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Optimal scheduling of electrical and thermal resources and appliances in a smart home under uncertainty

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  • Ghayour, Sepideh Saravani
  • Barforoushi, Taghi

Abstract

The development of renewable energy sources, using the Combined Heat and Power (CHP), along with controllable appliances, has provided new opportunities for scheduling resources and consumption in smart homes. This paper proposes a framework for the optimal scheduling of electrical appliances and sources of electricity and heat in a smart home. The smart home is able to purchase electricity through bilateral contracts and spot market. Real-Time Pricing (RTP) and Inclining Block Rate (IBR) tariffs are considered in the spot market. Uncertainties related to production of renewable resources, spot market prices and usage time of inelastic non-shiftable appliances are modeled by scenarios. The presented framework is modeled as a two-stage stochastic optimization problem, with the aim of minimizing the expected cost of the smart home. Then, the problem is formulated in the form of MILP problem. The simulation results showed that the cogeneration of electricity and heat significantly reduced the expected cost of the smart home by 125% compared to the base case study. Meanwhile, the Peak to Average Ratio index (PAR) due to the distribution of consumption along the scheduling horizon has decreased by 35% compared to the base case study.

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  • Ghayour, Sepideh Saravani & Barforoushi, Taghi, 2022. "Optimal scheduling of electrical and thermal resources and appliances in a smart home under uncertainty," Energy, Elsevier, vol. 261(PA).
  • Handle: RePEc:eee:energy:v:261:y:2022:i:pa:s0360544222021764
    DOI: 10.1016/j.energy.2022.125292
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    References listed on IDEAS

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    1. Thomas, Dimitrios & Deblecker, Olivier & Ioakimidis, Christos S., 2018. "Optimal operation of an energy management system for a grid-connected smart building considering photovoltaics’ uncertainty and stochastic electric vehicles’ driving schedule," Applied Energy, Elsevier, vol. 210(C), pages 1188-1206.
    2. Shirazi, Elham & Jadid, Shahram, 2017. "Cost reduction and peak shaving through domestic load shifting and DERs," Energy, Elsevier, vol. 124(C), pages 146-159.
    3. Rakipour, Davood & Barati, Hassan, 2019. "Probabilistic optimization in operation of energy hub with participation of renewable energy resources and demand response," Energy, Elsevier, vol. 173(C), pages 384-399.
    4. Kriett, Phillip Oliver & Salani, Matteo, 2012. "Optimal control of a residential microgrid," Energy, Elsevier, vol. 42(1), pages 321-330.
    5. Ghaffarpour, Reza & Mozafari, Babak & Ranjbar, Ali Mohammad & Torabi, Taghi, 2018. "Resilience oriented water and energy hub scheduling considering maintenance constraint," Energy, Elsevier, vol. 158(C), pages 1092-1104.
    6. Dini, Anoosh & Pirouzi, Sasan & Norouzi, Mohammadali & Lehtonen, Matti, 2019. "Grid-connected energy hubs in the coordinated multi-energy management based on day-ahead market framework," Energy, Elsevier, vol. 188(C).
    7. 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).
    8. Mohammadi Rad, Amin & Barforoushi, Taghi, 2020. "Optimal scheduling of resources and appliances in smart homes under uncertainties considering participation in spot and contractual markets," Energy, Elsevier, vol. 192(C).
    9. Jadidbonab, Mohammad & Babaei, Ebrahim & Mohammadi-ivatloo, Behnam, 2019. "CVaR-constrained scheduling strategy for smart multi carrier energy hub considering demand response and compressed air energy storage," Energy, Elsevier, vol. 174(C), pages 1238-1250.
    10. Muhammad Kashif Rafique & Zunaib Maqsood Haider & Khawaja Khalid Mehmood & Muhammad Saeed Uz Zaman & Muhammad Irfan & Saad Ullah Khan & Chul-Hwan Kim, 2018. "Optimal Scheduling of Hybrid Energy Resources for a Smart Home," Energies, MDPI, vol. 11(11), pages 1-19, November.
    11. Bianchi, Michele & De Pascale, Andrea & Spina, Pier Ruggero, 2012. "Guidelines for residential micro-CHP systems design," Applied Energy, Elsevier, vol. 97(C), pages 673-685.
    12. Yahia, Z. & Pradhan, A., 2018. "Optimal load scheduling of household appliances considering consumer preferences: An experimental analysis," Energy, Elsevier, vol. 163(C), pages 15-26.
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