TY - GEN
T1 - Optimal Generation Scheduling Considering Distributed Generator for Cost Minimization based on Adaptive Modified Firefly Algorithm
AU - Sujono,
AU - Priyadi, Ardyono
AU - Pujiantara, Margo
AU - Anam, Sjamsjul
AU - Yorino, Naoto
AU - Purnomo, Mauridhi Hery
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021/9/29
Y1 - 2021/9/29
N2 - The increasing load and the decreasing availability of non-renewable energy sources have encouraged the development of renewable energy utilization. This condition increases the complexity of the power system. Distributed generator (DG) connection causes a significant change in power flow. On the other hand, the load on the power system is dynamic, so it is necessary to adjust the power generation. Proper scheduling of generating units to improve the reliability of the power system is crucial. Scheduling optimization is the key in power system operation planning and control to achieve optimal power system operation, with minimal cost and power loss. This paper presents the optimization of generating unit scheduling by applying the Adaptive Modified Firefly Algorithm (AMFA). The performance of AMFA in optimizing generator scheduling for minimal generation costs and power losses is tested by using a modified IEEE 30-bus system. The simulation results show that AMFA has a better performance than the firefly algorithm (FA), with a convergence speed of 4 times faster. Additionally of optimization by applying a distributed generator shows an improvement in the condition of the bus voltage in the system, lower costs, and power losses. In a system without DG which is loaded with 130% baseload, the optimization results indicate that 67% of the buses are under voltage, the generation cost is 1458.702 /hour and the power loss is 23.345 MW. The integration of DG into the system is able to improve the system where only 3% of the buses are under voltage, the cost of generating 1143.111 /hour, and power loss 1333.521 MW.
AB - The increasing load and the decreasing availability of non-renewable energy sources have encouraged the development of renewable energy utilization. This condition increases the complexity of the power system. Distributed generator (DG) connection causes a significant change in power flow. On the other hand, the load on the power system is dynamic, so it is necessary to adjust the power generation. Proper scheduling of generating units to improve the reliability of the power system is crucial. Scheduling optimization is the key in power system operation planning and control to achieve optimal power system operation, with minimal cost and power loss. This paper presents the optimization of generating unit scheduling by applying the Adaptive Modified Firefly Algorithm (AMFA). The performance of AMFA in optimizing generator scheduling for minimal generation costs and power losses is tested by using a modified IEEE 30-bus system. The simulation results show that AMFA has a better performance than the firefly algorithm (FA), with a convergence speed of 4 times faster. Additionally of optimization by applying a distributed generator shows an improvement in the condition of the bus voltage in the system, lower costs, and power losses. In a system without DG which is loaded with 130% baseload, the optimization results indicate that 67% of the buses are under voltage, the generation cost is 1458.702 /hour and the power loss is 23.345 MW. The integration of DG into the system is able to improve the system where only 3% of the buses are under voltage, the cost of generating 1143.111 /hour, and power loss 1333.521 MW.
KW - distributed generation
KW - modified firefly
KW - optimization
KW - power flow
KW - scheduling
UR - http://www.scopus.com/inward/record.url?scp=85119961668&partnerID=8YFLogxK
U2 - 10.1109/IES53407.2021.9594032
DO - 10.1109/IES53407.2021.9594032
M3 - Conference contribution
AN - SCOPUS:85119961668
T3 - International Electronics Symposium 2021: Wireless Technologies and Intelligent Systems for Better Human Lives, IES 2021 - Proceedings
SP - 131
EP - 136
BT - International Electronics Symposium 2021
A2 - Yunanto, Andhik Ampuh
A2 - Kusuma N, Artiarini
A2 - Hermawan, Hendhi
A2 - Putra, Putu Agus Mahadi
A2 - Gamar, Farida
A2 - Ridwan, Mohamad
A2 - Prayogi, Yanuar Risah
A2 - Ruswiansari, Maretha
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 23rd International Electronics Symposium, IES 2021
Y2 - 29 September 2021 through 30 September 2021
ER -