Energy Management and Optimization Methods for Grid Energy Storage Systems
By R. Byrne, Tu Anh Nguyen, D. Copp, B. Chalamala, I. Gyuk. IEEE Access, 2018
326 citations recorded by the source corpus.
Today, the stability of the electric power grid is maintained through real time balancing of generation and demand. Grid scale energy storage systems are increasingly being deployed to provide grid operators the flexibility needed to maintain this balance. Energy storage also imparts resiliency and robustness to the grid infrastructure. Over the last few years, there has been a significant increase in the deployment of large scale energy storage systems. This growth has been driven by improvements in the cost and performance of energy storage technologies and the need to accommodate distributed generation, as well as incentives and government mandates. Energy management systems (EMSs) and optimization methods are required to effectively and safely utilize energy storage as a flexible grid asset that can provide multiple grid services. The EMS needs to be able to accommodate a variety of use cases and regulatory environments. In this paper, we provide a brief history of grid-scale energy storage, an overview of EMS architectures, and a summary of the leading applications for storage. These serve as a foundation for a discussion of EMS optimization methods and design.
Subfields: Control and Systems Engineering, Electrical and Electronic Engineering
View Paper: https://www.semanticscholar.org/paper/efe41761c2a6361985420e4c0f03746332ab93d7
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In Electrical and Electronic Engineering
Citations in the corpus
- Energy management system for smart grid: An overview and key issues (2020, methodology): “MILP is a programming method where some of the objective variables are constrained to be integer while additional variables are permissible to be noninteger.(188) When the system is subjected to dynamics with discrete decisions variables and nonlinearity, MINLP is helpful to find an optimal solution”