Designing modern heuristic algorithms to solve the Transmission Expansion Planning problem

• Type: Article in International Conference Proceedings Book
• Date: 2021-06-27

Authors

João Tomé Saraiva (Author) FEUP; Phillipe Vilaça (Author) Other; J. Manuel Colmenar (Author) Other; Abraham Duarte (Author) Other

Conference proceedings International

Title: 2021 IEEE MADRID POWERTECH

Pages: 1-6

14th IEEE Madrid PowerTech Conference (IEEE POWERTECH)

ELECTR NETWORK, JUN 28-JUL 02, 2021

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ScienceDirect (Elsevier)

Scientific classification

CORDIS: Technological sciences > Engineering > Electrical engineering

FOS: Engineering and technology > Electrical engineering, Electronic engineering, Information engineering

Other information

Authenticus ID: P-00V-N7Y

DOI: 10.1109/powertech46648.2021.9494932

Abstract (EN): Transmission Expansion Planning (TEP) aims at identifying a list of new assets to be installed on the transmission grid to meet the long-term forecasted demand while ensuring a safe supply over the entire planning horizon. As TEP is a Mixed Integer Non-Linear Problem (MINLP) with a huge search space, in the last years several modern heuristic algorithms were proposed to deal with its challenging characteristics. In this way, this paper describes and evaluates the impact and implementation of four operators that can be easily incorporated in any evolutionary algorithm, namely: Neighborhood Search for Local Improvement (NSLI), Diversity Control (DC), Elitist Reproduction (ER) and Boundary Local Search (BLS). The impact of these operators is assessed and discussed over a hundred simulations using a traditional Genetic Algorithm (GA) and a well-known test system, the RTS 24-bus. Regarding the results, the NSLI and the BLS operator considerably improved the GA performance in solving the TEP problem regarding both the final value of the objective function and the diversity of solutions.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 6