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Quantifying the contribution of individual technologies in integrated urban energy systems – A system value approach

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  • Jing, Rui
  • Kuriyan, Kamal
  • Lin, Jian
  • Shah, Nilay
  • Zhao, Yingru

Abstract

Integrated urban energy systems satisfy energy demands in a cost-effective manner by efficiently combining diverse technologies and energy saving strategies. However, the contribution of an individual technology within a complex system is difficult to quantify. This study introduces a generalized “system value” approach to quantify the contribution of an individual design decision towards improving the system design (e.g., achieving a lower cost design). It measures the contribution of an individual technology to the whole system in the range between two benchmarks that respectively represent complete exclusion of the technology and the optimal penetration level. The method is based on a technology-rich Mixed Integer Linear Programming (MILP) model for optimal design of urban energy systems. The model considers multi-energy supply technologies, networks, storage technologies and various energy saving strategies. A stochastic formulation is further developed to quantify uncertainties of the system value. The system values of nine kinds of energy supply technologies and three categories of energy-saving strategies are quantified via a case study, which illustrates the variation in the system values for individual technologies with different levels of penetration, and multi-energy supply technologies can have a large impact in integrated systems.

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  • Jing, Rui & Kuriyan, Kamal & Lin, Jian & Shah, Nilay & Zhao, Yingru, 2020. "Quantifying the contribution of individual technologies in integrated urban energy systems – A system value approach," Applied Energy, Elsevier, vol. 266(C).
    • Handle: RePEc:eee:appene:v:266:y:2020:i:c:s0306261920303718
    DOI: 10.1016/j.apenergy.2020.114859
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    as
    1. Jing, Rui & Kuriyan, Kamal & Kong, Qingyuan & Zhang, Zhihui & Shah, Nilay & Li, Ning & Zhao, Yingru, 2019. "Exploring the impact space of different technologies using a portfolio constraint based approach for multi-objective optimization of integrated urban energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 113(C), pages 1-1.
    2. Hirth, Lion & Ueckerdt, Falko & Edenhofer, Ottmar, 2015. "Integration costs revisited – An economic framework for wind and solar variability," Renewable Energy, Elsevier, vol. 74(C), pages 925-939.
    3. Zheng, Yingying & Jenkins, Bryan M. & Kornbluth, Kurt & Kendall, Alissa & Træholt, Chresten, 2018. "Optimization of a biomass-integrated renewable energy microgrid with demand side management under uncertainty," Applied Energy, Elsevier, vol. 230(C), pages 836-844.
    4. Reichenberg, Lina & Hedenus, Fredrik & Odenberger, Mikael & Johnsson, Filip, 2018. "The marginal system LCOE of variable renewables – Evaluating high penetration levels of wind and solar in Europe," Energy, Elsevier, vol. 152(C), pages 914-924.
    5. Du, W.C. & Xia, X.H., 2018. "How does urbanization affect GHG emissions? A cross-country panel threshold data analysis," Applied Energy, Elsevier, vol. 229(C), pages 872-883.
    6. O’Dwyer, Edward & Pan, Indranil & Acha, Salvador & Shah, Nilay, 2019. "Smart energy systems for sustainable smart cities: Current developments, trends and future directions," Applied Energy, Elsevier, vol. 237(C), pages 581-597.
    7. Siddaiah, Rajanna & Saini, R.P., 2016. "A review on planning, configurations, modeling and optimization techniques of hybrid renewable energy systems for off grid applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 58(C), pages 376-396.
    8. Schmid, Eva & Knopf, Brigitte, 2015. "Quantifying the long-term economic benefits of European electricity system integration," Energy Policy, Elsevier, vol. 87(C), pages 260-269.
    9. Zheng, Xuyue & Qiu, Yuwei & Zhan, Xiangyan & Zhu, Xingyi & Keirstead, James & Shah, Nilay & Zhao, Yingru, 2017. "Optimization based planning of urban energy systems: Retrofitting a Chinese industrial park as a case-study," Energy, Elsevier, vol. 139(C), pages 31-41.
    10. Diakaki, Christina & Grigoroudis, Evangelos & Kolokotsa, Dionyssia, 2013. "Performance study of a multi-objective mathematical programming modelling approach for energy decision-making in buildings," Energy, Elsevier, vol. 59(C), pages 534-542.
    11. Zheng, Yingying & Jenkins, Bryan M. & Kornbluth, Kurt & Træholt, Chresten, 2018. "Optimization under uncertainty of a biomass-integrated renewable energy microgrid with energy storage," Renewable Energy, Elsevier, vol. 123(C), pages 204-217.
    12. Iturriaga, E. & Aldasoro, U. & Terés-Zubiaga, J. & Campos-Celador, A., 2018. "Optimal renovation of buildings towards the nearly Zero Energy Building standard," Energy, Elsevier, vol. 160(C), pages 1101-1114.
    13. Zhang, Shenxi & Cheng, Haozhong & Li, Ke & Tai, Nengling & Wang, Dan & Li, Furong, 2018. "Multi-objective distributed generation planning in distribution network considering correlations among uncertainties," Applied Energy, Elsevier, vol. 226(C), pages 743-755.
    14. Nielsen, Maria Grønnegaard & Morales, Juan Miguel & Zugno, Marco & Pedersen, Thomas Engberg & Madsen, Henrik, 2016. "Economic valuation of heat pumps and electric boilers in the Danish energy system," Applied Energy, Elsevier, vol. 167(C), pages 189-200.
    15. Wu, Raphael & Mavromatidis, Georgios & Orehounig, Kristina & Carmeliet, Jan, 2017. "Multiobjective optimisation of energy systems and building envelope retrofit in a residential community," Applied Energy, Elsevier, vol. 190(C), pages 634-649.
    16. Jing, Rui & Wang, Meng & Zhang, Zhihui & Wang, Xiaonan & Li, Ning & Shah, Nilay & Zhao, Yingru, 2019. "Distributed or centralized? Designing district-level urban energy systems by a hierarchical approach considering demand uncertainties," Applied Energy, Elsevier, vol. 252(C), pages 1-1.
    17. de Sisternes, Fernando J. & Jenkins, Jesse D. & Botterud, Audun, 2016. "The value of energy storage in decarbonizing the electricity sector," Applied Energy, Elsevier, vol. 175(C), pages 368-379.
    18. Jennings, Mark & Fisk, David & Shah, Nilay, 2014. "Modelling and optimization of retrofitting residential energy systems at the urban scale," Energy, Elsevier, vol. 64(C), pages 220-233.
    19. Kitapbayev, Yerkin & Moriarty, John & Mancarella, Pierluigi, 2015. "Stochastic control and real options valuation of thermal storage-enabled demand response from flexible district energy systems," Applied Energy, Elsevier, vol. 137(C), pages 823-831.
    20. Wu, Qiong & Ren, Hongbo & Gao, Weijun & Ren, Jianxing, 2017. "Benefit allocation for distributed energy network participants applying game theory based solutions," Energy, Elsevier, vol. 119(C), pages 384-391.
    21. Sharifzadeh, Mahdi & Lubiano-Walochik, Helena & Shah, Nilay, 2017. "Integrated renewable electricity generation considering uncertainties: The UK roadmap to 50% power generation from wind and solar energies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 72(C), pages 385-398.
    22. 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.
    23. Mavromatidis, Georgios & Orehounig, Kristina & Carmeliet, Jan, 2018. "Design of distributed energy systems under uncertainty: A two-stage stochastic programming approach," Applied Energy, Elsevier, vol. 222(C), pages 932-950.
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    2. Wu, Zhiyue & Shi, Xin & Fang, Fang & Wen, Gangcheng & Mi, Yunjie, 2023. "Co-optimization of building energy systems with renewable generations combining active and passive energy-saving," Applied Energy, Elsevier, vol. 351(C).
    3. Yongli Wang & Chen Liu & Chengcong Cai & Ziben Ma & Minhan Zhou & Huanran Dong & Fang Li, 2022. "Bi-Level Planning Model for Urban Energy Steady-State Optimal Configuration Based on Nonlinear Dynamics," Sustainability, MDPI, vol. 14(11), pages 1-32, May.
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    5. Jing, Rui & Li, Yubing & Wang, Meng & Chachuat, Benoit & Lin, Jianyi & Guo, Miao, 2021. "Coupling biogeochemical simulation and mathematical optimisation towards eco-industrial energy systems design," Applied Energy, Elsevier, vol. 290(C).
    6. Jing, Rui & Hua, Weiqi & Lin, Jian & Lin, Jianyi & Zhao, Yingru & Zhou, Yue & Wu, Jianzhong, 2022. "Cost-efficient decarbonization of local energy systems by whole-system based design optimization," Applied Energy, Elsevier, vol. 326(C).
    7. Ren, Fukang & Wei, Ziqing & Zhai, Xiaoqiang, 2022. "A review on the integration and optimization of distributed energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 162(C).
    8. Jing, Rui & Liu, Jiahui & Zhang, Haoran & Zhong, Fenglin & Liu, Yupeng & Lin, Jianyi, 2022. "Unlock the hidden potential of urban rooftop agrivoltaics energy-food-nexus," Energy, Elsevier, vol. 256(C).
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