Decision Strategies based on Metaheuristics for Distribution Network Planning

• Type: Article in International Conference Proceedings Book
• Date: 2000

Authors

Teresa Ponce de Leão (Author) FEUP; Manuel Matos (Author) FEUP; José António Dominguez-Navarro (Author) FEUP; Ignacio J. Ramírez-Rosado (Author) FEUP

Conference proceedings International

Title: Proceedings of the 6th PMAPS - Int. Conf. on Probabilistic Methods Applied to Power Systems

Pages: 1-8

6th PMAPS - Int. Conf. on Probabilistic Methods Applied to Power Systems

Scientific classification

FOS: Engineering and technology > Other engineering and technologies

Other information

Abstract (EN): The classical distribution network planning problem involves deciding network investments to meet future demand at minimum cost while meeting technical restrictions. The decision whether to construct facilities and branches leads to a mixed integer programming problem with a great number of decision variables. The great deal of uncertainty associated with data that cannot be modeled using probabilistic methods leads to the use of fuzzy models to capture the uncertainty. In addition several criteria must be taken into account resulting in a fuzzy multiobjective problem. However this problem has reached maturity and researchers have recognized [1, 3, 7 e 8], that the problem must be dealt with as a decision problem were uncertainty and risk must be explicitly modeled. The combinatorial nature of the problem limits the use of traditional mathematical tools to limited size problems. This contribution presents a basic description of the application of two meta-heuristic methods to deal with the combinatorial decision problem taking into account uncertainties in loads and investment costs. These heuristic methods, SIMULATED ANNEALING and TABU SEARCH, will be evaluated and compared taking into account their performances and the quality of solutions provided. We will focus on the simplicity and versatility of these methods, its analogies and its conceptual differences. A case study allows a compared analysis and stands out for the advantages over traditional methods.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 8