Fuzzy unit commitment using absolutely stochastic simulated annealing

This paper presents a new approach to fuzzy unit commitment problem using absolutely stochastic simulated annealing method. In every iteration, a solution is taken with a certain probability. Typically in simulated annealing minimization method, a higher cost feasible solution is accepted with temperature dependent probability, but other solutions are accepted deterministically. However in this paper, all the solutions, both the higher and the lower cost, are associated with acceptance probabilities, i.e. minimum membership degree of all fuzzy variables. Besides, number of bits flipping is decided by linguistic fuzzy control. Excess units with system dependent distribution handle constraints efficiently and reduce overlooking the optimal solution. To reduce economic load dispatch (ELD) calculation, sign bit vector is introduced with imprecise calculation of fuzzy model as well. The proposed method is tested using the reported problem data set. Simulation results are compared to previous reported results. Numerical results show an improvement in solution cost and time compared to the results obtained from powerful algorithms