Journal
SUSTAINABILITY
Volume 14, Issue 6, Pages -Publisher
MDPI
DOI: 10.3390/su14063605
Keywords
cost-based ESS scheduling; energy efficiency; peak shaving; load balance; net zero emissions
Funding
- Korean National Police Agency [PR08-04-000-21]
- Korea Electric Power Corporation (KEPCO)
- Korean National Police Agency [PR08-04-000-21] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
Ask authors/readers for more resources
This paper proposes a method for cost minimization in energy storage system scheduling that takes into account the peak demand and load balancing simultaneously. A case study conducted in Korea Electric Power Corporation (KEPCO) reveals that demand charge is more important than energy charge, and solving the scheduling problem for cost reduction is beneficial for power system operation.
Various attempts have been made to reduce carbon emissions in the energy sector as part of global net zero emissions trends. Among them, interest in the use of energy storage systems (ESSs) for energy efficiency is growing. Utilities intend to improve the efficiency of investment and operating costs by reducing the maximum peak and leveling the load. Many ESS-scheduling optimization techniques have been studied to reduce the peak demand, balance the load, or reduce the cost corresponding to these two purposes from the customer's point of view. In this paper, a method for cost minimization that simultaneously considers both the peak demand and load balancing is proposed, and the results and analysis of a case study in Korea Electric Power Corporation (KEPCO), Korea are presented. Through these results, we show that there is a priority among the objective functions of the ESS schedule, that demand charge is more important than energy charge, and that the ESS schedule problem for customers to reduce costs is also beneficial to power system operation by the utility's rate policy.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available