An optimal stochastic energy management system for resilient microgrids

Jéssica Alice A. Silva, Juan Camilo López, Nataly Bañol Arias, Marcos J. Rider and Luiz C.P. da Silva

Applied Energy, 2021, vol. 300, issue C, No S0306261921008254

Abstract: This paper presents a stochastic mixed-integer nonlinear programming model for the optimal energy management system of unbalanced three-phase of alternating current microgrids. The proposed model considers the following random variables: nodal demands, nodal renewable generation and voltage reference at the point of common coupling. Furthermore, the proposed model is aimed at providing resilient energy management system solutions via contingency constraints. The proposed mixed-integer nonlinear programming model is transformed into a mixed-integer linear programming model through a set of linearizations that can be solved via off-the-shelf convex programming solvers. The analyzed microgrid comprises photovoltaic generation, energy storage systems, electric vehicle chargers, direct load control, and non-renewable generation, which operates when the microgrid is in islanded mode. The stochastic nature of the problem is considered through a scenario-based approach. The solution to the model determines the day-ahead operation of the microgrid resources that minimizes the average operational cost. An unexpected islanded operation at any given time is considered via contingency constraints. Tests are performed using data of the real microgrid at the Laboratory of Intelligent Electrical Networks (LabREI), at University of Campinas. Results show that the proposed model produces resilient day-ahead energy management system solutions while minimizing the average operational costs and maximizing the use of local renewable energy sources.

Keywords: Energy management system; Microgrids; Mixed-integer linear programming; Contingency constraints (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (15)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0306261921008254
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:appene:v:300:y:2021:i:c:s0306261921008254

Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/bibliographic
http://www.elsevier. ... 405891/bibliographic

DOI: 10.1016/j.apenergy.2021.117435

Access Statistics for this article

Applied Energy is currently edited by J. Yan

More articles in Applied Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().