TY - GEN
T1 - Piecewise Linear Optimization for Public EV Charging Depots in Different Utility Environments
AU - Brissette, Alexander
AU - Coats, David
AU - Scoffield, Don
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/12/16
Y1 - 2020/12/16
N2 - With the proliferation of electric vehicles (EVs), EV supply equipment technology is being pushed to increasingly higher power levels, such as extreme fast charging (XFC) at 300kW or more. As more public XFC depots are connected to electric distribution systems, utility operators will mitigate their impact with pricing schemes and programs such as demand response, demand charges, and time-varying prices. In this paper we describe an XFC management system that combines an on-site battery energy storage system and an optimization application that minimizes the cost to operate the depot in light of the utility pricing programs. We have designed the optimizer specially to use fast and simple linear programming so that it can be deployed to low-cost computing platforms. We also describe how several utility pricing schemes are integrated into a single piecewise model, reducing the engineering effort to implement the optimizer in different utility environments.
AB - With the proliferation of electric vehicles (EVs), EV supply equipment technology is being pushed to increasingly higher power levels, such as extreme fast charging (XFC) at 300kW or more. As more public XFC depots are connected to electric distribution systems, utility operators will mitigate their impact with pricing schemes and programs such as demand response, demand charges, and time-varying prices. In this paper we describe an XFC management system that combines an on-site battery energy storage system and an optimization application that minimizes the cost to operate the depot in light of the utility pricing programs. We have designed the optimizer specially to use fast and simple linear programming so that it can be deployed to low-cost computing platforms. We also describe how several utility pricing schemes are integrated into a single piecewise model, reducing the engineering effort to implement the optimizer in different utility environments.
KW - battery energy storage system
KW - demand response
KW - electric vehicles
KW - extreme fast EV charging
KW - time of use
UR - https://www.scopus.com/pages/publications/85105478335
UR - https://www.mendeley.com/catalogue/1c390251-7bd3-32cc-bc30-bf9ad32fe24a/
U2 - 10.1109/CSDE50874.2020.9411610
DO - 10.1109/CSDE50874.2020.9411610
M3 - Conference contribution
AN - SCOPUS:85105478335
T3 - 2020 IEEE Asia-Pacific Conference on Computer Science and Data Engineering, CSDE 2020
BT - 2020 IEEE Asia-Pacific Conference on Computer Science and Data Engineering, CSDE 2020
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2020 IEEE Asia-Pacific Conference on Computer Science and Data Engineering, CSDE 2020
Y2 - 16 December 2020 through 18 December 2020
ER -