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Multi-objective optimisation and planning of grid-connected cogeneration systems in presence of grid power fluctuations and energy storage dynamics

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  • Garmabdari, R.
  • Moghimi, M.
  • Yang, F.
  • Lu, J.

Abstract

In recent years, multi-generation systems (MGS) have been at the centre of attention for incorporating various energy sources and technologies to provide a reliable and sustainable energy supply. However, deciding on the most suitable configuration and optimal operation strategy of MGSs has always been a challenging issue due to the nonlinear and complex interactions between different energy converters. Cogeneration solutions offer excellent energy efficiency through the coproduced heat from the electricity generation process. This will lead to significant economic profitability compared to conventional independent heat and power production plants. This paper presents a mixed-integer quadratic based multi-objective structural design strategy for grid-connected cogeneration systems comprising combined heat and power (CHP) devices, ancillary boiler, and energy storage devices in presence of nonlinear and dynamic behaviour of the energy storage systems. The power fluctuations smoothing index (PFSI) and energy storage depreciation factor (ESDF) are defined to effectively mitigate the power grid fluctuations and extend the lifetime of the energy storage systems. Presenting three case scenarios, the obtained results demonstrate the efficacy and applicability of the developed technique and reflect the impact of the introduced factors on the optimal configuration and operation of cogeneration systems.

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  • Garmabdari, R. & Moghimi, M. & Yang, F. & Lu, J., 2020. "Multi-objective optimisation and planning of grid-connected cogeneration systems in presence of grid power fluctuations and energy storage dynamics," Energy, Elsevier, vol. 212(C).
  • Handle: RePEc:eee:energy:v:212:y:2020:i:c:s0360544220316972
    DOI: 10.1016/j.energy.2020.118589
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    References listed on IDEAS

    as
    1. Mancarella, Pierluigi, 2014. "MES (multi-energy systems): An overview of concepts and evaluation models," Energy, Elsevier, vol. 65(C), pages 1-17.
    2. Catalina, Tiberiu & Virgone, Joseph & Blanco, Eric, 2011. "Multi-source energy systems analysis using a multi-criteria decision aid methodology," Renewable Energy, Elsevier, vol. 36(8), pages 2245-2252.
    3. Morvaj, Boran & Evins, Ralph & Carmeliet, Jan, 2016. "Optimization framework for distributed energy systems with integrated electrical grid constraints," Applied Energy, Elsevier, vol. 171(C), pages 296-313.
    4. Vahid Amir & Shahram Jadid & Mehdi Ehsan, 2017. "Optimal Design of a Multi-Carrier Microgrid (MCMG) Considering Net Zero Emission," Energies, MDPI, vol. 10(12), pages 1-22, December.
    5. SoltaniNejad Farsangi, Alireza & Hadayeghparast, Shahrzad & Mehdinejad, Mehdi & Shayanfar, Heidarali, 2018. "A novel stochastic energy management of a microgrid with various types of distributed energy resources in presence of demand response programs," Energy, Elsevier, vol. 160(C), pages 257-274.
    6. Yang, Hongming & Xiong, Tonglin & Qiu, Jing & Qiu, Duo & Dong, Zhao Yang, 2016. "Optimal operation of DES/CCHP based regional multi-energy prosumer with demand response," Applied Energy, Elsevier, vol. 167(C), pages 353-365.
    7. Bianchi, M. & De Pascale, A. & Melino, F., 2013. "Performance analysis of an integrated CHP system with thermal and Electric Energy Storage for residential application," Applied Energy, Elsevier, vol. 112(C), pages 928-938.
    8. Mohammadi, Mohammad & Noorollahi, Younes & Mohammadi-ivatloo, Behnam & Yousefi, Hossein, 2017. "Energy hub: From a model to a concept – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 80(C), pages 1512-1527.
    9. Moghaddam, Iman Gerami & Saniei, Mohsen & Mashhour, Elaheh, 2016. "A comprehensive model for self-scheduling an energy hub to supply cooling, heating and electrical demands of a building," Energy, Elsevier, vol. 94(C), pages 157-170.
    10. Orehounig, Kristina & Evins, Ralph & Dorer, Viktor, 2015. "Integration of decentralized energy systems in neighbourhoods using the energy hub approach," Applied Energy, Elsevier, vol. 154(C), pages 277-289.
    11. 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.
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