TY - GEN
T1 - Optimization of Economic Scheduling for Generators Using Snake Optimizer Algorithm
AU - Krama, Arief Budiman
AU - Handoko, Susatyo
AU - Facta, Mochammad
AU - Andromeda, Trias
AU - Karnoto,
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - Currently, the cost of fuel in the electrical generation is the largest cost to produce electricity. The emission problem which raises environmental pollution needs to be considered because it can adversely affect the surrounding environment and cause global warming. The effect of valve settings commonly referred to as the Valve Point Effect (VPE) can cause amount of fuel consumption related to the cost. In addition, there are transmission losses (power losses) in the electricity delivery process to be considered. Solving the problems have been conducted using vary of metaheuristic algorithm. In this work, a novel metaheuristic algorithm as known as Snake Optimizer (SO) will be applied to optimize power plant scheduling with involving of several factors such as fuel, emission, valve point effect, and power losses. The snake optimizer algorithm is tested for reliability on IEEE 30 Bus electrical system test data using 6 generator units. The test are carried out with various power load percentages from 141.70 MW (50%) up to 354.25 MW (125%), performace test with various parameter such as iteration, population, and solution time with same load is 283.4 MW. In addition, the optimization results of the snake optimizer algorithm will also be compared with other algorithms using the same load is 250 MW. The results show that snake optimizer algorithm can provide a good optimization solution and had more efficient cost. The research contribution with involving of factors such as fuel, emission, valve point effect, and power losses also made the calculation of cost more optimal, accurate and realistic.
AB - Currently, the cost of fuel in the electrical generation is the largest cost to produce electricity. The emission problem which raises environmental pollution needs to be considered because it can adversely affect the surrounding environment and cause global warming. The effect of valve settings commonly referred to as the Valve Point Effect (VPE) can cause amount of fuel consumption related to the cost. In addition, there are transmission losses (power losses) in the electricity delivery process to be considered. Solving the problems have been conducted using vary of metaheuristic algorithm. In this work, a novel metaheuristic algorithm as known as Snake Optimizer (SO) will be applied to optimize power plant scheduling with involving of several factors such as fuel, emission, valve point effect, and power losses. The snake optimizer algorithm is tested for reliability on IEEE 30 Bus electrical system test data using 6 generator units. The test are carried out with various power load percentages from 141.70 MW (50%) up to 354.25 MW (125%), performace test with various parameter such as iteration, population, and solution time with same load is 283.4 MW. In addition, the optimization results of the snake optimizer algorithm will also be compared with other algorithms using the same load is 250 MW. The results show that snake optimizer algorithm can provide a good optimization solution and had more efficient cost. The research contribution with involving of factors such as fuel, emission, valve point effect, and power losses also made the calculation of cost more optimal, accurate and realistic.
KW - Emission
KW - Fuel
KW - IEEE 30 Bus
KW - Power Losses
KW - Snake Optimizer
KW - Valve Point Effect
UR - http://www.scopus.com/inward/record.url?scp=85214686564&partnerID=8YFLogxK
U2 - 10.1109/EECSI63442.2024.10776057
DO - 10.1109/EECSI63442.2024.10776057
M3 - Conference contribution
AN - SCOPUS:85214686564
T3 - International Conference on Electrical Engineering, Computer Science and Informatics (EECSI)
SP - 651
EP - 658
BT - Proceedings - 2024 11th International Conference on Electrical Engineering, Computer Science and Informatics, EECSI 2024
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 11th International Conference on Electrical Engineering, Computer Science and Informatics, EECSI 2024
Y2 - 26 September 2024 through 27 September 2024
ER -