IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v14y2021i21p7314-d671881.html
   My bibliography  Save this article

Investigation of Home Energy Management with Advanced Direct Load Control and Optimal Scheduling of Controllable Loads

Author

Listed:
  • Kanato Tamashiro

    (Fuculty of Engineering, University of the Ryukyus, 1 Senbaru, Nishihara-cho, Nakagami, Okinawa 903-0213, Japan)

  • Talal Alharbi

    (Department of Electrical Engineering, College of Engineering, Qassim University, Buraydah 52571, Saudi Arabia)

  • Alexey Mikhaylov

    (Financial Research Institute, Ministry of Finance of the Russian Federation, 127006 Moscow, Russia)

  • Ashraf M. Hemeida

    (Fuculty of Energy Engineering, Awan University, Aswan 81711, Egypt)

  • Narayanan Krishnan

    (Department of Electrical and Electronics Engineering, SASTRA Deemed University, Thanjavur 613401, India)

  • Mohammed Elsayed Lotfy

    (Fuculty of Engineering, University of the Ryukyus, 1 Senbaru, Nishihara-cho, Nakagami, Okinawa 903-0213, Japan
    Electrical Power & Machines Department, Zagazig University, Zagazig 44519, Egypt)

  • Tomonobu Senjyu

    (Fuculty of Engineering, University of the Ryukyus, 1 Senbaru, Nishihara-cho, Nakagami, Okinawa 903-0213, Japan)

Abstract

Due to the rapid changes in the energy situation on a global scale, the amount of RES installed using clean renewable energy sources such as Photovoltaic (PV) and Wind-power Generators (WGs) is rapidly increasing. As a result, there has been a great deal of research aimed at promoting the adoption of renewable energy. Research on Demand-side Management (DSM) has also been important in promoting the adoption of RES. However, the massive introduction of PV has changed the shape of the demand curve for electricity, which significantly impacts the operational planning of thermal generators. Therefore, this paper proposes an Advanced Direct Load Control (ADLC) model to temporarily shutdown the electric connection between the power grid and Smart Houses (SHs). The most important feature of the proposed model is that it temporarily shuts down the electric connection with the power grid. The shutdown is performed twice to increase the load demand during daytime hours and reduce the peak load during night-time hours. The proposed model also promotes the self-consumption of the generated power during the shutdown period, which is expected to reduce the operating cost. This paper considers six case studies for SH, and the operational costs and carbon dioxide emissions are compared and discussed. The results show that the SH with ADLC successfully reduces the operating costs and carbon dioxide emissions.

Suggested Citation

  • Kanato Tamashiro & Talal Alharbi & Alexey Mikhaylov & Ashraf M. Hemeida & Narayanan Krishnan & Mohammed Elsayed Lotfy & Tomonobu Senjyu, 2021. "Investigation of Home Energy Management with Advanced Direct Load Control and Optimal Scheduling of Controllable Loads," Energies, MDPI, vol. 14(21), pages 1-14, November.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:21:p:7314-:d:671881
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/14/21/7314/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/14/21/7314/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. An, Jaehyung & Mikhaylov, Alexey & Jung, Sang-Uk, 2021. "A Linear Programming approach for robust network revenue management in the airline industry," Journal of Air Transport Management, Elsevier, vol. 91(C).
    2. Javadi, Mohammad Sadegh & Gough, Matthew & Lotfi, Mohamed & Esmaeel Nezhad, Ali & Santos, Sérgio F. & Catalão, João P.S., 2020. "Optimal self-scheduling of home energy management system in the presence of photovoltaic power generation and batteries," Energy, Elsevier, vol. 210(C).
    3. 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.
    4. Jia Ning & Yi Tang & Qian Chen & Jianming Wang & Jianhua Zhou & Bingtuan Gao, 2017. "A Bi-Level Coordinated Optimization Strategy for Smart Appliances Considering Online Demand Response Potential," Energies, MDPI, vol. 10(4), pages 1-16, April.
    5. Qi Wang & Ping Chang & Runqing Bai & Wenfei Liu & Jianfeng Dai & Yi Tang, 2019. "Mitigation Strategy for Duck Curve in High Photovoltaic Penetration Power System Using Concentrating Solar Power Station," Energies, MDPI, vol. 12(18), pages 1-16, September.
    6. Hernández, J.C. & Medina, A. & Jurado, F., 2007. "Optimal allocation and sizing for profitability and voltage enhancement of PV systems on feeders," Renewable Energy, Elsevier, vol. 32(10), pages 1768-1789.
    7. Hou, Qingchun & Zhang, Ning & Du, Ershun & Miao, Miao & Peng, Fei & Kang, Chongqing, 2019. "Probabilistic duck curve in high PV penetration power system: Concept, modeling, and empirical analysis in China," Applied Energy, Elsevier, vol. 242(C), pages 205-215.
    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. Alexey Mikhaylov, 2022. "Sustainable Development and Renewable Energy: A New View to a Global Problem," Energies, MDPI, vol. 15(4), pages 1-4, February.

    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. Harsh Wardhan Pandey & Ramesh Kumar & Rajib Kumar Mandal, 2023. "Ranking of mitigation strategies for duck curve in Indian active distribution network using MCDM," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 14(4), pages 1255-1275, August.
    2. Binghui Han & Younes Zahraoui & Marizan Mubin & Saad Mekhilef & Mehdi Seyedmahmoudian & Alex Stojcevski, 2023. "Optimal Strategy for Comfort-Based Home Energy Management System Considering Impact of Battery Degradation Cost Model," Mathematics, MDPI, vol. 11(6), pages 1-26, March.
    3. Qi Wang & Ping Chang & Runqing Bai & Wenfei Liu & Jianfeng Dai & Yi Tang, 2019. "Mitigation Strategy for Duck Curve in High Photovoltaic Penetration Power System Using Concentrating Solar Power Station," Energies, MDPI, vol. 12(18), pages 1-16, September.
    4. Nazim Hajiyev & Klaudia Smoląg & Ali Abbasov & Valeriy Prasolov, 2020. "Energy War Strategies: The 21st Century Experience," Energies, MDPI, vol. 13(21), pages 1-15, November.
    5. Hao Wu & Lin Zhou & Yihao Wan & Qiang Liu & Siyu Zhou, 2019. "A Mixed Uncertainty Power Flow Algorithm-Based Centralized Photovoltaic (PV) Cluster," Energies, MDPI, vol. 12(20), pages 1-16, October.
    6. Sun, Wei & Harrison, Gareth P., 2019. "Wind-solar complementarity and effective use of distribution network capacity," Applied Energy, Elsevier, vol. 247(C), pages 89-101.
    7. Ahmad Abuelrub & Osama Saadeh & Hussein M. K. Al-Masri, 2018. "Scenario Aggregation-Based Grid-Connected Photovoltaic Plant Design," Sustainability, MDPI, vol. 10(4), pages 1-13, April.
    8. Hernández, J.C. & Ruiz-Rodriguez, F.J. & Jurado, F., 2017. "Modelling and assessment of the combined technical impact of electric vehicles and photovoltaic generation in radial distribution systems," Energy, Elsevier, vol. 141(C), pages 316-332.
    9. Sylwester Kozak, 2021. "The Impact of COVID-19 on Bank Equity and Performance: The Case of Central Eastern South European Countries," Sustainability, MDPI, vol. 13(19), pages 1-15, October.
    10. Li, Yanbin & Zhang, Feng & Li, Yun & Wang, Yuwei, 2021. "An improved two-stage robust optimization model for CCHP-P2G microgrid system considering multi-energy operation under wind power outputs uncertainties," Energy, Elsevier, vol. 223(C).
    11. Dong, Weijie & He, Guoqing & Cui, Quansheng & Sun, Wenwen & Hu, Zhenlong & Ahli raad, Erfan, 2022. "Self-scheduling of a novel hybrid GTSOFC unit in day-ahead energy and spinning reserve markets within ancillary services using a novel energy storage," Energy, Elsevier, vol. 239(PE).
    12. Yang, Wenjun & Guo, Jia & Vartosh, Aris, 2022. "Optimal economic-emission planning of multi-energy systems integrated electric vehicles with modified group search optimization," Applied Energy, Elsevier, vol. 311(C).
    13. Yan, Rujing & Wang, Jiangjiang & Wang, Jiahao & Tian, Lei & Tang, Saiqiu & Wang, Yuwei & Zhang, Jing & Cheng, Youliang & Li, Yuan, 2022. "A two-stage stochastic-robust optimization for a hybrid renewable energy CCHP system considering multiple scenario-interval uncertainties," Energy, Elsevier, vol. 247(C).
    14. Ying-Yi Hong & Gerard Francesco DG. Apolinario, 2021. "Uncertainty in Unit Commitment in Power Systems: A Review of Models, Methods, and Applications," Energies, MDPI, vol. 14(20), pages 1-47, October.
    15. Zhang, Li & Gao, Yan & Zhu, Hongbo & Tao, Li, 2022. "Bi-level stochastic real-time pricing model in multi-energy generation system: A reinforcement learning approach," Energy, Elsevier, vol. 239(PA).
    16. Sara Mehrab Daniali & Sergey Evgenievich Barykin & Farzin Mohammadbeigi Khortabi & Olga Vladimirovna Kalinina & Olga Anatolievna Tcukanova & Elena Konstantinovna Torosyan & Svetlana Poliakova & Sergey, 2022. "An Employee Competency Framework in a Welfare Organization," Sustainability, MDPI, vol. 14(4), pages 1-20, February.
    17. Rajesh, K. & Karthikeyan, K. & Kannan, S. & Thangaraj, C., 2016. "Generation expansion planning based on solar plants with storage," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 953-964.
    18. Zaffar Ahmed Shaikh & Polina Datsyuk & Laura M. Baitenova & Larisa Belinskaja & Natalia Ivolgina & Gulmira Rysmakhanova & Tomonobu Senjyu, 2022. "Effect of the COVID-19 Pandemic on Renewable Energy Firm’s Profitability and Capitalization," Sustainability, MDPI, vol. 14(11), pages 1-15, June.
    19. Karimi, Hamid & Jadid, Shahram, 2020. "Optimal energy management for multi-microgrid considering demand response programs: A stochastic multi-objective framework," Energy, Elsevier, vol. 195(C).
    20. Yi Hao & Zhigang Huang & Shiqian Ma & Jiakai Huang & Jiahao Chen & Bing Sun, 2023. "Evaluation Method of the Incremental Power Supply Capability Brought by Distributed Generation," Energies, MDPI, vol. 16(16), pages 1-17, August.

    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:14:y:2021:i:21:p:7314-:d:671881. 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.