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Research Article

Optimization strategy and capacity planning for coordinated operation of regional energy internet system based on sparrow search algorithm

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Pages 1486-1502 | Received 25 Jul 2021, Accepted 01 Nov 2021, Published online: 23 Jan 2022
 

ABSTRACT

Energy Internet is an important foundation platform for promoting carbon emission reduction and carbon neutralization. However, most of the existing literature focuses on the conceptual design of the energy internet, lacking in-depth analysis of its superiorities and external factors affecting its performance. This paper proposed a regional energy internet system (REI) and proved that the REI system was superior to the distribute energy system (DES) in the economy, energy-saving and emission reduction performance and the grid’s stable operation. This paper applied the sparrow search algorithm and the weighted coefficient method to solve the optimization problem. Results showed that compared to the DES, the REI system’s operation and maintenance cost averagely decreased 12.59%, carbon emission averagely reduced by 16.90%, energy consumption averagely declined 15.00%, and comprehensive performance averagely went up 14.41%. Besides, the REI system had a larger rational operation range than DES and varied with user load types. Furthermore, research regarded to the user load type on the REI system found an index for preliminary filtering the REI system’s favorable user load before algorithm optimization. The results indicated that the REI system and its user load screening index could effectively meet the energy-saving and emission reduction requirements of the energy system.

Nomenclature

η=

efficiency (-)

N=

Nominal capacity (kW)

E=

Electricity (kW)

Q=

Heat energy (kW)

F=

Gas consumption (m3 / h)

QC=

Cool energy (kW)

κ=

Absorption unit’s load rate (-)

f=

Natural gas (-)

χ=

Boiler operation efficiency (-)

=

Energy transmission efficiency (-)

C=

Cost (CNY)

c=

Cost (CNY)

τ=

Carbon emission coefficient (g/kW)

δ=

Energy consumption coefficient (g/kW)

λ=

Weight factor (-)

Subscript=

 

i=

Positive integer (form 1 to 48)

j=

Positive integer (1,2,3)

max=

Maximum value

min=

Minimum value

g=

The grid

gs=

Electricity sale to the grid

e=

Electricity

h=

Heating load

diff=

Differential value

Acronyms=

 

ICE=

Internal Combustion Engine

LHV=

Low Calorific Value

(kJ / m3)

AU=

Absorption Unit

EC=

Electric chiller

PV=

Photovoltaic Generation

WHRS=

Waste Heat Recovery System

DES=

Distribute Energy System

REI=

Regional Energy Internet

COP=

Coefficient of Performance

CE=

Carbon Emission

EU=

Energy Usage

SD=

Standard Deviation

Disclosure statement

No potential conflict of interest was reported by the author(s).

Supplementry material

Supplementry material for this article can be accessed on the Publisher website.

Additional information

Funding

This work was supported by the National Natural Science Foundation of China [51906173].

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