BAT algorithm and Ant Colony Optimization based Optimal Reactive Power Dispatch to Improve Voltage Stability

Rayudu Katuri, Guduri Yesuratnam and Askani Jayalaxmi
Additional contact information
Rayudu Katuri: B.V.Raju Institute of Technology Affiliated to Jawaharlal Nehru Technological University Hyderabad, Hyderabad.
Guduri Yesuratnam: University College of Engineering, Osmania University, Hyderabad
Askani Jayalaxmi: Jawaharlal Nehru Technological University Hyderabd

European Journal of Engineering and Technology Research, 2017, vol. 2, issue 6, 27-35

Abstract: One of the important tasks of a power system engineer is to run the system in safe and reliable mode for secure operation with increase in loading. So, it is significant to perform voltage stability analysis by optimal reactive power dispatch with Artificial Intelligence (AI) techniques. This paper presents the application of Ant Colony Optimization (ACO) and BAT algorithms for Optimal Reactive Power Dispatch (ORPD) to enhance voltage stability. The proposed ACO and BAT algorithms are used to find the optimal settings of On-load Tap changing Transformers (OLTC), Generator excitation and Static Var Compensators (SVC) to minimize the sum of the squares of the voltage stability L– indices of all the load buses. By calculating system parameters like L-Index, voltage error/deviation and real power loss for the practical Equivalent of Extra High Voltage (EHV) Southern Region Indian 24 bus system, voltage profile is improved and voltage stability is enhanced. A comparative analysis is done with the conventional optimization technique like Linear Programming (LP) for the given objective function to demonstrate the effectiveness of proposed ACO and BAT algorithms.

Keywords: Ant Colony Optimization; BAT algorithm; Linear Programming; Voltage Stability; L-Index; Optimal reactive power dispatch (search for similar items in EconPapers)
Date: 2017
References: Add references at CitEc
Citations:

Downloads: (external link)
https://eu-opensci.org/index.php/ejeng/article/view/60378 Abstract page (text/html)
https://eu-opensci.org/index.php/ejeng/article/download/60378/11776 Full text (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:epw:ejeng0:v:2:y:2017:i:6:id:60378

DOI: 10.24018/ejeng.2017.2.6.378

Access Statistics for this article

More articles in European Journal of Engineering and Technology Research from European Open Science
Bibliographic data for series maintained by Support ().