Economic Dispatch considering Valve Point Effects using Modified Teaching Learning based Optimisation

被引:0
作者
Sharmiladeve, V [1 ]
Geethanjali, S. [1 ]
机构
[1] Kumaraguru Coll Technol, Dept Elect & Elect Engn, Coimbatore, Tamil Nadu, India
来源
2015 IEEE INTERNATIONAL CONFERENCE ON ENGINEERING AND TECHNOLOGY (ICETECH) | 2015年
关键词
Economic Dispatch; Teaching Learning Based Optimisation; Generating units; Valve point effects; Modified Teaching Learning Based Optimisation; PARTICLE SWARM OPTIMIZATION; GENETIC ALGORITHM; LOAD DISPATCH;
D O I
暂无
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
In this paper, Modified Teaching Learning Based Optimisation is used to solve the Economic Dispatch problems of the generating units considering valve point loadings effects. The formulation of the objective function is carried out in such a way that the losses are neglected and a clarified solution is obtained from the generating units. A recently developed optimisation is the Teaching Learning Based Optimisation which operates on two different phases- teacher phase and learner phase. A modification is done in the Teaching Learning Based Optimisation and is used in this paper as Modified Teaching Learning Based Optimisation. Here, in addition to the two phases, an mutation phase is also introduced. In contrast to the other Optimisation methods this proposed method does not require any algorithm specific parameters, it does not depend on any tuning parameters of algorithm and it enables global optimum solution and also avoids premature convergence to local optima of the objective function. The proposed method finds an optimum solution, such that minimum fuel cost solution can be obtained with extraordinary convergence rates and high consistency. The proposed method is tested on standard IEEE bus with 13 generating unit system, 40 generating unit system with valve point effects. The effectiveness of this method is demonstrated by comparing the results with other optimization techniques. Also, the result confirms that this proposed method has a great potential in determining the optimum solution.
引用
收藏
页码:200 / 205
页数:6
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