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Thermo-Economic Modeling and Evaluation of Physical Energy Storage in Power System

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Abstract

In order to assess the electrical energy storage technologies, the thermo-economy for both capacity-type and power-type energy storage are comprehensively investigated with consideration of political, environmental and social influence. And for the first time, the Exergy Economy Benefit Ratio (EEBR) is proposed with thermo-economic model and applied to three different storage systems in various scenarios, including pumped storage, compressed air energy storage and flywheel energy storage. The impact of the total system efficiency, annual utilization hour, life time, and other key factors are also analyzed. The results show that the EEBRs of pumped storage and compressed air energy storage under peak load shaving condition and flywheel energy storage under frequency modulation service condition are all larger than zero, which means they are all thermo-economically feasible. With extra consideration of political, environmental and social impact, the exergy cost could reduce by about 25% and the EEBR doubles. The sensitivity analysis indicates the similarity and diversity of influence to EEBR between capacity-type and power-type energy storage systems. The former is that energy efficiency is the dominated factor for all three storage systems. The latter is that the difference of exergy benefit mode causes variety in other major factors. For energy-type storage system, like pumped storage and compressed air storage, the peak-to-valley price ratio is very sensitive in energy arbitrage. For power-type storage system, like flywheel storage, the mileage ratio is in leading position in auxiliary service benefit by mileage. In the three cases studied, the pumped storage has the best thermo-economy; the compressed air energy storage is the second, and the flywheel energy storage is the third. The main reason is that the pumped storage has the least non-exergy cost, and flywheel has the most.

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Abbreviations

B :

benefit

b :

unit benefit

C :

cost

c :

unit cost

E :

exergy

EEBR:

exergy economy benefit ratio

ex :

exergy coefficient

MR:

mileage ratio

m :

substance quality

N :

life time

P :

power

RC:

regulated capacity

RM:

regulated mileage

RMCCP:

regulation market capability clearing price

RMPCP:

regulation market performance clearing price

SC:

system capacity

T :

time

t :

unit time

δ :

performance factor

ζ :

actual performance score

η :

efficiency

κ :

marginal revenue factor

aux:

in auxiliary service

CO2 :

CO2 emission reduction subsidy

con:

construction

dem:

demand-side management incentive

elec:

electricity

env:

environment

exh:

exhausting

ex:

exergy

fina:

financial

fre:

frequency modulation

in:

inlet

max:

maximum

n, i, j, k :

tensor indexes

nc:

non-energy

new:

additional increased

non, elec:

non-electricity

ope:

operational and maintenance

out:

outlet

peak:

in electric peak-shaving auxiliary service

perp:

permanent

pol:

policy

price:

unit price

rew:

reward-fund standard

soc:

society

sub:

subsidy

tax:

tax preference

tem:

temporary

tot:

total

wat:

water resource fee

wind:

in wind power plant

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Acknowledgments

The work was funded by National Key R&D Plan (2017YFB0903605), National Natural Science Foundation of China (51606185), International Partnership Program, Bureau of International Cooperation of Chinese Academy of Sciences (182211KYSB20170029), Science and Technology Plan Program of Guizhou Province ([2017]1163), Beijing Key Laboratory of Distributed Combined Cooling Heating and Power System.

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Authors and Affiliations

  1. Institute of Engineering Thermophysics, Chinese Academy of Science, Beijing, 100190, China

    Shan Hu, Chang Liu, Jie Ding, Yujie Xu & Haisheng Chen

  2. University of Chinese Academy of Sciences, Beijing, 100049, China

    Jie Ding, Yujie Xu & Haisheng Chen

  3. National Energy Large Scale Physical Energy Storage Technologies R&D Center, Bijie, 551712, China

    Haisheng Chen & Xuezhi Zhou

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  1. Shan Hu
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Correspondence to Haisheng Chen.

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Hu, S., Liu, C., Ding, J. et al. Thermo-Economic Modeling and Evaluation of Physical Energy Storage in Power System. J. Therm. Sci. 30, 1861–1874 (2021). https://doi.org/10.1007/s11630-021-1417-4

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