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This paper proposes a new foraging ABC algorithm that integrates the features of ABC and Tabu search (TS) to solve the profit-based unit commitment (PBUC) problem in deregulated electricity market with emission limitations. The multiobjective optimisation problem is formulated to maximise the profit and minimise the pollutants into the atmosphere by satisfying all the system constraints. ABC algorithm is applied to solve the 1-0 part of the PBUC problem and lambda iterative method optimises the economic load dispatch problem. The ideas of Tabu array (TA) and logical aspiration factor are applied to adjust the search process in the solution space. The proposed TS-enhanced ABC algorithm is verified on IEEE 39 bus test system having 10 generating units for 24-h load pattern. The solutions of traditional UC and PBUC with and without emission limitations are compared with improved ABC shuffled frog leaping algorithm, Muller's and ACO method.

international journal of metaheuristics

Tabu search-enhanced artificial bee colony algorithm to solve profit-based unit commitment problem with emission limitations in deregulated electricity market