TY - GEN
T1 - Unit commitment with non-smooth generation cost function using binary particle swarm optimization
AU - Wibowo, Rony Seto
AU - Utama, Fahrizal Fitra
AU - Putra, Dimas Fajar Uman
AU - Aryani, Ni Ketut
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2017/1/20
Y1 - 2017/1/20
N2 - This paper deals with generation unit scheduling, well known as unit commitment (UC). Rather than using quadratic generation cost function, this paper utilizes non-smooth generation cost function (NSGCF). As NSGCF is difficult to handle using conventional technique such as quadratic programming, the metaheuristic technique, particle swarm optimization in this case, is used to solve the economic dispatch which is part of UC. In this UC, minimum up time, minimum down time, start up cost and shunt down cost are considered. In addition, spinning reserve is taken into account. Because UC is mix-integer optimization problem, Binary Particle Swarm Optimization (BPSO) is applied to complete UC. To show the effectiveness of the approach, system with 6 generators is utilized.
AB - This paper deals with generation unit scheduling, well known as unit commitment (UC). Rather than using quadratic generation cost function, this paper utilizes non-smooth generation cost function (NSGCF). As NSGCF is difficult to handle using conventional technique such as quadratic programming, the metaheuristic technique, particle swarm optimization in this case, is used to solve the economic dispatch which is part of UC. In this UC, minimum up time, minimum down time, start up cost and shunt down cost are considered. In addition, spinning reserve is taken into account. Because UC is mix-integer optimization problem, Binary Particle Swarm Optimization (BPSO) is applied to complete UC. To show the effectiveness of the approach, system with 6 generators is utilized.
KW - Binary Particle Swarm Optimization
KW - Non-Smooth generation cost function
KW - Spinning Reserve
KW - Unit Commitment
UR - http://www.scopus.com/inward/record.url?scp=85016751898&partnerID=8YFLogxK
U2 - 10.1109/ISITIA.2016.7828723
DO - 10.1109/ISITIA.2016.7828723
M3 - Conference contribution
AN - SCOPUS:85016751898
T3 - Proceeding - 2016 International Seminar on Intelligent Technology and Its Application, ISITIA 2016: Recent Trends in Intelligent Computational Technologies for Sustainable Energy
SP - 571
EP - 576
BT - Proceeding - 2016 International Seminar on Intelligent Technology and Its Application, ISITIA 2016
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2016 International Seminar on Intelligent Technology and Its Application, ISITIA 2016
Y2 - 28 July 2016 through 30 July 2016
ER -
