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Volume 12
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10.3390/en12112143
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Article

An Evolutionary Computational Approach for the Problem of Unit Commitment and Economic Dispatch in Microgrids under Several Operation Modes

by
L. Alvarado-Barrios
1,*,
A. Rodríguez del Nozal
1,
A. Tapia
1,
J. L. Martínez-Ramos
2 and
D. G. Reina
3
1
Departamento de Ingeniería, Universidad Loyola Andalucía, 41014 Seville, Spain
2
Electrical Engineering Department, University of Seville, 41092 Seville, Spain
3
Electronic Engineering Department, University of Seville, 41092 Seville, Spain
*
Author to whom correspondence should be addressed.
Energies 2019, 12(11), 2143; https://doi.org/10.3390/en12112143
Submission received: 17 April 2019 / Revised: 10 May 2019 / Accepted: 30 May 2019 / Published: 4 June 2019
(This article belongs to the Special Issue Artificial Intelligence in Data Science For Energy Management in Sustainability)
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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. Despite the positive features associated to this paradigm, new problems arise such as coordination and uncertainty. In this framework, microgrids constitute an effective solution to deal with the coordination and operation of these distributed energy resources. This paper proposes a Genetic Algorithm (GA) to address the combined problem of Unit Commitment (UC) and Economic Dispatch (ED). With this end, a model of a microgrid is introduced together with all the control variables and physical constraints. To optimally operate the microgrid, three operation modes are introduced. The first two attend to optimize economical and environmental factors, while the last operation mode considers the errors induced by the uncertainties in the demand forecasting. Therefore, it achieves a robust design that guarantees the power supply for different confidence levels. Finally, the algorithm was applied to an example scenario to illustrate its performance. The achieved simulation results demonstrate the validity of the proposed approach.
Keywords: microgrids; Unit Commitment; Economic Dispatch; Genetic Algorithm microgrids; Unit Commitment; Economic Dispatch; Genetic Algorithm

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MDPI and ACS Style

Alvarado-Barrios, L.; Rodríguez del Nozal, A.; Tapia, A.; Martínez-Ramos, J.L.; Reina, D.G. An Evolutionary Computational Approach for the Problem of Unit Commitment and Economic Dispatch in Microgrids under Several Operation Modes. Energies 2019, 12, 2143. https://doi.org/10.3390/en12112143

AMA Style

Alvarado-Barrios L, Rodríguez del Nozal A, Tapia A, Martínez-Ramos JL, Reina DG. An Evolutionary Computational Approach for the Problem of Unit Commitment and Economic Dispatch in Microgrids under Several Operation Modes. Energies. 2019; 12(11):2143. https://doi.org/10.3390/en12112143

Chicago/Turabian Style

Alvarado-Barrios, L., A. Rodríguez del Nozal, A. Tapia, J. L. Martínez-Ramos, and D. G. Reina. 2019. "An Evolutionary Computational Approach for the Problem of Unit Commitment and Economic Dispatch in Microgrids under Several Operation Modes" Energies 12, no. 11: 2143. https://doi.org/10.3390/en12112143

APA Style

Alvarado-Barrios, L., Rodríguez del Nozal, A., Tapia, A., Martínez-Ramos, J. L., & Reina, D. G. (2019). An Evolutionary Computational Approach for the Problem of Unit Commitment and Economic Dispatch in Microgrids under Several Operation Modes. Energies, 12(11), 2143. https://doi.org/10.3390/en12112143

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