IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2022i9p2981-d797136.html
   My bibliography  Save this article

Application of Artificial Intelligence in the Unit Commitment System in the Application of Energy Sustainability

Author

Listed:
  • Bohumír Garlík

    (Faculty of Civil Engineering, Czech Technical University, 166 29 Prague, Czech Republic)

Abstract

This article approaches the optimal solution of energy sustainability based on the use of artificial intelligence (AI). The application of renewable energy sources (RES) and unit commitment (UC) is the basic idea of this concept. Therefore, a new approach to solving the UC problem is introduced. The proposed method has a simple procedure to obtain the popular solutions in an acceptable time interval, by creating a basic model of the schedule of the state of energy units RES. It is obvious that individual consumer units, of an operational nature, take hourly performance values by performing economic evaluations on them in the sense of cost optimization. This is conducted through an artificial intelligence (AI) algorithm by optimizing the dedicated cost function, simulated by annealing. Despite the acceptable solution obtained from these two steps, another shift is proposed, called the TDD process in a given consumer area. This process in the application of AI in the system of selection of universal load TDD from hundreds of possible ones is based on the use of artificial neural networks and cluster analysis, which is represented by the application of the Kohonen map. This logical process to achieve a modified solution is a self-organizing map (SOM). It is a software tool for visualizing high-dimensional data. Converts complex, nonlinear statistical relationships (functions) between high-dimensional data to simple geometric relationships, low-dimensional representation. The output of SOM is an optimized load TDD on the basis of which the process of automatic control of UC in the local urban area is built. The results of the AI application in the case of sustainable energy solutions confirm that this UC method provides a robust solution to an almost optimal solution.

Suggested Citation

  • Bohumír Garlík, 2022. "Application of Artificial Intelligence in the Unit Commitment System in the Application of Energy Sustainability," Energies, MDPI, vol. 15(9), pages 1-33, April.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:9:p:2981-:d:797136
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/9/2981/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/15/9/2981/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Zhang, Xingxing & Lovati, Marco & Vigna, Ilaria & Widén, Joakim & Han, Mengjie & Gal, Csilla & Feng, Tao, 2018. "A review of urban energy systems at building cluster level incorporating renewable-energy-source (RES) envelope solutions," Applied Energy, Elsevier, vol. 230(C), pages 1034-1056.
    2. Cicea, Claudiu & Marinescu, Corina & Popa, Ion & Dobrin, Cosmin, 2014. "Environmental efficiency of investments in renewable energy: Comparative analysis at macroeconomic level," Renewable and Sustainable Energy Reviews, Elsevier, vol. 30(C), pages 555-564.
    3. Howell, Shaun & Rezgui, Yacine & Hippolyte, Jean-Laurent & Jayan, Bejay & Li, Haijiang, 2017. "Towards the next generation of smart grids: Semantic and holonic multi-agent management of distributed energy resources," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 193-214.
    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. Luciano Cavalcante Siebert & Alexandre Rasi Aoki & Germano Lambert-Torres & Nelson Lambert-de-Andrade & Nikolaos G. Paterakis, 2020. "An Agent-Based Approach for the Planning of Distribution Grids as a Socio-Technical System," Energies, MDPI, vol. 13(18), pages 1-13, September.
    2. Yamaguchi, Yohei & Shoda, Yuto & Yoshizawa, Shinya & Imai, Tatsuya & Perwez, Usama & Shimoda, Yoshiyuki & Hayashi, Yasuhiro, 2023. "Feasibility assessment of net zero-energy transformation of building stock using integrated synthetic population, building stock, and power distribution network framework," Applied Energy, Elsevier, vol. 333(C).
    3. Claudiu Cicea & Corina Marinescu & Nicolae Pintilie, 2021. "New Methodological Approach for Performance Assessment in the Bioenergy Field," Energies, MDPI, vol. 14(4), pages 1-19, February.
    4. Samrena Jabeen & Subha Malik & Soha Khan & Nohman Khan & Muhammad Imran Qureshi & Mohd Shamsuri Md Saad, 2021. "A Comparative Systematic Literature Review and Bibliometric Analysis on Sustainability of Renewable Energy Sources," International Journal of Energy Economics and Policy, Econjournals, vol. 11(1), pages 270-280.
    5. Yoo, Yoon-Sik & Newaz, S.H. Shah & Shannon, Peter David & Lee, Il-Woo & Choi, Jun Kyun, 2018. "Towards improving throughput and reducing latency: A simplified protocol conversion mechanism in distributed energy resources network," Applied Energy, Elsevier, vol. 213(C), pages 45-55.
    6. Markovič, Rene & Gosak, Marko & Grubelnik, Vladimir & Marhl, Marko & Virtič, Peter, 2019. "Data-driven classification of residential energy consumption patterns by means of functional connectivity networks," Applied Energy, Elsevier, vol. 242(C), pages 506-515.
    7. Antonopoulos, Ioannis & Robu, Valentin & Couraud, Benoit & Kirli, Desen & Norbu, Sonam & Kiprakis, Aristides & Flynn, David & Elizondo-Gonzalez, Sergio & Wattam, Steve, 2020. "Artificial intelligence and machine learning approaches to energy demand-side response: A systematic review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 130(C).
    8. Vosughi, Amirkhosro & Tamimi, Ali & King, Alexandra Beatrice & Majumder, Subir & Srivastava, Anurag K., 2022. "Cyber–physical vulnerability and resiliency analysis for DER integration: A review, challenges and research needs," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).
    9. Bendato, Ilaria & Cassettari, Lucia & Mosca, Marco & Mosca, Roberto, 2015. "A design of experiments/response surface methodology approach to study the economic sustainability of a 1MWe photovoltaic plant," Renewable and Sustainable Energy Reviews, Elsevier, vol. 51(C), pages 1664-1679.
    10. Peipei, Wang & Eyvazov, Elchin & Giyasova, Zeynab & Kazimova, Asli, 2023. "The nexus between natural resource rents and financial wealth on economic recovery: Evidence from European Union economies," Resources Policy, Elsevier, vol. 82(C).
    11. Wang, Shaojian & Li, Guangdong & Fang, Chuanglin, 2018. "Urbanization, economic growth, energy consumption, and CO2 emissions: Empirical evidence from countries with different income levels," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P2), pages 2144-2159.
    12. Weiguo Fan & Mengmeng Meng & Jianchang Lu & Xiaobin Dong & Hejie Wei & Xuechao Wang & Qing Zhang, 2020. "Decoupling Elasticity and Driving Factors of Energy Consumption and Economic Development in the Qinghai-Tibet Plateau," Sustainability, MDPI, vol. 12(4), pages 1-20, February.
    13. Ibrahim Alotaibi & Mohammed A. Abido & Muhammad Khalid & Andrey V. Savkin, 2020. "A Comprehensive Review of Recent Advances in Smart Grids: A Sustainable Future with Renewable Energy Resources," Energies, MDPI, vol. 13(23), pages 1-41, November.
    14. Shahbaz, Muhammad & Mahalik, Mantu Kumar & Shah, Syed Hasanat & Sato, João Ricardo, 2016. "Time-varying analysis of CO2 emissions, energy consumption, and economic growth nexus: Statistical experience in next 11 countries," Energy Policy, Elsevier, vol. 98(C), pages 33-48.
    15. Muhammad Bilal Khan & Hummera Saleem & Malik Shahzad Shabbir & Xie Huobao, 2022. "The effects of globalization, energy consumption and economic growth on carbon dioxide emissions in South Asian countries," Energy & Environment, , vol. 33(1), pages 107-134, February.
    16. Alharbi, Talal & Abo-Elyousr, Farag K. & Abdelshafy, Alaaeldin M., 2024. "Efficient Coordination of Renewable Energy Resources through Optimal Reversible Pumped Hydro-Storage Integration for Autonomous Microgrid Economic Operation," Energy, Elsevier, vol. 304(C).
    17. Oduro, Richard A. & Taylor, Peter G., 2023. "Future pathways for energy networks: A review of international experiences in high income countries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 171(C).
    18. Marcin Zygmunt & Dariusz Gawin, 2021. "Application of Artificial Neural Networks in the Urban Building Energy Modelling of Polish Residential Building Stock," Energies, MDPI, vol. 14(24), pages 1-15, December.
    19. Gideon Kwaku Minua Ampofo & Jinhua Cheng & Edwin Twum Ayimadu & Daniel Akwasi Asante, 2021. "Investigating the Asymmetric Effect of Economic Growth on Environmental Quality in the Next 11 Countries," Energies, MDPI, vol. 14(2), pages 1-29, January.
    20. Mbungu, Nsilulu T. & Bansal, Ramesh C. & Naidoo, Raj M. & Bettayeb, Maamar & Siti, Mukwanga W. & Bipath, Minnesh, 2020. "A dynamic energy management system using smart metering," Applied Energy, Elsevier, vol. 280(C).

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;
    ;
    ;
    ;
    ;

    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:gam:jeners:v:15:y:2022:i:9:p:2981-:d:797136. 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.