IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2022i13p4750-d850875.html
   My bibliography  Save this article

An Elastic Energy Management Algorithm in a Hierarchical Control System with Distributed Control Devices

Author

Listed:
  • Piotr Powroźnik

    (Institute of Metrology, Electronics and Computer Science, University of Zielona Gora, 65-516 Zielona Gora, Poland)

  • Paweł Szcześniak

    (Institute of Automatic Control, Electronics and Electrical Engineering, University of Zielona Gora, 65-516 Zielona Gora, Poland)

  • Krzysztof Turchan

    (IHP—Leibniz Institute for High Performance Microelectronics, 15236 Frankfurt (Oder), Germany)

  • Miłosz Krysik

    (IHP—Leibniz Institute for High Performance Microelectronics, 15236 Frankfurt (Oder), Germany)

  • Igor Koropiecki

    (IHP—Leibniz Institute for High Performance Microelectronics, 15236 Frankfurt (Oder), Germany)

  • Krzysztof Piotrowski

    (IHP—Leibniz Institute for High Performance Microelectronics, 15236 Frankfurt (Oder), Germany)

Abstract

In modern Electric Power Systems, emphasis is placed on the increasing share of electricity from renewable energy sources (PV, wind, hydro, etc.), at the expense of energy generated with the use of fossil fuels. This will lead to changes in energy supply. When there is excessive generation from RESs, there will be too much energy in the system, otherwise, there will be a shortage of energy. Therefore, smart devices should be introduced into the system, the operation of which can be initiated by the conditions of the power grid. This will allow the load profiles of the power grid to be changed and the electricity supply to be used more rationally. The article proposes an elastic energy management algorithm (EEM) in a hierarchical control system with distributed control devices for controlling domestic smart appliances (SA). In the simulation part, scenarios of the algorithm’s operation were carried out for 1000 households with the use of the distribution of activities of individual SAs. In experimental studies, simplified results for three SA types and 100 devices for each type were presented. The obtained results confirm that, thanks to the use of SAs and the appropriate algorithm for their control, it is possible to change the load profile of the power grid. The efficacious operation of SAs will be possible thanks to the change of habits of electricity users, which is briefly described in the article.

Suggested Citation

  • Piotr Powroźnik & Paweł Szcześniak & Krzysztof Turchan & Miłosz Krysik & Igor Koropiecki & Krzysztof Piotrowski, 2022. "An Elastic Energy Management Algorithm in a Hierarchical Control System with Distributed Control Devices," Energies, MDPI, vol. 15(13), pages 1-24, June.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:13:p:4750-:d:850875
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/13/4750/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/15/13/4750/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Chu Donatus Iweh & Samuel Gyamfi & Emmanuel Tanyi & Eric Effah-Donyina, 2021. "Distributed Generation and Renewable Energy Integration into the Grid: Prerequisites, Push Factors, Practical Options, Issues and Merits," Energies, MDPI, vol. 14(17), pages 1-34, August.
    2. Oussama Ouramdane & Elhoussin Elbouchikhi & Yassine Amirat & Franck Le Gall & Ehsan Sedgh Gooya, 2022. "Home Energy Management Considering Renewable Resources, Energy Storage, and an Electric Vehicle as a Backup," Energies, MDPI, vol. 15(8), pages 1-20, April.
    3. Daiva Stanelytė & Virginijus Radziukynas, 2022. "Analysis of Voltage and Reactive Power Algorithms in Low Voltage Networks," Energies, MDPI, vol. 15(5), pages 1-26, March.
    4. Maria C. Fotopoulou & Panagiotis Drosatos & Stefanos Petridis & Dimitrios Rakopoulos & Fotis Stergiopoulos & Nikolaos Nikolopoulos, 2021. "Model Predictive Control for the Energy Management in a District of Buildings Equipped with Building Integrated Photovoltaic Systems and Batteries," Energies, MDPI, vol. 14(12), pages 1-21, June.
    5. Joseph Ngatchou-Wandji & Marwa Ltaifa & Didier Alain Njamen Njomen & Jia Shen, 2022. "Nonparametric Estimation of the Density Function of the Distribution of the Noise in CHARN Models," Mathematics, MDPI, vol. 10(4), pages 1-20, February.
    6. Zhang, Fengqi & Hu, Xiaosong & Langari, Reza & Wang, Lihua & Cui, Yahui & Pang, Hui, 2021. "Adaptive energy management in automated hybrid electric vehicles with flexible torque request," Energy, Elsevier, vol. 214(C).
    7. Hussein Jumma Jabir & Jiashen Teh & Dahaman Ishak & Hamza Abunima, 2018. "Impacts of Demand-Side Management on Electrical Power Systems: A Review," Energies, MDPI, vol. 11(5), pages 1-19, April.
    8. Amit Shewale & Anil Mokhade & Nitesh Funde & Neeraj Dhanraj Bokde, 2022. "A Survey of Efficient Demand-Side Management Techniques for the Residential Appliance Scheduling Problem in Smart Homes," Energies, MDPI, vol. 15(8), pages 1-34, April.
    9. 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.
    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. Piotr Powroźnik & Paweł Szcześniak & Łukasz Sobolewski & Krzysztof Piotrowski, 2022. "Novel Functionalities of Smart Home Devices for the Elastic Energy Management Algorithm," Energies, MDPI, vol. 15(22), pages 1-17, November.

    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. Piotr Powroźnik & Paweł Szcześniak & Łukasz Sobolewski & Krzysztof Piotrowski, 2022. "Novel Functionalities of Smart Home Devices for the Elastic Energy Management Algorithm," Energies, MDPI, vol. 15(22), pages 1-17, November.
    2. Taimoor Ahmad Khan & Amjad Ullah & Ghulam Hafeez & Imran Khan & Sadia Murawwat & Faheem Ali & Sajjad Ali & Sheraz Khan & Khalid Rehman, 2022. "A Fractional Order Super Twisting Sliding Mode Controller for Energy Management in Smart Microgrid Using Dynamic Pricing Approach," Energies, MDPI, vol. 15(23), pages 1-14, November.
    3. Ovidiu Ivanov & Samiran Chattopadhyay & Soumya Banerjee & Bogdan-Constantin Neagu & Gheorghe Grigoras & Mihai Gavrilas, 2020. "A Novel Algorithm with Multiple Consumer Demand Response Priorities in Residential Unbalanced LV Electricity Distribution Networks," Mathematics, MDPI, vol. 8(8), pages 1-24, July.
    4. Tom Elliott & Joachim Geske & Richard Green, 2022. "Business Models for Active Buildings," Energies, MDPI, vol. 15(19), pages 1-17, October.
    5. Antans Sauhats & Andrejs Utans & Jurijs Silinevics & Gatis Junghans & Dmitrijs Guzs, 2021. "Enhancing Power System Frequency with a Novel Load Shedding Method Including Monitoring of Synchronous Condensers’ Power Injections," Energies, MDPI, vol. 14(5), pages 1-21, March.
    6. Anne Christine Lusk & Xin Li & Qiming Liu, 2023. "If the Government Pays for Full Home-Charger Installation, Would Affordable-Housing and Middle-Income Residents Buy Electric Vehicles?," Sustainability, MDPI, vol. 15(5), pages 1-26, March.
    7. Bernadeta Gołębiowska & Anna Bartczak & Mikołaj Czajkowski, 2020. "Energy Demand Management and Social Norms," Energies, MDPI, vol. 13(15), pages 1-20, July.
    8. Chen, Guanpeng & Gao, Xue & Zhao, Yijie & Xu, Xiaojun & Jiang, Yue, 2024. "Attitude stability control for 6WID unmanned ground vehicle during steering: A collaborative controller considering minimizing tire slip energy loss," Energy, Elsevier, vol. 302(C).
    9. Arjuna Nebel & Christine Krüger & Tomke Janßen & Mathieu Saurat & Sebastian Kiefer & Karin Arnold, 2020. "Comparison of the Effects of Industrial Demand Side Management and Other Flexibilities on the Performance of the Energy System," Energies, MDPI, vol. 13(17), pages 1-20, August.
    10. Bartłomiej Mroczek & Paweł Pijarski, 2022. "Machine Learning in Operating of Low Voltage Future Grid," Energies, MDPI, vol. 15(15), pages 1-30, July.
    11. Andrea Mazza & Hamidreza Mirtaheri & Gianfranco Chicco & Angela Russo & Maurizio Fantino, 2019. "Location and Sizing of Battery Energy Storage Units in Low Voltage Distribution Networks," Energies, MDPI, vol. 13(1), pages 1-20, December.
    12. Shreya Shree Das & Arup Das & Subhojit Dawn & Sadhan Gope & Taha Selim Ustun, 2022. "A Joint Scheduling Strategy for Wind and Solar Photovoltaic Systems to Grasp Imbalance Cost in Competitive Market," Sustainability, MDPI, vol. 14(9), pages 1-22, April.
    13. Gul, Eid & Baldinelli, Giorgio & Bartocci, Pietro & Shamim, Tariq & Domenighini, Piergiovanni & Cotana, Franco & Wang, Jinwen & Fantozzi, Francesco & Bianchi, Francesco, 2023. "Transition toward net zero emissions - Integration and optimization of renewable energy sources: Solar, hydro, and biomass with the local grid station in central Italy," Renewable Energy, Elsevier, vol. 207(C), pages 672-686.
    14. Hui Wang & Jun Wang & Zailin Piao & Xiaofang Meng & Chao Sun & Gang Yuan & Sitong Zhu, 2020. "The Optimal Allocation and Operation of an Energy Storage System with High Penetration Grid-Connected Photovoltaic Systems," Sustainability, MDPI, vol. 12(15), pages 1-22, July.
    15. Ussama Assad & Muhammad Arshad Shehzad Hassan & Umar Farooq & Asif Kabir & Muhammad Zeeshan Khan & S. Sabahat H. Bukhari & Zain ul Abidin Jaffri & Judit Oláh & József Popp, 2022. "Smart Grid, Demand Response and Optimization: A Critical Review of Computational Methods," Energies, MDPI, vol. 15(6), pages 1-36, March.
    16. Alya AlHammadi & Nasser Al-Saif & Ameena Saad Al-Sumaiti & Mousa Marzband & Tareefa Alsumaiti & Ehsan Heydarian-Forushani, 2022. "Techno-Economic Analysis of Hybrid Renewable Energy Systems Designed for Electric Vehicle Charging: A Case Study from the United Arab Emirates," Energies, MDPI, vol. 15(18), pages 1-20, September.
    17. Li, Yang & Vilathgamuwa, Mahinda & Choi, San Shing & Farrell, Troy W. & Tran, Ngoc Tham & Teague, Joseph, 2019. "Development of a degradation-conscious physics-based lithium-ion battery model for use in power system planning studies," Applied Energy, Elsevier, vol. 248(C), pages 512-525.
    18. Nuno Rego & Rui Castro & Carlos Santos Silva, 2023. "Assessment of Current Smart House Solutions: The Case of Portugal," Energies, MDPI, vol. 16(22), pages 1-23, November.
    19. Pannee Suanpang & Pitchaya Jamjuntr, 2024. "Optimal Electric Vehicle Battery Management Using Q-learning for Sustainability," Sustainability, MDPI, vol. 16(16), pages 1-50, August.
    20. Yousef Alharbi & Ahmed Darwish & Xiandong Ma, 2023. "A Comprehensive Review of Distributed MPPT for Grid-Tied PV Systems at the Sub-Module Level," Energies, MDPI, vol. 16(14), pages 1-23, July.

    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:13:p:4750-:d:850875. 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.