NDLI: Optimal undervoltage load shedding using Quantum-Inspired Evolutionary Programming

Content Provider	IEEE Xplore Digital Library
Author	Yasin, Z.M. Rahman, T.K.A. Zakaria, Z.
Copyright Year	2013
Description	Author affiliation: Fac. of Eng., Univ. Pertahanan Nasional, Kuala Lumpur, Malaysia (Rahman, T.K.A.) \|\| Fac. of Electr. Eng., Univ. Teknol. Mara, Shah Alam, Malaysia (Yasin, Z.M.; Zakaria, Z.)
Abstract	This paper presents a new technique to determine optimal undervoltage load shedding in a distribution system with load variation. The proposed technique is based on multiobjective approach namely Quantum-Inspired Evolutionary Programming (QIEP). This approach utilised the concept of quantum mechanics in the Evolutionary Programming (EP). Quantum-Inspired is implemented according to three levels defined by quantum individuals, quantum groups and quantum universe in order to improve the speed of the algorithm. The QIEP is employed to search for the best location and amount of load to be shed based on multiobjective functions which are power loss minimisation, voltage profile improvement and power interruption cost minimisation. The effectiveness of multiobjective QIEP optimisation technique is illustrated in IEEE 33-bus distribution test system. The result was also compared with other technique in terms of fitness values. The proposed technique also applied for IEEE 69-bus distribution test system and 141-bus distribution system with the variation of loading condition on the load curve.
Starting Page	337
Ending Page	341
File Size	157980
Page Count	5
File Format	PDF
ISBN	9781467363471
e-ISBN	9781467363495
DOI	10.1109/TENCONSpring.2013.6584467
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-04-17
Publisher Place	Australia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Interrupters Sociology Quantum mechanics Programming Power system stability Linear programming Statistics
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Multiobjective quantum-inspired evolutionary programming for optimal load shedding

Quantum-Inspired Evolutionary Programming-Artificial Neural Network for prediction of undervoltage load shedding

Prediction of Undervoltage Load Shedding using Quantum- Inspired Evolutionary Programming-Support Vector Machine

Adaptive undervoltage load shedding relay design using Thevenin equivalent estimation

Mixed integer linear formulation for undervoltage load shedding to provide voltage stability

Example of undervoltage load shedding implementation

Bacterial foraging optimization algorithm for load shedding

Optimal sizing of distributed generation by using quantum-inspired evolutionary programming

The optimization of undervoltage load shedding strategy

Optimal undervoltage load shedding using Quantum-Inspired Evolutionary Programming

Similar Documents

Multiobjective quantum-inspired evolutionary programming for optimal load shedding

Quantum-Inspired Evolutionary Programming-Artificial Neural Network for prediction of undervoltage load shedding

Prediction of Undervoltage Load Shedding using Quantum- Inspired Evolutionary Programming-Support Vector Machine

Adaptive undervoltage load shedding relay design using Thevenin equivalent estimation

Mixed integer linear formulation for undervoltage load shedding to provide voltage stability

Example of undervoltage load shedding implementation

Bacterial foraging optimization algorithm for load shedding

Optimal sizing of distributed generation by using quantum-inspired evolutionary programming

The optimization of undervoltage load shedding strategy

Optimal undervoltage load shedding using Quantum-Inspired Evolutionary Programming