| Title |
Application of genetic algorithms for unit commitment and economic dispatch problems in microgrids |
| Authors |
RODRÍGUEZ DEL NOZAL, ÁLVARO, TAPIA CÓRDOBA, ALEJANDRO, ALVARADO BARRIOS, LÁZARO, GUTIÉRREZ REINA, DANIEL |
| External publication |
No |
| Means |
Stud. Comput. Intell. |
| Scope |
Capítulo de un Libro |
| Nature |
Científica |
| SJR Quartile |
4 |
| SJR Impact |
0.18500 |
| Web |
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85076752343&doi=10.1007%2f978-3-030-33820-6_6&partnerID=40&md5=51d59dc8c8504f2731f9add1e8b65b1d |
| Publication date |
01/01/2020 |
| Scopus Id |
2-s2.0-85076752343 |
| DOI |
10.1007/978-3-030-33820-6_6 |
| Abstract |
In the last decades, new types of generation technologies have emerged and have been gradually integrated into the existing power systems, moving their classical architectures to distributed systems. In spite of the positive features associated to this paradigm, new problems arise such as coordination and uncertainty. In this framework, microgrids (MGs) constitute an effective solution to deal with the coordination and operation of these distributed energy resources. This book chapter proposes a Genetic Algorithm (GA) to address the combined problem of Unit Commitment (UC) and Economic Dispatch (ED). With this end, a detailed model of a MG is introduced together with all the control variables and power restrictions. In order to optimally operate the MG, two operation modes are introduced, which attend to optimize economical factors and the robustness of the solution with respect power demand uncertainty. Therefore, it achieves a robust design that guarantees the power supply for different confidence levels. Finally, the algorithm is applied to an example scenario to illustrate its performance. © Springer Nature Switzerland AG 2020. |
| Keywords |
Economic dispatch; Genetic algorithm; Microgrids; Unit commitment |
| Universidad Loyola members |
|
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