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http://dx.doi.org/10.5370/JEET.2017.12.4.1348

Generation Scheduling with Large-Scale Wind Farms using Grey Wolf Optimization  

Saravanan, R. (Dept. of Electrical Engineering, Annamalai University)
Subramanian, S. (Dept. of Electrical Engineering, Annamalai University)
Dharmalingam, V. (Dept. of Electrical and Electronics Engineering, Pandian Saraswathi Yadav Engineering College)
Ganesan, S. (Dept. of Electrical Engineering, Annamalai University)
Publication Information
Journal of Electrical Engineering and Technology / v.12, no.4, 2017 , pp. 1348-1356 More about this Journal
Abstract
Integration of wind generators with the conventional power plants will raise operational challenges to the electric power utilities due to the uncertainty of wind availability. Thus, the Generation Scheduling (GS) among the online generating units has become crucial. This process can be formulated mathematically as an optimization problem. The GS problem of wind integrated power system is inherently complex because the formulation involves non-linear operational characteristics of generating units, system and operational constraints. As the robust tool is viable to address the chosen problem, the modern bio-inspired algorithm namely, Grey Wolf Optimization (GWO) algorithm is chosen as the main optimization tool. The intended algorithm is implemented on the standard test systems and the attained numerical results are compared with the earlier reports. The comparison clearly indicates the intended tool is robust and a promising alternative for solving GS problems.
Keywords
Grey wolf optimization; Generation scheduling; Wind power;
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