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Neural Computing and Applications
Published in: Neural Computing and Applications 7/2020

18-11-2019 | Original Article

An optimum forceful generation scheduling and unit commitment of thermal power system using sine cosine algorithm

Authors: Ashutosh Bhadoria, Sanjay Marwaha, Vikram Kumar Kamboj

Published in: Neural Computing and Applications | Issue 7/2020

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Abstract

Conventional thermal power system-based units and its participation schedule known as unit commitment problem (UCP) is a significant and stimulating undertaking of allocating generated power among the dedicated units subject to numerous restrictions above a scheduled time prospect to obtain the slightest generation cost. This problem becomes further more complex by increasing the size of the power system. Since unit commitment problem is link optimization problem as it has both binary and continuous variable that is why it is most challenging problem to solve. In this paper, a recently invented optimizer sine–cosine is used to solve unit commitment problem. Sine cosine algorithm (SCA) is an innovative population centered optimization algorithm that has been used for solving the unit commitment optimization problems bounded by some constraints centered on the concept of a mathematical model of the sine and cosine functions. This paper offers the solution of unit commitment optimization problems of the electric power system by using the SCA, as UCP is linked optimization as it has both binary and continuous variables, the strategy adopted to tackle both variables is different. In this paper, proposed sine cosine algorithm searches allocation of generators (units that participate in generation to take upload) and once units are decided, allocation of generations (economic load dispatch) is done by mixed integer quadratic programming. The feasibility and efficacy of operation of SCA algorithm are verified for small- and medium-power systems, in which results for 4 unit, 5 unit, 6 unit, 7 unit, 10 units, 19 unit, 20 unit and 40 units are evaluated. The 10 generating units are evaluated with 5% and 10% spinning reserve. The results obviously show that the suggested method gives the superior type of solutions as compared to other algorithms.
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Appendix
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Metadata
Title
An optimum forceful generation scheduling and unit commitment of thermal power system using sine cosine algorithm
Authors
Ashutosh Bhadoria
Sanjay Marwaha
Vikram Kumar Kamboj
Publication date
18-11-2019
Publisher
Springer London
Published in
Neural Computing and Applications / Issue 7/2020
Print ISSN: 0941-0643
Electronic ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-019-04598-8

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