Optimizing energy storage participation in emerging power markets

Chen, Hao; Liu, Zhenhua; Coskun, Ayse K.; Wierman, Adam

doi:10.1109/igcc.2015.7393718

Cited by 22 publications

(12 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In addition, the manufacturing cost of lithium-ion batteries is expected to continue to decrease. Because of the increasing interest in applications of battery energy storage (BES) for energy arbitrage [4], frequency control [5], [6], voltage support [7], peak shaving [8], and as a demand response resource in data centers and smart buildings [9], [10], accurate methods for value assessment are needed. A key factor in the operational planning of BES is the operating cost, a majority of which stems from the degradation of battery cells.…”

Section: Introductionmentioning

confidence: 99%

Modeling of Lithium-Ion Battery Degradation for Cell Life Assessment

Oudalov

Ulbig

et al. 2018

IEEE Trans. Smart Grid

735

409

View full text Add to dashboard Cite

Rechargeable lithium-ion batteries are promising candidates for building grid-level storage systems because of their high energy and power density, low discharge rate, and decreasing cost. A vital aspect in energy storage planning and operations is to accurately model the aging cost of battery cells, especially in irregular cycling operations. This paper proposes a semi-empirical lithium-ion battery degradation model that assesses battery cell life loss from operating profiles. We formulate the model by combining fundamental theories of battery degradation and our observations in battery aging test results. The model is adaptable to different types of lithium-ion batteries, and methods for tuning the model coefficients based on manufacturer's data are presented. A cycle-counting method is incorporated to identify stress cycles from irregular operations, allowing the degradation model to be applied to any battery energy storage (BES) applications. The usefulness of this model is demonstrated through an assessment of the degradation that a BES would incur by providing frequency control in the PJM regulation market.

show abstract

Section: Introductionmentioning

confidence: 99%

Modeling of Lithium-Ion Battery Degradation for Cell Life Assessment

Oudalov

Ulbig

et al. 2018

IEEE Trans. Smart Grid

735

409

View full text Add to dashboard Cite

show abstract

“…(4) Energy storage system(ESS): composed of advances in the Li-ion battery technology in parallel or series, which not only be utilized to absorb excessive power and to carry out the way of charging and discharge as the signal from EMS, but has a fast response time following the cooperation control [23] [24].…”

Section: Power Architecture Of DC Rdsmentioning

confidence: 99%

Economic Power Schedule and Transactive Energy through Intelligent Centralized Energy Management System for DC Residential Distribution System

Yue¹,

Hu²,

Li³

et al. 2017

Preprint

View full text Add to dashboard Cite

DC residential distribution system (RDS) consisted by DC living home will be a significant integral part in the future green transmission. Meanwhile, the increasing number of distributed resources and intelligent devices will change the power flow between main grid and demand sides. The utilization of distributed generations (DGs) requires an economic operation, stability, environmentally friendly in the whole DC system. This paper not only presents an optimization schedule and transactive energy (TE) approach through centralized energy management system (CEMS), but a control approach to implement and ensure DG output voltages to various DC buses in DC RDS. Based on data collection, prediction and a certain objection, the expert system in CEMS can work out the optimization schedule, after this, the voltage droop control for steady voltage is aligned with the command of unit power schedule. In this work, a DC RDS is as a case study to demonstrate the process, the RDS is associated with unit economic models, cost minimization objective is proposed to achieve based on real-time electrical price. The results show that the proposed framework and methods will help the targeted DC residential system to reduce the total cost and reach stability and efficiency.

show abstract

“…Authors in [7,5,18,34,16,4,14] considers how data centers can participate in various energy markets. In particular, [7] considers different types of storage devices and show that depending on their degradation costs, it may not be economical for batteries to participate in some markets. In contrast to existing research, we show that if regulation market participation and data center operation are considered jointly, using batteries can be profitable even if it is separately not economical for each of the two applications.…”

Section: Frequency Regulationmentioning

confidence: 99%

Leveraging energy storage to optimize data center electricity cost in emerging power markets

Shi

Zhang

et al. 2016

Proceedings of the Seventh International Conference on Future Energy Systems

View full text Add to dashboard Cite

Energy storage in data centers has mainly been used as devices to backup generators during power outages. Recently, there has been a growing interest in using energy storage devices to actively shape power consumption in data centers to reduce their skyrocketing electricity bills. In this paper, we consider using energy storage in data centers for two applications in a joint fashion: reducing peak demand charges and enabling data centers to participate in regulation markets. We develop an optimization framework that captures the cost of electricity, degradation of energy storage devices, as well as the benefit from regulation markets. Under this framework, using real data Microsoft data center traces and PJM regulation signals, we show the electricity bill of a data center can be reduced by up to 20%. Furthermore, we demonstrate that the saving from joint optimization can be even larger than the sum of individually optimizing each component. We quantify the particular aspects of data center load profiles that lead to this superlinear gain. Compared to prior works that consider using energy storage devices for each single application alone, our results suggest that energy storage in data centers can have much larger impacts than previously thought possible.

show abstract

Optimizing energy storage participation in emerging power markets

Cited by 22 publications

References 22 publications

Modeling of Lithium-Ion Battery Degradation for Cell Life Assessment

Modeling of Lithium-Ion Battery Degradation for Cell Life Assessment

Economic Power Schedule and Transactive Energy through Intelligent Centralized Energy Management System for DC Residential Distribution System

Leveraging energy storage to optimize data center electricity cost in emerging power markets

Contact Info

Product

Resources

About