High-performance hybrid genetic algorithm to solve transmission network expansion planning

• Autor(a) principal: Gallego, Luis A.
• Data de Publicação: 2017
• Outros Autores: Garces, Lina P., Rahmani, Mohsen, Romero, Ruben A. [UNESP]
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Institucional da UNESP
• Texto Completo: http://dx.doi.org/10.1049/iet-gtd.2016.0511; http://hdl.handle.net/11449/162776
• topic: power transmission planning; genetic algorithms; linear programming; high-performance hybrid genetic algorithm; transmission network expansion planning; static transmission network expansion planning problem; multistage TNEP problem; high-performance HGA; path-relinking algorithm; constructive heuristic algorithm; fast relaxation strategy; linear programming problem; fitness function; South Brazilian 46-bus electrical system; Colombian 93-bus electrical system; North-Northeast Brazilian 87-bus electrical system

In this study, a high-performance hybrid genetic algorithm (HGA) is proposed to solve static and multistage transmission network expansion planning (TNEP) problem. The main features of the HGA are: (i) it avoids homogenised solutions by using a special genetic algorithm as the backbone of the procedure, (ii) uses a powerful path-relinking algorithm for the deep exploration of local solutions, (iii) employs an efficient constructive heuristic algorithm for finding high-quality initial solutions and for improving solution qualities and (iv) uses a fast relaxation strategy for solving the linear programming problems required for calculating the fitness functions. This procedure will result in an intelligent exploration of a large search space in less amount of time. The proposed methodology is tested with three electrical systems: South Brazilian 46-bus, Colombian 93-bus and the North-Northeast Brazilian 87-bus.