Planning low-carbon distributed power systems: Evaluating the role of energy storage
Jiachen Mao, Mehdi Jafari, Audun Botterud

TL;DR
This study develops a mathematical model to evaluate the impact of energy storage, especially batteries, on the decarbonization of distributed power systems, highlighting the importance of degradation modeling for future planning.
Contribution
It introduces a comprehensive modeling framework that incorporates battery degradation and dynamic efficiencies into generation expansion planning for low-carbon distributed power systems.
Findings
Battery degradation significantly affects expansion outcomes in deep decarbonization scenarios.
Dynamic efficiencies and cycling powers have limited impact on optimal portfolios but increase computational complexity.
Battery storage becomes economically viable for decarbonization by 2050 with technological advances.
Abstract
This paper introduces a mathematical formulation of energy storage systems into a generation capacity expansion framework to evaluate the role of energy storage in the decarbonization of distributed power systems. The modeling framework accounts for dynamic charging/discharging efficiencies and maximum cycling powers as well as cycle and calendar degradation of a Li-ion battery system. Results from a small-scale distributed power system indicate that incorporating the dynamic efficiencies and cycling powers of batteries in the generation planning problem does not significantly change the optimal generation portfolio, while adding substantial computational burden. In contrast, accounting for battery degradation leads to substantially different generation expansion outcomes, especially in deep decarbonization scenarios with larger energy storage capacities. Under the assumptions used in…
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