skip to main content
10.1145/3482632.3484058acmotherconferencesArticle/Chapter ViewAbstractPublication PagesiciscaeConference Proceedingsconference-collections
research-article

Research on Multi-Energy Complementary Linkage Technology and Economic Evaluation

Published: 22 November 2021 Publication History

Abstract

Because of the randomness, time-varying and intermittent characteristics of wind and solar power generation, the coordinated operation and control of the combined microgrid is very complex and rationally configuring the power supply can improve the reliability and economy of power supply. This paper studies the operation strategy of multi-energy complementary linkage in microgrid and proposes a set of multi-energy complementary economic evaluation methods based on nonlinear particle swarm optimization. The evaluation method takes economy and reliability as the objective functions, power balance and combination. The number of microgrids and battery capacity are constraints, and load, wind speed, light, and temperature are used as inputs. A complete economic cost calculation model is obtained. The optimal solution for economic evaluation is summarized through the optimization of nonlinear particle swarm optimization. Compared with the standard particle swarm optimization algorithm, the results show that the nonlinear particle swarm optimization algorithm has a strong optimization speed. The proposed multi-energy complementary economic evaluation method can realize the economic coordination and optimization of multi-source energy, and maximize the development and utilization of wind energy and solar energy at a more appropriate economic cost. The method can solve the problem of resource optimization of various types of power supply according to the environmental conditions, environmental type, investment cost, etc. of the construction site, and meet the requirements of diversity and reliability.

References

[1]
Wang C S,et al.Development and challenges of distributed generation, microgrid and intelligent distribution network[J].Automation of Electric Power Systems(in Chinese), 2010, 34(2):10-14.
[2]
Lasseter R, Akhil A, Marnay C, Integration of distributed energy resources. The CERTS Microgrid Concept[J]. 2002.
[3]
S. R. Wall, "Performance of inverter interfaced distributed generation," 2001 IEEE/PES Transmission and Distribution Conference and Exposition. Developing New Perspectives (Cat. No.01CH37294), Atlanta, GA, USA, 2001, pp. 945-950 vol.2.
[4]
Venkataramanan G, Marnay C. A larger role for microgrids[J]. IEEE Power & Energy Magazine, 2008, 6(3):78-82.
[5]
Zheng Z H, AI Q, Multi-objective optimal configuration of distributed generation considering environmental factors[J].Chinese Journal of Electrical Engineering (in Chinese),2009,29(13):23-28.
[6]
Ding M, Bao M. Unit Commitment of Distributed Energy Distributed Generation System[J]. Automation of Electric Power Systems (in Chinese), 2008(06):46-50.
[7]
Zhao G B, Liu T Q, Optimized configuration of distributed power generation as backup power[J].Automation of Electric Power Systems(in Chinese), 2009,33(01):85-89.
[8]
Soroudi A, Caire R, Hadjsaid N, Probabilistic dynamic multi-objective model for renewable and non-renewable distributed generation planning[J].IET Generation, Transmission & Distribution, 2011, 5(11):1.
[9]
Haghifam M R, Falaghi H, Malik O P. Risk-based distributed generation placement[J].IET Generation, Transmission & Distribution, 2008, 2(2):1.
[10]
Xiaojun, Liao.Liping He. A Review of Battery Management System[J]. Automotive Engineering, 2006, 28 (10): 961-964.
[11]
Jin L S. Research and Simulation of Wind Power Generation Simulation System[D]. 2017.
[12]
Liu H. Household solar photovoltaic power system[M]. Chemical Industry Press (in Chinese), 2007.
[13]
Huang H, Mao C, Lu J, Small-signal modelling and analysis of wind turbine with direct drive permanent magnet sy-nchronous generator connected to power grid[J]. Iet Renewable Power Generation, 2012, 6(1): 48-58.
[14]
H. Daneshi, A. L. Choobbari, M. Shahidehpour and Zuyi Li, "Mixed integer programming method to solve security constrained unit commitment with restricted operating zone limits," 2008 IEEE International Conference on Electro/Information Technology, Ames, IA, 2008, pp. 187-192.
[15]
G. W. Chang, Y. D. Tsai, C. Y. Lai and J. S. Chung, "A practical mixed integer linear programming based approach for unit commitment," IEEE Power Engineering Society General Meeting, 2004., Denver, CO, 2004, pp. 221-225.
[16]
Safari S, Ardehali M M, Sirizi M J. Particle swarm optimization based fuzzy logic controller for autonomous green power energy system with hydrogen storage [J]. Energy Conversion and Management, 2013, 65:41-49.
[17]
Yang Z P,Zhu L L, Research and Development of Particle Swarm Optimization Algorithm[J]. Computer Engineering and Science (in Chinese), 2007, 29(6).
[18]
Park J B, Lee K S, Shin J R, A particle swarm optimization for economic dispatch with nonsmooth cost functions [J]. IEEE Transactions on Power Systems, 2005, 20(1):34-42.

Recommendations

Comments

Information & Contributors

Information

Published In

cover image ACM Other conferences
ICISCAE 2021: 2021 4th International Conference on Information Systems and Computer Aided Education
September 2021
2972 pages
ISBN:9781450390255
DOI:10.1145/3482632
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 22 November 2021

Permissions

Request permissions for this article.

Check for updates

Qualifiers

  • Research-article
  • Research
  • Refereed limited

Conference

ICISCAE 2021

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • 0
    Total Citations
  • 24
    Total Downloads
  • Downloads (Last 12 months)7
  • Downloads (Last 6 weeks)1
Reflects downloads up to 17 Feb 2025

Other Metrics

Citations

View Options

Login options

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

HTML Format

View this article in HTML Format.

HTML Format

Figures

Tables

Media

Share

Share

Share this Publication link

Share on social media