IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i3p2407-d1050353.html
   My bibliography  Save this article

Achieving Sustainability and Cost-Effectiveness in Power Generation: Multi-Objective Dispatch of Solar, Wind, and Hydro Units

Author

Listed:
  • Mohammad Lotfi Akbarabadi

    (Department of Electrical and Electronic Engineering, Eastern Mediterranean University, Gazimagusa 99628, Turkey)

  • Reza Sirjani

    (Department of Engineering and Physics, Karlstad University, 65188 Karlstad, Sweden)

Abstract

In the power system, economic power dispatch is a popular and fundamental optimization problem. In its classical form, this problem only considers thermal generators and does not take into account network security constraints. However, other forms of the problem, such as economic emission dispatch (EED), are becoming increasingly important due to the emphasis on minimizing emissions for environmental purposes. The integration of renewable sources, such as solar, wind, and hydro units, is an important aspect of EED, but it can be challenging due to the stochastic nature of these sources. In this study, a multi-objective algorithm is developed to address the problem of economic emission power dispatch with the inclusion of these renewable sources. To account for the intermittent behavior of solar, wind, and hydro power, the algorithm uses Lognormal, Weibull, and Gumbel distributions, respectively. The algorithm also considers voltage limitations, transmission line capacities, prohibited areas of operation for thermal generator plants, and system restrictions. The multi-objective real coded non-dominated sorting genetic algorithm II (R-NSGA-II) is applied to the problem and includes a procedure for handling system restrictions to meet system limitations. Results are extracted using fuzzy decision-making and are analyzed and discussed. The proposed method is compared to other newer techniques from another study to demonstrate its robustness. The results show that the proposed method despite being older is cost-significant while maintaining the same or lower emissions. These results were observed consistently and did not happen by chance, detailed explanation of why and how is discussed.

Suggested Citation

  • Mohammad Lotfi Akbarabadi & Reza Sirjani, 2023. "Achieving Sustainability and Cost-Effectiveness in Power Generation: Multi-Objective Dispatch of Solar, Wind, and Hydro Units," Sustainability, MDPI, vol. 15(3), pages 1-33, January.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:3:p:2407-:d:1050353
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/3/2407/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/15/3/2407/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Meng, Anbo & Li, Jinbei & Yin, Hao, 2016. "An efficient crisscross optimization solution to large-scale non-convex economic load dispatch with multiple fuel types and valve-point effects," Energy, Elsevier, vol. 113(C), pages 1147-1161.
    2. Di Somma, M. & Graditi, G. & Heydarian-Forushani, E. & Shafie-khah, M. & Siano, P., 2018. "Stochastic optimal scheduling of distributed energy resources with renewables considering economic and environmental aspects," Renewable Energy, Elsevier, vol. 116(PA), pages 272-287.
    3. Reddy, S. Surender, 2017. "Optimal scheduling of thermal-wind-solar power system with storage," Renewable Energy, Elsevier, vol. 101(C), pages 1357-1368.
    4. 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.
    5. Cabus, Pieter, 2008. "River flow prediction through rainfall-runoff modelling with a probability-distributed model (PDM) in Flanders, Belgium," Agricultural Water Management, Elsevier, vol. 95(7), pages 859-868, July.
    6. Kheshti, Mostafa & Kang, Xiaoning & Bie, Zhaohong & Jiao, Zaibin & Wang, Xiuli, 2017. "An effective Lightning Flash Algorithm solution to large scale non-convex economic dispatch with valve-point and multiple fuel options on generation units," Energy, Elsevier, vol. 129(C), pages 1-15.
    7. Biswas, Partha P. & Suganthan, P.N. & Qu, B.Y. & Amaratunga, Gehan A.J., 2018. "Multiobjective economic-environmental power dispatch with stochastic wind-solar-small hydro power," Energy, Elsevier, vol. 150(C), pages 1039-1057.
    8. Jayabarathi, T. & Raghunathan, T. & Adarsh, B.R. & Suganthan, Ponnuthurai Nagaratnam, 2016. "Economic dispatch using hybrid grey wolf optimizer," Energy, Elsevier, vol. 111(C), pages 630-641.
    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. Olukorede Tijani Adenuga & Senthil Krishnamurthy, 2023. "Economic Power Dispatch of a Grid-Tied Photovoltaic-Based Energy Management System: Co-Optimization Approach," Mathematics, MDPI, vol. 11(15), pages 1-22, 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. Biswas, Partha P. & Suganthan, P.N. & Qu, B.Y. & Amaratunga, Gehan A.J., 2018. "Multiobjective economic-environmental power dispatch with stochastic wind-solar-small hydro power," Energy, Elsevier, vol. 150(C), pages 1039-1057.
    2. Xu, Shengping & Xiong, Guojiang & Mohamed, Ali Wagdy & Bouchekara, Houssem R.E.H., 2022. "Forgetting velocity based improved comprehensive learning particle swarm optimization for non-convex economic dispatch problems with valve-point effects and multi-fuel options," Energy, Elsevier, vol. 256(C).
    3. 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.
    4. Kheshti, Mostafa & Kang, Xiaoning & Bie, Zhaohong & Jiao, Zaibin & Wang, Xiuli, 2017. "An effective Lightning Flash Algorithm solution to large scale non-convex economic dispatch with valve-point and multiple fuel options on generation units," Energy, Elsevier, vol. 129(C), pages 1-15.
    5. 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.
    6. 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.
    7. 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.
    8. Naila & Shaikh Saaqib Haroon & Shahzad Hassan & Salman Amin & Intisar Ali Sajjad & Asad Waqar & Muhammad Aamir & Muneeb Yaqoob & Imtiaz Alam, 2018. "Multiple Fuel Machines Power Economic Dispatch Using Stud Differential Evolution," Energies, MDPI, vol. 11(6), pages 1-20, May.
    9. Kheshti, Mostafa & Ding, Lei & Ma, Shicong & Zhao, Bing, 2018. "Double weighted particle swarm optimization to non-convex wind penetrated emission/economic dispatch and multiple fuel option systems," Renewable Energy, Elsevier, vol. 125(C), pages 1021-1037.
    10. 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.
    11. Yuan, Wenlin & Wang, Xinqi & Su, Chengguo & Cheng, Chuntian & Liu, Zhe & Wu, Zening, 2021. "Stochastic optimization model for the short-term joint operation of photovoltaic power and hydropower plants based on chance-constrained programming," Energy, Elsevier, vol. 222(C).
    12. 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.
    13. Wang, Guibin & Zha, Yongxing & Wu, Ting & Qiu, Jing & Peng, Jian-chun & Xu, Gang, 2020. "Cross entropy optimization based on decomposition for multi-objective economic emission dispatch considering renewable energy generation uncertainties," Energy, Elsevier, vol. 193(C).
    14. Meng, Anbo & Xu, Xuancong & Zhang, Zhan & Zeng, Cong & Liang, Ruduo & Zhang, Zheng & Wang, Xiaolin & Yan, Baiping & Yin, Hao & Luo, Jianqiang, 2022. "Solving high-dimensional multi-area economic dispatch problem by decoupled distributed crisscross optimization algorithm with population cross generation strategy," Energy, Elsevier, vol. 258(C).
    15. 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).
    16. Rajakumar Ramalingam & Dinesh Karunanidy & Sultan S. Alshamrani & Mamoon Rashid & Swamidoss Mathumohan & Ankur Dumka, 2022. "Oppositional Pigeon-Inspired Optimizer for Solving the Non-Convex Economic Load Dispatch Problem in Power Systems," Mathematics, MDPI, vol. 10(18), pages 1-24, September.
    17. Ali S. Alghamdi, 2022. "Greedy Sine-Cosine Non-Hierarchical Grey Wolf Optimizer for Solving Non-Convex Economic Load Dispatch Problems," Energies, MDPI, vol. 15(11), pages 1-19, May.
    18. El-Sayed, Wael T. & El-Saadany, Ehab F. & Zeineldin, Hatem H. & Al-Sumaiti, Ameena S., 2020. "Fast initialization methods for the nonconvex economic dispatch problem," Energy, Elsevier, vol. 201(C).
    19. Meng, Anbo & Li, Jinbei & Yin, Hao, 2016. "An efficient crisscross optimization solution to large-scale non-convex economic load dispatch with multiple fuel types and valve-point effects," Energy, Elsevier, vol. 113(C), pages 1147-1161.
    20. Chen, Xu, 2020. "Novel dual-population adaptive differential evolution algorithm for large-scale multi-fuel economic dispatch with valve-point effects," Energy, Elsevier, vol. 203(C).

    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:gam:jsusta:v:15:y:2023:i:3:p:2407-:d:1050353. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.