IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v11y2018i11p3125-d182278.html
   My bibliography  Save this article

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

Author

Listed:
  • Muhammad Awais

    (Department of Computer Sciences, COMSATS University Islamabad, Islamabad 44000, Pakistan)

  • Nadeem Javaid

    (Department of Computer Sciences, COMSATS University Islamabad, Islamabad 44000, Pakistan)

  • Khursheed Aurangzeb

    (College of Computer and Information Sciences, King Saud University, Riyadh 11543, Saudi Arabia)

  • Syed Irtaza Haider

    (College of Computer and Information Sciences, King Saud University, Riyadh 11543, Saudi Arabia)

  • Zahoor Ali Khan

    (Computer Information Science, Higher Colleges of Technology, Fujairah 4114, UAE)

  • Danish Mahmood

    (Shaheed Zulfikar Ali Bhutto Institute of Science and Technology, Islamabad 44000, Pakistan)

Abstract

Nowadays, automated appliances are exponentially increasing. Therefore, there is a need for a scheme to accomplish the electricity demand of automated appliances. Recently, many Demand Side Management (DSM) schemes have been explored to alleviate Electricity Cost (EC) and Peak to Average Ratio (PAR). In this paper, energy consumption problem in a residential area is considered. To solve this problem, a heuristic based DSM technique is proposed to minimize EC and PAR with affordable user’s Waiting Time (WT). In heuristic techniques: Bacterial Foraging Optimization Algorithm (BFOA) and Flower Pollination Algorithm (FPA) are implemented. Furthermore, a novel heuristic algorithm has been proposed by merging the best features of the aforementioned existing algorithms. We test the proposed scheme on single homes and on smart community (involving multiple households). Different Operational Time Intervals (OTIs) are also considered for implementation. We have performed simulations for validating the our scheme. Results clearly demonstrate that the proposed Hybrid Bacterial Flower Pollination Algorithm (HBFPA) shows efficacy for EC and for reduction of PAR with reasonable user WT.

Suggested Citation

  • 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.
  • Handle: RePEc:gam:jeners:v:11:y:2018:i:11:p:3125-:d:182278
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/11/11/3125/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/11/11/3125/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Sheraz Aslam & Zafar Iqbal & Nadeem Javaid & Zahoor Ali Khan & Khursheed Aurangzeb & Syed Irtaza Haider, 2017. "Towards Efficient Energy Management of Smart Buildings Exploiting Heuristic Optimization with Real Time and Critical Peak Pricing Schemes," Energies, MDPI, vol. 10(12), pages 1-25, December.
    2. Kakran, Sandeep & Chanana, Saurabh, 2018. "Smart operations of smart grids integrated with distributed generation: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 524-535.
    3. Zafar Iqbal & Nadeem Javaid & Saleem Iqbal & Sheraz Aslam & Zahoor Ali Khan & Wadood Abdul & Ahmad Almogren & Atif Alamri, 2018. "A Domestic Microgrid with Optimized Home Energy Management System," Energies, MDPI, vol. 11(4), pages 1-39, April.
    4. 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.
    5. 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.
    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. Li, Yuanyuan & Li, Junxiang & He, Jianjia & Zhang, Shuyuan, 2021. "The real-time pricing optimization model of smart grid based on the utility function of the logistic function," Energy, Elsevier, vol. 224(C).
    2. Ouédraogo, S. & Faggianelli, G.A. & Notton, G. & Duchaud, J.L. & Voyant, C., 2022. "Impact of electricity tariffs and energy management strategies on PV/Battery microgrid performances," Renewable Energy, Elsevier, vol. 199(C), pages 816-825.
    3. Fahad Alsokhiry & Pierluigi Siano & Andres Annuk & Mohamed A. Mohamed, 2022. "A Novel Time-of-Use Pricing Based Energy Management System for Smart Home Appliances: Cost-Effective Method," Sustainability, MDPI, vol. 14(21), pages 1-20, November.
    4. Pergantis, Elias N. & Reyes Premer, Levi D. & Lee, Alex H. & Priyadarshan, & Liu, Haotian & Groll, Eckhard A. & Ziviani, Davide & Kircher, Kevin J., 2025. "Protecting residential electrical panels and service through model predictive control: A field study," Applied Energy, Elsevier, vol. 386(C).
    5. Makhadmeh, Sharif Naser & Khader, Ahamad Tajudin & Al-Betar, Mohammed Azmi & Naim, Syibrah & Abasi, Ammar Kamal & Alyasseri, Zaid Abdi Alkareem, 2019. "Optimization methods for power scheduling problems in smart home: Survey," Renewable and Sustainable Energy Reviews, Elsevier, vol. 115(C).
    6. Miltiadis D. Lytras & Kwok Tai Chui, 2019. "The Recent Development of Artificial Intelligence for Smart and Sustainable Energy Systems and Applications," Energies, MDPI, vol. 12(16), pages 1-7, August.
    7. Tri-Hai Nguyen & Luong Vuong Nguyen & Jason J. Jung & Israel Edem Agbehadji & Samuel Ofori Frimpong & Richard C. Millham, 2020. "Bio-Inspired Approaches for Smart Energy Management: State of the Art and Challenges," Sustainability, MDPI, vol. 12(20), pages 1-24, October.
    8. 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.
    9. Wang, Guotao & Zhou, Yifan & Lin, Zhenjia & Zhu, Shibo & Qiu, Rui & Chen, Yuntian & Yan, Jinyue, 2024. "Robust energy management through aggregation of flexible resources in multi-home micro energy hub," Applied Energy, Elsevier, vol. 357(C).
    10. 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.

    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. 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.
    2. Zafar Iqbal & Nadeem Javaid & Syed Muhammad Mohsin & Syed Muhammad Abrar Akber & Muhammad Khalil Afzal & Farruh Ishmanov, 2018. "Performance Analysis of Hybridization of Heuristic Techniques for Residential Load Scheduling," Energies, MDPI, vol. 11(10), pages 1-31, October.
    3. Tri-Hai Nguyen & Luong Vuong Nguyen & Jason J. Jung & Israel Edem Agbehadji & Samuel Ofori Frimpong & Richard C. Millham, 2020. "Bio-Inspired Approaches for Smart Energy Management: State of the Art and Challenges," Sustainability, MDPI, vol. 12(20), pages 1-24, October.
    4. Hafiz Majid Hussain & Nadeem Javaid & Sohail Iqbal & Qadeer Ul Hasan & Khursheed Aurangzeb & Musaed Alhussein, 2018. "An Efficient Demand Side Management System with a New Optimized Home Energy Management Controller in Smart Grid," Energies, MDPI, vol. 11(1), pages 1-28, January.
    5. 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.
    6. Wadim Strielkowski & Dalia Streimikiene & Alena Fomina & Elena Semenova, 2019. "Internet of Energy (IoE) and High-Renewables Electricity System Market Design," Energies, MDPI, vol. 12(24), pages 1-17, December.
    7. Roth, Jonathan & Martin, Amory & Miller, Clayton & Jain, Rishee K., 2020. "SynCity: Using open data to create a synthetic city of hourly building energy estimates by integrating data-driven and physics-based methods," Applied Energy, Elsevier, vol. 280(C).
    8. Hafezi, Reza & Akhavan, AmirNaser & Pakseresht, Saeed & Wood, David A., 2019. "A Layered Uncertainties Scenario Synthesizing (LUSS) model applied to evaluate multiple potential long-run outcomes for Iran's natural gas exports," Energy, Elsevier, vol. 169(C), pages 646-659.
    9. Hafiz Abdul Muqeet & Rehan Liaqat & Mohsin Jamil & Asharf Ali Khan, 2023. "A State-of-the-Art Review of Smart Energy Systems and Their Management in a Smart Grid Environment," Energies, MDPI, vol. 16(1), pages 1-23, January.
    10. Amro M Elshurafa & Abdel Rahman Muhsen, 2019. "The Upper Limit of Distributed Solar PV Capacity in Riyadh: A GIS-Assisted Study," Sustainability, MDPI, vol. 11(16), pages 1-20, August.
    11. Chibuike Chiedozie Ibebuchi, 2025. "Day-Ahead Energy Price Forecasting with Machine Learning: Role of Endogenous Predictors," Forecasting, MDPI, vol. 7(2), pages 1-16, April.
    12. Rezaei, Navid & Pezhmani, Yasin & Khazali, Amirhossein, 2022. "Economic-environmental risk-averse optimal heat and power energy management of a grid-connected multi microgrid system considering demand response and bidding strategy," Energy, Elsevier, vol. 240(C).
    13. Walzberg, Julien & Dandres, Thomas & Merveille, Nicolas & Cheriet, Mohamed & Samson, Réjean, 2020. "Should we fear the rebound effect in smart homes?," Renewable and Sustainable Energy Reviews, Elsevier, vol. 125(C).
    14. Sivakavi Naga Venkata Bramareswara Rao & Yellapragada Venkata Pavan Kumar & Darsy John Pradeep & Challa Pradeep Reddy & Aymen Flah & Habib Kraiem & Jawad F. Al-Asad, 2022. "Power Quality Improvement in Renewable-Energy-Based Microgrid Clusters Using Fuzzy Space Vector PWM Controlled Inverter," Sustainability, MDPI, vol. 14(8), pages 1-20, April.
    15. Xiaolin Ayón & María Ángeles Moreno & Julio Usaola, 2017. "Aggregators’ Optimal Bidding Strategy in Sequential Day-Ahead and Intraday Electricity Spot Markets," Energies, MDPI, vol. 10(4), pages 1-20, April.
    16. Jayesh Thaker & Robert Höller, 2022. "A Comparative Study of Time Series Forecasting of Solar Energy Based on Irradiance Classification," Energies, MDPI, vol. 15(8), pages 1-26, April.
    17. Shengli Du & Mingchao Li & Shuai Han & Jonathan Shi & Heng Li, 2019. "Multi-Pattern Data Mining and Recognition of Primary Electric Appliances from Single Non-Intrusive Load Monitoring Data," Energies, MDPI, vol. 12(6), pages 1-20, March.
    18. José Adriano da Costa & David Alves Castelo Branco & Max Chianca Pimentel Filho & Manoel Firmino de Medeiros Júnior & Neilton Fidelis da Silva, 2019. "Optimal Sizing of Photovoltaic Generation in Radial Distribution Systems Using Lagrange Multipliers," Energies, MDPI, vol. 12(9), pages 1-19, May.
    19. Kalim Ullah & Sajjad Ali & Taimoor Ahmad Khan & Imran Khan & Sadaqat Jan & Ibrar Ali Shah & Ghulam Hafeez, 2020. "An Optimal Energy Optimization Strategy for Smart Grid Integrated with Renewable Energy Sources and Demand Response Programs," Energies, MDPI, vol. 13(21), pages 1-17, November.
    20. Seongwoo Lee & Joonho Seon & Byungsun Hwang & Soohyun Kim & Youngghyu Sun & Jinyoung Kim, 2024. "Recent Trends and Issues of Energy Management Systems Using Machine Learning," Energies, MDPI, vol. 17(3), pages 1-24, January.

    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:11:y:2018:i:11:p:3125-:d:182278. 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.