A genetic algorithm for solving the unit commitment problem of ahydro-thermal power system

摘要

The paper presents a two layer approach to solve the unitncommitment problem of a hydro-thermal power system. The first layer usesna genetic algorithm (GA) to decide the on/off status of the units. Thensecond layer uses a nonlinear programming formulation solved by anLagrangian relaxation to perform the economic dispatch while meeting allnplant and system constraints. In order to deal effectively with thenconstraints of the problem and prune the search space of the GA innadvance, the difficult minimum up/down-time constraints of thermalngeneration units and the turbine/pump operating constraint of storagenpower stations are embedded in the binary strings that are coded tonrepresent the on/off-states of the generating units. The othernconstraints are handled by integrating penalty costs into the fitnessnfunction. In order to save execution time, the economic dispatch is onlynperformed if the given unit commitment schedule is able to meet the loadnbalance, energy, and begin/end level constraints. The proposed solutionnapproach was tested on a real scaled hydro-thermal power system over anperiod of a day in half-hour time-steps for different GA-parameters. Thensimulation results reveal that the features of easy implementation,nconvergence within an acceptable execution time, and a highly optimalnsolution in solving the unit commitment problem can be achieved