Planning low-carbon distributed power systems: Evaluating the role of energy storage

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 smallscale 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 this study, it is found that battery energy storage is economically viable for 2020 only under strict carbon emission constraints. In contrast, given the projected technology advances and corresponding cost reductions, battery energy storage exhibits an attractive option to enable deep decarbonization in 2050. (c) 2021 Elsevier Ltd. All rights reserved.

Automated summary

This study introduces a mathematical formulation of energy storage systems into a generation capacity expansion framework and finds that dynamic parameters of batteries do not significantly impact the optimal generation portfolio, while battery degradation leads to substantially different generation expansion outcomes. Battery energy storage is economically viable for 2020 only under strict carbon emission constraints, but by 2050, it becomes an attractive option for deep decarbonization given projected technology advances and cost reductions.