IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v101y2016icp506-518.html
   My bibliography  Save this article

Implementation of flower pollination algorithm for solving economic load dispatch and combined economic emission dispatch problems in power systems

Author

Listed:
  • Abdelaziz, A.Y.
  • Ali, E.S.
  • Abd Elazim, S.M.

Abstract

ELD (Economic Load Dispatch ) is the process of allocating the required load between the available generation units such that the cost of operation is minimized. The ELD problem is formulated as a nonlinear constrained optimization problem with both equality and inequality constraints. The dual-objective CEED (Combined Economic Emission Dispatch ) problem is considering the environmental impacts that accumulated from emission of gaseous pollutants of fossil-fueled power plants. In this paper, an implementation of FPA (Flower Pollination Algorithm ) to solve ELD and CEED problems in power systems is discussed. Results obtained by the proposed FPA are compared with other optimization algorithms for various power systems. The results introduced in this paper show that the proposed FPA outlasts other techniques even for large scale power system considering valve point effect in terms of total cost and computational time.

Suggested Citation

  • Abdelaziz, A.Y. & Ali, E.S. & Abd Elazim, S.M., 2016. "Implementation of flower pollination algorithm for solving economic load dispatch and combined economic emission dispatch problems in power systems," Energy, Elsevier, vol. 101(C), pages 506-518.
  • Handle: RePEc:eee:energy:v:101:y:2016:i:c:p:506-518
    DOI: 10.1016/j.energy.2016.02.041
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544216300846
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.energy.2016.02.041?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. Say, Nuriye Peker & Yucel, Muzaffer, 2006. "Energy consumption and CO2 emissions in Turkey: Empirical analysis and future projection based on an economic growth," Energy Policy, Elsevier, vol. 34(18), pages 3870-3876, December.
    2. Coelho, Leandro dos Santos & Souza, Rodrigo Clemente Thom & Mariani, Viviana Cocco, 2009. "Improved differential evolution approach based on cultural algorithm and diversity measure applied to solve economic load dispatch problems," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(10), pages 3136-3147.
    3. Aydin, Gokhan, 2014. "Modeling of energy consumption based on economic and demographic factors: The case of Turkey with projections," Renewable and Sustainable Energy Reviews, Elsevier, vol. 35(C), pages 382-389.
    4. Niknam, Taher & Mojarrad, Hassan Doagou & Nayeripour, Majid, 2010. "A new fuzzy adaptive particle swarm optimization for non-smooth economic dispatch," Energy, Elsevier, vol. 35(4), pages 1764-1778.
    5. Niknam, Taher, 2010. "A new fuzzy adaptive hybrid particle swarm optimization algorithm for non-linear, non-smooth and non-convex economic dispatch problem," Applied Energy, Elsevier, vol. 87(1), pages 327-339, January.
    6. Alsumait, J.S. & Sykulski, J.K. & Al-Othman, A.K., 2010. "A hybrid GA-PS-SQP method to solve power system valve-point economic dispatch problems," Applied Energy, Elsevier, vol. 87(5), pages 1773-1781, May.
    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. Le Chi Kien & Thang Trung Nguyen & Chiem Trong Hien & Minh Quan Duong, 2019. "A Novel Social Spider Optimization Algorithm for Large-Scale Economic Load Dispatch Problem," Energies, MDPI, vol. 12(6), pages 1-26, March.
    2. Li, Zheng & Zhou, Bo & Hensher, David A., 2022. "Forecasting automobile gasoline demand in Australia using machine learning-based regression," Energy, Elsevier, vol. 239(PD).
    3. Mahdi, Fahad Parvez & Vasant, Pandian & Kallimani, Vish & Watada, Junzo & Fai, Patrick Yeoh Siew & Abdullah-Al-Wadud, M., 2018. "A holistic review on optimization strategies for combined economic emission dispatch problem," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P2), pages 3006-3020.
    4. Tawhid, M.A. & Ibrahim, A.M., 2021. "Solving nonlinear systems and unconstrained optimization problems by hybridizing whale optimization algorithm and flower pollination algorithm," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 190(C), pages 1342-1369.
    5. Adewuyi, Adeolu O. & Awodumi, Olabanji B., 2017. "Biomass energy consumption, economic growth and carbon emissions: Fresh evidence from West Africa using a simultaneous equation model," Energy, Elsevier, vol. 119(C), pages 453-471.
    6. Ahmed I. Omar & Ziad M. Ali & Mostafa Al-Gabalawy & Shady H. E. Abdel Aleem & Mujahed Al-Dhaifallah, 2020. "Multi-Objective Environmental Economic Dispatch of an Electricity System Considering Integrated Natural Gas Units and Variable Renewable Energy Sources," Mathematics, MDPI, vol. 8(7), pages 1-37, July.
    7. Elattar, Ehab E., 2019. "Environmental economic dispatch with heat optimization in the presence of renewable energy based on modified shuffle frog leaping algorithm," Energy, Elsevier, vol. 171(C), pages 256-269.
    8. Yang, Wenqiang & Zhu, Xinxin & Xiao, Qinge & Yang, Zhile, 2023. "Enhanced multi-objective marine predator algorithm for dynamic economic-grid fluctuation dispatch with plug-in electric vehicles," Energy, Elsevier, vol. 282(C).
    9. Al-Bahrani, Loau Tawfak & Horan, Ben & Seyedmahmoudian, Mehdi & Stojcevski, Alex, 2020. "Dynamic economic emission dispatch with load dema nd management for the load demand of electric vehicles during crest shaving and valley filling in smart cities environment," Energy, Elsevier, vol. 195(C).
    10. Elsakaan, Asmaa A. & El-Sehiemy, Ragab A. & Kaddah, Sahar S. & Elsaid, Mohammed I., 2018. "An enhanced moth-flame optimizer for solving non-smooth economic dispatch problems with emissions," Energy, Elsevier, vol. 157(C), pages 1063-1078.
    11. Ismail Marouani & Tawfik Guesmi & Hsan Hadj Abdallah & Badr M. Alshammari & Khalid Alqunun & Ahmed S. Alshammari & Salem Rahmani, 2022. "Combined Economic Emission Dispatch with and without Consideration of PV and Wind Energy by Using Various Optimization Techniques: A Review," Energies, MDPI, vol. 15(12), pages 1-35, June.
    12. Elattar, Ehab E., 2018. "Modified harmony search algorithm for combined economic emission dispatch of microgrid incorporating renewable sources," Energy, Elsevier, vol. 159(C), pages 496-507.
    13. Shin, Hansol & Kim, Tae Hyun & Kim, Hyoungtae & Lee, Sungwoo & Kim, Wook, 2019. "Environmental shutdown of coal-fired generators for greenhouse gas reduction: A case study of South Korea," Applied Energy, Elsevier, vol. 252(C), pages 1-1.
    14. Zhang, Xian & Wang, Huaizhi & Peng, Jian-chun & Liu, Yitao & Wang, Guibin & Jiang, Hui, 2018. "GPNBI inspired MOSDE for electric power dispatch considering wind energy penetration," Energy, Elsevier, vol. 144(C), pages 404-419.
    15. Ali, E.S. & Elazim, S.M. Abd & Balobaid, A.S., 2023. "Implementation of coyote optimization algorithm for solving unit commitment problem in power systems," Energy, Elsevier, vol. 263(PA).
    16. Jaspar Hasudungan & Jangkung Raharjo, 2022. "Determination of Emission Reduction Costs Through Optimization of Generator Scheduling in Indonesia," International Journal of Energy Economics and Policy, Econjournals, vol. 12(3), pages 395-400, May.
    17. Uyikumhe Damisa & Peter Olabisi Oluseyi & Nnamdi Ikechi Nwulu, 2022. "Blockchain-Based Gas Auctioning Coupled with a Novel Economic Dispatch Formulation for Gas-Deficient Thermal Plants," Energies, MDPI, vol. 15(14), pages 1-13, July.
    18. 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.
    19. Ahmed M. Nassef & Mohammad Ali Abdelkareem & Hussein M. Maghrabie & Ahmad Baroutaji, 2023. "Review of Metaheuristic Optimization Algorithms for Power Systems Problems," Sustainability, MDPI, vol. 15(12), pages 1-27, June.
    20. Qi Liu & Jie Zhao & Youguo Shao & Libin Wen & Jianxu Wu & Dichen Liu & Yuhui Ma, 2019. "Multi-Power Joint Peak-Shaving Optimization for Power System Considering Coordinated Dispatching of Nuclear Power and Wind Power," Sustainability, MDPI, vol. 11(17), pages 1-23, September.
    21. Raheela Jamal & Baohui Men & Noor Habib Khan & Muhammad Asif Zahoor Raja, 2019. "Hybrid Bio-Inspired Computational Heuristic Paradigm for Integrated Load Dispatch Problems Involving Stochastic Wind," Energies, MDPI, vol. 12(13), pages 1-23, July.

    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. Glotić, Arnel & Zamuda, Aleš, 2015. "Short-term combined economic and emission hydrothermal optimization by surrogate differential evolution," Applied Energy, Elsevier, vol. 141(C), pages 42-56.
    2. Vo, Dieu Ngoc & Ongsakul, Weerakorn, 2012. "Economic dispatch with multiple fuel types by enhanced augmented Lagrange Hopfield network," Applied Energy, Elsevier, vol. 91(1), pages 281-289.
    3. Alsumait, J.S. & Sykulski, J.K. & Al-Othman, A.K., 2010. "A hybrid GA-PS-SQP method to solve power system valve-point economic dispatch problems," Applied Energy, Elsevier, vol. 87(5), pages 1773-1781, May.
    4. Zou, Dexuan & Li, Steven & Wang, Gai-Ge & Li, Zongyan & Ouyang, Haibin, 2016. "An improved differential evolution algorithm for the economic load dispatch problems with or without valve-point effects," Applied Energy, Elsevier, vol. 181(C), pages 375-390.
    5. Yaşar, Celal & Özyön, Serdar, 2011. "A new hybrid approach for nonconvex economic dispatch problem with valve-point effect," Energy, Elsevier, vol. 36(10), pages 5838-5845.
    6. 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.
    7. Guojiang Xiong & Jing Zhang & Xufeng Yuan & Dongyuan Shi & Yu He & Yao Yao & Gonggui Chen, 2018. "A Novel Method for Economic Dispatch with Across Neighborhood Search: A Case Study in a Provincial Power Grid, China," Complexity, Hindawi, vol. 2018, pages 1-18, November.
    8. Cai, Jiejin & Li, Qiong & Li, Lixiang & Peng, Haipeng & Yang, Yixian, 2012. "A hybrid FCASO-SQP method for solving the economic dispatch problems with valve-point effects," Energy, Elsevier, vol. 38(1), pages 346-353.
    9. Jiangtao Yu & Chang-Hwan Kim & Abdul Wadood & Tahir Khurshiad & Sang-Bong Rhee, 2018. "A Novel Multi-Population Based Chaotic JAYA Algorithm with Application in Solving Economic Load Dispatch Problems," Energies, MDPI, vol. 11(8), pages 1-25, July.
    10. Xiong, Guojiang & Shi, Dongyuan & Duan, Xianzhong, 2013. "Multi-strategy ensemble biogeography-based optimization for economic dispatch problems," Applied Energy, Elsevier, vol. 111(C), pages 801-811.
    11. Ara, A. Lashkar & Kazemi, A. & Niaki, S.A. Nabavi, 2011. "Optimal location of Hybrid Flow Controller considering modified steady-state model," Applied Energy, Elsevier, vol. 88(5), pages 1578-1585, May.
    12. Roche, Robin & Idoumghar, Lhassane & Suryanarayanan, Siddharth & Daggag, Mounir & Solacolu, Christian-Anghel & Miraoui, Abdellatif, 2013. "A flexible and efficient multi-agent gas turbine power plant energy management system with economic and environmental constraints," Applied Energy, Elsevier, vol. 101(C), pages 644-654.
    13. Bhowmik, Chiranjib & Bhowmik, Sumit & Ray, Amitava & Pandey, Krishna Murari, 2017. "Optimal green energy planning for sustainable development: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 71(C), pages 796-813.
    14. Goudarzi, Arman & Swanson, Andrew G. & Van Coller, John & Siano, Pierluigi, 2017. "Smart real-time scheduling of generating units in an electricity market considering environmental aspects and physical constraints of generators," Applied Energy, Elsevier, vol. 189(C), pages 667-696.
    15. Golberg, Alexander, 2015. "Environmental exergonomics for sustainable design and analysis of energy systems," Energy, Elsevier, vol. 88(C), pages 314-321.
    16. 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.
    17. Ebrahim Farjah & Mosayeb Bornapour & Taher Niknam & Bahman Bahmanifirouzi, 2012. "Placement of Combined Heat, Power and Hydrogen Production Fuel Cell Power Plants in a Distribution Network," Energies, MDPI, vol. 5(3), pages 1-25, March.
    18. Dong, Lianxin & Fan, Shuai & Wang, Zhihua & Xiao, Jucheng & Zhou, Huan & Li, Zuyi & He, Guangyu, 2021. "An adaptive decentralized economic dispatch method for virtual power plant," Applied Energy, Elsevier, vol. 300(C).
    19. Erickson Diogo Pereira Puchta & Priscilla Bassetto & Lucas Henrique Biuk & Marco Antônio Itaborahy Filho & Attilio Converti & Mauricio dos Santos Kaster & Hugo Valadares Siqueira, 2021. "Swarm-Inspired Algorithms to Optimize a Nonlinear Gaussian Adaptive PID Controller," Energies, MDPI, vol. 14(12), pages 1-20, June.
    20. Rafiee, A. & Dias, E. & Koomen, E., 2019. "Analysing the impact of spatial context on the heat consumption of individual households," Renewable and Sustainable Energy Reviews, Elsevier, vol. 112(C), pages 461-470.

    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:101:y:2016:i:c:p:506-518. 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.