TY - GEN
T1 - Battery energy storage scheduling for optimal load variance minimization
AU - Zhang, Yichen
AU - Melin, Alexander
AU - Olama, Mohammed
AU - Djouadi, Seddik
AU - Dong, Jin
AU - Tomsovic, Kevin
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/7/3
Y1 - 2018/7/3
N2 - Generation portfolio can be significantly altered due to the deployment of distributed energy resources (DER) in distribution networks and the concept of microgrid. Generally, distribution networks can operate in a more resilient and economic fashion through proper coordination of DER. However, due to the partially uncontrollable and stochastic nature of some DER, the variance of net load of distribution systems increases, which raises the operational cost and complicates operation for transmission companies. This motivates peak shaving and valley filling using energy storage units deployed in distribution systems. This paper aims at theoretical formulation of optimal load variance minimization, where the infinity norm of net load is minimized. Then, the problem is reformulated equivalently as a linear program. A case study is performed with capacity-limited battery energy storage model and the simplified power flow model of a radial distribution network. The influence of capacity limit and deployment location are studied.
AB - Generation portfolio can be significantly altered due to the deployment of distributed energy resources (DER) in distribution networks and the concept of microgrid. Generally, distribution networks can operate in a more resilient and economic fashion through proper coordination of DER. However, due to the partially uncontrollable and stochastic nature of some DER, the variance of net load of distribution systems increases, which raises the operational cost and complicates operation for transmission companies. This motivates peak shaving and valley filling using energy storage units deployed in distribution systems. This paper aims at theoretical formulation of optimal load variance minimization, where the infinity norm of net load is minimized. Then, the problem is reformulated equivalently as a linear program. A case study is performed with capacity-limited battery energy storage model and the simplified power flow model of a radial distribution network. The influence of capacity limit and deployment location are studied.
UR - http://www.scopus.com/inward/record.url?scp=85050668596&partnerID=8YFLogxK
U2 - 10.1109/ISGT.2018.8403324
DO - 10.1109/ISGT.2018.8403324
M3 - Conference contribution
AN - SCOPUS:85050668596
T3 - 2018 IEEE Power and Energy Society Innovative Smart Grid Technologies Conference, ISGT 2018
SP - 1
EP - 5
BT - 2018 IEEE Power and Energy Society Innovative Smart Grid Technologies Conference, ISGT 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2018 IEEE Power and Energy Society Innovative Smart Grid Technologies Conference, ISGT 2018
Y2 - 19 February 2018 through 22 February 2018
ER -
