IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0189282.html
   My bibliography  Save this article

An enhanced artificial bee colony algorithm (EABC) for solving dispatching of hydro-thermal system (DHTS) problem

Author

Listed:
  • Yi Yu
  • Yonggang Wu
  • Binqi Hu
  • Xinglong Liu

Abstract

The dispatching of hydro-thermal system is a nonlinear programming problem with multiple constraints and high dimensions and the solution techniques of the model have been a hotspot in research. Based on the advantage of that the artificial bee colony algorithm (ABC) can efficiently solve the high-dimensional problem, an improved artificial bee colony algorithm has been proposed to solve DHTS problem in this paper. The improvements of the proposed algorithm include two aspects. On one hand, local search can be guided in efficiency by the information of the global optimal solution and its gradient in each generation. The global optimal solution improves the search efficiency of the algorithm but loses diversity, while the gradient can weaken the loss of diversity caused by the global optimal solution. On the other hand, inspired by genetic algorithm, the nectar resource which has not been updated in limit generation is transformed to a new one by using selection, crossover and mutation, which can ensure individual diversity and make full use of prior information for improving the global search ability of the algorithm. The two improvements of ABC algorithm are proved to be effective via a classical numeral example at last. Among which the genetic operator for the promotion of the ABC algorithm’s performance is significant. The results are also compared with those of other state-of-the-art algorithms, the enhanced ABC algorithm has general advantages in minimum cost, average cost and maximum cost which shows its usability and effectiveness. The achievements in this paper provide a new method for solving the DHTS problems, and also offer a novel reference for the improvement of mechanism and the application of algorithms.

Suggested Citation

  • Yi Yu & Yonggang Wu & Binqi Hu & Xinglong Liu, 2018. "An enhanced artificial bee colony algorithm (EABC) for solving dispatching of hydro-thermal system (DHTS) problem," PLOS ONE, Public Library of Science, vol. 13(1), pages 1-19, January.
    • Handle: RePEc:plo:pone00:0189282
    DOI: 10.1371/journal.pone.0189282
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0189282
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0189282&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0189282?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. de Queiroz, Anderson Rodrigo, 2016. "Stochastic hydro-thermal scheduling optimization: An overview," Renewable and Sustainable Energy Reviews, Elsevier, vol. 62(C), pages 382-395.
    2. Narang, Nitin & Dhillon, J.S. & Kothari, D.P., 2012. "Multiobjective fixed head hydrothermal scheduling using integrated predator-prey optimization and Powell search method," Energy, Elsevier, vol. 47(1), pages 237-252.
    3. Chen, Fang & Zhou, Jianzhong & Wang, Chao & Li, Chunlong & Lu, Peng, 2017. "A modified gravitational search algorithm based on a non-dominated sorting genetic approach for hydro-thermal-wind economic emission dispatching," Energy, Elsevier, vol. 121(C), pages 276-291.
    4. Xin-She Yang, 2014. "Diversity and Mechanisms in Swarm Intelligence," International Journal of Swarm Intelligence Research (IJSIR), IGI Global, vol. 5(2), pages 1-12, April.
    5. Xiangxiang Zeng & Li Liu & Stephen Leung & Jiangze Du & Xun Wang & Tao Li, 2017. "A decision support model for investment on P2P lending platform," PLOS ONE, Public Library of Science, vol. 12(9), pages 1-18, September.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Feng, Zhong-kai & Niu, Wen-jing & Cheng, Chun-tian, 2017. "Multi-objective quantum-behaved particle swarm optimization for economic environmental hydrothermal energy system scheduling," Energy, Elsevier, vol. 131(C), pages 165-178.
    2. Nazari-Heris, M. & Mohammadi-Ivatloo, B. & B. Gharehpetian, G., 2017. "Short-term scheduling of hydro-based power plants considering application of heuristic algorithms: A comprehensive review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 74(C), pages 116-129.
    3. Fernández-Blanco, R. & Kavvadias, K. & Hidalgo González, I., 2017. "Quantifying the water-power linkage on hydrothermal power systems: A Greek case study," Applied Energy, Elsevier, vol. 203(C), pages 240-253.
    4. Wang, Lixiao & Jing, Z.X. & Zheng, J.H. & Wu, Q.H. & Wei, Feng, 2018. "Decentralized optimization of coordinated electrical and thermal generations in hierarchical integrated energy systems considering competitive individuals," Energy, Elsevier, vol. 158(C), pages 607-622.
    5. Rahmani, Shima & Amjady, Nima, 2017. "A new optimal power flow approach for wind energy integrated power systems," Energy, Elsevier, vol. 134(C), pages 349-359.
    6. Hafiz, Faeza & Rodrigo de Queiroz, Anderson & Fajri, Poria & Husain, Iqbal, 2019. "Energy management and optimal storage sizing for a shared community: A multi-stage stochastic programming approach," Applied Energy, Elsevier, vol. 236(C), pages 42-54.
    7. Ata Allah Taleizadeh & Aria Zaker Safaei & Arijit Bhattacharya & Alireza Amjadian, 2022. "Online peer-to-peer lending platform and supply chain finance decisions and strategies," Annals of Operations Research, Springer, vol. 315(1), pages 397-427, August.
    8. Santhosh, Apoorva & Farid, Amro M. & Youcef-Toumi, Kamal, 2014. "Real-time economic dispatch for the supply side of the energy-water nexus," Applied Energy, Elsevier, vol. 122(C), pages 42-52.
    9. Paulo Vitor Larroyd & Renata Pedrini & Felipe Beltrán & Gabriel Teixeira & Erlon Cristian Finardi & Lucas Borges Picarelli, 2022. "Dealing with Negative Inflows in the Long-Term Hydrothermal Scheduling Problem," Energies, MDPI, vol. 15(3), pages 1-19, February.
    10. Li, Chaoshun & Wang, Wenxiao & Chen, Deshu, 2019. "Multi-objective complementary scheduling of hydro-thermal-RE power system via a multi-objective hybrid grey wolf optimizer," Energy, Elsevier, vol. 171(C), pages 241-255.
    11. Glotić, Arnel & Glotić, Adnan & Kitak, Peter & Pihler, Jože & Tičar, Igor, 2014. "Optimization of hydro energy storage plants by using differential evolution algorithm," Energy, Elsevier, vol. 77(C), pages 97-107.
    12. McLarty, Dustin & Panossian, Nadia & Jabbari, Faryar & Traverso, Alberto, 2019. "Dynamic economic dispatch using complementary quadratic programming," Energy, Elsevier, vol. 166(C), pages 755-764.
    13. Santhosh, Apoorva & Farid, Amro M. & Youcef-Toumi, Kamal, 2014. "The impact of storage facility capacity and ramping capabilities on the supply side economic dispatch of the energy–water nexus," Energy, Elsevier, vol. 66(C), pages 363-377.
    14. Anderson Passos de Aragão & Patrícia Teixeira Leite Asano & Ricardo de Andrade Lira Rabêlo, 2020. "A Reservoir Operation Policy Using Inter-Basin Water Transfer for Maximizing Hydroelectric Benefits in Brazil," Energies, MDPI, vol. 13(10), pages 1-26, May.
    15. Tejada-Arango, Diego A. & Wogrin, Sonja & Siddiqui, Afzal S. & Centeno, Efraim, 2019. "Opportunity cost including short-term energy storage in hydrothermal dispatch models using a linked representative periods approach," Energy, Elsevier, vol. 188(C).
    16. Faria, Victor. A.D. & de Queiroz, Anderson Rodrigo & Lima, Luana M.M. & Lima, José W.M., 2018. "Cooperative game theory and last addition method in the allocation of firm energy rights," Applied Energy, Elsevier, vol. 226(C), pages 905-915.
    17. de Queiroz, A.R. & Mulcahy, D. & Sankarasubramanian, A. & Deane, J.P. & Mahinthakumar, G. & Lu, N. & DeCarolis, J.F., 2019. "Repurposing an energy system optimization model for seasonal power generation planning," Energy, Elsevier, vol. 181(C), pages 1321-1330.
    18. Zhou, Yanlai & Guo, Shenglian & Chang, Fi-John & Liu, Pan & Chen, Alexander B., 2018. "Methodology that improves water utilization and hydropower generation without increasing flood risk in mega cascade reservoirs," Energy, Elsevier, vol. 143(C), pages 785-796.
    19. Eshraghi, Hadi & Rodrigo de Queiroz, Anderson & Sankarasubramanian, A. & DeCarolis, Joseph F., 2021. "Quantification of climate-induced interannual variability in residential U.S. electricity demand," Energy, Elsevier, vol. 236(C).
    20. Saket Gupta & Narendra Kumar & Laxmi Srivastava & Hasmat Malik & Alberto Pliego Marugán & Fausto Pedro García Márquez, 2021. "A Hybrid Jaya–Powell’s Pattern Search Algorithm for Multi-Objective Optimal Power Flow Incorporating Distributed Generation," Energies, MDPI, vol. 14(10), pages 1-24, May.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pone00:0189282. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.