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Energy generation cost in multi-energy systems; an application to a non-merchant energy hub in supplying price responsive loads

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  • Aghamohamadi, Mehrdad
  • Samadi, Mahdi
  • Rahmati, Iman

Abstract

Integration of different energy carriers as well as the large scale energy storages and converters, allows the energy hubs (EH) to supply loads at a lower cost. This cost however can be conceptualized as the EH generation cost when playing the role of a generation unit. This reduction in EH generation cost can directly affect the behavior of the price responsive loads which enables the customers to maintain their benefit function. In this paper therefore, a new EH operation optimization model is proposed, which determines the optimum response of the responsive loads to the associated EH generation costs, in order to minimize the total operation cost of the EH as well as the customers’ payments. To this end, a general analytical framework is proposed to determine the EH generation cost per each energy type at the demand side. Also an integrated responsive load model is applied to simulate the responsive load modifications. This study demonstrates how the EH employment can reduce the energy prices at the demand side, and how this price reduction would change the responsiveness of elastic loads. Further, to evaluate the performance of the proposed model, a comprehensive case study has been conducted.

Suggested Citation

  • Aghamohamadi, Mehrdad & Samadi, Mahdi & Rahmati, Iman, 2018. "Energy generation cost in multi-energy systems; an application to a non-merchant energy hub in supplying price responsive loads," Energy, Elsevier, vol. 161(C), pages 878-891.
    • Handle: RePEc:eee:energy:v:161:y:2018:i:c:p:878-891
    DOI: 10.1016/j.energy.2018.07.144
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    Cited by:

    1. Mishra, Dillip Kumar & Ghadi, Mojtaba Jabbari & Azizivahed, Ali & Li, Li & Zhang, Jiangfeng, 2021. "A review on resilience studies in active distribution systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
    2. Alabi, Tobi Michael & Aghimien, Emmanuel I. & Agbajor, Favour D. & Yang, Zaiyue & Lu, Lin & Adeoye, Adebusola R. & Gopaluni, Bhushan, 2022. "A review on the integrated optimization techniques and machine learning approaches for modeling, prediction, and decision making on integrated energy systems," Renewable Energy, Elsevier, vol. 194(C), pages 822-849.
    3. Mostafavi Sani, Mostafa & Noorpoor, Alireza & Shafie-Pour Motlagh, Majid, 2019. "Optimal model development of energy hub to supply water, heating and electrical demands of a cement factory," Energy, Elsevier, vol. 177(C), pages 574-592.
    4. Zamani Gargari, Milad & Ghaffarpour, Reza, 2020. "Reliability evaluation of multi-carrier energy system with different level of demands under various weather situation," Energy, Elsevier, vol. 196(C).

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