IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v10y2017i3p335-d92658.html
   My bibliography  Save this article

Orchestrating an Effective Formulation to Investigate the Impact of EMSs (Energy Management Systems) for Residential Units Prior to Installation

Author

Listed:
  • Danish Mahmood

    (COMSATS Institute of Information Technology, Islamabad 44000, Pakistan)

  • Nadeem Javaid

    (COMSATS Institute of Information Technology, Islamabad 44000, Pakistan)

  • Sheraz Ahmed

    (COMSATS Institute of Information Technology, Islamabad 44000, Pakistan
    Institute of Management Sciences (IMS), Peshawar 25000, Pakistan)

  • Imran Ahmed

    (Institute of Management Sciences (IMS), Peshawar 25000, Pakistan)

  • Iftikhar Azim Niaz

    (COMSATS Institute of Information Technology, Islamabad 44000, Pakistan)

  • Wadood Abdul

    (Department of Computer Engineering, College of Computer and Information Sciences, King Saud University, Riyadh 11633, Saudi Arabia)

  • Sanaa Ghouzali

    (Information Technology Department, College of Computer and Information Sciences, King Saud University, Riyadh 11633, Saudi Arabia)

Abstract

Demand Response (DR) programs under the umbrella of Demand Side Management (DSM) tend to involve end users in optimizing their Power Consumption (PC) patterns and offer financial incentives to shift the load at “low-priced” hours. However, users have their own preferences of anticipating the amount of consumed electricity. While installing an Energy Management System (EMS), the user must be assured that this investment gives optimum comfort of bill savings, as well as appliance utility considering Time of Use (ToU). Moreover, there is a difference between desired load distribution and optimally-scheduled load across a 24-h time frame for lowering electricity bills. This difference in load usage timings, if it is beyond the tolerance level of a user, increases frustration. The comfort level is a highly variable phenomenon. An EMS giving optimum comfort to one user may not be able to provide the same level of satisfaction to another who has different preferences regarding electricity bill savings or appliance utility. Under such a diversity of human behaviors, it is difficult to select an EMS for an individual user. In this work, a numeric performance metric,“User Comfort Level (UCL)”isformulatedonthebasisofuserpreferencesoncostsaving,toleranceindelayregardinguse of an appliance and return of investment. The proposed framework (UCL) allows the user to select an EMS optimally that suits his.her preferences well by anticipating electricity bill reduction, tolerable delay in ToU of the appliance and return on investment. Furthermore, an extended literature analysis is conducted demonstrating generic strategies of EMSs. Five major building blocks are discussed and a comparative analysis is presented on the basis of the proposed performance metric.

Suggested Citation

  • Danish Mahmood & Nadeem Javaid & Sheraz Ahmed & Imran Ahmed & Iftikhar Azim Niaz & Wadood Abdul & Sanaa Ghouzali, 2017. "Orchestrating an Effective Formulation to Investigate the Impact of EMSs (Energy Management Systems) for Residential Units Prior to Installation," Energies, MDPI, vol. 10(3), pages 1-25, March.
    • Handle: RePEc:gam:jeners:v:10:y:2017:i:3:p:335-:d:92658
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/10/3/335/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/10/3/335/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Zhou, Bin & Li, Wentao & Chan, Ka Wing & Cao, Yijia & Kuang, Yonghong & Liu, Xi & Wang, Xiong, 2016. "Smart home energy management systems: Concept, configurations, and scheduling strategies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 61(C), pages 30-40.
    2. Gabriele Lobaccaro & Salvatore Carlucci & Erica Löfström, 2016. "A Review of Systems and Technologies for Smart Homes and Smart Grids," Energies, MDPI, vol. 9(5), pages 1-33, May.
    3. Tiago D. P. Mendes & Radu Godina & Eduardo M. G. Rodrigues & João C. O. Matias & João P. S. Catalão, 2015. "Smart Home Communication Technologies and Applications: Wireless Protocol Assessment for Home Area Network Resources," Energies, MDPI, vol. 8(7), pages 1-33, July.
    4. Haider, Haider Tarish & See, Ong Hang & Elmenreich, Wilfried, 2016. "Residential demand response scheme based on adaptive consumption level pricing," Energy, Elsevier, vol. 113(C), pages 301-308.
    5. Bingtuan Gao & Wenhu Zhang & Yi Tang & Mingjin Hu & Mingcheng Zhu & Huiyu Zhan, 2014. "Game-Theoretic Energy Management for Residential Users with Dischargeable Plug-in Electric Vehicles," Energies, MDPI, vol. 7(11), pages 1-20, November.
    6. Nikoleta Andreadou & Miguel Olariaga Guardiola & Gianluca Fulli, 2016. "Telecommunication Technologies for Smart Grid Projects with Focus on Smart Metering Applications," Energies, MDPI, vol. 9(5), pages 1-35, May.
    7. Pusnik, Matevz & Al-Mansour, Fouad & Sucic, Boris & Gubina, A.F., 2016. "Gap analysis of industrial energy management systems in Slovenia," Energy, Elsevier, vol. 108(C), pages 41-49.
    8. Tadahiro Taniguchi & Koki Kawasaki & Yoshiro Fukui & Tomohiro Takata & Shiro Yano, 2015. "Automated Linear Function Submission-Based Double Auction as Bottom-up Real-Time Pricing in a Regional Prosumers’ Electricity Network," Energies, MDPI, vol. 8(7), pages 1-26, July.
    9. Hye Yeon Kim & Hae Jin Kang, 2016. "A Study on Development of a Cost Optimal and Energy Saving Building Model: Focused on Industrial Building," Energies, MDPI, vol. 9(3), pages 1-19, March.
    10. Luay N. Dwaikat & Kherun N. Ali, 2016. "Measuring the Actual Energy Cost Performance of Green Buildings: A Test of the Earned Value Management Approach," Energies, MDPI, vol. 9(3), pages 1-20, March.
    11. Menezes, Anna Carolina & Cripps, Andrew & Bouchlaghem, Dino & Buswell, Richard, 2012. "Predicted vs. actual energy performance of non-domestic buildings: Using post-occupancy evaluation data to reduce the performance gap," Applied Energy, Elsevier, vol. 97(C), pages 355-364.
    12. Augustine Ikpehai & Bamidele Adebisi & Khaled M. Rabie & Russell Haggar & Mike Baker, 2016. "Experimental Study of 6LoPLC for Home Energy Management Systems," Energies, MDPI, vol. 9(12), pages 1-19, December.
    13. Ferruzzi, Gabriella & Cervone, Guido & Delle Monache, Luca & Graditi, Giorgio & Jacobone, Francesca, 2016. "Optimal bidding in a Day-Ahead energy market for Micro Grid under uncertainty in renewable energy production," Energy, Elsevier, vol. 106(C), pages 194-202.
    14. Whei-Min Lin & Chia-Sheng Tu & Ming-Tang Tsai, 2015. "Energy Management Strategy for Microgrids by Using Enhanced Bee Colony Optimization," Energies, MDPI, vol. 9(1), pages 1-16, December.
    15. Mulder, Grietus & Six, Daan & Claessens, Bert & Broes, Thijs & Omar, Noshin & Mierlo, Joeri Van, 2013. "The dimensioning of PV-battery systems depending on the incentive and selling price conditions," Applied Energy, Elsevier, vol. 111(C), pages 1126-1135.
    16. Zdenek Bradac & Vaclav Kaczmarczyk & Petr Fiedler, 2014. "Optimal Scheduling of Domestic Appliances via MILP," Energies, MDPI, vol. 8(1), pages 1-16, December.
    17. Graditi, G. & Ippolito, M.G. & Telaretti, E. & Zizzo, G., 2016. "Technical and economical assessment of distributed electrochemical storages for load shifting applications: An Italian case study," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 515-523.
    18. Zheng, Menglian & Meinrenken, Christoph J. & Lackner, Klaus S., 2014. "Agent-based model for electricity consumption and storage to evaluate economic viability of tariff arbitrage for residential sector demand response," Applied Energy, Elsevier, vol. 126(C), pages 297-306.
    19. Danish Mahmood & Nadeem Javaid & Nabil Alrajeh & Zahoor Ali Khan & Umar Qasim & Imran Ahmed & Manzoor Ilahi, 2016. "Realistic Scheduling Mechanism for Smart Homes," Energies, MDPI, vol. 9(3), pages 1-28, March.
    20. Jaffe, Adam B. & Stavins, Robert N., 1994. "The energy-efficiency gap What does it mean?," Energy Policy, Elsevier, vol. 22(10), pages 804-810, October.
    21. Brian L. Thomas & Diane J. Cook, 2016. "Activity-Aware Energy-Efficient Automation of Smart Buildings," Energies, MDPI, vol. 9(8), pages 1-17, August.
    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. Nadeem Javaid & Sardar Mehboob Hussain & Ibrar Ullah & Muhammad Asim Noor & Wadood Abdul & Ahmad Almogren & Atif Alamri, 2017. "Demand Side Management in Nearly Zero Energy Buildings Using Heuristic Optimizations," Energies, MDPI, vol. 10(8), pages 1-29, August.

    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. Augustine Ikpehai & Bamidele Adebisi & Khaled M. Rabie & Russell Haggar & Mike Baker, 2016. "Experimental Study of 6LoPLC for Home Energy Management Systems," Energies, MDPI, vol. 9(12), pages 1-19, December.
    2. WeiYu Ji & Edwin H. W. Chan, 2019. "Critical Factors Influencing the Adoption of Smart Home Energy Technology in China: A Guangdong Province Case Study," Energies, MDPI, vol. 12(21), pages 1-24, November.
    3. Carlos Cruz & Esther Palomar & Ignacio Bravo & Alfredo Gardel, 2020. "Cooperative Demand Response Framework for a Smart Community Targeting Renewables: Testbed Implementation and Performance Evaluation," Energies, MDPI, vol. 13(11), pages 1-20, June.
    4. Byeongkwan Kang & Kyuhee Jang & Sounghoan Park & Myeong-in Choi & Sehyun Park, 2018. "Energy Storage System Control Algorithm by Operating Target Power to Improve Energy Sustainability of Smart Home," Sustainability, MDPI, vol. 10(1), pages 1-16, January.
    5. Flavio Martins & Maria Fatima Almeida & Rodrigo Calili & Agatha Oliveira, 2020. "Design Thinking Applied to Smart Home Projects: A User-Centric and Sustainable Perspective," Sustainability, MDPI, vol. 12(23), pages 1-27, December.
    6. Chen, Chien-fei & Nelson, Hannah & Xu, Xiaojing & Bonilla, Gregory & Jones, Nicholas, 2021. "Beyond technology adoption: Examining home energy management systems, energy burdens and climate change perceptions during COVID-19 pandemic," Renewable and Sustainable Energy Reviews, Elsevier, vol. 145(C).
    7. Mahmoud H. Elkholy & Tomonobu Senjyu & Mohammed Elsayed Lotfy & Abdelrahman Elgarhy & Nehad S. Ali & Tamer S. Gaafar, 2022. "Design and Implementation of a Real-Time Smart Home Management System Considering Energy Saving," Sustainability, MDPI, vol. 14(21), pages 1-22, October.
    8. Adnan Ahmad & Asif Khan & Nadeem Javaid & Hafiz Majid Hussain & Wadood Abdul & Ahmad Almogren & Atif Alamri & Iftikhar Azim Niaz, 2017. "An Optimized Home Energy Management System with Integrated Renewable Energy and Storage Resources," Energies, MDPI, vol. 10(4), pages 1-35, April.
    9. Syed Ali Abbas Kazmi & Muhammad Khuram Shahzad & Akif Zia Khan & Dong Ryeol Shin, 2017. "Smart Distribution Networks: A Review of Modern Distribution Concepts from a Planning Perspective," Energies, MDPI, vol. 10(4), pages 1-47, April.
    10. Dufo-López, Rodolfo, 2015. "Optimisation of size and control of grid-connected storage under real time electricity pricing conditions," Applied Energy, Elsevier, vol. 140(C), pages 395-408.
    11. Andrzej Ożadowicz, 2017. "A New Concept of Active Demand Side Management for Energy Efficient Prosumer Microgrids with Smart Building Technologies," Energies, MDPI, vol. 10(11), pages 1-22, November.
    12. 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.
    13. Muhammad Awais & Nadeem Javaid & Khursheed Aurangzeb & Syed Irtaza Haider & Zahoor Ali Khan & Danish Mahmood, 2018. "Towards Effective and Efficient Energy Management of Single Home and a Smart Community Exploiting Heuristic Optimization Algorithms with Critical Peak and Real-Time Pricing Tariffs in Smart Grids," Energies, MDPI, vol. 11(11), pages 1-30, November.
    14. Alvaro Llaria & Jessye Dos Santos & Guillaume Terrasson & Zina Boussaada & Christophe Merlo & Octavian Curea, 2021. "Intelligent Buildings in Smart Grids: A Survey on Security and Privacy Issues Related to Energy Management," Energies, MDPI, vol. 14(9), pages 1-37, May.
    15. Khalid, Muhammad & Ahmadi, Abdollah & Savkin, Andrey V. & Agelidis, Vassilios G., 2016. "Minimizing the energy cost for microgrids integrated with renewable energy resources and conventional generation using controlled battery energy storage," Renewable Energy, Elsevier, vol. 97(C), pages 646-655.
    16. Patil, Vikas R. & Biradar, Vijay Irappa & Shreyas, R. & Garg, Pardeep & Orosz, Matthew S. & Thirumalai, N.C., 2017. "Techno-economic comparison of solar organic Rankine cycle (ORC) and photovoltaic (PV) systems with energy storage," Renewable Energy, Elsevier, vol. 113(C), pages 1250-1260.
    17. Natarajan, Anisha & Krishnasamy, Vijayakumar & Singh, Munesh, 2022. "Occupancy detection and localization strategies for demand modulated appliance control in Internet of Things enabled home energy management system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(C).
    18. Nan, Sibo & Zhou, Ming & Li, Gengyin, 2018. "Optimal residential community demand response scheduling in smart grid," Applied Energy, Elsevier, vol. 210(C), pages 1280-1289.
    19. Graditi, G. & Ippolito, M.G. & Telaretti, E. & Zizzo, G., 2016. "Technical and economical assessment of distributed electrochemical storages for load shifting applications: An Italian case study," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 515-523.
    20. Gao, Zhikun & Yu, Junqi & Zhao, Anjun & Hu, Qun & Yang, Siyuan, 2022. "A hybrid method of cooling load forecasting for large commercial building based on extreme learning machine," Energy, Elsevier, vol. 238(PC).

    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:10:y:2017:i:3:p:335-:d:92658. 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.