Next Article in Journal
Statistical Diagnosis of the Best Weibull Methods for Wind Power Assessment for Agricultural Applications
Previous Article in Journal
A Combined State of Charge Estimation Method for Lithium-Ion Batteries Used in a Wide Ambient Temperature Range
Energies 2014, 7(5), 3033-3055; doi:10.3390/en7053033

A Simulation Framework for Optimal Energy Storage Sizing

1,* , 2 and 2
1 SPEC Energy Consulting, Rosario Norte 400/51, 7561156 Las Condes, Santiago, Chile 2 Energy Centre FCFM, Universidad de Chile, Avenida Tupper 2007, 8370451 Santiago, Chile
* Author to whom correspondence should be addressed.
Received: 7 March 2014 / Revised: 7 April 2014 / Accepted: 14 April 2014 / Published: 2 May 2014
View Full-Text   |   Download PDF [1458 KB, uploaded 17 March 2015]   |   Browse Figures


Despite the increasing interest in Energy Storage Systems (ESS), quantification of their technical and economical benefits remains a challenge. To assess the use of ESS, a simulation approach for ESS optimal sizing is presented. The algorithm is based on an adapted Unit Commitment, including ESS operational constraints, and the use of high performance computing (HPC). Multiple short-term simulations are carried out within a multiple year horizon. Evaluation is performed for Chile's Northern Interconnected Power System (SING). The authors show that a single year evaluation could lead to sub-optimal results when evaluating optimal ESS size. Hence, it is advisable to perform long-term evaluations of ESS. Additionally, the importance of detailed simulation for adequate assessment of ESS contributions and to fully capture storage value is also discussed. Furthermore, the robustness of the optimal sizing approach is evaluated by means of a sensitivity analyses. The results suggest that regulatory frameworks should recognize multiple value streams from storage in order to encourage greater ESS integration.
Keywords: energy storage systems; unit commitment; renewable energy; optimal sizing; high performance computing energy storage systems; unit commitment; renewable energy; optimal sizing; high performance computing
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Share & Cite This Article

Further Mendeley | CiteULike
Export to BibTeX |
MDPI and ACS Style

Suazo-Martínez, C.; Pereira-Bonvallet, E.; Palma-Behnke, R. A Simulation Framework for Optimal Energy Storage Sizing. Energies 2014, 7, 3033-3055.

View more citation formats

Related Articles

Article Metrics

For more information on the journal, click here


Cited By

[Return to top]
Energies EISSN 1996-1073 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert