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A relaxed constrained decentralised demand side management system of a community-based residential microgrid with realistic appliance models

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  • Morsali, Roozbeh
  • Thirunavukkarasu, Gokul Sidarth
  • Seyedmahmoudian, Mehdi
  • Stojcevski, Alex
  • Kowalczyk, Ryszard

Abstract

Reducing the environmental impacts caused by conventional power sources in smart grids, achieving socio-economic sustainability, and effectively addressing the rapidly increasing energy demand are some of the critical characteristics of demand-side management systems. In this paper, a multi-agent-based decentralised relaxed-constrained energy management strategy for a community-based residential microgrid system using demand-side management is presented. The proposed demand-side management system controls the creative decision-making process of the residential customer agents interconnected within the proposed residential microgrid system. The main objectives of the proposed demand-side management controllers are to make decisions that reduce the peak demand of the load to each agent and to reshape the profile of the power load based on their energy consumption pattern. In addition to this, the novel realistic appliance models with discrete operational levels and on–off capabilities proposed in this research makes the optimisation process a non-convex mixed-integer problem. The proposed decentralised optimisation scheme addressed this issue, by initially relaxing the constraints on the appliances and then using the gradient descent algorithm to decompose and solve the realistic schedules for the devices in the scheduling period. Results indicated that the proposed decentralised relaxed constrain approach is more feasible, effective, economical and efficient in addressing the energy management problem of a residential community microgrid.

Suggested Citation

  • Morsali, Roozbeh & Thirunavukkarasu, Gokul Sidarth & Seyedmahmoudian, Mehdi & Stojcevski, Alex & Kowalczyk, Ryszard, 2020. "A relaxed constrained decentralised demand side management system of a community-based residential microgrid with realistic appliance models," Applied Energy, Elsevier, vol. 277(C).
  • Handle: RePEc:eee:appene:v:277:y:2020:i:c:s0306261920311284
    DOI: 10.1016/j.apenergy.2020.115626
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    References listed on IDEAS

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    1. Fatih Issi & Orhan Kaplan, 2018. "The Determination of Load Profiles and Power Consumptions of Home Appliances," Energies, MDPI, vol. 11(3), pages 1-18, March.
    2. Hannan, M.A. & Hoque, M.M. & Mohamed, A. & Ayob, A., 2017. "Review of energy storage systems for electric vehicle applications: Issues and challenges," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 771-789.
    3. 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.
    4. Haider, Haider Tarish & See, Ong Hang & Elmenreich, Wilfried, 2016. "A review of residential demand response of smart grid," Renewable and Sustainable Energy Reviews, Elsevier, vol. 59(C), pages 166-178.
    5. VanDeventer, William & Jamei, Elmira & Thirunavukkarasu, Gokul Sidarth & Seyedmahmoudian, Mehdi & Soon, Tey Kok & Horan, Ben & Mekhilef, Saad & Stojcevski, Alex, 2019. "Short-term PV power forecasting using hybrid GASVM technique," Renewable Energy, Elsevier, vol. 140(C), pages 367-379.
    6. Mehdi Seyedmahmoudian & Tey Kok Soon & Elmira Jamei & Gokul Sidarth Thirunavukkarasu & Ben Horan & Saad Mekhilef & Alex Stojcevski, 2018. "Maximum Power Point Tracking for Photovoltaic Systems under Partial Shading Conditions Using Bat Algorithm," Sustainability, MDPI, vol. 10(5), pages 1-16, April.
    7. Meng, Lexuan & Sanseverino, Eleonora Riva & Luna, Adriana & Dragicevic, Tomislav & Vasquez, Juan C. & Guerrero, Josep M., 2016. "Microgrid supervisory controllers and energy management systems: A literature review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 60(C), pages 1263-1273.
    8. Khan, Ahsan Raza & Mahmood, Anzar & Safdar, Awais & Khan, Zafar A. & Khan, Naveed Ahmed, 2016. "Load forecasting, dynamic pricing and DSM in smart grid: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 54(C), pages 1311-1322.
    9. Raza, Muhammad Qamar & Khosravi, Abbas, 2015. "A review on artificial intelligence based load demand forecasting techniques for smart grid and buildings," Renewable and Sustainable Energy Reviews, Elsevier, vol. 50(C), pages 1352-1372.
    10. Mehdi Seyedmahmoudian & Elmira Jamei & Gokul Sidarth Thirunavukkarasu & Tey Kok Soon & Michael Mortimer & Ben Horan & Alex Stojcevski & Saad Mekhilef, 2018. "Short-Term Forecasting of the Output Power of a Building-Integrated Photovoltaic System Using a Metaheuristic Approach," Energies, MDPI, vol. 11(5), pages 1-23, May.
    11. Zhao, Bo & Xue, Meidong & Zhang, Xuesong & Wang, Caisheng & Zhao, Junhui, 2015. "An MAS based energy management system for a stand-alone microgrid at high altitude," Applied Energy, Elsevier, vol. 143(C), pages 251-261.
    12. Tabar, Vahid Sohrabi & Jirdehi, Mehdi Ahmadi & Hemmati, Reza, 2017. "Energy management in microgrid based on the multi objective stochastic programming incorporating portable renewable energy resource as demand response option," Energy, Elsevier, vol. 118(C), pages 827-839.
    13. Harrison, Gillian & Thiel, Christian, 2017. "An exploratory policy analysis of electric vehicle sales competition and sensitivity to infrastructure in Europe," Technological Forecasting and Social Change, Elsevier, vol. 114(C), pages 165-178.
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    Cited by:

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    2. Minkyu Kim & Chankook Park, 2021. "Academic Topics Related to Household Energy Consumption Using the Future Sign Detection Technique," Energies, MDPI, vol. 14(24), pages 1-24, December.
    3. Misconel, Steffi & Zöphel, Christoph & Möst, Dominik, 2021. "Assessing the value of demand response in a decarbonized energy system – A large-scale model application," Applied Energy, Elsevier, vol. 299(C).
    4. Inês F. G. Reis & Ivo Gonçalves & Marta A. R. Lopes & Carlos Henggeler Antunes, 2021. "Assessing the Influence of Different Goals in Energy Communities’ Self-Sufficiency—An Optimized Multiagent Approach," Energies, MDPI, vol. 14(4), pages 1-32, February.
    5. Seshu Kumar, R. & Phani Raghav, L. & Koteswara Raju, D. & Singh, Arvind R., 2021. "Impact of multiple demand side management programs on the optimal operation of grid-connected microgrids," Applied Energy, Elsevier, vol. 301(C).

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