Optimization of Unit Commitment Problems Integrated PV Generation Plants Based on Particle Swarm Optimization Algorithm
DOI:
https://doi.org/10.25139/ijair.v7i2.10510Keywords:
Particle Swarm Optimization, PSO, Unit Commitment, Frequency Nadir, PhotovoltaicAbstract
The increasing integration of renewable energy sources, particularly photovoltaic (PV) systems, poses significant challenges in the Unit Commitment (UC) problem due to their intermittent and inertial nature. This condition can cause frequency instability during system disturbances, necessitating the development of new strategies to maintain reliable power system operation. This study proposes an enhanced UC optimization framework by integrating conventional thermal generating units, PV plants, and energy storage systems (ESS) that act as virtual inertia providers. To solve the optimization problem while considering various technical constraints—such as ramping limits, minimum on/off times, rotating reserve requirements, and nadir frequency thresholds—a modified Particle Swarm Optimization (PSO) algorithm is employed. The model is tested on a generating system consisting of nine thermal units, one PV plant, and one ESS. Simulation results show that the proposed method is capable of maintaining the system frequency above the nadir threshold of 49.5 Hz during disturbances while minimizing the total operating cost. Specifically, the optimal configurations without nadir constraints and with ESS integration achieve convergence in only four iterations with a computational time of 1.9 seconds. These findings demonstrate the effectiveness of integrating ESS as virtual inertia and the efficiency of a modified PSO algorithm in handling UC in systems with high renewable energy penetration. This framework offers a promising approach to improving cost efficiency and frequency stability in future renewable energy-based power systems.
References
M. Qian, J. Wang, D. Yang, H. Yin, and J. Zhang, "An Optimization Strategy for Unit Commitment in High Wind Power Penetration Power Systems Considering Demand Response and Frequency Stability Constraints," Energies (Basel), vol. 17, no. 22, Nov. 2024, doi: 10.3390/en17225725.
M. I. Romadhon and R. A. Nugraha, “KONSULI: Knowledge on Sustainability and Innovative Technology Optimisasi dan Permasalahan Pada Pembangkit Listrik Berbasis Energi baru Terbarukan,” 2025.
A. Aharwar, R. Naresh, V. Sharma, and V. Kumar, "Unit commitment problem for transmission system, models and approaches: A review," Electric Power Systems Research, vol. 223, p. 109671, Oct. 2023, doi: 10.1016/j.epsr.2023.109671.
A. A. B. Osman, M. J. Afroni, D. Efendi, and S. Wirateruna, “Perencanaan Jadwal Pembangkit Listrik untuk Mempertahankan Frekuensi Jaringan dengan Integrasi Baterai dan Tenaga Surya yang Tinggi Menggunakan Algoritma PSO.”
“Voc_Isc_Vm_Im_Vm_Im_2_5_Voc_Isc_Tegangan”.
A. O. Olasoji, D. T. O. Oyedokun, S. O. Omogoye, and C. Thron, "Review of frequency response strategies in renewable-dominated power system grids: Market adaptations and unit commitment formulation," Sci Afr, vol. 26, p. e02357, Dec. 2024, doi: 10.1016/j.sciaf.2024.e02357.
F. M. Noor and A. F. Rahman, “Studi Penerapan Integrasi Sumber Energi Baru Terbarukan dengan Smart grid dan Sistem Pengendalian SCADA.”
N. Zhang, Q. Zhou, and H. Hu, "Minimum Frequency and Voltage Stability Constrained Unit Commitment for AC/DC Transmission Systems," Applied Sciences, vol. 9, no. 16, p. 3412, Aug. 2019, doi: 10.3390/app9163412.
Z. Chu and F. Teng, "Voltage Stability Constrained Unit Commitment in High IBG-Penetrated Power Systems," Dec. 2021.
Z. Chu and F. Teng, "Voltage Stability Constrained Unit Commitment in High IBG-Penetrated Power Systems," Dec. 2021.
A. Giedraityte, S. Rimkevicius, M. Marciukaitis, V. Radziukynas, and R. Bakas, "Hybrid Renewable Energy Systems—A Review of Optimization Approaches and Future Challenges," Applied Sciences, vol. 15, no. 4, p. 1744, Feb. 2025, doi: 10.3390/app15041744.
A. S. Daroini, “Security Constrained Unit Commitment Mempertimbangkan Kapasitas Dan Rugi Daya Saluran Transmisi Dengan Kurva Biaya Tidak Rata Menggunakan Algoritma Binary Particle Swarm Optimization (BPSO) Pada Sistem IEEE 30 BUS.”
M. Arindra, R. S. Wibowo, and D. C. Riawan, “Unit Commitment Pada Sistem Pembangkitan Tenaga Angin Untuk Mengurangi Emis Menggunakan Particle Swarm Optimization,” Jurnal Teknik ITS, vol. 5, no. 2, Sep. 2016, doi: 10.12962/j23373539.v5i2.16122.
G. Shaari, N. Tekbiyik-Ersoy, and M. Dagbasi, "The state of art in particle swarm optimization based unit commitment: A review," 2019, MDPI AG. doi: 10.3390/pr7100733.
M. A. Mquqwana and S. Krishnamurthy, "Particle Swarm Optimization for an Optimal Hybrid Renewable Energy Microgrid System under Uncertainty," Energies (Basel), vol. 17, no. 2, Jan. 2024, doi: 10.3390/en17020422.
E. S. Wirateruna, M. J. Afroni, and A. F. Ayu, "Implementation of PSO algorithm on MPPT PV System using Arduino Uno under PSC," International Journal of Artificial Intelligence & Robotics (IJAIR), vol. 5, no. 1, pp. 13–20, May 2023, doi: 10.25139/ijair.v5i1.6029.
E. S. Wirateruna and A. F. A. Millenia, "Design of MPPT PV using Particle Swarm Optimization Algorithm under Partial Shading Condition," International Journal of Artificial Intelligence & Robotics (IJAIR), vol. 4, no. 1, pp. 24–30, May 2022, doi: 10.25139/ijair.v4i1.4327.
P. Pengukuhan and J. Guru Besar, “Integrasi Variable Renewable Energy Dalam Perencanaan Dan Operasi Sistem Tenaga Listrik Menuju Transisi Energi Berkelanjutan Universitas Gadjah Mada.”
P. Denholm, T. Mai, R. W. Kenyon, B. Kroposki, and M. O'malley, "Inertia and the Power Grid: A Guide Without the Spin," 2020.
H. O. R. Howlader, O. B. Adewuyi, Y. Y. Hong, P. Mandal, A. M. Hemeida, and T. Senjyu, "Energy storage system analysis review for optimal unit commitment," Energies (Basel), vol. 13, no. 1, Jan. 2020, doi: 10.3390/en13010158.
P. Aaslid, M. Korpås, M. M. Belsnes, and O. B. Fosso, "Stochastic operation of energy constrained microgrids considering battery degradation," Electric Power Systems Research, vol. 212, p. 108462, Nov. 2022, doi: 10.1016/j.epsr.2022.108462.
"Inertia and Rate of Change of Frequency (RoCoF)," 2020.
M. Rajabdorri, B. Kazemtabrizi, M. Troffaes, L. Sigrist, and E. Lobato, "Inclusion of frequency nadir constraint in the unit commitment problem of small power systems using machine learning," Sustainable Energy, Grids and Networks, vol. 36, p. 101161, Dec. 2023, doi: 10.1016/j.segan.2023.101161.
Downloads
Published
How to Cite
Issue
Section
License
Authors who publish with International Journal of Artificial Intelligence & Robotics (IJAIR) agree to the following terms:
-
Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License (CC BY-SA 4.0) that allows others to share the work with an acknowledgment 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 acknowledgment 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) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work.
