Issue |
Int. J. Simul. Multidisci. Des. Optim.
Volume 14, 2023
|
|
---|---|---|
Article Number | 14 | |
Number of page(s) | 8 | |
DOI | https://doi.org/10.1051/smdo/2023017 | |
Published online | 27 November 2023 |
Research article
Optimization of multi-period investment planning in street lighting systems by mixed-integer linear programming
1
Instituto de Energía Eléctrica, Universidad Nacional de San Juan – CONICET San Juan, Argentina
2
Departamento de Ingeniería Eléctrica, Universidad Nacional de Colombia Bogota Colombia
* e-mail: srriverar@unal.edu.co
Received:
17
November
2022
Accepted:
24
October
2023
This article proposed the use of multi-period mixed-integer linear programming method for investment planning to support decision-making processes in upgrading and managing street lighting systems. The technique incorporates a multi-variate model that maximizes energy-saving by considering budget constraints, the state of the lighting system, and the available technology in the market to replace the existing streetlights. This topic is novel because the complexity of the problem relies on the existence of several potentially large investments. As explained in this paper, the proposed method optimally considers the investments and returns as a combination that maximizes energy savings. The method was tested using actual data from an undisclosed public lighting system in Colombia. The results obtained revealed that multi-period investment optimization based on mixed-integer linear programming is an ideal investment plan, particularly in streetlight systems. Therefore, it forms an invaluable tool for street lighting systems' administrators and decision-makers in optimizing and facilitating the critical decision-making process in their work environment.
Key words: Energy efficiency / mixed-integer linear programming / upgrade / resource allocation
© C.C. Rodríguez et al., Published by EDP Sciences, 2023
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.