Algoritmo tabu search especializado para o problema de planejamento da expansao de sistemas de transmissão

• Autor(a) principal: Khorasani, Hamid [UNESP]
• Data de Publicação: 2015
• Tipo de documento: Tese
• Idioma: eng
• Título da fonte: Repositório Institucional da UNESP
• Texto Completo: http://hdl.handle.net/11449/124514; http://www.athena.biblioteca.unesp.br/exlibris/bd/cathedra/18-06-2015/000836108.pdf
• topic: Sistemas de energia eletrica; Energia eletrica - Transmissão; Automação; Algoritmos; Algoritmos genéticos; TABU (Linguagem de programação de computador); Electric power systems

Transmission system plays an undeniable role to avoid load shedding, black out, etc. by supplying the power to all type of consumers under critical circumstances. A transmission network expansion planning (TNEP) enables a network to transmit enough generated power to load centers at a specified times to satisfy the increased electric power demand. In TNEP problem, in addition to satisfying all the technical constraints, an economic plan is demanded. The expansion of transmission network is one of the initiatives, in which the necessary decisions are made and planned at the national level to absorb significant financial resources. Therefore, planning for an optimal expansion project with the least cost and highest reliability is a crucial task. From the viewpoint of the structure of power systems, it can be stated that TNEP is analyzed in both regulated and deregulated environments. The main objective of TNEP in a regulated environment is to meet the load demand at the least cost while the reliability criterion is taken into account. On the other hand, in restructured power systems, the transmission expansion is primarily intended to create a competitive environment without any discrimination to access to the transmission network. This can perfectly ensure competitive markets. In general TNEP problem in regulated environments is a non-linear mixed integer programming problem, which subjects with some difficulties, such as the time- consuming nature of the problem as well as the need for a non-convex optimization technique. In addition, due to the complicacy of the combinatorial optimization problems and also, since there exist many local minima for this problem, it is considered as a time- consuming problem. Moreover, since the conventional mathematical programming methods do not necessarily work very satisfactorily, therefore, various meta-heuristic optimization techniques have been examined for this problem. However, the scope and ...