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Capacity-operation collaborative optimization of the system integrated with wind power/photovoltaic/concentrating solar power with S-CO2 Brayton cycle

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Abstract

This paper proposes a new power generating system that combines wind power (WP), photovoltaic (PV), trough concentrating solar power (CSP) with a supercritical carbon dioxide (S-CO2) Brayton power cycle, a thermal energy storage (TES), and an electric heater (EH) subsystem. The wind power/photovoltaic/concentrating solar power (WP–PV–CSP) with the S-CO2 Brayton cycle system is powered by renewable energy. Then, it constructs a bi-level capacity-operation collaborative optimization model and proposes a non-dominated sorting genetic algorithm-II (NSGA-II) nested linear programming (LP) algorithm to solve this optimization problem, aiming to obtain a set of optimal capacity configurations that balance carbon emissions, economics, and operation scheduling. Afterwards, using Zhangbei area, a place in China which has significant wind and solar energy resources as a practical application case, it utilizes a bi-level optimization model to improve the capacity and annual load scheduling of the system. Finally, it establishes three reference systems to compare the annual operating characteristics of the WP–PV–CSP (S-CO2) system, highlighting the benefits of adopting the S-CO2 Brayton cycle and equipping the system with EH. After capacity-operation collaborative optimization, the levelized cost of energy (LCOE) and carbon emissions of the WP–PV–CSP (S-CO2) system are decreased by 3.43% and 92.13%, respectively, compared to the reference system without optimization.

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Abbreviations

CSP:

Concentrating solar power

EH:

Electric heater

HT:

Hot tank

PV:

Photovoltaic

S-CO2 :

Supercritical carbon dioxide

SF:

Solar field

TES:

Thermal energy storage

WP:

Wind power

WT:

Wind turbine

A :

Area/m2

B :

Coal consumption/t

C :

Capacity/MW

DNI:

Direct solar irradiation/(W·m−2)

GI:

Global irradiance/(W·m−2)

h :

Height/m

IC:

Investment costs/$

LCOE:

Levelized cost of electricity/($·kWh−1)

m :

Mass flow rate/(kg·s−1)

P :

Power/MW

Q :

Quantity of heat/MW

T :

Temperature/°C

v :

Wind speed/(m·s−1)

W :

Work/MW

η :

Efficiency

a:

Ambient

ab:

Abandoned

C:

Compressor

c:

Charge

d:

Discharge

HE:

Heat exchanger

INV:

Inverterin input

NOM:

Normal

O&M:

Operation and maintenance

out:

Output

ref:

Reference

s:

Standard

T:

Turbine

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Acknowledgements

This work was supported by the Major Program of the National Natural Science Foundation of China (Grant No. 52090060).

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Authors and Affiliations

  1. School of Energy, Power and Mechanical Engineering, North China Electric Power University, Beijing, 102206, China

    Yangdi Hu, Rongrong Zhai & Lintong Liu

Authors
  1. Yangdi Hu
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  2. Rongrong Zhai
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Corresponding author

Correspondence to Rongrong Zhai.

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Hu, Y., Zhai, R. & Liu, L. Capacity-operation collaborative optimization of the system integrated with wind power/photovoltaic/concentrating solar power with S-CO2 Brayton cycle. Front. Energy (2024). https://doi.org/10.1007/s11708-024-0922-z

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