A genetic algorithm to solve the thermal unit commitment problem

2014 ◽  
Vol 5 (4) ◽  
pp. 344
Author(s):  
Yacine Labbi ◽  
Djilani Benattous
Keyword(s):  
Genetic Algorithm ◽  
Unit Commitment ◽  
Thermal Unit ◽  
Unit Commitment Problem ◽  
Commitment Problem

scholarly journals Advanced Method for Unit Commitment Problem Using Genetic Algorithm and Mathematical Programming

1999 ◽  
Vol 119 (3) ◽  
pp. 333-343 ◽  
Author(s):  
Toru Takata ◽  
Junichi Takahashi ◽  
Hiroomi Yokoi ◽  
Hiroshi Nakano ◽  
Mari Aoyagi ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Mathematical Programming ◽  
Unit Commitment ◽  
Unit Commitment Problem ◽  
Advanced Method ◽  
Commitment Problem

Enhanced Genetic Algorithm with Guarantee of Feasibility for the Unit Commitment Problem

2008 ◽  
pp. 291-302 ◽  
Author(s):  
Guillaume Sandou ◽  
Stéphane Font ◽  
Sihem Tebbani ◽  
Arnaud Hiret ◽  
Christian Mondon
Keyword(s):  
Genetic Algorithm ◽  
Unit Commitment ◽  
Unit Commitment Problem ◽  
Commitment Problem

scholarly journals Stochastic Unit Commitment Problem, Incorporating Wind Power and an Energy Storage System

2020 ◽  
Vol 12 (23) ◽  
pp. 10100
Author(s):  
Khalid Alqunun ◽  
Tawfik Guesmi ◽  
Abdullah F. Albaker ◽  
Mansoor T. Alturki
Keyword(s):  
Energy Storage ◽  
Wind Power ◽  
Unit Commitment ◽  
Mixed Integer ◽  
Master Problem ◽  
Thermal Unit ◽  
Unit Commitment Problem ◽  
Battery Energy Storage ◽  
Commitment Problem ◽  
Battery Energy

This paper presents a modified formulation for the wind-battery-thermal unit commitment problem that combines battery energy storage systems with thermal units to compensate for the power dispatch gap caused by the intermittency of wind power generation. The uncertainty of wind power is described by a chance constraint to escape the probabilistic infeasibility generated by classical approximations of wind power. Furthermore, a mixed-integer linear programming algorithm was applied to solve the unit commitment problem. The uncertainty of wind power was classified as a sub-problem and separately computed from the master problem of the mixed-integer linear programming. The master problem tracked and minimized the overall operation cost of the entire model. To ensure a feasible and efficient solution, the formulation of the wind-battery-thermal unit commitment problem was designed to gather all system operating constraints. The solution to the optimization problem was procured on a personal computer using a general algebraic modeling system. To assess the performance of the proposed model, a simulation study based on the ten-unit power system test was applied. The effects of battery energy storage and wind power were deeply explored and investigated throughout various case studies.

An MILP Formulation for the Thermal Unit Commitment Problem Considering Start-Up and Shut-Down Power Trajectories

2014 ◽  
Vol 672-674 ◽  
pp. 493-498 ◽  
Author(s):  
Jun Deng ◽  
Hua Wei
Keyword(s):  
Unit Commitment ◽  
Mixed Integer ◽  
Test Case ◽  
Thermal Unit ◽  
Unit Commitment Problem ◽  
Binary Variables ◽  
Computational Performance ◽  
Start Up ◽  
Commitment Problem ◽  
Mixed Integer Linear Formulation

This paper presents a mixed-integer linear formulation for the thermal unit commitment problem considering the start-up and shut-down power trajectories. A realistic and accurate modeling of the unit’s operating phase is given, which includes the phases of start-up, dispatchable and shut-down. The start-up type is decided by the unit’s prior off-line time. The start-up costs and power trajectories depend on the type of start-up. A new set of binary variables is introduced to represent the dispatchable status, which can decrease the binary variables and constraints significantly. Finally, a test case study is analyzed to verify the correctness and show the computational performance of the proposed formulation.

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