Aplikasi ORCA Algorithm Pada Optimasi Penyediaan Daya Sistem Berbasis Mobilitas Kendaraan Listrik

Authors

  • A.N. Afandi Universitas Negeri Malang
  • Farrel Candra W.A Smart Power and Advanced Energy Systems (SPAES) Research Center, Batu, Indonesia
  • Machrus Ali Universitas Darul Ulum

DOI:

https://doi.org/10.32492/jeetech.v4i2.4204

Keywords:

Dynamic Dispatch, Electric Vehicle, Flexible Load, Orca Algorithm, Power System

Abstract

In reality, the electric power system is run by combining several production units to commit to meeting changes in load demand at each operating time. Apart from that, it also takes into account efforts to reduce overall costs while maintaining the specified technical limits. The general thing that is often done to achieve this condition is carried out with an economical operational approach which leads to minimizing operational costs. During 24 hour operations, the model that is often used is Dynamic Economic Operation (DEO) which takes into account changes in load demand over a 24 hour seven day period. This study uses the IEEE-62 bus system as a model, which is optimized using the Orca Algorithm. The load flexibility pattern is based on the effect of charging integration for Electric Vehicles (EV). The simulation results show that the Orca algorithm solves problems with fast iteration and provides the best results. The Orca algorithm provides good levels of convergence, power output and overall operational costs. EV distances and routes also have varying driving characteristics and varying power utilization. In terms of travel modes, which include one way and two trips, it has a mobility of 208,000 EVs, with respective distributions for working/business/study, service/shopping, leisure time, and other purposes.

Author Biographies

A.N. Afandi, Universitas Negeri Malang

Departemen Teknik Elektro dan Informatika, Universitas Negeri Malang, Malang, Indonesia

Smart Power and Advanced Energy Systems (SPAES) Research Center, Batu, Indonesia

Farrel Candra W.A, Smart Power and Advanced Energy Systems (SPAES) Research Center, Batu, Indonesia

Smart Power and Advanced Energy Systems (SPAES) Research Center, Batu, Indonesia

Machrus Ali, Universitas Darul Ulum

Teknik Elektro, Universitas Darul Ulum, Jombang, Indonesia

References

A. Domyshev and D. Sidorov, “Optimization of the Structure of Power System Multi-Agent Control,” IFAC-Pap., vol. 55, no. 9, pp. 250–255, Jan. 2022, doi: 10.1016/j.ifacol.2022.07.044.

Z. Zhu, F. Zeng, G. Qi, Y. Li, H. Jie, and N. Mazur, “Power system structure optimization based on reinforcement learning and sparse constraints under DoS attacks in cloud environments,” Simul. Model. Pract. Theory, vol. 110, p. 102272, Jul. 2021, doi: 10.1016/j.simpat.2021.102272.

D. R. Aryani, H. Song, and Y.-S. Cho, “Operation strategy of battery energy storage systems for stability improvement of the Korean power system,” J. Energy Storage, vol. 56, p. 106091, Dec. 2022, doi: 10.1016/j.est.2022.106091.

A. N. Afandi, I. Fadlika, and Y. Sulistyorini, “Solution of dynamic economic dispatch considered dynamic penalty factor,” in 2016 3rd Conference on Power Engineering and Renewable Energy (ICPERE), Yogyakarta, Indonesia: IEEE, 2016, pp. 241–246. doi: 10.1109/ICPERE.2016.7904870.

I. Ahmed, M. Rehan, A. Basit, S. H. Malik, U.-E.-H. Alvi, and K.-S. Hong, “Multi-area economic emission dispatch for large-scale multi-fueled power plants contemplating inter-connected grid tie-lines power flow limitations,” Energy, vol. 261, p. 125178, Dec. 2022, doi: 10.1016/j.energy.2022.125178.

W. Luo, X. Yu, and Y. Wei, “Solving combined economic and emission dispatch problems using reinforcement learning-based adaptive differential evolution algorithm,” Eng. Appl. Artif. Intell., vol. 126, p. 107002, Nov. 2023, doi: 10.1016/j.engappai.2023.107002.

C. Shao, Y. Ding, and J. Wang, “A low-carbon economic dispatch model incorporated with consumption-side emission penalty scheme,” Appl. Energy, vol. 238, pp. 1084–1092, Mar. 2019, doi: 10.1016/j.apenergy.2019.01.108.

R. Chen et al., “Multi-region dynamic economic dispatch with active power real-time balance constraint,” Energy Rep., vol. 9, pp. 1353–1362, Oct. 2023, doi: 10.1016/j.egyr.2023.05.186.

Z. Lin, C. Song, J. Zhao, and H. Yin, “Improved approximate dynamic programming for real-time economic dispatch of integrated microgrids,” Energy, vol. 255, p. 124513, Sep. 2022, doi: 10.1016/j.energy.2022.124513.

D. Zou, D. Gong, and H. Ouyang, “The dynamic economic emission dispatch of the combined heat and power system integrated with a wind farm and a photovoltaic plant,” Appl. Energy, vol. 351, p. 121890, Dec. 2023, doi: 10.1016/j.apenergy.2023.121890.

A. N. Afandi, “Optimal scheduling power generations using HSABC algorithm considered a new penalty factor approach,” in The 2nd IEEE Conference on Power Engineering and Renewable Energy (ICPERE) 2014, Bali, Indonesia: IEEE, Dec. 2014, pp. 13–18. doi: 10.1109/ICPERE.2014.7067227.

E. Zio, P. Baraldi, and N. Pedroni, “Optimal power system generation scheduling by multi-objective genetic algorithms with preferences,” Reliab. Eng. Syst. Saf., vol. 94, no. 2, pp. 432–444, Feb. 2009, doi: 10.1016/j.ress.2008.04.004.

K. Balu and V. Mukherjee, “Optimal allocation of electric vehicle charging stations and renewable distributed generation with battery energy storage in radial distribution system considering time sequence characteristics of generation and load demand,” J. Energy Storage, vol. 59, p. 106533, Mar. 2023, doi: 10.1016/j.est.2022.106533.

L. Fu, T. Wang, M. Song, Y. Zhou, and S. Gao, “Electric vehicle charging scheduling control strategy for the large-scale scenario with non-cooperative game-based multi-agent reinforcement learning,” Int. J. Electr. Power Energy Syst., vol. 153, p. 109348, Nov. 2023, doi: 10.1016/j.ijepes.2023.109348.

Y. Jiang, Q. Wu, S. Zhu, and L. Zhang, “Orca predation algorithm: A novel bio-inspired algorithm for global optimization problems,” Expert Syst. Appl., vol. 188, p. 116026, Feb. 2022, doi: 10.1016/j.eswa.2021.116026.

Published

2023-11-04

How to Cite

[1]
A.N. Afandi, F. Candra W.A, and M. Ali, “Aplikasi ORCA Algorithm Pada Optimasi Penyediaan Daya Sistem Berbasis Mobilitas Kendaraan Listrik”, jeetech, vol. 4, no. 2, pp. 103-108, Nov. 2023.