Research on Grid Connected Optimization Scheduling of Micro-grid Utilizing on Improved Bee Colony Method

Authors

  • Qiangshan Zhang Xinyang Vocational and Technical College, China

DOI:

https://doi.org/10.13052/dgaej2156-3306.3712

Keywords:

Optimal dispatch, improved bee colony algorithm, micro-grid grid connection.

Abstract

In order to achieve grid connected optimal dispatch of micro-grid, a improved
bee colony method is put forward to carry out optimization of grid connected
dispatch. Firstly, the optimal scheduling model of micro-grid grid connection,
and the overall cost of generating electricity and environmental cost of micro-
grid grid connection is used as objective function, and system power balance
constraint, power constraint of micro power supply, contact line constraint
that interacted with main grid and charge and discharge cycle of battery
are used as constraint conditions. Secondly, the improved bee colony algo-
rithm is established through introducing particle swarm algorithm. Finally,
a residential area is used as an example, and the optimal dispatch of
micro-grid grid connection is carried out based on proposed model, and
simulation results showed that the proposed model has higher correctness and
efficiency.

Downloads

Download data is not yet available.

Author Biography

Qiangshan Zhang, Xinyang Vocational and Technical College, China

Qiangshan Zhang, male, master, associate professor, school of mathematics
and computer science, xinyang vocational and technical college, xinyang out-
standing young science and technology expert, member of Chinese computer
society.
He mainly teaches computer network technology, data structure, database
technology, website design and management, introduction to e-commerce
and other professional courses. His main research direction is computer
network and database.
He graduated from the Department of Computer Science, Henan Univer-
sity with a bachelor’s degree in June 1997. He graduated from the School
of Computer Science, Wuhan University with a master’s degree in June
2010.
He has presided over and participated in a number of scientific research
projects, including science and technology research projects sponsored by
the Department of Science and Technology of Henan Province and projects
sponsored by the Department of Education of Henan Province for young backbone teachers. He has won a second prize of Xinyang City Science
and Technology Progress Award, a third prize of Xinyang City Science and
Technology Progress Award, a first prize of Henan Division of the National
Multimedia Education Software Grand Prix, and a number of first and second
prizes of Henan Provincial Department of Education.

References

Saeed Abrisham ForoushanAsl, Majid Gandomkar, Javad Nikoukar,

Optimal protection coordination in the micro-grid including inverter-

based distributed generations and energy storage system with con-

sidering grid-connected and islanded modes, Electric Power Systems

Research, 2020, 184(7):106317.

Wei Jin, Yongli Li, Guangyu Sun, Yan Gao, Admittance Model for

Three-phase AC Micro-grid with Unbalanced Load Compensated by

the Multi-functional Grid-connected Inverter, Energy Procedia, 2019,

(2):2475–2480.

Seyed Masoud Moghaddas-Tafreshi, Soheil Mohseni, Mohammad

Ehsan Karami, Scott Kelly, Optimal energy management of a grid-

connected multiple energy carrier micro-grid, Applied Thermal Engi-

neering, 2019, 152(4):796–806.

Martin Vincent Mancuso, Pietro Elia Campana, Jinyue Yan, Evaluation

of Grid-Connected Micro-Grid Operational Strategies, Energy Procedia,

, 158(2):1273–1278.

Brida V. Mbuwir, Fred Spiessens, Geert Deconinck, Distributed opti-

mization for scheduling energy flows in community micro-grids, Elec-

tric Power Systems Research, 2020, (187):106479.

M.F. Roslan, M.A. Hannan, Pin Jern Ker, R.A. Begum TMIndra Mahlia,

Z.Y. Dong, Scheduling controller for micro-grids energy management

system using optimization algorithm in achieving cost saving and

emission reduction, Applied Energy, 2021, 292(6):116883.

Simon Eberlein, Krzysztof Rudion, Small-signal stability modelling,

sensitivity analysis and optimization of droop controlled inverters in

LV micro-grids, International Journal of Electrical Power & Energy

Systems, 2021, 125(2):106404.

Sergio F. Contreras, Camilo A. Cortés, Johanna M.A. Myrzik, Proba-

bilistic multi-objective micro-grid planning methodology for optimizing

the ancillary services provision, Electric Power Systems Research, 2020,

(12): 106633.

Xiaoyi Ding, Wei Sun, Gareth P. Harrison, Xiaojing Lv, Yiwu Weng,

Multi-objective optimization for an integrated renewable, power-to-

gas and solid oxide fuel cell/gas turbine hybrid system in micro-grid,

Energy, 2020, 213(12):118804.

Koraljka Kovaˇcevi ́c Markov, Nikola Rajakovi ́c, Multi-energy micro-

grids with ecotourism purposes: The impact of the power market

and the connection line, Energy Conversion and Management, 2019,

(9):1105–1112.

Yibing Li, Weixing Huang, Rui Wu, Kai Guo, An improved arti-

ficial bee colony algorithm for solving multi-objective low-carbon

flexible job shop scheduling problem, Applied Soft Computing, 2020,

(10):106544.

Hu Yu, Sun Zhensheng, Cao Lijia, Zhang Yin, Pan Pengfei, Opti-

mization configuration of gas path sensors using a hybrid method

based on tabu search artificial bee colony and improved genetic algo-

rithm in turbofan engine, Aerospace Science and Technology, 2021,

(5):1006642.

Laifu Wen, Jiulong Cheng, Fei Li, Jiahong Zhao, Zhihao Shi,

Hongchuan Zhang, Global optimization of controlled source audio-

frequency magnetotelluric data with an improved artificial bee colony

algorithm, Journal of Applied Geophysics, 2019, 170(11):103845.

Mei Zhang, Yingtong Tan, Jinhui Zhu, Yinong Chen, Haiming Liu,

Modeling and simulation of improved artificial bee colony algorithm

with data-driven optimization, Simulation Modelling Practice and The-

ory, 2019, 93(5):305–321.

Depeng Kong, Tianqing Chang, Wenjun Dai, Quandong Wang, Haoze

Sun, An improved artificial bee colony algorithm based on elite group

guidance and combined breadth-depth search strategy, Information

Sciences, 2018, 442–443(5):54–71.

Hong Liu, Bin Xu, Dianjie Lu, Guijuan Zhang, A path planning

approach for crowd evacuation in buildings based on improved artificial

bee colony algorithm, Applied Soft Computing, 2018, 68(7):360–376.

Kunkun Peng, Quanke Pan, Biao Zhang, An improved artificial

bee colony algorithm for steelmaking–refining–continuous casting

scheduling problem, Chinese Journal of Chemical Engineering, 2018,

(8):1727–1735.

Min-Rong Chen, Jun-Han Chen, Guo-Qiang Zeng, Kang-Di Lu, Xin-

Fa Jian, An improved artificial bee colony algorithm combined with

extremal optimization and Boltzmann Selection probability, Swarm and

Evolutionary Computation, 2019, 49(9):158–177.

Włodzimierz Jefimowski, Adam Szel ̨ag, Marcin Steczek, Anatolii

Nikitenko, Vanadium redox flow battery parameters optimization in a

transportation micro-grid: A case study, Energy, 2020, 195(5):116943.

I. Zafeiratou, I. Prodan, F. Boem, L. Lefevre, Handling power losses in a

DC micro-grid through constrained optimization, IFAC-PapersOnLine,

, 53(2):12956–12961.

Published

2021-08-27

How to Cite

Zhang, Q. (2021). Research on Grid Connected Optimization Scheduling of Micro-grid Utilizing on Improved Bee Colony Method. Distributed Generation &Amp; Alternative Energy Journal, 37(1), 23–40. https://doi.org/10.13052/dgaej2156-3306.3712

Issue

Section

Articles