TY - GEN
T1 - Security Constrained Unit Commitment Considering Ramp Rate and Transmission Line Losses Using Binary Particle Swarm Optimization Based on IEEE 30 Bus System
AU - Aryani, Ni Ketut
AU - Putra, Dimas Fajar Uman
AU - Arifin, Elpha Aulia
AU - Daroini, Ahmad Saad
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/8
Y1 - 2019/8
N2 - The amount of power generation every time changes according to load demand. In order to get the optimal amount of power generation, a unit commitment study is needed with the aim of obtaining a combination of generation that meets the demand at the cheapest cost. In the calculation of the Unit Commitment, there are constraints that must be considered, Those are the minimum up and down time, spinning reverse, ramp rate, power balance, start-up cost, and power balance. To get a combination of generators that meet the required limits, there are several artificial intelligence algorithms approach, one of the algorithms is Binary Particle Swarm Optimization (BPSO). In this paper, a unit commitment study will be implemented on IEEE 30 bus system by considering ramp rate and transmission line power losses using the Binary Particle Swarm Optimization (BPSO) algorithm to obtain the most optimal combination of generation with the lowest generation costs.
AB - The amount of power generation every time changes according to load demand. In order to get the optimal amount of power generation, a unit commitment study is needed with the aim of obtaining a combination of generation that meets the demand at the cheapest cost. In the calculation of the Unit Commitment, there are constraints that must be considered, Those are the minimum up and down time, spinning reverse, ramp rate, power balance, start-up cost, and power balance. To get a combination of generators that meet the required limits, there are several artificial intelligence algorithms approach, one of the algorithms is Binary Particle Swarm Optimization (BPSO). In this paper, a unit commitment study will be implemented on IEEE 30 bus system by considering ramp rate and transmission line power losses using the Binary Particle Swarm Optimization (BPSO) algorithm to obtain the most optimal combination of generation with the lowest generation costs.
KW - BPSO
KW - Ramp Rate
KW - Transmission line losses
KW - Unit Commitment
UR - http://www.scopus.com/inward/record.url?scp=85078500303&partnerID=8YFLogxK
U2 - 10.1109/ISITIA.2019.8937246
DO - 10.1109/ISITIA.2019.8937246
M3 - Conference contribution
AN - SCOPUS:85078500303
T3 - Proceedings - 2019 International Seminar on Intelligent Technology and Its Application, ISITIA 2019
SP - 132
EP - 137
BT - Proceedings - 2019 International Seminar on Intelligent Technology and Its Application, ISITIA 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2019 International Seminar on Intelligent Technology and Its Application, ISITIA 2019
Y2 - 28 August 2019 through 29 August 2019
ER -