Power Command Optimal Allocation Model of Distributed Energy System Based on Improved Firefly Algorithm

Authors

  • Xiao Xue School of Information Engineering, Nanyang Institute of Technology, Nanyang 473004, Henan, China
  • Yangbing Zheng College of Mechanical and Electronic Engineering, Nanyang Normal University, Nanyang 473061, Henan, China, Qinghai Wandong Ecological Environment Development Co.LTD, Geermu 816000, Qinghai, China
  • Chao Lu Nanyang Zehui Technology Co., LTD, Nanyang, 473000, Henan, China

DOI:

https://doi.org/10.13052/dgaej2156-3306.37321

Keywords:

Distributed energy system, power command allocation, improved firefly algorithm.

Abstract

In order to enhance the power command allocation effect of distributed
energy system, the modified firefly algorithm is established to deal with the
optimal model of the proposed power command allocation. Firstly, the basic
function and physical structure of power grid system distributed energy sys-
tem are analyzed. Secondly, theoretical model of power command allocation
model distributed energy system is constructed. Thirdly, the improved firefly
algorithm is established. Finally, a power grid system distributed energy
system with eight units is selected to carry out simulation analysis, results
illustrate that the model has quickest convergence efficiency, and can obtain
optimal power command allocation effect distributed energy system.

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Author Biographies

Xiao Xue, School of Information Engineering, Nanyang Institute of Technology, Nanyang 473004, Henan, China

Xiao Xue, Associate Professor of School of Electronic and Electrical Engi-
neering in Nanyang Institute of Technology, Nanyang, China. He received
his Bachelor of Engineering Science in Electronic Information Engineering
from Nanyang Institute of Technology, Henan, China, in 2003; the Doctor
Degree of Engineering in detection technology and automatic equipment
from China University of Geosciences, Wuhan, China, in 2015. His current research interests include Detection technology, and intelligent control.

Yangbing Zheng, College of Mechanical and Electronic Engineering, Nanyang Normal University, Nanyang 473061, Henan, China, Qinghai Wandong Ecological Environment Development Co.LTD, Geermu 816000, Qinghai, China

Yangbing Zheng, Associate Professor of control science and engineering,
with Nanyang Normal University, Nanyang, China. She received her Bach-
elor of Engineering Science in Electronic Information Engineering from
Nanyang Institute of Technology, Henan, China, in 2006; and the Doctor
Degree of Engineering in detection technology and automatic equipment
from China University of Mining and Technology, Beijing, China, in 2013,
respectively. Her current research interests include active robot control, and
nonlinear control.

Chao Lu, Nanyang Zehui Technology Co., LTD, Nanyang, 473000, Henan, China

Chao Lu, Engineer of Nanyang Zehui Technology Co., LTD. He received his
Bachelor of Engineering Science in electronic information engineering form
Nanyang Institute of Technology, Henan, China, in 2015.

References

Abdulhameed Adamu, Mohammed Abdullahia, Sahalu Balarabe

Junaidua, Ibrahim Hayatu Hassana, An hybrid particle swarm optimiza-

tion with crow search algorithm for feature selection, Machine Learning

with Applications, 2021, 6(12):100108.

Alba Muñoz, Fernando Rubio, Evaluating genetic algorithms through

the approximability hierarchy, Journal of Computational Science, 2021,

(7):101388.

Kaipu Wang, Xinyu Li, Liang Gao, Peigen Li, Surendra M. Gupta, A

genetic simulated annealing algorithm for parallel partial disassembly

line balancing problem, Applied Soft Computing, 2021, 107(8):107404.

Hao Zhang, Yuxin Shi, Xueran Yang, Ruiling Zhou, A firefly algorithm

modified support vector machine for the credit risk assessment of supply

chain finance, Research in International Business and Finance, 2021,

(12):101482.

Janmenjoy Nayak, Bighnaraj Naik, Pandit Byomakesha Dash, Alireza

Souri, Vimal Shanmuganathan, Hyper-parameter tuned light gradient

boosting machine using memetic firefly algorithm for hand gesture

recognition, Applied Soft Computing, 2021, 107(8):107478.

Jie Shan, Jeng-Shyang Pan, Cheng-Kuo Chang, Shu-Chuan Chu, Shi-

Guang Zheng, A distributed parallel firefly algorithm with communica-

tion strategies and its application for the control of variable pitch wind

turbine, ISA Transactions, 2021, 115(9):79–94.

Power Command Optimal Allocation Model of Distributed Energy System 861

Manousos Rigakis, Dimitra Trachanatzi, Magdalene Marinaki, Yannis

Marinakis, Tourist group itinerary design: When the firefly algorithm

meets the n-person Battle of Sexes, Knowledge-Based Systems, 2021,

(9):107257.

Hussam S. Alhadawi, Dragan Lambi ́c, Mohamad Fadli Zolkipli,

Musheer Ahmad, Globalized firefly algorithm and chaos for designing

substitution box, Journal of Information Security and Applications,

, 55(12):102671.

Hana Gharrad, Nafaa Jabeur, Ansar Ul-Haque Yasar, Stephane Galland,

Mohammed Mbarki, A five-step drone collaborative planning approach

for the management of distributed spatial events and vehicle notification

using multi-agent systems and firefly algorithms, Computer Networks,

, 198(10):108282.

Junfei Zhang, Yimiao Huang, Guowei Ma, Yanmei Yuan, Brett Nener,

Automating the mixture design of lightweight foamed concrete using

multi-objective firefly algorithm and support vector regression, Cement

and Concrete Composites, 2021, 121(8):104103.

Shanze Huang, Jin He, Shuo Li, Zhiyuan Cao, Jiankang Li, A 20-Gb/s

wideband automatic generation control amplifier with 26-dB dynamic

range in 0.18-μm SiGe BiCMOS, Integration, 2021, 81(11):160–166.

Matouš Glanc, Kasper Van Gelderen, Lukas Hoermayer, Shutang Tan,

Satoshi Naramoto, Xixi Zhang, David Domjan, automatic genera-

tion control kinases and MAB4/MEL proteins maintain PIN polarity

by limiting lateral diffusion in plant cells, Current Biology, 2021,

(9):1918–1930.

Jiawen Li, Tao Yu, Xiaoshun Zhang, Fusheng Li, Dan Lin, Hanxin Zhu,

Efficient experience replay based deep deterministic policy gradient

for automatic generation control dispatch in integrated energy system,

Applied Energy, 2021, 285(3):116386.

Nizamuddin Hakimuddin, Anita Khosla, Jitendra Kumar Garg, Central-

ized and decentralized automatic generation control schemes in 2-area

interconnected power system considering multi source power plants in

each area, Journal of King Saud University - Engineering Sciences,

, 32(2):123–132.

I. Saboya, I. Egido, E. Lobato, L. Sigrist, MOPSO-tuning of a threshold-

based algorithm to start up and shut-down rapid-start units in automatic

generation control, International Journal of Electrical Power & Energy

Systems, 2019, 108(6):153–161.

X. Xue et al.

Mita Cokic, Ivan Seskar, FSoftware defined network management for

dynamic smart GRID traffic, Future Generation Computer Systems,

, 96(7):270–282.

A. Arsenov, G.M. Dimirovski, B. Percinkova, Fast Method for

Constrained Load-allocation Strategy in Hydro-thermo-pump Electric

Energy Systems, IFAC Proceedings Volumes, 1989, 22(10):409–413.

Feng Zhang, Aihui Fu, Lei Ding, Qiuwei Wu, Bing Zhao, Peng Zi, Opti-

mal sizing of ESS for reducing automatic generation control payment

in a power system with high PV penetration, International Journal of

Electrical Power & Energy Systems, 2019, 110(9):809–818.

Yi Dong, Zhen Dong, Tianqiao Zhao, Zhengtao Ding, A Strategic Day-

ahead bidding strategy and operation for battery energy storage system

by reinforcement learning, Electric Power Systems Research, 2021,

(7):107229.

Anuj Banshwar, Naveen Kumar Sharma, Yog Raj Sood, Rajnish Shrivas-

tava, An international experience of technical and economic aspects of

ancillary services in deregulated power industry: Lessons for emerging

BRIC electricity markets, Renewable and Sustainable Energy Reviews,

, 90(7):774–801.

Jinran Wu, You-Gan Wang, Kevin Burrage, Yu-Chu Tian, Brodie

Lawson, Zhe Ding, An improved firefly algorithm for global contin-

uous optimization problems, Expert Systems with Applications, 2020,

(7):113340.

Tian Mengchu, Bo Yuming, Chen Zhimin, Wu Panlong, Yue Cong,

Multi-target tracking method based on improved firefly algorithm opti-

mized particle filter, Neurocomputing, 2019, 359(9):438–448.

Krishna Gopal Dhal, Arunita Das, Swarnajit Ray, Jorge Gálvez, Ran-

domly Attracted Rough Firefly Algorithm for histogram based fuzzy

image clustering, Knowledge-Based Systems, 2021, 216(3):106814.

Mahya Mohammadi Golchi, Shideh Saraeian, Mehrnoosh Heydari, A

hybrid of firefly and improved particle swarm optimization algorithms

for load balancing in cloud environments: Performance evaluation,

Computer Networks, 2019, 162(10):106860.

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Published

2022-02-19

How to Cite

Xue, X. ., Zheng, Y. ., & Lu, C. . (2022). Power Command Optimal Allocation Model of Distributed Energy System Based on Improved Firefly Algorithm. Distributed Generation &Amp; Alternative Energy Journal, 37(3), 845–864. https://doi.org/10.13052/dgaej2156-3306.37321

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