Abstract
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.
| Original language | English (US) |
|---|---|
| Title of host publication | 2018 IEEE Power and Energy Society General Meeting, PESGM 2018 |
| Publisher | IEEE Computer Society |
| Volume | 2018-August |
| ISBN (Electronic) | 9781538677032 |
| DOIs | |
| State | Published - Dec 21 2018 |
| Event | 2018 IEEE Power and Energy Society General Meeting, PESGM 2018 - Portland, United States Duration: Aug 5 2018 → Aug 10 2018 |
Other
| Other | 2018 IEEE Power and Energy Society General Meeting, PESGM 2018 |
|---|---|
| Country | United States |
| City | Portland |
| Period | 8/5/18 → 8/10/18 |
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Keywords
- Energy storage
- Progressive hedging
- Resilience
ASJC Scopus subject areas
- Energy Engineering and Power Technology
- Nuclear Energy and Engineering
- Renewable Energy, Sustainability and the Environment
- Electrical and Electronic Engineering
Cite this
Enhancing Distribution Resilience with Mobile Energy Storage : A Progressive Hedging Approach. / Kim, Jip; Dvorkin, Yury.
2018 IEEE Power and Energy Society General Meeting, PESGM 2018. Vol. 2018-August IEEE Computer Society, 2018. 8585791.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Enhancing Distribution Resilience with Mobile Energy Storage
T2 - A Progressive Hedging Approach
AU - Kim, Jip
AU - Dvorkin, Yury
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
UR - http://www.scopus.com/inward/record.url?scp=85060789222&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85060789222&partnerID=8YFLogxK
U2 - 10.1109/PESGM.2018.8585791
DO - 10.1109/PESGM.2018.8585791
M3 - Conference contribution
AN - SCOPUS:85060789222
VL - 2018-August
BT - 2018 IEEE Power and Energy Society General Meeting, PESGM 2018
PB - IEEE Computer Society
ER -