Control Strategy of OLTC using Quantum Binary Particle Swarm Optimization to Improve the Voltage Stability Index
Received: 25 November 2024 | Revised: 2 January 2025, 23 January 2025, and 4 February 2025 | Accepted: 6 February 2025 | Online: 3 April 2025
Corresponding author: Adi Soeprijanto
Abstract
Efficient voltage regulation in distribution and transmission systems heavily relies on transformers with On-Load Tap Changers (OLTC). This study introduces a novel optimization technique, called Quantum Binary Particle Swarm Optimization (QBPSO), to optimize transformer tap settings to improve voltage stability and reducing power losses. QBPSO combines the principles of quantum computing with binary particle swarm optimization, enhancing the algorithm's exploration and exploitation capabilities. Utilizing the Bus Injection to Branch Current-Branch Current to Bus Voltage (BIBC-BCBV) method for power flow analysis, this research evaluates the performance of the proposed method on the IEEE 34-bus 20 kV radial distribution system. The results indicate a significant reduction in the Voltage Stability Index (VSI) from 0.2257 to 0.2069, a decrease in power losses from 21.756 kW to 19.1573 kW, and an improvement in the average voltage from 19.0047 kV to 19.9453 kV. A comparative analysis with Genetic Algorithm (GA), Binary Particle Swarm Optimization (BPSO), and Quantum Differential Evolution (QDE) demonstrates that QBPSO achieves superior performance in computational efficiency and voltage stability enhancement. These results highlight the effectiveness of QBPSO as a powerful tool for optimizing OLTC settings, contributing to the reliability and efficiency of power distribution systems.
Keywords:
BIBC-BCBV, distribution network, OLTC, QBPSO, VSIDownloads
References
V. K. B. Ponnam and K. Swarnasri, "Multi-Objective Optimal Allocation of Electric Vehicle Charging Stations and Distributed Generators in Radial Distribution Systems using Metaheuristic Optimization Algorithms," Engineering, Technology & Applied Science Research, vol. 10, no. 3, pp. 5837–5844, Jun. 2020.
T. L. Duong and T. T. Nguyen, "Network Reconfiguration for an Electric Distribution System with Distributed Generators based on Symbiotic Organisms Search," Engineering, Technology & Applied Science Research, vol. 9, no. 6, pp. 4925–4932, Dec. 2019.
P. Balamurugan, T. Yuvaraj, and P. Muthukannan, "Optimal Allocation of DSTATCOM in Distribution Network Using Whale Optimization Algorithm," Engineering, Technology & Applied Science Research, vol. 8, no. 5, pp. 3445–3449, Oct. 2018.
R. Małkowski, M. Izdebski, and P. Miller, "Adaptive Algorithm of a Tap-Changer Controller of the Power Transformer Supplying the Radial Network Reducing the Risk of Voltage Collapse," Energies, vol. 13, no. 20, Jan. 2020, Art. no. 5403.
A. N. Hasan and N. Tshivhase, "Voltage regulation system for OLTC in distribution power systems with high penetration level of embedded generation," International Transactions on Electrical Energy Systems, vol. 29, no. 7, 2019, Art. no. e12111.
A. Del Pizzc, L. Di Noia, D. Lauria, M. Crispino, A. Cantiello, and F. Mottola, "Control of OLTC distribution transformer addressing voltage regulation and lifetime preservation," in 2018 International Symposium on Power Electronics, Electrical Drives, Automation and Motion (SPEEDAM), Amalfi, Italy, Jun. 2018, pp. 1002–1007.
N. Tshivhase, A. N. Hasan, and T. Shongwe, "A Fault Level-Based System to Control Voltage and Enhance Power Factor Through an On-Load Tap Changer and Distributed Generators," IEEE Access, vol. 9, pp. 34023–34039, 2021.
K. Kotsalos, I. Miranda, J. L. Dominguez-Garcia, H. Leite, N. Silva, and N. Hatziargyriou, "Exploiting OLTC and BESS Operation Coordinated with Active Network Management in LV Networks," Sustainability, vol. 12, no. 8, Jan. 2020, Art. no. 3332.
D. F. Teshome, W. Xu, P. Bagheri, A. Nassif, and Y. Zhou, "A Reactive Power Control Scheme for DER-Caused Voltage Rise Mitigation in Secondary Systems," IEEE Transactions on Sustainable Energy, vol. 10, no. 4, pp. 1684–1695, Jul. 2019.
A. A. Firdaus, "Optimasi On-Load Tap-Changing Menggunakan Quantum Differential Evolution Untuk Meminimalkan Kerugian Daya," Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer, vol. 2, no. 1, pp. 9–17, Jun. 2018.
G. Wenjie, Y. Litao, H. Aoyang, and L. Zhengjie, "Optimal Dispatch Model of Active Distribution Network Based on Particle Swarm optimization Algorithm with Random Weight," in 2021 IEEE 2nd International Conference on Big Data, Artificial Intelligence and Internet of Things Engineering (ICBAIE), Nanchang, China, Mar. 2021, pp. 482–485.
P. R. Chinda and R. Dalapati Rao, "A binary particle swarm optimization approach for power system security enhancement," International Journal of Electrical and Computer Engineering (IJECE), vol. 12, no. 2, Apr. 2022, Art. no 1929.
N. A. Nguyen, T. N. Le, and H. M. V. Nguyen, "Multi-Goal Feature Selection Function in Binary Particle Swarm Optimization for Power System Stability Classification," Engineering, Technology & Applied Science Research, vol. 13, no. 2, pp. 10535–10540, Apr. 2023.
S. Tu, O. U. Rehman, S. U. Rehman, S. Ullah, M. Waqas, and R. Zhu, "A Novel Quantum Inspired Particle Swarm Optimization Algorithm for Electromagnetic Applications," IEEE Access, vol. 8, pp. 21909–21916, 2020.
Y. Wang and X. Chen, "Hybrid quantum particle swarm optimization algorithm and its application," Science China Information Sciences, vol. 63, no. 5, May 2020, Art. no. 159201.
C. Li, M. Shi, Y. Zhou, and E. Wang, "Quantum Particle Swarm Optimization Extraction Algorithm Based on Quantum Chaos Encryption," Complexity, vol. 2021, no. 1, 2021, Art. no. 6627804.
M. Kamel, A. A. Karrar, and A. H. Eltom, "Development and Application of a New Voltage Stability Index for On-Line Monitoring and Shedding," IEEE Transactions on Power Systems, vol. 33, no. 2, pp. 1231–1241, Mar. 2018.
D. Hamid and N. Gupta, "Stability Improvement of Power System with Wind Integration based on L-index," in 2021 Innovations in Power and Advanced Computing Technologies (i-PACT), Kuala Lumpur, Malaysia, Nov. 2021, pp. 1–6.
A. A. Firdaus, O. Penangsang, A. Soeprijanto, and D. F. U.p, "Distribution Network Reconfiguration Using Binary Particle Swarm Optimization to Minimize Losses and Decrease Voltage Stability Index," Bulletin of Electrical Engineering and Informatics, vol. 7, no. 4, pp. 514–521, Dec. 2018.
A. Azizivahed et al., "Energy Management Strategy in Dynamic Distribution Network Reconfiguration Considering Renewable Energy Resources and Storage," IEEE Transactions on Sustainable Energy, vol. 11, no. 2, pp. 662–673, Apr. 2020.
A. Al-Sakkaf and M. AlMuhaini, "Power Flow Analysis of Weakly Meshed Distribution Network Including DG," Engineering, Technology & Applied Science Research, vol. 8, no. 5, pp. 3398–3404, Oct. 2018.
Q. Wu, Y. Shen, Z. Ma, J. Fan, and R. Ge, "iBQPSO: an Improved BQPSO Algorithm for Feature Selection," in 2018 International Joint Conference on Neural Networks (IJCNN), Rio de Janeiro, Brazil, Jul. 2018, pp. 1–8.
S. K. Sahoo, E. H. Houssein, M. Premkumar, A. K. Saha, and M. M. Emam, "Self-adaptive moth flame optimizer combined with crossover operator and Fibonacci search strategy for COVID-19 CT image segmentation," Expert Systems with Applications, vol. 227, Oct. 2023, Art. no. 120367.
S. Chakraborty, A. K. Saha, and A. Chhabra, "Improving Whale Optimization Algorithm with Elite Strategy and Its Application to Engineering-Design and Cloud Task Scheduling Problems," Cognitive Computation, vol. 15, no. 5, pp. 1497–1525, Sep. 2023.
S. Sharma, A. K. Saha, S. Roy, S. Mirjalili, and S. Nama, "A mixed sine cosine butterfly optimization algorithm for global optimization and its application," Cluster Computing, vol. 25, no. 6, pp. 4573–4600, Dec. 2022.
S. Chakraborty, A. K. Saha, S. Sharma, S. K. Sahoo, and G. Pal, "Comparative Performance Analysis of Differential Evolution Variants on Engineering Design Problems," Journal of Bionic Engineering, vol. 19, no. 4, pp. 1140–1160, Jul. 2022.
S. Sharma, A. K. Saha, A. Majumder, and S. Nama, "MPBOA - A novel hybrid butterfly optimization algorithm with symbiosis organisms search for global optimization and image segmentation," Multimedia Tools and Applications, vol. 80, no. 8, pp. 12035–12076, Mar. 2021.
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Copyright (c) 2025 Aji Akbar Firdaus, Adi Soeprijanto, Ardyono Priyadi, Dimas Fajar Uman Putra
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