IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v212y2020ics0360544220316972.html
   My bibliography  Save this article

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

Author

Listed:
  • 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.

Suggested Citation

  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544220316972
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2020.118589?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Chen, Jie & Huang, Shoujun & Shahabi, Laleh, 2021. "Economic and environmental operation of power systems including combined cooling, heating, power and energy storage resources using developed multi-objective grey wolf algorithm," Applied Energy, Elsevier, vol. 298(C).
    2. Alrobaian, Abdulrahman A. & Alsagri, Ali Sulaiman, 2023. "Multi-agent-based energy management for a fully electrified residential consumption," Energy, Elsevier, vol. 282(C).
    3. Mao, Jiachen & Jafari, Mehdi & Botterud, Audun, 2022. "Planning low-carbon distributed power systems: Evaluating the role of energy storage," Energy, Elsevier, vol. 238(PA).
    4. Cui, Jia & Zhang, Ximing & Liu, Wei & Yan, Xinyue & Hu, Zhen & Li, Chaoran & Huang, Jingbo, 2024. "A novel trading optimization strategy of source-load bilateral thermoelectric spot based on industrial parks interior," Energy, Elsevier, vol. 302(C).
    5. Manfren, Massimiliano & Nastasi, Benedetto & Tronchin, Lamberto & Groppi, Daniele & Garcia, Davide Astiaso, 2021. "Techno-economic analysis and energy modelling as a key enablers for smart energy services and technologies in buildings," Renewable and Sustainable Energy Reviews, Elsevier, vol. 150(C).
    6. Wu, Yaling & Liu, Zhongbing & Liu, Jiangyang & Xiao, Hui & Liu, Ruimiao & Zhang, Ling, 2022. "Optimal battery capacity of grid-connected PV-battery systems considering battery degradation," Renewable Energy, Elsevier, vol. 181(C), pages 10-23.
    7. Lin, Zhiyi & Song, Chunyue & Zhao, Jun & Yin, Huan, 2022. "Improved approximate dynamic programming for real-time economic dispatch of integrated microgrids," Energy, Elsevier, vol. 255(C).
    8. Pang, Xinfu & Wang, Yibao & Yu, Yang & Liu, Wei, 2024. "Optimal scheduling of a cogeneration system via Q-learning-based memetic algorithm considering demand-side response," Energy, Elsevier, vol. 300(C).
    9. Capone, Martina & Guelpa, Elisa & Verda, Vittorio, 2021. "Multi-objective optimization of district energy systems with demand response," Energy, Elsevier, vol. 227(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Lasemi, Mohammad Ali & Arabkoohsar, Ahmad & Hajizadeh, Amin & Mohammadi-ivatloo, Behnam, 2022. "A comprehensive review on optimization challenges of smart energy hubs under uncertainty factors," Renewable and Sustainable Energy Reviews, Elsevier, vol. 160(C).
    2. Kiani-Moghaddam, Mohammad & Soltani, Mohsen N. & Kalogirou, Soteris A. & Mahian, Omid & Arabkoohsar, Ahmad, 2023. "A review of neighborhood level multi-carrier energy hubs—uncertainty and problem-solving process," Energy, Elsevier, vol. 281(C).
    3. Antonio Pepiciello & Alfredo Vaccaro & Mario Mañana, 2019. "Robust Optimization of Energy Hubs Operation Based on Extended Affine Arithmetic," Energies, MDPI, vol. 12(12), pages 1-15, June.
    4. 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.
    5. Ma, Tengfei & Wu, Junyong & Hao, Liangliang & Lee, Wei-Jen & Yan, Huaguang & Li, Dezhi, 2018. "The optimal structure planning and energy management strategies of smart multi energy systems," Energy, Elsevier, vol. 160(C), pages 122-141.
    6. Mohammadi, Mohammad & Noorollahi, Younes & Mohammadi-ivatloo, Behnam & Hosseinzadeh, Mehdi & Yousefi, Hossein & Khorasani, Sasan Torabzadeh, 2018. "Optimal management of energy hubs and smart energy hubs – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 89(C), pages 33-50.
    7. Liu, Tianhao & Tian, Jun & Zhu, Hongyu & Goh, Hui Hwang & Liu, Hui & Wu, Thomas & Zhang, Dongdong, 2023. "Key technologies and developments of multi-energy system: Three-layer framework, modelling and optimisation," Energy, Elsevier, vol. 277(C).
    8. Waibel, Christoph & Evins, Ralph & Carmeliet, Jan, 2019. "Co-simulation and optimization of building geometry and multi-energy systems: Interdependencies in energy supply, energy demand and solar potentials," Applied Energy, Elsevier, vol. 242(C), pages 1661-1682.
    9. Cheng, Yaohua & Zhang, Ning & Kirschen, Daniel S. & Huang, Wujing & Kang, Chongqing, 2020. "Planning multiple energy systems for low-carbon districts with high penetration of renewable energy: An empirical study in China," Applied Energy, Elsevier, vol. 261(C).
    10. Yu Huang & Kai Yang & Weiting Zhang & Kwang Y. Lee, 2018. "Hierarchical Energy Management for the MultiEnergy Carriers System with Different Interest Bodies," Energies, MDPI, vol. 11(10), pages 1-18, October.
    11. Scheller, Fabian & Bruckner, Thomas, 2019. "Energy system optimization at the municipal level: An analysis of modeling approaches and challenges," Renewable and Sustainable Energy Reviews, Elsevier, vol. 105(C), pages 444-461.
    12. 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.
    13. Ghanbari, Ali & Karimi, Hamid & Jadid, Shahram, 2020. "Optimal planning and operation of multi-carrier networked microgrids considering multi-energy hubs in distribution networks," Energy, Elsevier, vol. 204(C).
    14. Braeuer, Fritz & Kleinebrahm, Max & Naber, Elias & Scheller, Fabian & McKenna, Russell, 2022. "Optimal system design for energy communities in multi-family buildings: the case of the German Tenant Electricity Law," Applied Energy, Elsevier, vol. 305(C).
    15. Heendeniya, Charitha Buddhika & Sumper, Andreas & Eicker, Ursula, 2020. "The multi-energy system co-planning of nearly zero-energy districts – Status-quo and future research potential," Applied Energy, Elsevier, vol. 267(C).
    16. Scheller, Fabian & Burgenmeister, Balthasar & Kondziella, Hendrik & Kühne, Stefan & Reichelt, David G. & Bruckner, Thomas, 2018. "Towards integrated multi-modal municipal energy systems: An actor-oriented optimization approach," Applied Energy, Elsevier, vol. 228(C), pages 2009-2023.
    17. Qiu, Dawei & Dong, Zihang & Zhang, Xi & Wang, Yi & Strbac, Goran, 2022. "Safe reinforcement learning for real-time automatic control in a smart energy-hub," Applied Energy, Elsevier, vol. 309(C).
    18. Ma, Tengfei & Pei, Wei & Xiao, Hao & Kong, Li & Mu, Yunfei & Pu, Tianjiao, 2020. "The energy management strategies based on dynamic energy pricing for community integrated energy system considering the interactions between suppliers and users," Energy, Elsevier, vol. 211(C).
    19. Tronchin, Lamberto & Manfren, Massimiliano & Nastasi, Benedetto, 2018. "Energy efficiency, demand side management and energy storage technologies – A critical analysis of possible paths of integration in the built environment," Renewable and Sustainable Energy Reviews, Elsevier, vol. 95(C), pages 341-353.
    20. Manfren, Massimiliano & Nastasi, Benedetto & Groppi, Daniele & Astiaso Garcia, Davide, 2020. "Open data and energy analytics - An analysis of essential information for energy system planning, design and operation," Energy, Elsevier, vol. 213(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:energy:v:212:y:2020:i:c:s0360544220316972. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.