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Optimum planning of energy hub with participation in electricity market and heat markets and application of integrated load response program with improved particle swarm algorithm

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  • Liao, Zitian
  • Liao, Xiaoqun
  • Khakichi, Aroos

Abstract

The drive for improved energy efficiency and flexibility has birthed an innovative solution: an energy hub. This hub operates in sync with natural gas and electricity grids, integrating batteries and thermal storage to optimize renewable energy use, reduce costs, and bolster network stability. In addressing these objectives, a mathematical optimization model for energy hub operation is developed in this paper. This model captures the intricate interplays between electricity and natural gas networks, accounting for the intricacies posed by uncertainties and variations in renewable energy sources and demand profiles. Also, this paper uniquely delves into the integration of load response programs, an approach geared towards amplifying the energy hub system's flexibility and reliability. Through these programs, subscribers gain the agency to calibrate their energy consumption based on real-time pricing signals and incentives dispensed by the energy hub. The simulation findings serve as a compelling testament to the efficacy of the proposed system. Operating costs witness a substantial reduction, the adoption of renewable energy sources is markedly heightened, and the stability and reliability of the upstream energy networks are tangibly ameliorated. The integration of load response programs emerges as a particularly effective strategy in mitigating peak demand and augmenting the system's overall energy efficiency. Underpinning the entirety of this innovative solution is the transformation of the challenges into an optimization problem. This catalyzes the employment of a newly developed particle community algorithm, custom-tailored to surmount the challenges of local optima. This algorithm inherently bolsters the system's search capabilities, minimizing the risk of entrapment within localized solutions. Ultimately, the proposed energy hub system encapsulates a promising trajectory toward the realization of a sustainable and adaptable energy landscape. By seamlessly integrating diverse energy sources and storage systems, augmenting energy flexibility and efficiency, and aligning with broader energy transition and decarbonization goals, this solution presents a formidable contender. The simulation outcomes underscore its potential by showcasing a substantial 4.57 % reduction in the cost of procuring energy from the upstream electrical network.

Suggested Citation

  • Liao, Zitian & Liao, Xiaoqun & Khakichi, Aroos, 2024. "Optimum planning of energy hub with participation in electricity market and heat markets and application of integrated load response program with improved particle swarm algorithm," Energy, Elsevier, vol. 286(C).
  • Handle: RePEc:eee:energy:v:286:y:2024:i:c:s036054422302981x
    DOI: 10.1016/j.energy.2023.129587
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    References listed on IDEAS

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    1. Mahyar Lasemi Imeni & Mohammad Sadegh Ghazizadeh & Mohammad Ali Lasemi & Zhenyu Yang, 2023. "Optimal Scheduling of a Hydrogen-Based Energy Hub Considering a Stochastic Multi-Attribute Decision-Making Approach," Energies, MDPI, vol. 16(2), pages 1-23, January.
    2. Fan, Linyuan & Ji, Dandan & Lin, Geng & Lin, Peng & Liu, Lixi, 2023. "Information gap-based multi-objective optimization of a virtual energy hub plant considering a developed demand response model," Energy, Elsevier, vol. 276(C).
    3. Kamyab, Farhad & Bahrami, Shahab, 2016. "Efficient operation of energy hubs in time-of-use and dynamic pricing electricity markets," Energy, Elsevier, vol. 106(C), pages 343-355.
    4. Liu, Jiejie & Li, Yao & Ma, Yanan & Qin, Ruomu & Meng, Xianyang & Wu, Jiangtao, 2023. "Two-layer multiple scenario optimization framework for integrated energy system based on optimal energy contribution ratio strategy," Energy, Elsevier, vol. 285(C).
    5. Najafi, Arsalan & Falaghi, Hamid & Contreras, Javier & Ramezani, Maryam, 2016. "Medium-term energy hub management subject to electricity price and wind uncertainty," Applied Energy, Elsevier, vol. 168(C), pages 418-433.
    6. Davatgaran, Vahid & Saniei, Mohsen & Mortazavi, Seyed Saeidollah, 2018. "Optimal bidding strategy for an energy hub in energy market," Energy, Elsevier, vol. 148(C), pages 482-493.
    7. Ghappani, Seyyed Aliasghar & Karimi, Ali, 2023. "Optimal operation framework of an energy hub with combined heat, hydrogen, and power (CHHP) system based on ammonia," Energy, Elsevier, vol. 266(C).
    8. Bashiri Khouzestani, Leyla & Sheikh-El-Eslami, Mohammad Kazem & Salemi, Amir Hosein & Gerami Moghaddam, Iman, 2023. "Virtual smart energy Hub: A powerful tool for integrated multi energy systems operation," Energy, Elsevier, vol. 265(C).
    9. Foslie, Sverre Stefanussen & Knudsen, Brage Rugstad & Korpås, Magnus, 2023. "Integrated design and operational optimization of energy systems in dairies," Energy, Elsevier, vol. 281(C).
    10. Aghamohammadloo, Hossein & Talaeizadeh, Valiollah & Shahanaghi, Kamran & Aghaei, Jamshid & Shayanfar, Heidarali & Shafie-khah, Miadreza & Catalão, João P.S., 2021. "Integrated Demand Response programs and energy hubs retail energy market modelling," Energy, Elsevier, vol. 234(C).
    11. Sheikhi, Aras & Bahrami, Shahab & Ranjbar, Ali Mohammad, 2015. "An autonomous demand response program for electricity and natural gas networks in smart energy hubs," Energy, Elsevier, vol. 89(C), pages 490-499.
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