NDLI: Quantum-Inspired Evolutionary Algorithm Approach for Unit Commitment

Content Provider	IEEE Xplore Digital Library
Author	Lau, T.W. Chung, C.Y. Wong, K.P. Chung, T.S. Ho, S.L.
Copyright Year	1969
Abstract	This paper presents a novel method for solving the unit commitment (UC) problem based on quantum-inspired evolutionary algorithm (QEA). The proposed method applies QEA to handle the unit-scheduling problem and the Lambda-iteration technique to solve the economic dispatch problem. The QEA method is based on the concept and principles of quantum computing, such as quantum bits, quantum gates and superposition of states. QEA employs quantum bit representation, which has better population diversity compared with other representations used in evolutionary algorithms, and uses quantum gate to drive the population towards the best solution. The mechanism of QEA can inherently treat the balance between exploration and exploitation and also achieve better quality of solutions, even with a small population. The proposed method is applied to systems with the number of generating units in the range of 10 to 100 in a 24-hour scheduling horizon and is compared to conventional methods in the literature. Moreover, the proposed method is extended to solve a large-scale UC problem in which 100 units are scheduled over a seven-day horizon with unit ramp-rate limits considered. The application studies have demonstrated the superior performance and feasibility of the proposed algorithm.
Sponsorship	IEEE Power Engineering Society
Starting Page	1503
Ending Page	1512
Page Count	10
File Size	368511
File Format	PDF
ISSN	08858950
Volume Number	24
Issue Number	3
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-08-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Evolutionary computation Quantum computing Processor scheduling Costs Dynamic programming Power generation economics Large-scale systems Production Lagrangian functions Integer linear programming unit commitment Evolutionary algorithm quantum computing quantum-inspired evolutionary algorithm
Content Type	Text
Resource Type	Article
Subject	Energy Engineering and Power Technology Electrical and Electronic Engineering

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
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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
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9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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