Issue |
E3S Web Conf.
Volume 114, 2019
International Conference of Young Scientists “Energy Systems Research 2019”
|
|
---|---|---|
Article Number | 03002 | |
Number of page(s) | 7 | |
Section | Reliability and Safety of Energy Systems | |
DOI | https://doi.org/10.1051/e3sconf/201911403002 | |
Published online | 04 September 2019 |
Application the differential evolution for solving the problem of minimizing the power shortage of electric power systems
Melentiev Energy Systems Institute of Siberian Branch of the Russian Academy of Sciences, Irkutsk, Russian Federation ;
Based on the experience of domestic and foreign researchers, it is known that there are various mathematical models, software systems, and optimization methods used to solve the set tasks for assessing the resource adequacy of electric power systems (EPS). However, the continuous development of EPS leads to the complication and integration of systems against the background of which it becomes necessary to take into account an increasing number of its elements and parameters in one task. Thus, for more effective (in terms of speed and accuracy) solutions of modified models, it is required to analyze and search the most appropriate set of optimization methods. In this connection, the purpose of this study is to analyze the applicability and the effectiveness of applying the method of differential evolution and gradient optimization methods for the model of minimizing the power deficit, which should be also compared. The article considers the analysis of the results of the work that optimization methods, studies were conducted on a test isolated EPS, with various tuning parameters. As a result, it was confirmed that these methods could be used to solve the problem. From the point of view of accuracy and resources expended on calculations, the most efficient among the implemented methods was the method of differential evolution, which was confirmed by numerical experiments on the small systems.
Key words: energy system / resource adequacy / power shortage / optimization methods / heuristic methods.
© The Authors, published by EDP Sciences, 2019
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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