پیوندهای مفید
آمار
| تعداد نشریات | 22 |
| تعداد شمارهها | 705 |
| تعداد مقالات | 10,146 |
| تعداد مشاهده مقاله | 71,451,114 |
| تعداد دریافت فایل اصل مقاله | 63,174,120 |
Evolutionary programming and multi-verse optimization based Technique for risk-based voltage stability control | ||
| International Journal of Nonlinear Analysis and Applications | ||
| دوره 12، Special Issue، اسفند 2021، صفحه 1011-1024 اصل مقاله (479.26 K) | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22075/ijnaa.2021.5547 | ||
| نویسندگان | ||
| Lutfiah Hanim Lut1؛ Ismail Musirin* 1؛ Muhammad Murtadha Othman1؛ Nor Azwan Mohamed Kamari2؛ Thuraiya Mohd3؛ Shazlyn Milleana Shaharudin4؛ Suraya Masrom3 | ||
| 1School of Electrical Engineering, College of Engineering, Universiti Teknologi MARA, Shah Alam, Selangor, Malaysia | ||
| 2Department of Electrical, Electronic and Systems Engineering,Faculty of Engineering and Built Environment,,Universiti Kebangsaan Malaysia | ||
| 3Department of Built Environment and Technology, Faculty of Architecture, Planning and Surveying, Universiti Teknologi MARA Perak Branch, Seri Iskandar, 32610, Malaysia | ||
| 4Department of Mathematics, Faculty of Science and Mathematics, Universiti Pendidikan Sultan Idris, Perak, Malaysia | ||
| تاریخ دریافت: 30 خرداد 1400، تاریخ پذیرش: 22 شهریور 1400 | ||
| چکیده | ||
| Power system these days appears to work at high-stress load, which could trigger voltage security problems. This is due to the fact that the system will operate under low voltage conditions, which could be possibly below the allowable voltage limit. The voltage collapse phenomenon can become one of the remarkable issues in the power systems which can lead to severe consequences of voltage instability. This paper proposes a method for managing the voltage stability risk using two methods which are evolutionary programming (EP) and multiverse optimization (MVO). Consequently, EP and MVO were used to manage the risk in the power system due to load variations. The risk assessment is made in order to determine the risk of collapse for the system utilizing a pre-developed voltage stability index termed as Fast Voltage Stability Index (FVSI). It is used as the indicator of voltage stability conditions. Results obtained from the study revealed that the MVO technique is much more effective compared to EP. | ||
| کلیدواژهها | ||
| Voltage stability؛ Fast voltage stability index؛ Multiverse optimization (MVO) and Evolutionary programming (EP)؛ Risk assessment | ||
| مراجع | ||
|
[1] H. H. Alhelou, M. E. Hamedani-Golshan, T. C. Njenda, and P. Siano, A survey on power system blackout and cascading events: Research motivations and challenges, Energies, 12 (4) (2019) 1–28,doi: 10.3390/en12040682. [2] N. Aminudin, T. K. A. Rahman, N. M. M. Razali, M. Marsadek, N. M. Ramli, and M. I. Yassin, Voltage collapse risk index prediction for real time system’s security monitoring, 2015 IEEE 15th Int. Conf. Environ. Electr. Eng. EEEIC 2015 - Conf. Proc., (2017) (2015) 415–420, doi: 10.1109/EEEIC.2015.7165198. [3] I. Benmessahel, K. Xie, and M. Chellal, A new competitive multiverse optimization technique for solving singleobjective and multiobjective problems, Eng. Reports, 2 (3) (2020) 1–33, doi: 10.1002/eng2.12124. [4] L. Chen, L. Li, and W. Kuang, A hybrid multiverse optimisation algorithm based on differential evolution and adaptive mutation, J. Exp. Theor. Artif. Intell., 00 (00) (2020) 1–23, doi: 10.1080/0952813X.2020.1735532. [5] E. Hosseini, K. Z. Ghafoor, A. Emrouznejad, A. S. Sadiq, and D. B. Rawat, Novel metaheuristic based on multiverse theory for optimization problems in emerging systems, Appl. Intell., 2020, doi: 10.1007/s10489-020- 01920-z. [6] N. A. M. Ismail, A. A. M. Zin, A. Khairuddin, and S. Khokhar, A comparison of voltage stability indices, Proc. 2014 IEEE 8th Int. Power Eng. Optim. Conf. PEOCO 2014, (2014) 30–34, doi: 10.1109/PEOCO.2014.6814394. [7] M. Janga Reddy and D. Nagesh Kumar, Evolutionary algorithms, swarm intelligence methods, and their applications in water resources engineering: a state-of-the-art review, H2Open J., 3 (1)(2020) 135–188, doi: 10.2166/h2oj.2020.128. [8] K. Karthikeyan and P. K. Dhal, Multiverse Optimization (MVO) technique based voltage stability analysis through continuation power flow in IEEE 57 Bus, Energy Procedia, 117 (2017) 583–591, doi: 10.1016/j.egypro.2017.05.153. [9] M. Mahzarnia, M. Parsa Moghaddam, P. Siano, and M. R. Haghifam, A comprehensive assessment of power system resilience to a hurricane using a two-stage analytical approach incorporating risk-based index, Sustain. Energy Technol. Assessments, 4 (2020) 100831, doi: 10.1016/j.seta.2020.100831. [10] S. Mirjalili, S. M. Mirjalili, and A. Hatamlou, Multi-Verse Optimizer: a nature-inspired algorithm for global optimization, Neural Comput. Appl., 27 (2)(2016) 495–513, doi: 10.1007/s00521-015-1870-7. [11] I. Musirin and T. K. Abdul Rahman, Novel fast voltage stability index (FVSI) for voltage stability analysis in power transmission system, 2002 Student Conf. Res. Dev. Glob. Res. Dev. Electr. Electron. Eng. SCOReD 2002 - Proc., (2002) 265–268, doi: 10.1109/SCORED.2002.1033108. [12] H. Musa, An Overview on Voltage Stability Indices as Indicators of Voltage Stability for Networks with Distributed Generations Penetration, Int. J. Sci. Technol. Soc., 3 (4) (2015) 244, doi: 10.11648/j.ijsts.20150304.26. [13] N. M. Ni, J. D. McCalley, V. Vittal, and T. Tayyib, Online Risk-Based Security Assessment, IEEE Power Eng. Rev., 22 (11) (2002) 59, doi: 10.1109/MPER.2002.4311832. [14] O. P. Rahi, A. K. Yadav, H. Malik, A. Azeem, and K. Bhupesh, Power system voltage stability assessment through artificial neural network, Procedia Eng., 30 (2011) (2012) 53–60, doi: 10.1016/j.proeng.2012.01.833. [15] R. Rocchetta and E. Patelli, A post-contingency power flow emulator for generalized probabilistic risks assessment of power grids, Reliab. Eng. Syst. Saf., 197 (2019) (2020) 106817, doi: 10.1016/j.ress.2020.106817. [16] L. Rodriguez-Garcia, S. Perez-Londono, and J. Mora-Florez, An optimization-based approach for load modelling dependent voltage stability analysis, Electr. Power Syst. Res., 177 (2018) (2019) 10, doi: 10.1016/j.epsr.2019.105960. [17] A. Slowik and H. Kwasnicka, Evolutionary algorithms and their applications to engineering problems, Neural Comput. Appl., 8 (2020), doi: 10.1007/s00521-020-04832-8. [18] C. Tufon, A. Isemonger, B. Kirby, J. Kueck, and F. Li, A tariff for reactive power, 2009 IEEE/PES Power Syst. Conf. Expo. PSCE 2009, (2009) 1–7, doi: 10.1109/PSCE.2009.4839932. [19] R. Verayiah, A. Mohamed, H. Shareef, and I. H. Z. Abidin, “Performance comparison of voltage stability indices for weak bus identification in power systems,” IOP Conf. Ser. Earth Environ. Sci., 16 (1) (2013) 1–5, doi: 10.1088/1755-1315/16/1/012022. [20] Z. Wang, D. J. Hill, G. Chen, and Z. Y. Dong, Power system cascading risk assessment based on complex network theory, Phys. A Stat. Mech. its Appl., 482 (2017) 532–543, doi: 10.1016/j.physa.2017.04.031. | ||
|
آمار تعداد مشاهده مقاله: 44,350 تعداد دریافت فایل اصل مقاله: 50,380 |
||