IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v138y2017icp1112-1123.html
   My bibliography  Save this article

Surrogate worth trade-off method for multi-objective thermal power load dispatch

Author

Listed:
  • Singh, Nirbhow Jap
  • Dhillon, J.S.
  • Kothari, D.P.

Abstract

The multi-objective thermal power dispatch (MTPLD) problem allocates power demand among the committed generating units while minimizing the operating cost and pollutant's emission objectives simultaneously, subject to physical and technological constraints. The success to find MTPLD solution relies on the decision-maker's ability to select compromised solution under uncertain/diverse conditions and the search algorithm's potential to generate non-dominated solutions. Owing to ambiguous choice of objectives, this paper presents a fuzzy surrogate worth trade-off approach to decide the preferred solution among the non-dominated solution set. The uniformity of non-dominated solution set is maintained exploiting a quality measure approach. This paper presents a novel foraging activity paradigm to generate non-dominated solutions. The presented approach comprises of fly and walk behavior of preys. The direction of turn heuristic of prey handles system's equality constraint. The search algorithm balances exploration and exploitation and handles system constraints autonomously. The performance of proposed algorithm is investigated using generalized benchmark functions and multi-fuel, medium and large power system MTPLD problems. The experimental results shows that the proposed approach is robust, depends on least parameters and retains Pareto quality in independent trials while generating non-dominated solutions in a trial run.

Suggested Citation

  • Singh, Nirbhow Jap & Dhillon, J.S. & Kothari, D.P., 2017. "Surrogate worth trade-off method for multi-objective thermal power load dispatch," Energy, Elsevier, vol. 138(C), pages 1112-1123.
  • Handle: RePEc:eee:energy:v:138:y:2017:i:c:p:1112-1123
    DOI: 10.1016/j.energy.2017.07.063
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544217312392
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.energy.2017.07.063?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Arul, R. & Velusami, S. & Ravi, G., 2015. "A new algorithm for combined dynamic economic emission dispatch with security constraints," Energy, Elsevier, vol. 79(C), pages 496-511.
    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. Basu, M., 2014. "Fuel constrained economic emission dispatch using nondominated sorting genetic algorithm-II," Energy, Elsevier, vol. 78(C), pages 649-664.
    4. Secui, Dinu Calin, 2015. "The chaotic global best artificial bee colony algorithm for the multi-area economic/emission dispatch," Energy, Elsevier, vol. 93(P2), pages 2518-2545.
    5. Niu, Qun & Zhang, Hongyun & Li, Kang & Irwin, George W., 2014. "An efficient harmony search with new pitch adjustment for dynamic economic dispatch," Energy, Elsevier, vol. 65(C), pages 25-43.
    6. Adarsh, B.R. & Raghunathan, T. & Jayabarathi, T. & Yang, Xin-She, 2016. "Economic dispatch using chaotic bat algorithm," Energy, Elsevier, vol. 96(C), pages 666-675.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Patwal, Rituraj Singh & Narang, Nitin, 2020. "Multi-objective generation scheduling of integrated energy system using fuzzy based surrogate worth trade-off approach," Renewable Energy, Elsevier, vol. 156(C), pages 864-882.

    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. Zaman, Forhad & Elsayed, Saber M. & Ray, Tapabrata & Sarker, Ruhul A., 2016. "Evolutionary algorithms for power generation planning with uncertain renewable energy," Energy, Elsevier, vol. 112(C), pages 408-419.
    2. Nwulu, Nnamdi I. & Xia, Xiaohua, 2015. "Implementing a model predictive control strategy on the dynamic economic emission dispatch problem with game theory based demand response programs," Energy, Elsevier, vol. 91(C), pages 404-419.
    3. Secui, Dinu Calin, 2016. "A modified Symbiotic Organisms Search algorithm for large scale economic dispatch problem with valve-point effects," Energy, Elsevier, vol. 113(C), pages 366-384.
    4. Al-Bahrani, Loau Tawfak & Chandra Patra, Jagdish, 2018. "Multi-gradient PSO algorithm for optimization of multimodal, discontinuous and non-convex fuel cost function of thermal generating units under various power constraints in smart power grid," Energy, Elsevier, vol. 147(C), pages 1070-1091.
    5. Panpan Mei & Lianghong Wu & Hongqiang Zhang & Zhenzu Liu, 2019. "A Hybrid Multi-Objective Crisscross Optimization for Dynamic Economic/Emission Dispatch Considering Plug-In Electric Vehicles Penetration," Energies, MDPI, vol. 12(20), pages 1-21, October.
    6. Jin, Jingliang & Zhou, Peng & Li, Chenyu & Bai, Yang & Wen, Qinglan, 2020. "Optimization of power dispatching strategies integrating management attitudes with low carbon factors," Renewable Energy, Elsevier, vol. 155(C), pages 555-568.
    7. Secui, Dinu Calin, 2015. "The chaotic global best artificial bee colony algorithm for the multi-area economic/emission dispatch," Energy, Elsevier, vol. 93(P2), pages 2518-2545.
    8. Ma, Haiping & Yang, Zhile & You, Pengcheng & Fei, Minrui, 2017. "Multi-objective biogeography-based optimization for dynamic economic emission load dispatch considering plug-in electric vehicles charging," Energy, Elsevier, vol. 135(C), pages 101-111.
    9. Chen, Min-Rong & Zeng, Guo-Qiang & Lu, Kang-Di, 2019. "Constrained multi-objective population extremal optimization based economic-emission dispatch incorporating renewable energy resources," Renewable Energy, Elsevier, vol. 143(C), pages 277-294.
    10. Wei Sun & Junjian Zhang, 2020. "Carbon Price Prediction Based on Ensemble Empirical Mode Decomposition and Extreme Learning Machine Optimized by Improved Bat Algorithm Considering Energy Price Factors," Energies, MDPI, vol. 13(13), pages 1-22, July.
    11. 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.
    12. Dehnavi, Ehsan & Abdi, Hamdi, 2016. "Optimal pricing in time of use demand response by integrating with dynamic economic dispatch problem," Energy, Elsevier, vol. 109(C), pages 1086-1094.
    13. Mario Šipoš & Zvonimir Klaić & Emmanuel Karlo Nyarko & Krešimir Fekete, 2021. "Determining the Optimal Location and Number of Voltage Dip Monitoring Devices Using the Binary Bat Algorithm," Energies, MDPI, vol. 14(1), pages 1-13, January.
    14. Jianzhong Xu & Fu Yan & Kumchol Yun & Lifei Su & Fengshu Li & Jun Guan, 2019. "Noninferior Solution Grey Wolf Optimizer with an Independent Local Search Mechanism for Solving Economic Load Dispatch Problems," Energies, MDPI, vol. 12(12), pages 1-26, June.
    15. 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.
    16. 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.
    17. Fitiwi, Desta Z. & Olmos, L. & Rivier, M. & de Cuadra, F. & Pérez-Arriaga, I.J., 2016. "Finding a representative network losses model for large-scale transmission expansion planning with renewable energy sources," Energy, Elsevier, vol. 101(C), pages 343-358.
    18. 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.
    19. Modiri-Delshad, Mostafa & Aghay Kaboli, S. Hr. & Taslimi-Renani, Ehsan & Rahim, Nasrudin Abd, 2016. "Backtracking search algorithm for solving economic dispatch problems with valve-point effects and multiple fuel options," Energy, Elsevier, vol. 116(P1), pages 637-649.
    20. Ghasemi, Mojtaba & Ghavidel, Sahand & Ghanbarian, Mohammad Mehdi & Gharibzadeh, Masihallah & Azizi Vahed, Ali, 2014. "Multi-objective optimal power flow considering the cost, emission, voltage deviation and power losses using multi-objective modified imperialist competitive algorithm," Energy, Elsevier, vol. 78(C), pages 276-289.

    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:eee:energy:v:138:y:2017:i:c:p:1112-1123. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    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.