4.7 Article

Short-Term Scheduling of Thermal Generators and Battery Storage With Depth of Discharge-Based Cost Model

Journal

IEEE TRANSACTIONS ON POWER SYSTEMS
Volume 30, Issue 4, Pages 2110-2118

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TPWRS.2014.2352333

Keywords

Battery short-term cost model; ramping; short-term scheduling; short-term storage scheduling

Ask authors/readers for more resources

Utility scale battery storage will soon reach a level of maturity where the modular design of the technology and aggregation will allow custom-built solutions for energy and ancillary service needs of the power system. Several projects are in the demonstration phase worldwide and hold promise for successful incorporation of battery storage into traditional power systems operations. In contrast to thermal generators and pumped hydro stations, there is a strong connection between the short-term operation and life of the battery storage systems. Due to this long-term consequence of short-term decisions for battery technologies, a constant short-term cost model is inadequate. Instead an adaptable short-term cost model is required which reflects the operation of the battery. Such a model of the battery is presented considering battery cycling and depth of discharge. Further, this paper aims to elucidate this relation between short-term and long-term costs of utility scale battery energy storage and presents a mathematical formulation for short-term 24-h scheduling problem in conjunction with thermal generation. The model is illustrated and storage efficacy is examined by scheduling alongside traditional generation with prices typical in Ontario, Canada and battery storage is used to alleviate price spikes caused by ramping requirements.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.7
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available