پیوندهای مفید
آمار
| تعداد نشریات | 21 |
| تعداد شمارهها | 682 |
| تعداد مقالات | 9,946 |
| تعداد مشاهده مقاله | 70,271,693 |
| تعداد دریافت فایل اصل مقاله | 53,785,298 |
Analyzing the Load Modelling Impacts on Uncertain Optimal Reactive Power Dispatch Problem by Using Grey Wolf Optimization | ||
| Journal of Modeling and Simulation in Electrical and Electronics Engineering | ||
| مقاله 4، دوره 1، شماره 3 - شماره پیاپی 5، بهمن 2021، صفحه 27-34 اصل مقاله (887.48 K) | ||
| نوع مقاله: Research Article | ||
| شناسه دیجیتال (DOI): 10.22075/mseee.2021.24582.1070 | ||
| نویسندگان | ||
| Hamdi Abdi* 1؛ Mansour Moradi2؛ Shahram Karimi3 | ||
| 1Electrical Engineering Department, Engineering Faculty, Razi University, Kermanshah, Iran | ||
| 2Young Researchers and Elite Club, Islamic Azad University, Kermanshah Branch | ||
| 3Electrical Engineering Department, Engineering Faculty, Razi University, Kermanshah,Iran | ||
| تاریخ دریافت: 28 شهریور 1400، تاریخ بازنگری: 26 آبان 1400، تاریخ پذیرش: 22 دی 1400 | ||
| چکیده | ||
| Optimal Reactive Power Dispatch (ORPD) is an essential subject in the economic operation of power systems. This issue is generally an optimization constrained problem satisfying the dominant control parameters. Due to the non-linear nature of the ORPD problem, solutions include several optima, and deterministic methods may lead to poor performance. On the other hand, the diversity and stochastic nature of electrical loads, arising from renewable energy penetration in the power system create significant challenges in solving this problem. Therefore, stochastic methods are required to find the appropriate solutions. In this paper, the Monte Carlo Simulation (MCS) is used to model the uncertainty of loads. Static modeling methods implement the type of load modeling. The polynomial ZIP method is applied to solve the ORPD problem for the first time. Optimizing the control parameters by applying the Grey Wolf Optimization (GWO) and based on the IEEE 30-bus standard as a general model is performed. Due to this, in the proposed method, the minimum voltage level will be 0.4 per unit less than the other methods. Also, the rate of system losses is improved by 7.61% compared to the base-case network, but compared to the other methods, regardless of the load model, it has a 10.76% higher loss rate. The simulation results show that the load models have a significant effect on the ORPD problem, and this concept is completely and directly transferred to the operation of the power system, and power system stability, accordingly. | ||
| کلیدواژهها | ||
| Optimal Reactive Power Dispatch (ORPD)؛ Uncertainty؛ Load Model؛ Monte Carlo Simulation (MCS)؛ Grey Wolf Optimization (GWO)؛ Power Losses | ||
| مراجع | ||
|
[1] Abdi, H., Moradi, M., Asadi, R., Naderi, S., Amirian, B., & Karimi, F. (2021). Optimal reactive power dispatch problem: A comprehensive study on meta-heuristic algorithms. J. Energy Management Technol., 5(3), 67-77. [2] Hassan, Mohamed H., et al. "Optimal reactive power dispatch with time- varying demand and renewable energy uncertainty using Rao-3 algorithm." IEEE Access 9 (2021): 23264-23283. [3] Chi, Rui, et al. "Reactive power optimization of power system based on improved differential evolution algorithm." Mathematical Problems in Engin., 2021. [4] S. M. Mohseni-Bonab, A. Rabiee, and B. Mohammadi-Ivatloo, "Voltage stability constrained multi-objective optimal reactive power dispatch under load and wind power uncertainties: A stochastic approach," Renewable Energy, vol. 85, pp. 598-609, 2016. [5] M. Ghasemi, S. Ghavidel, M. M. Ghanbarian, and A. Habibi, "A new hybrid algorithm for optimal reactive power dispatch problem with discrete and continuous control variables," Applied soft computing, vol. 22, pp. 126-140, 2014. [6] M. H. Sulaiman, Z. Mustaffa, M. R. Mohamed, and O. Aliman, "Using the gray wolf optimizer for solving optimal reactive power dispatch problem," Applied Soft Computing, vol. 32, pp. 286-292, 2015. [7] Shaheen, Mohamed AM, Hany M. Hasanien, and Abdulaziz Alkuhayli. "A novel hybrid GWO-PSO optimization technique for optimal reactive power dispatch problem solution." Ain Shams Engin. J. 12.1 (2021): 621-630. [8] Lopez, Juan C., and Marcos J. Rider. "Optimal Reactive Power Dispatch with Discrete Controllers Using a Branch-and-Bound Algorithm: A Semidefinite Relaxation Approach." IEEE Trans. on Power Syst. 2021. [9] D. B. Das and C. Patvardhan, "A new hybrid evolutionary strategy for reactive power dispatch," Electric Power Systems Research, vol. 65, pp. 83-90, 2003. [10] W. Yan, S. Lu, and D. C. Yu, "A novel optimal reactive power dispatch method based on an improved hybrid evolutionary programming technique," IEEE Trans. Power syst., vol. 19, pp. 913-918, 2004. [11] B. Shaw, V. Mukherjee, and S. Ghoshal, "Solution of reactive power dispatch of power systems by an opposition-based gravitational search algorithm," Int. J. Elec.l Power Energy Syst., vol. 55, pp. 29-40, 2014. [12] D. G. Rojas, J. L. Lezama, and W. Villa, "Metaheuristic Techniques Applied to the Optimal Reactive Power Dispatch: A Review," IEEE Latin America Trans., vol. 14, pp. 2253-2263, 2016. [13] B. Zhao, C. Guo, and Y. Cao, "A multiagent-based particle swarm optimization approach for optimal reactive power dispatch," IEEE Trans. Power syst., vol. 20, pp. 1070-1078, 2005. [14] W. Yan, F. Liu, C. Chung, and K. Wong, "A hybrid genetic algorithm-interior point method for optimal reactive power flow," IEEE Trans. Power syst., vol. 21, pp. 1163-1169, 2006. [15] A. Bokhari, A. Alkan, R. Dogan, M. Diaz-Aguiló, F. De Leon, D. Czarkowski, et al., "Experimental determination of the ZIP coefficients for modern residential, commercial, and industrial loads," IEEE Trans. Power Delivery, vol. 29, pp. 1372-1381, 2014. [16] S. Mirjalili, S. M. Mirjalili, and A. Lewis, "Grey wolf optimizer," Adv. Engin. Software, vol. 69, pp. 46-61,2014. [17] S. M. Mohseni-Bonab, A. Rabiee, and B. Mohammadi-Ivatloo, "Multi-objective optimal reactive power dispatch considering uncertainties in the wind integrated power systems," Reactive Power Control in AC Power Systems: Fundamentals and Current Issues, N. Mahdavi Tabatabaei, A. Jafari Aghbolaghi, N. Bizon, and F. Blaabjerg, Eds., ed Cham: Springer International Publishing, 2017, pp. 475-513. | ||
|
آمار تعداد مشاهده مقاله: 397 تعداد دریافت فایل اصل مقاله: 256 |
||