Optimizing the Power System Operation Problem towards minimizing Generation and Damage Costs due to Load Shedding
Received: 24 July 2023 | Revised: 8 August 2023 | Accepted: 12 August 2023 | Online: 8 October 2023
Corresponding author: Trong Nghia Le
Abstract
Optimizing the operational parameters and control of the power system in steady-state conditions is a crucial issue in reducing the costs of power generation and operation. In the case of long-term operation of a power system, besides aiming to minimize power generation costs, the cost of damage caused by load shedding also needs to be considered. This paper presents the optimization of the total cost of a power system including minimizing the generation cost function of power plants or power companies and minimizing the damage cost function caused to customers due to load shedding or power outages. At the same time, the objective function must also ensure the constraints on the operating conditions of the power system. This contributes to maintaining the continuity of the power supply to critical loads and minimizing damage. Base loads, priority loads, or loads that are not allowed to be shed are considered as constraints. The optimization problem is addressed by using the Particle Swarm Optimization (PSO) algorithm and the Cuckoo Search Algorithm (CSA). The IEEE 30-bus test system is applied to validate the reduction in total cost. The result comparison shows that when applying the CSA, the total cost is significantly reduced by 3.75% in comparison with the PSO algorithm. The algorithms are implemented in Matlab to demonstrate the efficiency and accuracy of the proposed method.
Keywords:
optimal load shedding, PSO algorithm, Cuckoo Search algorithm, Economic Dispatch, cost functionDownloads
References
R. Małkowski and J. Nieznański, "Underfrequency Load Shedding: An Innovative Algorithm Based on Fuzzy Logic," Energies, vol. 13, no. 6, Jan. 2020, Art. no. 1456.
B. Potel, V. Debusschere, F. Cadoux, and L. de Alvaro Garcia, "Under-frequency load shedding schemes characteristics and performance criteria," in 2017 IEEE Manchester PowerTech, Manchester, UK, Jun. 2017.
S. M. Kisengeu, C. M. Muriithi, and G. N. Nyakoe, "Under voltage load shedding using hybrid ABC-PSO algorithm for voltage stability enhancement," Heliyon, vol. 7, no. 10, Oct. 2021.
M. Usman, A. Amin, M. M. Azam, and H. Mokhlis, "Optimal under voltage load shedding scheme for a distribution network using EPSO algorithm," in 2018 1st International Conference on Power, Energy and Smart Grid (ICPESG), Mirpur Azad Kashmir, Pakistan, Apr. 2018.
M. A. Zdiri, A. S. Alshammari, A. A. Alzamil, M. B. Ammar, and H. H. Abdallah, "Optimal Shedding Against Voltage Collapse Based on Genetic Algorithm," Engineering, Technology & Applied Science Research, vol. 11, no. 5, pp. 7695–7701, Oct. 2021.
M. Talaat, A. Y. Hatata, A. S. Alsayyari, and A. Alblawi, "A smart load management system based on the grasshopper optimization algorithm using the under-frequency load shedding approach," Energy, vol. 190, Jan. 2020, Art. no. 116423.
L. T. H. Nhung, T. T. Phung, H. M. V. Nguyen, T. N. Le, T. A. Nguyen, and T. D. Vo, "Load Shedding in Microgrids with Dual Neural Networks and AHP Algorithm," Engineering, Technology & Applied Science Research, vol. 12, no. 1, pp. 8090–8095, Feb. 2022.
M. Moazzami, A. Khodabakhshian, and R.-A. Hooshmand, "A New Optimal Under-frequency Load-shedding Method Using Hybrid Culture–Particle Swarm Optimization–Co-evolutionary Algorithm and Artificial Neural Networks," Electric Power Components and Systems, vol. 43, no. 1, pp. 69–82, Jan. 2015.
T. N. Le, H. A. Quyen, and N. A. Nguyen, "Application of fuzzy-analytic hierarchy process algorithm and fuzzy load profile for load shedding in power systems," International Journal of Electrical Power & Energy Systems, vol. 77, pp. 178–184, May 2016.
M. E. Jabian, R. Funaki, and J. Murata, "Load Shedding Optimization Considering Consumer Appliance Prioritization Using Genetic Algorithm for Real-time Application," IFAC-PapersOnLine, vol. 51, no. 28, pp. 486–491, Jan. 2018.
Md. S. Abid, H. J. Apon, A. Ahmed, and K. A. Morshed, "Chaotic slime mould optimization algorithm for optimal load-shedding in distribution system," Ain Shams Engineering Journal, vol. 13, no. 4, p. 101659, Jun. 2022.
G. A. Alshammari, F. A. Alshammari, T. Guesmi, B. M. Alshammari, A. S. Alshammari, and N. A. Alshammari, "A New Particle Swarm Optimization Based Strategy for the Economic Emission Dispatch Problem Including Wind Energy Sources," Engineering, Technology & Applied Science Research, vol. 11, no. 5, pp. 7585–7590, Oct. 2021.
T. Dridi, H. Jouini, A. Mami, A. E. Mhamedi, and E. M. Dafaoui, "Application of the Levenberg-Marquardt Algorithm in Solving the Economic Emission Dispatch Problem Integrating Renewable Energy," Engineering, Technology & Applied Science Research, vol. 12, no. 4, pp. 8850–8855, Aug. 2022.
M. A. Abido, "Optimal power flow using particle swarm optimization," International Journal of Electrical Power & Energy Systems, vol. 24, no. 7, pp. 563–571, Oct. 2002.
R. C. Eberhart, Y. Shi, and J. Kennedy, Swarm Intelligence, 1st ed. San Francisco, CA, USA: Morgan Kaufmann, 2001.
D. Wang, D. Tan, and L. Liu, "Particle swarm optimization algorithm: an overview," Soft Computing, vol. 22, no. 2, pp. 387–408, Jan. 2018.
X.-S. Yang and S. Deb, "Cuckoo Search via Lévy flights," in 2009 World Congress on Nature & Biologically Inspired Computing (NaBIC), Coimbatore, India, Sep. 2009, pp. 210–214.
S. A. Mohamed, N. Anwer, and M. M. Mahmoud, "Solving optimal power flow problem for IEEE-30 bus system using a developed particle swarm optimization method: towards fuel cost minimization," International Journal of Modelling and Simulation, Apr. 2023, Art. no. 2201043.
Downloads
How to Cite
License
Copyright (c) 2023 Trong Nghia Le, Hoang Minh Vu Nguyen, Thi Trang Hoang, Ngoc Au Nguyen
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Authors retain the copyright and grant the journal the right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) after its publication in ETASR with an acknowledgement of its initial publication in this journal.
