Battery Energy Storage Scheduling for Optimal Load Variance Minimization
By:
Melin, Alexander ; Olama, Mohammed M; Djouadi, Seddik; Dong, Jin ; Tomsovic, Kevin; Zhang, Yichen
Book Title:
2018 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT)
Publication Date:
April 1, 2024
Publisher Location:
IEEE, New Jersey, United States of America
Conference Name:
Innovative Smart Grid Technologies
Conference Location:
Washington D.C., District of Columbia, United States of America
Conference Sponsor:
IEEE Power & Energy Systems
Abstract
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.
