Multiperiod optimal planning of thermal generation using cross decomposition

This work addresses the Multiperiod Optimal Planning of Thermal Generation (MOPTG). The model considered is based on a Unit Commitment Problem that has multiperiod character and determines the start up and shut down schedules of thermal plants considering the line capacity limits of transmission and...

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Bibliographic Details
Published in:Journal of computer & systems sciences international 2011-10, Vol.50 (5), p.793-804
Main Authors: Marmolejo, J. A., Litvinchev, I., Aceves, R., Ramirez, J. M.
Format: Article
Language:English
Subjects:
Algorithms
Computation
Control
Control Systems for Technological Processes
Decomposition
Electricity distribution
Engineering
Generators
Integer programming
Linear programming
Mathematical analysis
Mathematical models
Mechatronics
Mixed integer
Numerical analysis
Operating costs
Optimization
Optimization techniques
Power plants
Reserve requirements
Robotics
Strategy
Studies
Thermal energy
Unit commitment
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Summary:This work addresses the Multiperiod Optimal Planning of Thermal Generation (MOPTG). The model considered is based on a Unit Commitment Problem that has multiperiod character and determines the start up and shut down schedules of thermal plants considering the line capacity limits of transmission and line losses. The mathematical model is stated in the form of a Mixed Integer Non Linear Problem (MINLP) with binary variables. To reduce the computational time caused by the large number of time periods and electric generation nodes we apply the Generalized Cross Decomposition [1, 2]. The later exploits the structure of the problem to reduce solution time by decomposing the MOPTG into a primal subproblem, which is a Non Linear Problem (NLP), a dual subproblem, which is a MINLP, and a Mixed Integer Problem (MIP) called master problem. The approach is compared with Lagrangean Relaxation [3] and Generalized Benders Decomposition [4], To demonstrate the efficiency of the proposed decomposition strategy we present numerical results obtained for three test systems. The computational experiments show the superiority of the Cross Decomposition approach.
ISSN:1064-2307
1555-6530
DOI:10.1134/S1064230711050145