Optimal placement of meters for power system state estimation by using artificial intellegence techniques : a comparative study
Other Title(s)
الموقع الأفضل للمقاييس لتخمين حالة منظومة القدرة باستخدام تقنيات الذكاء الصناعي
Joint Authors
al-Anbari, Qasim Abd al-Razzaq Ali
al-Anbari, Qasim Abd al-Razzaq Ali
Hasan, Muhammad Falih
Source
Journal of Engineering and Sustainable Development
Publisher
al-Mustansyriah University College of Engineering
Publication Date
2018-03-31
Country of Publication
Iraq
No. of Pages
18
Main Subjects
English Abstract
Meters placements play an important role in attaining the system observability for estimating the state of the power system.
This paper presents algorithms to select the best locations for installing the meters by using artificial intelligence techniques.
Two algorithms have been proposed and implemented in order to avoid the circumstances arisen by random distribution of the meters.
The first algorithm include optimal placement of meters by using Particle Swarm Optimization (PSO).
The second algorithm utilizes the Artificial Bee Colony (ABC) to select the best allocation of meters.
The proposed algorithms randomly searches the best location of meter placement based on the minimum error of state estimation.
In comparison to traditional methods, PSO and ABC able to search the optimal measurement placement without having to test possible location one after another since PSO and ABC are an optimization method.
The performance of the proposed algorithms are verified by applying the proposed algorithms on IEEE-14 and 30 bus standard test system.
The obtained results reveal the importance of optimal selection of meter placement in accelerating the convergence the state estimation process.
The capability of the proposed algorithm in determining the best estimate of the state variables accurately with a less number of iterations and less execution time than conventional method (WLS) is clarified.
Data Type
Conference Papers
Record ID
BIM-906801
American Psychological Association (APA)
al-Anbari, Qasim Abd al-Razzaq Ali& al-Anbari, Qasim Abd al-Razzaq Ali& Hasan, Muhammad Falih. 2018-03-31. Optimal placement of meters for power system state estimation by using artificial intellegence techniques : a comparative study. . Vol. 22, no. 2 (Mar. 2018), pp.15-32.Baghdad Iraq : al-Mustansyriah University College of Engineering.
https://search.emarefa.net/detail/BIM-906801
Modern Language Association (MLA)
al-Anbari, Qasim Abd al-Razzaq Ali& al-Anbari, Qasim Abd al-Razzaq Ali& Hasan, Muhammad Falih. Optimal placement of meters for power system state estimation by using artificial intellegence techniques : a comparative study. . Baghdad Iraq : al-Mustansyriah University College of Engineering. 2018-03-31.
https://search.emarefa.net/detail/BIM-906801
American Medical Association (AMA)
al-Anbari, Qasim Abd al-Razzaq Ali& al-Anbari, Qasim Abd al-Razzaq Ali& Hasan, Muhammad Falih. Optimal placement of meters for power system state estimation by using artificial intellegence techniques : a comparative study. .
https://search.emarefa.net/detail/BIM-906801