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

被引:20
作者
Logenthiran, Thillainathan [1 ]
Woo, Wai Lok [1 ]
Van Tung Phan [1 ]
机构
[1] Newcastle Univ, Sch Elect & Elect Engn, Singapore 569830, Singapore
关键词
Short-term generation scheduling; Profit-based unit commitment; Cost-based unit commitment; Lagrangian relaxation; Evolutionary algorithm; Economic dispatch; UNIT COMMITMENT; GENETIC ALGORITHM;
D O I
10.1016/j.ijepes.2014.07.044
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
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. (C) 2014 Elsevier Ltd. All rights reserved.
引用
收藏
页码:356 / 364
页数:9
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