languages: English
• ISSNs: 1758-8715

Abstract

Transmission network expansion planning (TNEP) is a significant problem in the field of the power system. The TNEP deals with the required expansion of the existing networks in the planning process based on future load requirements. The solution to the TNEP problem was carried out mathematically in the past decades. In the meantime, the complexity of TNEP increased due to increased load demand. Looking at the present complex nature of the TNEP, the outcomes provided by mathematical methods were not up to the mark. Researchers of various domains are working on nature-inspired algorithms (NIAs) nowadays to solve complex real-world problems. In this series, this paper is an attempt to enlist the significant contributions in the field of NIAs to solve the TNEP problem. The categorisation of the reviewed literature is carried out based on different types of NIAs. Also, different types of TNEP, namely static TNEP (STNEP), dynamic TNEP (DTNEP), and hybrid TNEP (HTNEP) have been considered for the review. Further, the advantages and limitations of various contributions are also presented along with specific recommendations.