IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v16y2024i4p1708-d1341712.html
   My bibliography  Save this article

Multi-Objective Profit-Based Unit Commitment with Renewable Energy and Energy Storage Units Using a Modified Optimization Method

Author

Listed:
  • Hossein Lotfi

    (Department of Electrical and Computer Engineering, Hakim Sabzevari University, Sabzevar 96131, Iran)

  • Mohammad Hasan Nikkhah

    (Department of Electrical and Computer Engineering, Hakim Sabzevari University, Sabzevar 96131, Iran)

Abstract

The unit commitment (UC) problem aims to reduce the power generation costs of power generation units in the traditional power system structure. However, under the current arrangement, the problem of cutting the cost of producing electricity has turned into an opportunity to boost power generation units’ profits. Emission concerns are now given considerable weight when talking about the performance planning of power generation units, in addition to economic objectives. Because emissions are viewed as a limitation rather than an objective function in the majority of recent research that has been published in the literature, this paper solves the multi-objective profit-based unit commitment (PBUC) problem while taking into account energy storage systems (ESSs) and renewable energy systems (RESs) in the presence of uncertainty sources, such as demand and energy prices, in order to minimize generated emissions and maximize profits by power generation units in the fiercely competitive energy market. Owing to the intricacy of the optimization problem, a novel mutation-based modified version of the shuffled frog leaping algorithm (SFLA) is suggested as a way to get around the PBUC problem’s difficulty. A 10-unit test system is used for the simulation, which is run for a whole day to demonstrate the effectiveness of the suggested approach. The proposed algorithm’s output is compared with the best-known approaches from various references. The simulated results generated by the suggested algorithms and the previously reported algorithms to solve the PBUC problem show that the proposed method is better than other evolutionary methods utilized in this study and prior investigations. For example, the overall profit from the suggested MSFLA is around 4% and 5.5% higher than that from other algorithms like the ICA and Muller methods in the presence and absence of reserve allocation, respectively. Furthermore, the MSFLA emissions value is approximately 2% and 8% lower than the optimum emissions values obtained using the PSO and ICA approaches, respectively.

Suggested Citation

  • Hossein Lotfi & Mohammad Hasan Nikkhah, 2024. "Multi-Objective Profit-Based Unit Commitment with Renewable Energy and Energy Storage Units Using a Modified Optimization Method," Sustainability, MDPI, vol. 16(4), pages 1-29, February.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:4:p:1708-:d:1341712
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/16/4/1708/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/16/4/1708/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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).
    2. Aneke, Mathew & Wang, Meihong, 2016. "Energy storage technologies and real life applications – A state of the art review," Applied Energy, Elsevier, vol. 179(C), pages 350-377.
    3. Anand, Himanshu & Narang, Nitin & Dhillon, J.S., 2018. "Profit based unit commitment using hybrid optimization technique," Energy, Elsevier, vol. 148(C), pages 701-715.
    4. Mostafa Nasouri Gilvaei & Mahmood Hosseini Imani & Mojtaba Jabbari Ghadi & Li Li & Anahita Golrang, 2021. "Profit-Based Unit Commitment for a GENCO Equipped with Compressed Air Energy Storage and Concentrating Solar Power Units," Energies, MDPI, vol. 14(3), pages 1-20, January.
    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. Lucas Santiago Nepomuceno & Layon Mescolin de Oliveira & Ivo Chaves da Silva Junior & Edimar José de Oliveira & Arthur Neves de Paula, 2023. "Modified Genetic Algorithm for the Profit-Based Unit Commitment Problem in Competitive Electricity Market," Energies, MDPI, vol. 16(23), pages 1-22, November.
    2. Miguel J. Prieto & Juan Á. Martínez & Rogelio Peón & Lourdes Á. Barcia & Fernando Nuño, 2017. "On the Convenience of Using Simulation Models to Optimize the Control Strategy of Molten-Salt Heat Storage Systems in Solar Thermal Power Plants," Energies, MDPI, vol. 10(7), pages 1-17, July.
    3. Guelpa, Elisa & Bischi, Aldo & Verda, Vittorio & Chertkov, Michael & Lund, Henrik, 2019. "Towards future infrastructures for sustainable multi-energy systems: A review," Energy, Elsevier, vol. 184(C), pages 2-21.
    4. Barelli, L. & Bidini, G. & Bonucci, F. & Castellini, L. & Fratini, A. & Gallorini, F. & Zuccari, A., 2019. "Flywheel hybridization to improve battery life in energy storage systems coupled to RES plants," Energy, Elsevier, vol. 173(C), pages 937-950.
    5. Liu, Jicheng & Sun, Jiakang & Yuan, Hanying & Su, Yihan & Feng, Shuxian & Lu, Chaoran, 2022. "Behavior analysis of photovoltaic-storage-use value chain game evolution in blockchain environment," Energy, Elsevier, vol. 260(C).
    6. Parwal, Arvind & Fregelius, Martin & Temiz, Irinia & Göteman, Malin & Oliveira, Janaina G. de & Boström, Cecilia & Leijon, Mats, 2018. "Energy management for a grid-connected wave energy park through a hybrid energy storage system," Applied Energy, Elsevier, vol. 231(C), pages 399-411.
    7. Bossink, Bart A.G., 2017. "Demonstrating sustainable energy: A review based model of sustainable energy demonstration projects," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 1349-1362.
    8. Ghosh, Sourav & Yadav, Sarita & Devi, Ambika & Thomas, Tiju, 2022. "Techno-economic understanding of Indian energy-storage market: A perspective on green materials-based supercapacitor technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 161(C).
    9. Zhou, Zhizuan & Wang, Dong & Peng, Yang & Li, Maoyu & Wang, Boxuan & Cao, Bei & Yang, Lizhong, 2022. "Experimental study on the thermal management performance of phase change material module for the large format prismatic lithium-ion battery," Energy, Elsevier, vol. 238(PC).
    10. Meng, Hui & Wang, Meihong & Olumayegun, Olumide & Luo, Xiaobo & Liu, Xiaoyan, 2019. "Process design, operation and economic evaluation of compressed air energy storage (CAES) for wind power through modelling and simulation," Renewable Energy, Elsevier, vol. 136(C), pages 923-936.
    11. Soha, Tamás & Munkácsy, Béla & Harmat, Ádám & Csontos, Csaba & Horváth, Gergely & Tamás, László & Csüllög, Gábor & Daróczi, Henriett & Sáfián, Fanni & Szabó, Mária, 2017. "GIS-based assessment of the opportunities for small-scale pumped hydro energy storage in middle-mountain areas focusing on artificial landscape features," Energy, Elsevier, vol. 141(C), pages 1363-1373.
    12. Bhattarai, Arjun & Wai, Nyunt & Schweiss, Rüdiger & Whitehead, Adam & Scherer, Günther G. & Ghimire, Purna C. & Lim, Tuti M. & Hng, Huey Hoon, 2019. "Vanadium redox flow battery with slotted porous electrodes and automatic rebalancing demonstrated on a 1 kW system level," Applied Energy, Elsevier, vol. 236(C), pages 437-443.
    13. Pan, Jeng-Shyang & Hu, Pei & Chu, Shu-Chuan, 2021. "Binary fish migration optimization for solving unit commitment," Energy, Elsevier, vol. 226(C).
    14. Jannesar, Mohammad Rasol & Sedighi, Alireza & Savaghebi, Mehdi & Guerrero, Josep M., 2018. "Optimal placement, sizing, and daily charge/discharge of battery energy storage in low voltage distribution network with high photovoltaic penetration," Applied Energy, Elsevier, vol. 226(C), pages 957-966.
    15. Qi, Meng & Park, Jinwoo & Kim, Jeongdong & Lee, Inkyu & Moon, Il, 2020. "Advanced integration of LNG regasification power plant with liquid air energy storage: Enhancements in flexibility, safety, and power generation," Applied Energy, Elsevier, vol. 269(C).
    16. José Manuel Andújar & Francisca Segura & Jesús Rey & Francisco José Vivas, 2022. "Batteries and Hydrogen Storage: Technical Analysis and Commercial Revision to Select the Best Option," Energies, MDPI, vol. 15(17), pages 1-32, August.
    17. Jiang, Yinghua & Kang, Lixia & Liu, Yongzhong, 2019. "A unified model to optimize configuration of battery energy storage systems with multiple types of batteries," Energy, Elsevier, vol. 176(C), pages 552-560.
    18. Farihan Mohamad & Jiashen Teh & Ching-Ming Lai & Liang-Rui Chen, 2018. "Development of Energy Storage Systems for Power Network Reliability: A Review," Energies, MDPI, vol. 11(9), pages 1-19, August.
    19. Su, Chengguo & Cheng, Chuntian & Wang, Peilin & Shen, Jianjian & Wu, Xinyu, 2019. "Optimization model for long-distance integrated transmission of wind farms and pumped-storage hydropower plants," Applied Energy, Elsevier, vol. 242(C), pages 285-293.
    20. Sivaneasan, Balakrishnan & Kandasamy, Nandha Kumar & Lim, May Lin & Goh, Kwang Ping, 2018. "A new demand response algorithm for solar PV intermittency management," Applied Energy, Elsevier, vol. 218(C), pages 36-45.

    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:16:y:2024:i:4:p:1708-:d:1341712. 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.