IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v12y2019i9p1811-d230588.html
   My bibliography  Save this article

Energy Management Optimization and Voltage Evaluation for Residential and Commercial Areas

Author

Listed:
  • Hayder O. Alwan

    (Department of Electrical and Computer Engineering, Virginia Commonwealth University, Richmond, VA 23220, USA)

  • Hamidreza Sadeghian

    (Department of Electrical and Computer Engineering, Virginia Commonwealth University, Richmond, VA 23220, USA)

  • Sherif Abdelwahed

    (Department of Electrical and Computer Engineering, Virginia Commonwealth University, Richmond, VA 23220, USA)

Abstract

In most smart grids, load management techniques are required to handle multiple loads of several types. This paper studies decentralized demand-side management (DSM) in a grid with different types of appliances in two service areas: one with many residential households, and one bus with commercial customers. Each building runs an individual optimal DSM to reschedule the usage time of its flexible appliances to reduce its electric energy cost at a manageable sacrifice of inconvenience according to the forecasted time-varying electricity price. Using the developed model, we examined the effectiveness of decentralized DSM by comparing its performance on the operation status of the grid in terms of electricity cost saving, rooftop photovoltaic (PV) utilization efficiency, voltage fluctuation, power loss, voltage rises, and reverse power flows, which can easily be seen at the commercial load bus.

Suggested Citation

  • Hayder O. Alwan & Hamidreza Sadeghian & Sherif Abdelwahed, 2019. "Energy Management Optimization and Voltage Evaluation for Residential and Commercial Areas," Energies, MDPI, vol. 12(9), pages 1-21, May.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:9:p:1811-:d:230588
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/12/9/1811/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/12/9/1811/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Iver Bakken Sperstad & Magnus Korpås, 2019. "Energy Storage Scheduling in Distribution Systems Considering Wind and Photovoltaic Generation Uncertainties," Energies, MDPI, vol. 12(7), pages 1-24, March.
    2. Esther, B. Priya & Kumar, K. Sathish, 2016. "A survey on residential Demand Side Management architecture, approaches, optimization models and methods," Renewable and Sustainable Energy Reviews, Elsevier, vol. 59(C), pages 342-351.
    3. Antimo Barbato & Antonio Capone, 2014. "Optimization Models and Methods for Demand-Side Management of Residential Users: A Survey," Energies, MDPI, vol. 7(9), pages 1-38, September.
    4. Sadeghian, H.R. & Ardehali, M.M., 2016. "A novel approach for optimal economic dispatch scheduling of integrated combined heat and power systems for maximum economic profit and minimum environmental emissions based on Benders decomposition," Energy, Elsevier, vol. 102(C), pages 10-23.
    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. Saman Nikkhah & Adib Allahham & Janusz W. Bialek & Sara L. Walker & Damian Giaouris & Simira Papadopoulou, 2021. "Active Participation of Buildings in the Energy Networks: Dynamic/Operational Models and Control Challenges," Energies, MDPI, vol. 14(21), pages 1-28, November.
    2. Grace Muriithi & Sunetra Chowdhury, 2021. "Optimal Energy Management of a Grid-Tied Solar PV-Battery Microgrid: A Reinforcement Learning Approach," Energies, MDPI, vol. 14(9), pages 1-24, May.

    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. Xia, Yuanxing & Xu, Qingshan & Tao, Siyu & Du, Pengwei & Ding, Yixing & Fang, Jicheng, 2022. "Preserving operation privacy of peer-to-peer energy transaction based on Enhanced Benders Decomposition considering uncertainty of renewable energy generations," Energy, Elsevier, vol. 250(C).
    2. Saffari, Mohammad & de Gracia, Alvaro & Fernández, Cèsar & Belusko, Martin & Boer, Dieter & Cabeza, Luisa F., 2018. "Optimized demand side management (DSM) of peak electricity demand by coupling low temperature thermal energy storage (TES) and solar PV," Applied Energy, Elsevier, vol. 211(C), pages 604-616.
    3. Aryuanto Soetedjo & Yusuf Ismail Nakhoda & Choirul Saleh, 2019. "An Embedded Platform for Testbed Implementation of Multi-Agent System in Building Energy Management System," Energies, MDPI, vol. 12(19), pages 1-29, September.
    4. de Christo, Tiago Malavazi & Perron, Sylvain & Fardin, Jussara Farias & Simonetti, Domingos Sávio Lyrio & de Alvarez, Cristina Engel, 2019. "Demand-side energy management by cooperative combination of plans: A multi-objective method applicable to isolated communities," Applied Energy, Elsevier, vol. 240(C), pages 453-472.
    5. Fabio Bignucolo & Massimiliano Coppo & Giorgio Crugnola & Andrea Savio, 2017. "Application of a Simplified Thermal-Electric Model of a Sodium-Nickel Chloride Battery Energy Storage System to a Real Case Residential Prosumer," Energies, MDPI, vol. 10(10), pages 1-29, September.
    6. Amit Shewale & Anil Mokhade & Nitesh Funde & Neeraj Dhanraj Bokde, 2020. "An Overview of Demand Response in Smart Grid and Optimization Techniques for Efficient Residential Appliance Scheduling Problem," Energies, MDPI, vol. 13(16), pages 1-31, August.
    7. Dominique Barth & Benjamin Cohen-Boulakia & Wilfried Ehounou, 2022. "Distributed Reinforcement Learning for the Management of a Smart Grid Interconnecting Independent Prosumers," Energies, MDPI, vol. 15(4), pages 1-19, February.
    8. Thijs Klauw & Marco E. T. Gerards & Johann L. Hurink, 2017. "Resource allocation problems in decentralized energy management," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 39(3), pages 749-773, July.
    9. Simona-Vasilica Oprea & Adela Bâra & Adriana Reveiu, 2018. "Informatics Solution for Energy Efficiency Improvement and Consumption Management of Householders," Energies, MDPI, vol. 11(1), pages 1-31, January.
    10. Rizk-Allah, Rizk M. & Hassanien, Aboul Ella & Snášel, Václav, 2022. "A hybrid chameleon swarm algorithm with superiority of feasible solutions for optimal combined heat and power economic dispatch problem," Energy, Elsevier, vol. 254(PC).
    11. Li, Yang & Wang, Jinlong & Zhao, Dongbo & Li, Guoqing & Chen, Chen, 2018. "A two-stage approach for combined heat and power economic emission dispatch: Combining multi-objective optimization with integrated decision making," Energy, Elsevier, vol. 162(C), pages 237-254.
    12. Zhenghao Wang & Yonghui Liu & Zihao Yang & Wanhao Yang, 2021. "Load Frequency Control of Multi-Region Interconnected Power Systems with Wind Power and Electric Vehicles Based on Sliding Mode Control," Energies, MDPI, vol. 14(8), pages 1-15, April.
    13. Muhammad Riaz & Aamir Hanif & Haris Masood & Muhammad Attique Khan & Kamran Afaq & Byeong-Gwon Kang & Yunyoung Nam, 2021. "An Optimal Power Flow Solution of a System Integrated with Renewable Sources Using a Hybrid Optimizer," Sustainability, MDPI, vol. 13(23), pages 1-12, December.
    14. Sellak, Hamza & Ouhbi, Brahim & Frikh, Bouchra & Palomares, Iván, 2017. "Towards next-generation energy planning decision-making: An expert-based framework for intelligent decision support," Renewable and Sustainable Energy Reviews, Elsevier, vol. 80(C), pages 1544-1577.
    15. Gianluca Serale & Massimo Fiorentini & Alfonso Capozzoli & Daniele Bernardini & Alberto Bemporad, 2018. "Model Predictive Control (MPC) for Enhancing Building and HVAC System Energy Efficiency: Problem Formulation, Applications and Opportunities," Energies, MDPI, vol. 11(3), pages 1-35, March.
    16. Hortay, Olivér & Kökény, László, 2020. "A villamosenergia-fogyasztás elhalasztásával kapcsolatos lakossági attitűd felmérése Magyarországon [A survey of popular attitudes to deferment of electricity consumption in Hungary]," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(7), pages 657-687.
    17. Mei, Fei & Zhang, Jiatang & Lu, Jixiang & Lu, Jinjun & Jiang, Yuhan & Gu, Jiaqi & Yu, Kun & Gan, Lei, 2021. "Stochastic optimal operation model for a distributed integrated energy system based on multiple-scenario simulations," Energy, Elsevier, vol. 219(C).
    18. 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.
    19. Huang, Pei & Wu, Hunjun & Huang, Gongsheng & Sun, Yongjun, 2018. "A top-down control method of nZEBs for performance optimization at nZEB-cluster-level," Energy, Elsevier, vol. 159(C), pages 891-904.
    20. Carli, Raffaele & Dotoli, Mariagrazia & Jantzen, Jan & Kristensen, Michael & Ben Othman, Sarah, 2020. "Energy scheduling of a smart microgrid with shared photovoltaic panels and storage: The case of the Ballen marina in Samsø," Energy, Elsevier, vol. 198(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:jeners:v:12:y:2019:i:9:p:1811-:d:230588. 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.