IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v16y2023i10p4129-d1148430.html
   My bibliography  Save this article

Theoretical Analysis of Integrated Community Energy Systems (ICES) Considering Integrated Demand Response (IDR): A Review of the System Modelling and Optimization

Author

Listed:
  • Dezhou Kong

    (Department of Architecture and Built Environment, University of Nottingham Ningbo China, Ningbo 315100, China)

  • Jianru Jing

    (Department of Architecture and Built Environment, University of Nottingham Ningbo China, Ningbo 315100, China)

  • Tingyue Gu

    (Department of Architecture and Built Environment, University of Nottingham Ningbo China, Ningbo 315100, China)

  • Xuanyue Wei

    (Department of Architecture and Built Environment, University of Nottingham Ningbo China, Ningbo 315100, China)

  • Xingning Sa

    (Department of Architecture and Built Environment, University of Nottingham Ningbo China, Ningbo 315100, China)

  • Yimin Yang

    (Department of Architecture and Built Environment, University of Nottingham Ningbo China, Ningbo 315100, China)

  • Zhiang Zhang

    (Department of Architecture and Built Environment, University of Nottingham Ningbo China, Ningbo 315100, China)

Abstract

The transition of the energy model dominated by centralized fossil energy use and the emergence of the Energy Internet and the Integrated Community Energy System (ICES) has gained attention. ICES involved the connection of electricity, heat, gas, and other kinds of energy, and was a significant form of the targeted transformation of conventional single energy networks. Within this system, the traditional demand response (DR) was transformed into an integrated demand response (IDR) in which all energy consumers could participate. The purpose of this study is to discuss the important technologies and models along with assessment and optimization strategies for the implementation of ICES and IDR, based on an extensive literature review. The analysis results show the “IDR + ICES” ecosystem proved to hold great potential for achieving renewable energy penetration, energy efficiency, and climate change control goals, while there are still many limitations in the coordination and reliability of the model and the design of the market mechanism. To conclude, the challenges and opportunities that ICES and IDR face were summarized, and future avenues for research are outlined.

Suggested Citation

  • Dezhou Kong & Jianru Jing & Tingyue Gu & Xuanyue Wei & Xingning Sa & Yimin Yang & Zhiang Zhang, 2023. "Theoretical Analysis of Integrated Community Energy Systems (ICES) Considering Integrated Demand Response (IDR): A Review of the System Modelling and Optimization," Energies, MDPI, vol. 16(10), pages 1-22, May.
  • Handle: RePEc:gam:jeners:v:16:y:2023:i:10:p:4129-:d:1148430
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/16/10/4129/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/16/10/4129/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Christoph Goebel & Vicky Cheng & Hans-Arno Jacobsen, 2017. "Profitability of Residential Battery Energy Storage Combined with Solar Photovoltaics," Energies, MDPI, vol. 10(7), pages 1-17, July.
    2. van der Stelt, Sander & AlSkaif, Tarek & van Sark, Wilfried, 2018. "Techno-economic analysis of household and community energy storage for residential prosumers with smart appliances," Applied Energy, Elsevier, vol. 209(C), pages 266-276.
    3. Yi Yu & Xishan Wen & Jian Zhao & Zhao Xu & Jiayong Li, 2018. "Co-Planning of Demand Response and Distributed Generators in an Active Distribution Network," Energies, MDPI, vol. 11(2), pages 1-18, February.
    4. Xiang, Yue & Cai, Hanhu & Gu, Chenghong & Shen, Xiaodong, 2020. "Cost-benefit analysis of integrated energy system planning considering demand response," Energy, Elsevier, vol. 192(C).
    5. Patteeuw, Dieter & Reynders, Glenn & Bruninx, Kenneth & Protopapadaki, Christina & Delarue, Erik & D’haeseleer, William & Saelens, Dirk & Helsen, Lieve, 2015. "CO2-abatement cost of residential heat pumps with active demand response: demand- and supply-side effects," Applied Energy, Elsevier, vol. 156(C), pages 490-501.
    6. Reza Arghandeh & Jeremy Woyak & Ahmet Onen & Jaesung Jung & Robert P. Broadwater, 2014. "Economic Optimal Operation of Community Energy Storage Systems in Competitive Energy Markets," Papers 1407.0433, arXiv.org, revised Sep 2014.
    7. Paliwal, Priyanka & Patidar, N.P. & Nema, R.K., 2014. "Determination of reliability constrained optimal resource mix for an autonomous hybrid power system using Particle Swarm Optimization," Renewable Energy, Elsevier, vol. 63(C), pages 194-204.
    8. Zou, Peng & Chen, Qixin & Yu, Yang & Xia, Qing & Kang, Chongqing, 2017. "Electricity markets evolution with the changing generation mix: An empirical analysis based on China 2050 High Renewable Energy Penetration Roadmap," Applied Energy, Elsevier, vol. 185(P1), pages 56-67.
    9. Fujimori, Shinichiro & Masui, Toshihiko & Matsuoka, Yuzuru, 2014. "Development of a global computable general equilibrium model coupled with detailed energy end-use technology," Applied Energy, Elsevier, vol. 128(C), pages 296-306.
    10. Khaled Abedrabboh & Luluwah Al-Fagih, 2021. "Applications of Mechanism Design in Market-Based Demand-Side Management," Papers 2106.14659, arXiv.org.
    11. Morteza Zare Oskouei & Ayşe Aybike Şeker & Süleyman Tunçel & Emin Demirbaş & Tuba Gözel & Mehmet Hakan Hocaoğlu & Mehdi Abapour & Behnam Mohammadi-Ivatloo, 2022. "A Critical Review on the Impacts of Energy Storage Systems and Demand-Side Management Strategies in the Economic Operation of Renewable-Based Distribution Network," Sustainability, MDPI, vol. 14(4), pages 1-34, February.
    12. 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.
    13. Zhang, Ning & Sun, Qiuye & Yang, Lingxiao, 2021. "A two-stage multi-objective optimal scheduling in the integrated energy system with We-Energy modeling," Energy, Elsevier, vol. 215(PB).
    14. Chicco, Gianfranco, 2012. "Overview and performance assessment of the clustering methods for electrical load pattern grouping," Energy, Elsevier, vol. 42(1), pages 68-80.
    15. Yuehao Zhao & Ke Peng & Bingyin Xu & Huimin Li & Yuquan Liu & Xinhui Zhang, 2018. "Bilevel Optimal Dispatch Strategy for a Multi-Energy System of Industrial Parks by Considering Integrated Demand Response," Energies, MDPI, vol. 11(8), pages 1-21, July.
    16. Capone, Martina & Guelpa, Elisa & Verda, Vittorio, 2021. "Multi-objective optimization of district energy systems with demand response," Energy, Elsevier, vol. 227(C).
    17. Yongli Wang & Yujing Huang & Yudong Wang & Haiyang Yu & Ruiwen Li & Shanshan Song, 2018. "Energy Management for Smart Multi-Energy Complementary Micro-Grid in the Presence of Demand Response," Energies, MDPI, vol. 11(4), pages 1-19, April.
    18. Wang, Jianxiao & Zhong, Haiwang & Ma, Ziming & Xia, Qing & Kang, Chongqing, 2017. "Review and prospect of integrated demand response in the multi-energy system," Applied Energy, Elsevier, vol. 202(C), pages 772-782.
    19. Hussein Jumma Jabir & Jiashen Teh & Dahaman Ishak & Hamza Abunima, 2018. "Impacts of Demand-Side Management on Electrical Power Systems: A Review," Energies, MDPI, vol. 11(5), pages 1-19, April.
    20. Wang, Yongli & Ma, Yuze & Song, Fuhao & Ma, Yang & Qi, Chengyuan & Huang, Feifei & Xing, Juntai & Zhang, Fuwei, 2020. "Economic and efficient multi-objective operation optimization of integrated energy system considering electro-thermal demand response," Energy, Elsevier, vol. 205(C).
    21. Taibi, Emanuele & Fernández del Valle, Carlos & Howells, Mark, 2018. "Strategies for solar and wind integration by leveraging flexibility from electric vehicles: The Barbados case study," Energy, Elsevier, vol. 164(C), pages 65-78.
    22. Amara, Sihem & Toumi, Sana & Salah, Chokri Ben & Saidi, Abdelaziz Salah, 2021. "Improvement of techno-economic optimal sizing of a hybrid off-grid micro-grid system," Energy, Elsevier, vol. 233(C).
    23. Çiçek, Alper & Şengör, İbrahim & Erenoğlu, Ayşe Kübra & Erdinç, Ozan, 2020. "Decision making mechanism for a smart neighborhood fed by multi-energy systems considering demand response," Energy, Elsevier, vol. 208(C).
    24. Ahmad Alzahrani & Senthil Kumar Ramu & Gunapriya Devarajan & Indragandhi Vairavasundaram & Subramaniyaswamy Vairavasundaram, 2022. "A Review on Hydrogen-Based Hybrid Microgrid System: Topologies for Hydrogen Energy Storage, Integration, and Energy Management with Solar and Wind Energy," Energies, MDPI, vol. 15(21), pages 1-32, October.
    25. Arghandeh, Reza & Woyak, Jeremy & Onen, Ahmet & Jung, Jaesung & Broadwater, Robert P., 2014. "Economic optimal operation of Community Energy Storage systems in competitive energy markets," Applied Energy, Elsevier, vol. 135(C), pages 71-80.
    26. Hu, Maomao & Xiao, Fu & Wang, Shengwei, 2021. "Neighborhood-level coordination and negotiation techniques for managing demand-side flexibility in residential microgrids," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
    27. Li, Peng & Wang, Zixuan & Liu, Haitao & Wang, Jiahao & Guo, Tianyu & Yin, Yunxing, 2021. "Bi-level optimal configuration strategy of community integrated energy system with coordinated planning and operation," Energy, Elsevier, vol. 236(C).
    28. Gu, Wei & Wang, Jun & Lu, Shuai & Luo, Zhao & Wu, Chenyu, 2017. "Optimal operation for integrated energy system considering thermal inertia of district heating network and buildings," Applied Energy, Elsevier, vol. 199(C), pages 234-246.
    29. Yang, Xiaohui & Chen, Zaixing & Huang, Xin & Li, Ruixin & Xu, Shaoping & Yang, Chunsheng, 2021. "Robust capacity optimization methods for integrated energy systems considering demand response and thermal comfort," Energy, Elsevier, vol. 221(C).
    30. 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.
    31. Bai, Linquan & Li, Fangxing & Cui, Hantao & Jiang, Tao & Sun, Hongbin & Zhu, Jinxiang, 2016. "Interval optimization based operating strategy for gas-electricity integrated energy systems considering demand response and wind uncertainty," Applied Energy, Elsevier, vol. 167(C), pages 270-279.
    32. Cui, Hantao & Li, Fangxing & Hu, Qinran & Bai, Linquan & Fang, Xin, 2016. "Day-ahead coordinated operation of utility-scale electricity and natural gas networks considering demand response based virtual power plants," Applied Energy, Elsevier, vol. 176(C), pages 183-195.
    33. Mansouri, Seyed Amir & Ahmarinejad, Amir & Javadi, Mohammad Sadegh & Catalão, João P.S., 2020. "Two-stage stochastic framework for energy hubs planning considering demand response programs," Energy, Elsevier, vol. 206(C).
    34. 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.
    35. Rodrigues, Renato & Linares, Pedro, 2015. "Electricity load level detail in computational general equilibrium – part II – welfare impacts of a demand response program," Energy Economics, Elsevier, vol. 47(C), pages 52-67.
    36. Motalleb, Mahdi & Annaswamy, Anuradha & Ghorbani, Reza, 2018. "A real-time demand response market through a repeated incomplete-information game," Energy, Elsevier, vol. 143(C), pages 424-438.
    37. Song, Xiaoling & Wang, Yudong & Zhang, Zhe & Shen, Charles & Peña-Mora, Feniosky, 2021. "Economic-environmental equilibrium-based bi-level dispatch strategy towards integrated electricity and natural gas systems," Applied Energy, Elsevier, vol. 281(C).
    38. Jiajia Li & Jinfu Liu & Peigang Yan & Xingshuo Li & Guowen Zhou & Daren Yu, 2021. "Operation Optimization of Integrated Energy System under a Renewable Energy Dominated Future Scene Considering Both Independence and Benefit: A Review," Energies, MDPI, vol. 14(4), pages 1-36, February.
    39. Zhou, Yizhou & Wei, Zhinong & Sun, Guoqiang & Cheung, Kwok W. & Zang, Haixiang & Chen, Sheng, 2018. "A robust optimization approach for integrated community energy system in energy and ancillary service markets," Energy, Elsevier, vol. 148(C), pages 1-15.
    40. Mathiesen, B.V. & Lund, H. & Connolly, D. & Wenzel, H. & Østergaard, P.A. & Möller, B. & Nielsen, S. & Ridjan, I. & Karnøe, P. & Sperling, K. & Hvelplund, F.K., 2015. "Smart Energy Systems for coherent 100% renewable energy and transport solutions," Applied Energy, Elsevier, vol. 145(C), pages 139-154.
    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. Puming Wang & Liqin Zheng & Tianyi Diao & Shengquan Huang & Xiaoqing Bai, 2023. "Robust Bilevel Optimal Dispatch of Park Integrated Energy System Considering Renewable Energy Uncertainty," Energies, MDPI, vol. 16(21), pages 1-23, October.

    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. Zhu, Xu & Sun, Yuanzhang & Yang, Jun & Dou, Zhenlan & Li, Gaojunjie & Xu, Chengying & Wen, Yuxin, 2022. "Day-ahead energy pricing and management method for regional integrated energy systems considering multi-energy demand responses," Energy, Elsevier, vol. 251(C).
    2. Shen, Ziqi & Wei, Wei & Wu, Lei & Shafie-khah, Miadreza & Catalão, João P.S., 2021. "Economic dispatch of power systems with LMP-dependent demands: A non-iterative MILP model," Energy, Elsevier, vol. 233(C).
    3. 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).
    4. Terlouw, Tom & AlSkaif, Tarek & Bauer, Christian & van Sark, Wilfried, 2019. "Optimal energy management in all-electric residential energy systems with heat and electricity storage," Applied Energy, Elsevier, vol. 254(C).
    5. Li, Yang & Wang, Bin & Yang, Zhen & Li, Jiazheng & Chen, Chen, 2022. "Hierarchical stochastic scheduling of multi-community integrated energy systems in uncertain environments via Stackelberg game," Applied Energy, Elsevier, vol. 308(C).
    6. Hafiz, Faeza & Rodrigo de Queiroz, Anderson & Fajri, Poria & Husain, Iqbal, 2019. "Energy management and optimal storage sizing for a shared community: A multi-stage stochastic programming approach," Applied Energy, Elsevier, vol. 236(C), pages 42-54.
    7. Zheng, Ling & Zhou, Bin & Cao, Yijia & Wing Or, Siu & Li, Yong & Wing Chan, Ka, 2022. "Hierarchical distributed multi-energy demand response for coordinated operation of building clusters," Applied Energy, Elsevier, vol. 308(C).
    8. Yan, Rujing & Wang, Jiangjiang & Wang, Jiahao & Tian, Lei & Tang, Saiqiu & Wang, Yuwei & Zhang, Jing & Cheng, Youliang & Li, Yuan, 2022. "A two-stage stochastic-robust optimization for a hybrid renewable energy CCHP system considering multiple scenario-interval uncertainties," Energy, Elsevier, vol. 247(C).
    9. Tengfei Ma & Junyong Wu & Liangliang Hao & Huaguang Yan & Dezhi Li, 2018. "A Real-Time Pricing Scheme for Energy Management in Integrated Energy Systems: A Stackelberg Game Approach," Energies, MDPI, vol. 11(10), pages 1-19, October.
    10. Ghahramani, Mehrdad & Nazari-Heris, Morteza & Zare, Kazem & Mohammadi-Ivatloo, Behnam, 2022. "A two-point estimate approach for energy management of multi-carrier energy systems incorporating demand response programs," Energy, Elsevier, vol. 249(C).
    11. Gährs, Swantje & Knoefel, Jan, 2020. "Stakeholder demands and regulatory framework for community energy storage with a focus on Germany," Energy Policy, Elsevier, vol. 144(C).
    12. Li, Peng & Wang, Zixuan & Yang, Weihong & Liu, Haitao & Yin, Yunxing & Wang, Jiahao & Guo, Tianyu, 2021. "Hierarchically partitioned coordinated operation of distributed integrated energy system based on a master-slave game," Energy, Elsevier, vol. 214(C).
    13. Sturmberg, B.C.P. & Shaw, M.E. & Mediwaththe, C.P. & Ransan-Cooper, H. & Weise, B. & Thomas, M. & Blackhall, L., 2021. "A mutually beneficial approach to electricity network pricing in the presence of large amounts of solar power and community-scale energy storage," Energy Policy, Elsevier, vol. 159(C).
    14. Lu, Qing & Guo, Qisheng & Zeng, Wei, 2022. "Optimization scheduling of integrated energy service system in community: A bi-layer optimization model considering multi-energy demand response and user satisfaction," Energy, Elsevier, vol. 252(C).
    15. Scheller, Fabian & Burkhardt, Robert & Schwarzeit, Robert & McKenna, Russell & Bruckner, Thomas, 2020. "Competition between simultaneous demand-side flexibility options: the case of community electricity storage systems," Applied Energy, Elsevier, vol. 269(C).
    16. Terlouw, Tom & AlSkaif, Tarek & Bauer, Christian & van Sark, Wilfried, 2019. "Multi-objective optimization of energy arbitrage in community energy storage systems using different battery technologies," Applied Energy, Elsevier, vol. 239(C), pages 356-372.
    17. 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).
    18. Chen, Xi & Wang, Chengfu & Wu, Qiuwei & Dong, Xiaoming & Yang, Ming & He, Suoying & Liang, Jun, 2020. "Optimal operation of integrated energy system considering dynamic heat-gas characteristics and uncertain wind power," Energy, Elsevier, vol. 198(C).
    19. Wang, Shouxiang & Wang, Shaomin & Zhao, Qianyu & Dong, Shuai & Li, Hao, 2023. "Optimal dispatch of integrated energy station considering carbon capture and hydrogen demand," Energy, Elsevier, vol. 269(C).
    20. Ding, Jianyong & Gao, Ciwei & Song, Meng & Yan, Xingyu & Chen, Tao, 2022. "Bi-level optimal scheduling of virtual energy station based on equal exergy replacement mechanism," Applied Energy, Elsevier, vol. 327(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:gam:jeners:v:16:y:2023:i:10:p:4129-:d:1148430. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.