TY - GEN
T1 - Enhancing Distribution Resilience with Mobile Energy Storage
T2 - 2018 IEEE Power and Energy Society General Meeting, PESGM 2018
AU - Kim, Jip
AU - Dvorkin, Yury
N1 - Funding Information:
The authors are with the Department of Electrical and Computer Engineering, Tandon School of Engineering, New York University. This work was supported in part by the US NSF Grant No. ECCS-1760540.
Funding Information:
This work was supported in part by the US NSF Grant No. ECCS-1760540.
Publisher Copyright:
© 2018 IEEE.
PY - 2018/12/21
Y1 - 2018/12/21
N2 - Electrochemical energy storage (ES) units (e.g. batteries) have been field-validated as an efficient back-up resource that enhance resilience of the distribution system in case of natural disasters. However, using these units for resilience is not sufficient to economically justify their installation and, therefore, these units are often installed in locations where they incur the greatest economic value during normal operations. Motivated by the recent progress in transportable ES technologies, i.e. ES units can be moved using public transportation routes, this paper proposes to use this spatial flexibility to bridge the gap between the economically optimal locations during normal operations and disaster-specific locations where extra back-up capacity is necessary. We propose a two-stage optimization model that optimizes investments in mobile ES units in the first stage and can re-route the installed mobile ES units in the second stage to avoid the expected load shedding caused by disaster forecasts. Since the proposed model cannot be solved efficiently with off-the-shelf solvers, even for relatively small instances, we apply a progressive hedging algorithm. The proposed model and progressive hedging algorithm are tested through two illustrative examples on a 15-bus radial distribution test system.
AB - Electrochemical energy storage (ES) units (e.g. batteries) have been field-validated as an efficient back-up resource that enhance resilience of the distribution system in case of natural disasters. However, using these units for resilience is not sufficient to economically justify their installation and, therefore, these units are often installed in locations where they incur the greatest economic value during normal operations. Motivated by the recent progress in transportable ES technologies, i.e. ES units can be moved using public transportation routes, this paper proposes to use this spatial flexibility to bridge the gap between the economically optimal locations during normal operations and disaster-specific locations where extra back-up capacity is necessary. We propose a two-stage optimization model that optimizes investments in mobile ES units in the first stage and can re-route the installed mobile ES units in the second stage to avoid the expected load shedding caused by disaster forecasts. Since the proposed model cannot be solved efficiently with off-the-shelf solvers, even for relatively small instances, we apply a progressive hedging algorithm. The proposed model and progressive hedging algorithm are tested through two illustrative examples on a 15-bus radial distribution test system.
KW - Energy storage
KW - Progressive hedging
KW - Resilience
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U2 - 10.1109/PESGM.2018.8585791
DO - 10.1109/PESGM.2018.8585791
M3 - Conference contribution
AN - SCOPUS:85060789222
T3 - IEEE Power and Energy Society General Meeting
BT - 2018 IEEE Power and Energy Society General Meeting, PESGM 2018
PB - IEEE Computer Society
Y2 - 5 August 2018 through 10 August 2018
ER -