IEEE Power & Energy Magazine - September/October 2017 - 31

Compared to other types of batteries, Li-ion batteries
have the advantages of high energy density, high efficiency,
long cycle life, and environmental friendliness.
to balance intermittent renewables, control power quality, and
achieve load leveling. However, RFBs must prove their cost
competitiveness for broader market penetration. From the perspective of technology, membrane materials have until now
been susceptible to premature degradation and contamination; they are also very expensive. To address energy density
and cost limits, more research efforts are required if fundamental breakthroughs in key materials, especially for electrodes and membranes, are to be achieved. Some forthcoming
chemistries (e.g., hydrogen bromine and iron chromium) are
quite promising. Moreover, stack design and system integration with a holistic approach are expected to significantly
improve RFBs' overall performance and economy. From the
perspective of commercialization and marketing, more effective policy incentives and judicious business modes are also
critical to promote practical large-scale deployment of RFB
energy storage in the utility.

Hybrid Energy Storage
A single energy storage technology may be inadequate to
satisfy the requirements of certain applications. It is thus
desirable to develop hybrid energy storage systems (HESSs)
that consist of two or more energy storage devices with
complementary characteristics. These systems may combine
different battery technologies or integrate a battery with a
supercapacitor, fuel cell, flywheel, and/or superconductive
magnetic device. Usually, when a battery is adopted for
low-frequency fluctuation mitigation, another high-power
density medium can be combined for smoothing highfrequency fluctuation.
A HESS can potentially form an economical, sustainable
solution to power system issues. This class of storage has now
been piloted, e.g., in the city of Aachen, Germany, where a
hybrid Li-ion and lead-acid 5-MW facility came into operation in 2015 to provide testing, demonstration, and powerfrequency balancing. Another battery storage system composed
of a 2-MWh Li-ion battery and a 1-MWh VRB has also been
connected to a wind farm in Braderup, Germany.

Battery Management
The continuing proliferation of and advances in information and communication technologies, development of powerful cloud computing capabilities, and a growing Internet
of Things will significantly enhance or even transform the
concept of battery management, as modeling and control of
thousands of cells in large-scale battery storage will become
easier. In this sense, complicated but high-fidelity electroseptember/october 2017

chemical battery models, which can be cumbersome in onboard BMSs, can be harnessed in the cloud, where relevant
estimation/control algorithms based on distributed-parameter systems (e.g., three-dimensional thermal analysis) can
be efficiently computed (see Figure 8). Then, the generated
commands can be transmitted to each local battery storage
station via rapid, bidirectional communication. In such a
cloud-based BMS, the accuracy, resilience, reliability, and
safety of battery monitoring and management can be determined simultaneously. Cybersecurity, however, should be
thoroughly considered in any BMS scenario.

For Further Reading
M. Aneke and M. Wang, "Energy storage technologies and real
life applications: A state of the art review," Appl. -Energy, vol.
179, pp. 350-377, Oct. 2016.
X. Luo, J. Wang, M. Dooner, and J. Clarke, "Overview of
current development in electrical energy storage technologies
and the application potential in power system -operation," Appl.
Energy, vol. 137, pp. 511-536, Jan. 2015.
X. Hu, J. Jiang, D. Cao, and B. Egardt, "Battery health
prognosis for electric vehicles using sample entropy and sparse
Bayesian predictive modeling," IEEE Trans. Ind. Electron.,
vol. 63, no. 4, pp. 2645-2656, 2016.
X. Hu, S. Li, H. Peng, and F. Sun, "Charging time and loss
optimization for LiNMC and LiFePO4 batteries based on
equivalent circuit models," J. Power Sources, vol. 239, no. 10,
pp. 449-457, 2013.
C. Zou, C. Manzie, and D. Nesic, "A framework for simplification of PDE-based lithium-ion battery models," IEEE Trans.
Control Syst. Technol., vol. 24, no. 5, pp. 1594-1609, 2016.
Navigant Research (2014). Energy storage reduces diesel use
in microgrids [Online]. Available: www.navigantre-search.com/
blog/energy-storage-reduces--diesel-use-in-microgrids?utm_so
urce=Energy+Storage+Report&utm_campaign=bb361544d9ESR_2_10_1210_2_2012&utm_medium=email&utm_
term=0_bd57f7e9aa-bb361544d9-86107101

Biographies
Xiaosong Hu is with Chongqing University, China.
Changfu Zou is with Chalmers University of Technology, Gothenburg, Sweden.
Caiping Zhang is with Beijing Jiaotong University,
-China.
Yang Li is with Dongfang Electric Corporation, Chengdu, China.

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