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Lagrangian relaxation hybrid with evolutionary algorithm for short-term generation scheduling

Lookup NU author(s): Dr Thillainathan Logenthiran, Dr Wai Lok Woo, Dr Van-Tung Phan


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Short-term generation scheduling is an important function in daily operational planning of power systems. It is defined as optimal scheduling of power generators over a scheduling period while respecting various generator constraints and system constraints. Objective of the problem includes costs associated with energy production, start-up cost and shut-down cost along with profits. The resulting problem is a large scale nonlinear mixed-integer optimization problem for which there is no exact solution technique available. The solution to the problem can be obtained only by complete enumeration, often at the cost of a prohibitively computation time requirement for realistic power systems. This paper presents a hybrid algorithm which combines Lagrangian Relaxation (LR) together with Evolutionary Algorithm (EA) to solve the problem in cooperative and competitive energy environments. Simulation studies were carried out on different systems containing various numbers of units. The outcomes from different algorithms are compared with that from the proposed hybrid algorithm and the advantages of the proposed algorithm are briefly discussed.

Publication metadata

Author(s): Logenthiran T, Woo WL, Phan VT

Publication type: Article

Publication status: Published

Journal: International Journal of Electrical Power & Energy Systems

Year: 2015

Volume: 64

Pages: 356-364

Print publication date: 01/01/2015

Online publication date: 13/08/2014

Acceptance date: 17/07/2014

ISSN (print): 0142-0615

ISSN (electronic): 1879-3517

Publisher: Elsevier


DOI: 10.1016/j.ijepes.2014.07.044


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