Unit commitment using a stochastic extended neighbourhood search

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© IEE
Published 30/07/2012

Abstract

A simulated annealing is combined with a tabu search, to develop a robust and powerful optimisation technique for solving the unit commitment problem. The problem is broken down into a combinatorial subproblem in unit status variables and a quadratic programming subproblem in unit power output variables. The combinatorial subproblem is solved using the proposed method. In the hybrid algorithm, which is referred to as a stochastic extended neighbourhood search, simulated annealing is used as the main stochastic algorithm, and a tabu search is used as an extended neighbourhood search, to locally improve the solution obtained by simulated annealing. The neighbourhood search uses local domain-knowledge, which results in rapid convergence of the simulated annealing algorithm. The results obtained for several example systems illustrate the potential of the hybrid approach.

Inspec keywords: search problems; combinatorial mathematics; simulated annealing; stochastic processes; power generation scheduling; power generation dispatch; quadratic programming; power generation planning

Other keywords: tabu search; stochastic extended neighbourhood search; unit power output variables; combinatorial subproblem; optimisation technique; quadratic programming subproblem; unit commitment; unit status variables; simulated annealing

Subjects: Combinatorial mathematics; Generating stations and plants; Power system planning and layout; Optimisation techniques; Power system management, operation and economics

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