In this work, we analyze the impact of different options to represent the operation decisions in the study of energy storage (ES) investment for long-term planning models. We compare the representative days and the system-states approaches for the representation of these operation decisions. We proposed enhanced versions of these approaches to improve the ES investment approximation. An Spanish case study is evaluated and the results are used to identify the potential profits that energy storage investment can obtain.
Keywords: Planning, Energy, Optimization, Integer Programming
INFORMS Anual Meeting - INFORMS 2017, Houston, Texas (United States of America). 22-25 October 2017
Publication date: October 2017.
D.A. Tejada, S. Wogrin, E. Centeno, Enhanced representative days and system states modeling for energy storage investment, INFORMS Anual Meeting - INFORMS 2017. Houston, United States of America, 22-25 October 2017