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Optimization of Operation Strategies for a Combined Cooling, Heating and Power System based on Adiabatic Compressed Air Energy Storage

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Abstract

The fluctuations of renewable energy and various energy demands are crucial issues for the optimal design and operation of combined cooling, heating and power (CCHP) system. In this paper, a novel CCHP system is simulated with advanced adiabatic compressed air energy storage (AA-CAES) technology as a join to connect with wind energy generation and an internal-combustion engine (ICE). The capital cost of utilities, energy cost, environmental protection cost and primary energy savings ratio (PESR) are used as system performance indicators. To fulfill the cooling, heating and power requirements of a district and consider the thermal-electric coupling of ICE and AA-CAES in CCHP system, three operation strategies are established to schedule the dispatch of AA-CAES and ICE: ICE priority operation strategy, CAES priority operation strategy and simultaneous operation strategy. Each strategy leads the operation load of AA-CAES or ICE to improve the energy supply efficiency of the system. Moreover, to minimize comprehensive costs and maximize the PESR, a novel optimization algorithm based on intelligent updating multi-objective differential evolution (MODE) is proposed to solve the optimization model. Considering the multi-interface characteristic and active management ability of the ICE and AA-CAES, the economic benefits and energy efficiency of the three operation strategies are compared by the simulation with the same system configuration. On a typical summer day, the simultaneous strategy is the best solution as the total cost is 3643 USD and the PESR is 66.1%, while on a typical winter day, the ICE priority strategy is the best solution as the total cost is 4529 USD and the PESR is 64.4%. The proposed methodology provides the CCHP based AA-CAES system with a better optimized operation.

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Abbreviations

C :

cost/USD

c :

specific heats/kJ·(kg·K)−1

G :

gas/kW

h :

specific enthalpy/kJ·kg−1

M :

mass of air contained in the volume/kg

m :

mass flow rate/kg·s−1

P :

electricity power/kW

p :

pressure/Pa

Q :

thermal power/kW

R g :

gas constant relative to air/J·(mol·K)−1

T :

Temperature/K

t :

time/h

V :

volume of the storage chamber/m3

W :

work/J

b :

boil

c :

Compression process

ch :

air storage process in chamber

ci :

inlet air of chamber

cl :

cooling load

cold :

cold water

com :

compressor

e :

electricity load

ec :

electric chiller

ex :

exhaust gas heat of the ICE

hl :

heating load

hot :

hot water

ic :

intercool of the ICE

in :

inlet

jw :

jacket water of the ICE

loss :

heat loss of the ICE

max:

maximum

min:

minimum

out :

outlet

Pe :

electrical efficiency of the ICE

r :

ration

t :

Expansion process

te :

thermal efficiency of the ICE

tur :

turbines

v :

velocity

π :

pressure ratio

η :

efficiency

ε :

heat exchanger effectiveness

AA-CAES:

advanced adiabatic-CAES

CAES:

compressed air energy storage

ICE:

internal combustion engine

MODE:

multi-objective differential evaluation

O&M:

operation and maintenance

SOC:

state of charge

TES:

thermal energy storage

WT:

wind turbine

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Acknowledgments

The work was supported by the National Fundamental Research Program of China 973 project (2014CB249201).

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Authors and Affiliations

  1. School of Mechanical and Energy Engineering, Tongji University, Shanghai, 201804, China

    Shang Chen, Tong Zhu & Liuchen Liu

  2. ENN Science and Technology Development Co., Ltd., Langfang, 065000, China

    Zhongxue Gan & Xiaojun Zhu

Authors
  1. Shang Chen
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  2. Tong Zhu
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  3. Zhongxue Gan
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  4. Xiaojun Zhu
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  5. Liuchen Liu
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Correspondence to Tong Zhu.

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Chen, S., Zhu, T., Gan, Z. et al. Optimization of Operation Strategies for a Combined Cooling, Heating and Power System based on Adiabatic Compressed Air Energy Storage. J. Therm. Sci. 29, 1135–1148 (2020). https://doi.org/10.1007/s11630-020-1170-0

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  • DOI: https://doi.org/10.1007/s11630-020-1170-0

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