By Topic

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

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Rudolf, A. ; Program & Syst. Eng., Siemens AG, Austria ; Bayrleithner, R.

The paper presents a two layer approach to solve the unit commitment problem of a hydro-thermal power system. The first layer uses a genetic algorithm (GA) to decide the on/off status of the units. The second layer uses a nonlinear programming formulation solved by a Lagrangian relaxation to perform the economic dispatch while meeting all plant and system constraints. In order to deal effectively with the constraints of the problem and prune the search space of the GA in advance, the difficult minimum up/down-time constraints of thermal generation units and the turbine/pump operating constraint of storage power stations are embedded in the binary strings that are coded to represent the on/off-states of the generating units. The other constraints are handled by integrating penalty costs into the fitness function. In order to save execution time, the economic dispatch is only performed if the given unit commitment schedule is able to meet the load balance, energy, and begin/end level constraints. The proposed solution approach was tested on a real scaled hydro-thermal power system over a period of a day in half-hour time-steps for different GA-parameters. The simulation results reveal that the features of easy implementation, convergence within an acceptable execution time, and a highly optimal solution in solving the unit commitment problem can be achieved

Published in:

Power Systems, IEEE Transactions on  (Volume:14 ,  Issue: 4 )