Open AccessNew Strategy Based on Combined Use of Genetic Algorithm and Gradient to Solve the UC Problem: Theoretical Investigation and Comparative Study
Author(s) -
Sahbi Marrouchi,
Moez Ben Hessine,
Souad Chebbi
Publication year - 2018
Publication title -
international journal of engineering and technology
Language(s) - English
Resource type - Journals
ISSN - 2227-524X
DOI - 10.14419/ijet.v7i3.13.16322
Subject(s) - mathematical optimization , genetic algorithm , convergence (economics) , discretization , computer science , metaheuristic , population , margin (machine learning) , algorithm , mathematics , machine learning , mathematical analysis , demography , sociology , economics , economic growth
This paper presents a comparative study between a new strategy based on hybrid Gradient-Genetic Algorithm method and metaheuristic methods for solving Unit Commitment problem. Strategies have been applied on the IEEE electrical network 14 bus test system for a variable load profile during a discretized margin of time (24-hour time requirement). The right choice of the initial population and the best knowledge of the technical constraints specific to each generator (power balance constraints, Spinning reserve constraints, minimum up time, minimum down time ) suggests the possibility of obtaining improvements in the time execution. The adopted strategy has presented high performance both for minimizing the production cost and for the rapidity of convergence to optimal solutions and is promising compared to Genetic algorithm.