[Home ] [Archive]   [ فارسی ]  
:: Main :: About :: Current Issue :: Archive :: Search :: Submit :: Contact ::
Main Menu
Home::
Journal Information::
Articles archive::
For Authors::
For Reviewers::
Registration::
Contact us::
Site Facilities::
::
Social Network Membership
Linkedin
Researchgate
..
Indexing Databases
..
DOI
کلیک کنید
..
ِDOR
..
Search in website

Advanced Search
..
Receive site information
Enter your Email in the following box to receive the site news and information.
..
:: Volume 14, Issue 4 (12-2025) ::
ieijqp 2025, 14(4): 60-77 Back to browse issues page
Presenting a new index to improve voltage stability and optimal placement of wind turbines in the distribution network considering uncertainty
Amirhossein Foomani1 , Majid Moradlou *1 , Peyman Nazarian1
1- Department of Electrical Engineering, Za.C., Islamic Azad University, Zanjan, Iran
Abstract:   (754 Views)

The use of distributed generation resources and communication infrastructure for awareness of generation levels, load, and technical constraints in the distribution system transforms the existing system into an active distribution system. In this paper, by introducing a new index for voltage stability and incorporating it into the problem of optimal distributed generation placement, a new problem is defined, and its effectiveness in improving voltage stability is investigated. In this paper, the objective function is defined as a profit function for the private sector investor (wind turbine owner) and the distribution system operator, and indices for voltage stability, active power losses, and reactive power losses are also included. By assigning different weights to each index, the profit function is derived from the perspectives of both the private sector and the distribution system operator. Furthermore, the wind turbine is examined in two modes: constant power factor and variable power factor. to solve the optimization problem in this paper, a Genetic Algorithm has been used. Based on the results obtained for different indices and schemes, and by using Analytical Hierarchy Process (AHP), the results are prioritized for different perspectives (from the viewpoint of the private sector and the distribution system operator). additionally, in this paper, the uncertainty of wind turbine generation as well as load demand uncertainty are considered in the optimization problem, and the study is conducted for various load models. By implementing the proposed method on the standard IEEE 33-bus and 37-bus test systems and comparing it with other indices, the efficiency of the proposed method is proven.
 

Keywords: AHP
Full-Text [PDF 2222 kb]   (207 Downloads)    
Type of Study: Research |
Received: 2025/11/22 | Accepted: 2026/03/16 | Published: 2026/04/6
References
1. Ali Farhan R, Shahgholian G, Fani B. (2024). Providing a Protection Strategy to Reduce the Impact of Distributed Generation in Electrical Energy Distribution Systems. ieijqp; 13 (3).‏ [DOI:10.61186/ieijqp.13.3.3]
2. ADEGOKE, Samson Ademola; SUN, Yanxia. (2023). Power system optimization approach to mitigate voltage instability issues: A review. Cogent Engineering, 10.1: 2153416.‏ [DOI:10.1080/23311916.2022.2153416]
3. D.Chung Phan, T.Trinh, D.Truc Ha. (2024). Optimal placement of wind turbine in distribution grid to minimize energy loss considering power generation probability. Bulletin of Electrical Engineering and Informatics Vol. 13, No. 4, August, pp. 2251~2259. [DOI:10.11591/eei.v13i4.7827]
4. Djemoui Benkhetta1, Abdelhafid Rouina, Abdelouahab Necira. (2024). Optimal Placement and sizing of DG Units Using LCA Algorithm. EAI Endorsed Transactions on Energy Web Volume 11. [DOI:10.4108/ew.4345]
5. F. A. Jumaa, O. M. Neda, and M. A. Mhawesh. (2021). Optimal distributed generation placement using artificial intelligence for improving active radial distribution system. Bull of Electr. Eng. & Inf., vol. 10, no. 5, pp. 2345-2354, Oct. [DOI:10.11591/eei.v10i5.2949]
6. G. A. Adepoju, B. A. Aderemi, S. A. Salimon, and O. J. Alabi. (2023). Optimal placement and sizing of distributed generation for power loss minimization in distribution network using particle swarm optimization technique. Eur. J. Eng. Sci. Tech., vol. 8, no. 1, pp. 19-25. [DOI:10.24018/ejeng.2023.8.1.2886]
7. H.Hamed and M.Farsadi. (2015).Utlization Cat Swarm Optimization Algorithm for Selected Harmonic Elemination in Current Source Inverter. International Journal of Power Electronics and Drive Systems (IJPEDS) 6, no. 4. [DOI:10.11591/ijpeds.v6.i4.pp888-896]
8. López, M.Zamudio, H.Zareipour and M.Quashie. (2024). Forecasting the Occurrence of Electricity Price Spikes: A Statistical-Economic Investigation Study", Forecasting 6, no. 1: 1-23. [DOI:10.3390/forecast6010007]
9. M. A. Sameh, A. A. Aloukili, M. A. El-Sharkawy, M. A. Attia, and A. O. Badr. (2022). Optimal DGs siting and sizing considering hybrid static and dynamic loads, and overloading conditions. Processes, vol. 10, no. 12, p. 2713, Dec. [DOI:10.3390/pr10122713]
10. M.Hemmati, N.Amjady and M. Ehsan. (2023). Islanded Micro-Grid Modeling and Optimization of its Operation Considering Cost of Energy not Served by an Enhanced Differential Search Algorithm. Energy Engineering and Management 3, no. 4: 2-13.
11. M.Shafiee. (2022). Wind Energy Development Site Selection Using an Integrated Fuzzy ANP-TOPSIS Decision Model. Energies, 15, 4289. [DOI:10.3390/en15124289]
12. Moazen M, Saghafi M. (2024). Power Control of VSVP BDFRG - Wind Turbine System Considering Wind Shear and Tower Shadow Effects. ieijqp; 13 (3). [DOI:10.61186/ieijqp.13.3.4]
13. Mohammad Aryanfar. (2023). Optimal Dispatchable DG Location and Sizing with an Analytical Method, based on a New Voltage Stability Index. International Journal of Research and Technology in Electrical Industry IJRTEI., Vol.2, No. 1, pp. 87-96 [DOI:10.52547/ijrtei.1.1.95]
14. N. Srilatha. (2023). Distributed Generation Placement Using Voltage Stability Index and Optimal Sizing Using Adaptive Particle Swarm Optimization. E3S Web of Conferences 399, 01007. [DOI:10.1051/e3sconf/202339901007]
15. S.Rezaeeian, N.Bayat, A.Rabiee, S.Nikkhah and A.Soroudi. (2022). Optimal Scheduling of Reconfigurable Microgrids in Both Grid-Connected and Isolated Modes Considering the Uncertainty of DERs. Energies 15, no. 15: 5369. [DOI:10.3390/en15155369]
16. T. A. Boghdady, S. G. A. Nasser, and E. E. D. A. Zahab. (2022). Energy harvesting maximization by integration of distributed generation based on economic benefits. Indones. J. Electr. Eng. Comput. Sci., vol. 25, no. 2, pp. 610-625. [DOI:10.11591/ijeecs.v25.i2.pp610-625]
17. Tourani M. (2025). Microgrid power scheduling considering the risk of power supply from renewable units in the presence of electric vehicle. Ieijqp,14 (1) :9-18.
18. T. T. Nguyen, T. T. Ngoc, T. T. Nguyen, T. P. Nguyen, and N. A. Nguyen. (2021). Optimization of location and size of distributed generations for maximizing their capacity and minimizing power loss of distribution system based on cuckoo search algorithm. Bull of Electr. Eng. & Inf., vol. 10, no. 4, pp. 1769-1776. [DOI:10.11591/eei.v10i4.2278]
19. Y. Merzoug, B. Abdelkrim, and B. Larbi. (2020). Optimal placement of wind turbine in a radial distribution network using PSO method. Int. J. Power Electron. Drive Syst., vol. 11, no. 2, pp. 1074-108. [DOI:10.11591/ijpeds.v11.i2.pp1074-1081]
20. Zhang, Lidong, Jiao Li, Xiandong Xu, Fengrui Liu, Yuanjun Guo, Zhile Yang, and Tianyu Hu. (2023). High spatial granularity residential heating load forecast based on Dendrite net model. Energy 269, no. [DOI:10.1016/j.energy.2023.126787]
21. Zhihui Lia, Yanli Zou and Zheng Gao. (2020). The Research on Optimal Location and Sizing of Distributed Generation Considering Voltage Stability Index and Line Loss Reduction Rate. Materials Science and Engineering 782-032047. [DOI:10.1088/1757-899X/782/3/032047]


XML   Persian Abstract   Print


Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Foomani A, Moradlou M, Nazarian P. Presenting a new index to improve voltage stability and optimal placement of wind turbines in the distribution network considering uncertainty. ieijqp 2025; 14 (4) :60-77
URL: http://ieijqp.ir/article-1-1051-en.html


Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Volume 14, Issue 4 (12-2025) Back to browse issues page
نشریه علمی- پژوهشی کیفیت و بهره وری صنعت برق ایران Iranian Electric Industry Journal of Quality and Productivity
Persian site map - English site map - Created in 0.1 seconds with 38 queries by YEKTAWEB 4772