TY - GEN
T1 - Completion of Contingency Ranking Selection (N-1) Using Ant Colony Optimization Algorithm on 500 kV JAMALI System
AU - Priyadi, Irnanda
AU - Ramli, Kalamullah
AU - Daratha, Novalio
AU - Fathoni, Evan
AU - Gunawan, Teddy Surya
AU - Ihsanto, Eko
N1 - Funding Information:
ACKNOWLEDGMENT The authors would like to acknowledge support from Universitas Indonesia, Universitas Bengkulu, International Islamic University Malaysia, and Universitas Mercu Buana.
Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - Indonesia is an archipelago nation with the world's fourth-largest population. With such a large population, the demand for electricity increases proportionately. At the moment, the JAMALI interconnection system serves the majority of Indonesia's electricity consumers in Jawa, Madura, and Bali. On the other hand, improving the electric power system's safety quality is a requirement that an electric power system must meet. To ensure the power system's security, the Ant Colony Optimization (ACO) algorithm was used to run several contingency scenarios (N-1). The ACO algorithm was implemented in this study through the initial parameter initialization stages, the probability value calculation stage, and the 0/1 knapsack problem calculation stage using the maximum cost function. The test is conducted by varying the capacity of the knapsack. According to the results of the voltage performance index on the JAMALI 500 kV system, the highest value was 95.39 on line 35 connecting bus 26 (Bangil) and bus 27 (Paiton), followed by NaN on line 56 connecting the Krian and Gresik buses. While line 59, which connects bus 46 (Grati) and bus 47 (South Surabaya), has the lowest ranking with the lowest value at 95.14.
AB - Indonesia is an archipelago nation with the world's fourth-largest population. With such a large population, the demand for electricity increases proportionately. At the moment, the JAMALI interconnection system serves the majority of Indonesia's electricity consumers in Jawa, Madura, and Bali. On the other hand, improving the electric power system's safety quality is a requirement that an electric power system must meet. To ensure the power system's security, the Ant Colony Optimization (ACO) algorithm was used to run several contingency scenarios (N-1). The ACO algorithm was implemented in this study through the initial parameter initialization stages, the probability value calculation stage, and the 0/1 knapsack problem calculation stage using the maximum cost function. The test is conducted by varying the capacity of the knapsack. According to the results of the voltage performance index on the JAMALI 500 kV system, the highest value was 95.39 on line 35 connecting bus 26 (Bangil) and bus 27 (Paiton), followed by NaN on line 56 connecting the Krian and Gresik buses. While line 59, which connects bus 46 (Grati) and bus 47 (South Surabaya), has the lowest ranking with the lowest value at 95.14.
KW - ant colony optimization
KW - Contingency
KW - JAMALI system
KW - knapsack problem
KW - voltage performance index
UR - http://www.scopus.com/inward/record.url?scp=85132755175&partnerID=8YFLogxK
U2 - 10.1109/CSPA55076.2022.9782019
DO - 10.1109/CSPA55076.2022.9782019
M3 - Conference contribution
AN - SCOPUS:85132755175
T3 - 2022 IEEE 18th International Colloquium on Signal Processing and Applications, CSPA 2022 - Proceeding
SP - 144
EP - 149
BT - 2022 IEEE 18th International Colloquium on Signal Processing and Applications, CSPA 2022 - Proceeding
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 18th IEEE International Colloquium on Signal Processing and Applications, CSPA 2022
Y2 - 12 May 2022
ER -