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An interval optimization strategy of household multi-energy system considering tolerance degree and integrated demand response

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  • Su, Yongxin
  • Zhou, Yao
  • Tan, Mao

Abstract

Under the background of the popularity of household gas-electric equipment, an interval optimization method considering the Integrated Demand Response (IDR) and tolerance degree is proposed to deal with the household load scheduling. The proposed method mainly tackles the dynamic switching of energy forms (natural gas and electricity) and uncertain variables in the system caused by household load and photovoltaic (PV). The thermostatically controllable loads contain gas-electric heater and air conditioning, and the interruptible loads contain gas-electric kitchen stove and clothes washer. An interval optimization model is formulated to optimize the operation cost and emissions of a household multi-energy system. The uncertain parameters are modeled as interval numbers, and the constraints are relaxed by tolerance degree. To solve the equation, the interval optimization model is transformed into a deterministic optimization model based on the interval order relation and interval possibility degree. Then, Genetic Algorithm is applied to solve the deterministic optimization model. Simulation results indicate that interval optimization is robust to the uncertainties and flexible to meet users’ demands. Both IDR and tolerance degree are able to optimize users’ energy cost, and the optimization results are accumulative. For a gas-electric equipment installed home, the proposed method can reduce expenditures by up to 23.4% compared with traditional method that do not consider IDR, tolerance degree and interval optimization.

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  • Su, Yongxin & Zhou, Yao & Tan, Mao, 2020. "An interval optimization strategy of household multi-energy system considering tolerance degree and integrated demand response," Applied Energy, Elsevier, vol. 260(C).
    • Handle: RePEc:eee:appene:v:260:y:2020:i:c:s0306261919318318
    DOI: 10.1016/j.apenergy.2019.114144
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    1. Barukčić, M. & Hederić, Ž. & Hadžiselimović, M. & Seme, S., 2018. "A simple stochastic method for modelling the uncertainty of photovoltaic power production based on measured data," Energy, Elsevier, vol. 165(PB), pages 246-256.
    2. Mazhar, Abdur Rehman & Liu, Shuli & Shukla, Ashish, 2018. "A state of art review on the district heating systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 96(C), pages 420-439.
    3. Fabrizio, Enrico & Corrado, Vincenzo & Filippi, Marco, 2010. "A model to design and optimize multi-energy systems in buildings at the design concept stage," Renewable Energy, Elsevier, vol. 35(3), pages 644-655.
    4. Muhammad Babar Rasheed & Nadeem Javaid & Ashfaq Ahmad & Mohsin Jamil & Zahoor Ali Khan & Umar Qasim & Nabil Alrajeh, 2016. "Energy Optimization in Smart Homes Using Customer Preference and Dynamic Pricing," Energies, MDPI, vol. 9(8), pages 1-25, July.
    5. Fontenot, Hannah & Dong, Bing, 2019. "Modeling and control of building-integrated microgrids for optimal energy management – A review," Applied Energy, Elsevier, vol. 254(C).
    6. 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).
    7. Mehrjerdi, Hasan & Bornapour, Mosayeb & Hemmati, Reza & Ghiasi, Seyyed Mohammad Sadegh, 2019. "Unified energy management and load control in building equipped with wind-solar-battery incorporating electric and hydrogen vehicles under both connected to the grid and islanding modes," Energy, Elsevier, vol. 168(C), pages 919-930.
    8. Ogunjuyigbe, A.S.O. & Ayodele, T.R. & Akinola, O.A., 2017. "User satisfaction-induced demand side load management in residential buildings with user budget constraint," Applied Energy, Elsevier, vol. 187(C), pages 352-366.
    9. Jiang, C. & Han, X. & Liu, G.R. & Liu, G.P., 2008. "A nonlinear interval number programming method for uncertain optimization problems," European Journal of Operational Research, Elsevier, vol. 188(1), pages 1-13, July.
    10. Sengupta, Atanu & Pal, Tapan Kumar, 2000. "On comparing interval numbers," European Journal of Operational Research, Elsevier, vol. 127(1), pages 28-43, November.
    11. Jin, Ming & Feng, Wei & Marnay, Chris & Spanos, Costas, 2018. "Microgrid to enable optimal distributed energy retail and end-user demand response," Applied Energy, Elsevier, vol. 210(C), pages 1321-1335.
    12. Anvari-Moghaddam, Amjad & Rahimi-Kian, Ashkan & Mirian, Maryam S. & Guerrero, Josep M., 2017. "A multi-agent based energy management solution for integrated buildings and microgrid system," Applied Energy, Elsevier, vol. 203(C), pages 41-56.
    13. Jin, Xin & Baker, Kyri & Christensen, Dane & Isley, Steven, 2017. "Foresee: A user-centric home energy management system for energy efficiency and demand response," Applied Energy, Elsevier, vol. 205(C), pages 1583-1595.
    14. Bai, Linquan & Li, Fangxing & Cui, Hantao & Jiang, Tao & Sun, Hongbin & Zhu, Jinxiang, 2016. "Interval optimization based operating strategy for gas-electricity integrated energy systems considering demand response and wind uncertainty," Applied Energy, Elsevier, vol. 167(C), pages 270-279.
    15. Adefarati, T. & Bansal, R.C., 2019. "Reliability, economic and environmental analysis of a microgrid system in the presence of renewable energy resources," Applied Energy, Elsevier, vol. 236(C), pages 1089-1114.
    16. Liu, Peiyun & Ding, Tao & Zou, Zhixiang & Yang, Yongheng, 2019. "Integrated demand response for a load serving entity in multi-energy market considering network constraints," Applied Energy, Elsevier, vol. 250(C), pages 512-529.
    17. Simpson, Michael C. & Chatzopoulou, Maria Anna & Oyewunmi, Oyeniyi A. & Le Brun, Niccolo & Sapin, Paul & Markides, Christos N., 2019. "Technoeconomic analysis of internal combustion engine – organic Rankine cycle systems for combined heat and power in energy-intensive buildings," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    18. Miller, Reid & Golab, Lukasz & Rosenberg, Catherine, 2017. "Modelling weather effects for impact analysis of residential time-of-use electricity pricing," Energy Policy, Elsevier, vol. 105(C), pages 534-546.
    Full references (including those not matched with items on IDEAS)

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