IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v219y2021ics0360544220326694.html
   My bibliography  Save this article

A partition optimization design method for a regional integrated energy system based on a clustering algorithm

Author

Listed:
  • Li, Yiming
  • Liu, Che
  • Zhang, Lizhi
  • Sun, Bo

Abstract

This study proposes a partition optimization design method that combines K-means and genetic algorithm (GA) for regional integrated energy systems (IESs) composed of complex loads. Building partitions are obtained by a multi-energy unified clustering model based on a K-means algorithm and performed for the electrical, heating, cooling, and gas loads of various buildings. The availability of all types of resources is evaluated by clustering the local resource data. According to the unified analysis of characteristics such as the thermoelectric ratio of loads and availability of resources, suitable energy supply equipment are selected to form an alternative structure set. Capacity configuration optimization models are established based on energy, economy, and environmental evaluation indicators considering the off-design performance of the equipment. The GA is used to optimize the configuration of each alternative structure for every partition. The system evaluation indicators are sorted by the linear weighting method to obtain an optimal system configuration suitable for each building partition. A case study is used to verify the effectiveness of the proposed method. The energy supply effect of the system designed for each partition is significantly improved compared with that of a separated production system. The proposed method has engineering significance for guiding the construction of regional IESs.

Suggested Citation

  • Li, Yiming & Liu, Che & Zhang, Lizhi & Sun, Bo, 2021. "A partition optimization design method for a regional integrated energy system based on a clustering algorithm," Energy, Elsevier, vol. 219(C).
  • Handle: RePEc:eee:energy:v:219:y:2021:i:c:s0360544220326694
    DOI: 10.1016/j.energy.2020.119562
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544220326694
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.energy.2020.119562?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. Wu, J.Y. & Wang, J.L. & Li, S. & Wang, R.Z., 2014. "Experimental and simulative investigation of a micro-CCHP (micro combined cooling, heating and power) system with thermal management controller," Energy, Elsevier, vol. 68(C), pages 444-453.
    2. Lizhi Zhang & Fan Li & Bo Sun & Chenghui Zhang, 2019. "Integrated Optimization Design of Combined Cooling, Heating, and Power System Coupled with Solar and Biomass Energy," Energies, MDPI, vol. 12(4), pages 1-21, February.
    3. Yi, Ji Hyun & Ko, Woong & Park, Jong-Keun & Park, Hyeongon, 2018. "Impact of carbon emission constraint on design of small scale multi-energy system," Energy, Elsevier, vol. 161(C), pages 792-808.
    4. Zhou, Yuekuan & Zheng, Siqian & Zhang, Guoqiang, 2020. "Machine learning-based optimal design of a phase change material integrated renewable system with on-site PV, radiative cooling and hybrid ventilations—study of modelling and application in five clima," Energy, Elsevier, vol. 192(C).
    5. Zhang, Xingxing & Lovati, Marco & Vigna, Ilaria & Widén, Joakim & Han, Mengjie & Gal, Csilla & Feng, Tao, 2018. "A review of urban energy systems at building cluster level incorporating renewable-energy-source (RES) envelope solutions," Applied Energy, Elsevier, vol. 230(C), pages 1034-1056.
    6. Deng, Na & Cai, Rongchang & Gao, Yuan & Zhou, Zhihua & He, Guansong & Liu, Dongyi & Zhang, Awen, 2017. "A MINLP model of optimal scheduling for a district heating and cooling system: A case study of an energy station in Tianjin," Energy, Elsevier, vol. 141(C), pages 1750-1763.
    7. Zhang, Zhihui & Jing, Rui & Lin, Jian & Wang, Xiaonan & van Dam, Koen H. & Wang, Meng & Meng, Chao & Xie, Shan & Zhao, Yingru, 2020. "Combining agent-based residential demand modeling with design optimization for integrated energy systems planning and operation," Applied Energy, Elsevier, vol. 263(C).
    8. Wang, Jiangjiang & Sui, Jun & Jin, Hongguang, 2015. "An improved operation strategy of combined cooling heating and power system following electrical load," Energy, Elsevier, vol. 85(C), pages 654-666.
    9. Liu, Mingxi & Shi, Yang & Fang, Fang, 2013. "Optimal power flow and PGU capacity of CCHP systems using a matrix modeling approach," Applied Energy, Elsevier, vol. 102(C), pages 794-802.
    10. Zhu, Xingyi & Zhan, Xiangyan & Liang, Hao & Zheng, Xuyue & Qiu, Yuwei & Lin, Jian & Chen, Jincan & Meng, Chao & Zhao, Yingru, 2020. "The optimal design and operation strategy of renewable energy-CCHP coupled system applied in five building objects," Renewable Energy, Elsevier, vol. 146(C), pages 2700-2715.
    11. Guozheng Li & Rui Wang & Tao Zhang & Mengjun Ming, 2018. "Multi-Objective Optimal Design of Renewable Energy Integrated CCHP System Using PICEA-g," Energies, MDPI, vol. 11(4), pages 1-26, March.
    12. 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.
    13. Evangelos Bellos & Christos Tzivanidis, 2017. "Optimization of a Solar-Driven Trigeneration System with Nanofluid-Based Parabolic Trough Collectors," Energies, MDPI, vol. 10(7), pages 1-31, June.
    14. Li, Fan & Sun, Bo & Zhang, Chenghui & Liu, Che, 2019. "A hybrid optimization-based scheduling strategy for combined cooling, heating, and power system with thermal energy storage," Energy, Elsevier, vol. 188(C).
    15. Sakalis, George N. & Frangopoulos, Christos A., 2018. "Intertemporal optimization of synthesis, design and operation of integrated energy systems of ships: General method and application on a system with Diesel main engines," Applied Energy, Elsevier, vol. 226(C), pages 991-1008.
    16. Wang, Yongli & Li, Ruiwen & Dong, Huanran & Ma, Yuze & Yang, Jiale & Zhang, Fuwei & Zhu, Jinrong & Li, Shuqing, 2019. "Capacity planning and optimization of business park-level integrated energy system based on investment constraints," Energy, Elsevier, vol. 189(C).
    17. Li, Bei & Roche, Robin & Paire, Damien & Miraoui, Abdellatif, 2018. "Optimal sizing of distributed generation in gas/electricity/heat supply networks," Energy, Elsevier, vol. 151(C), pages 675-688.
    18. Zatti, Matteo & Gabba, Marco & Freschini, Marco & Rossi, Michele & Gambarotta, Agostino & Morini, Mirko & Martelli, Emanuele, 2019. "k-MILP: A novel clustering approach to select typical and extreme days for multi-energy systems design optimization," Energy, Elsevier, vol. 181(C), pages 1051-1063.
    19. Yang, G. & Zhai, X.Q., 2019. "Optimal design and performance analysis of solar hybrid CCHP system considering influence of building type and climate condition," Energy, Elsevier, vol. 174(C), pages 647-663.
    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. Wang, Yongli & Liu, Zhen & Cai, Chengcong & Xue, Lu & Ma, Yang & Shen, Hekun & Chen, Xin & Liu, Lin, 2022. "Research on the optimization method of integrated energy system operation with multi-subject game," Energy, Elsevier, vol. 245(C).
    2. Zhe Chen & Zihan Sun & Da Lin & Zhihao Li & Jian Chen, 2024. "Optimal Configuration of Multi-Energy Storage in an Electric–Thermal–Hydrogen Integrated Energy System Considering Extreme Disaster Scenarios," Sustainability, MDPI, vol. 16(6), pages 1-25, March.
    3. de Oliveira, Glauber Cardoso & Bertone, Edoardo & Stewart, Rodney A., 2022. "Challenges, opportunities, and strategies for undertaking integrated precinct-scale energy–water system planning," Renewable and Sustainable Energy Reviews, Elsevier, vol. 161(C).
    4. Kittel, Martin & Hobbie, Hannes & Dierstein, Constantin, 2022. "Temporal aggregation of time series to identify typical hourly electricity system states: A systematic assessment of relevant cluster algorithms," Energy, Elsevier, vol. 247(C).
    5. Li, Peng & Guo, Tianyu & Abeysekera, Muditha & Wu, Jianzhong & Han, Zhonghe & Wang, Zixuan & Yin, Yunxing & Zhou, Fengquan, 2021. "Intraday multi-objective hierarchical coordinated operation of a multi-energy system," Energy, Elsevier, vol. 228(C).
    6. Liu, Xinrui & Hou, Min & Sun, Siluo & Wang, Jiawei & Sun, Qiuye & Dong, Chaoyu, 2022. "Multi-time scale optimal scheduling of integrated electricity and district heating systems considering thermal comfort of users: An enhanced-interval optimization method," Energy, Elsevier, vol. 254(PB).
    7. Qiao, Yiyang & Hu, Fan & Xiong, Wen & Guo, Zihao & Zhou, Xiaoguang & Li, Yajun, 2023. "Multi-objective optimization of integrated energy system considering installation configuration," Energy, Elsevier, vol. 263(PC).

    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. Lizhi Zhang & Fan Li & Bo Sun & Chenghui Zhang, 2019. "Integrated Optimization Design of Combined Cooling, Heating, and Power System Coupled with Solar and Biomass Energy," Energies, MDPI, vol. 12(4), pages 1-21, February.
    2. Jin, Baohong, 2023. "Impact of renewable energy penetration in power systems on the optimization and operation of regional distributed energy systems," Energy, Elsevier, vol. 273(C).
    3. Fan Li & Jingxi Su & Bo Sun, 2023. "An Optimal Scheduling Method for an Integrated Energy System Based on an Improved k-Means Clustering Algorithm," Energies, MDPI, vol. 16(9), pages 1-22, April.
    4. Yuan, Yu & Bai, Zhang & Zhou, Shengdong & Zheng, Bo & Hu, Wenxin, 2022. "Potential of applying the thermochemical recuperation in combined cooling, heating and power generation: Flexible demand response characteristics," Applied Energy, Elsevier, vol. 325(C).
    5. Xiao Gong & Fan Li & Bo Sun & Dong Liu, 2020. "Collaborative Optimization of Multi-Energy Complementary Combined Cooling, Heating, and Power Systems Considering Schedulable Loads," Energies, MDPI, vol. 13(4), pages 1-17, February.
    6. Yang, Yu & Liu, Zhiqiang & Xie, Nan & Wang, Jiaqiang & Cui, Yanping & Agbodjan, Yawovi Souley, 2023. "Multi-criteria optimization of multi-energy complementary systems considering reliability, economic and environmental effects," Energy, Elsevier, vol. 269(C).
    7. Pinto, Edwin S. & Gronier, Timothé & Franquet, Erwin & Serra, Luis M., 2023. "Opportunities and economic assessment for a third-party delivering electricity, heat and cold to residential buildings," Energy, Elsevier, vol. 272(C).
    8. 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).
    9. Jiyuan Kuang & Chenghui Zhang & Fan Li & Bo Sun, 2018. "Dynamic Optimization of Combined Cooling, Heating, and Power Systems with Energy Storage Units," Energies, MDPI, vol. 11(9), pages 1-16, August.
    10. Zhou, Yuan & Wang, Jiangjiang & Dong, Fuxiang & Qin, Yanbo & Ma, Zherui & Ma, Yanpeng & Li, Jianqiang, 2021. "Novel flexibility evaluation of hybrid combined cooling, heating and power system with an improved operation strategy," Applied Energy, Elsevier, vol. 300(C).
    11. 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).
    12. Baohong Jin & Zhichao Liu & Yichuan Liao, 2023. "Exploring the Impact of Regional Integrated Energy Systems Performance by Energy Storage Devices Based on a Bi-Level Dynamic Optimization Model," Energies, MDPI, vol. 16(6), pages 1-21, March.
    13. 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).
    14. Das, Barun K. & Al-Abdeli, Yasir M. & Kothapalli, Ganesh, 2021. "Integrating renewables into stand-alone hybrid systems meeting electric, heating, and cooling loads: A case study," Renewable Energy, Elsevier, vol. 180(C), pages 1222-1236.
    15. Bruck, Axel & Díaz Ruano, Santiago & Auer, Hans, 2022. "One piece of the puzzle towards 100 Positive Energy Districts (PEDs) across Europe by 2025: An open-source approach to unveil favourable locations of PV-based PEDs from a techno-economic perspective," Energy, Elsevier, vol. 254(PA).
    16. Chen, W.D. & Chua, K.J., 2022. "A novel and optimized operation strategy map for CCHP systems considering optimal thermal energy utilization," Energy, Elsevier, vol. 259(C).
    17. Zou, Dexuan & Gong, Dunwei & Ouyang, Haibin, 2023. "A non-dominated sorting genetic approach using elite crossover for the combined cooling, heating, and power system with three energy storages," Applied Energy, Elsevier, vol. 329(C).
    18. Li, Ke & Yang, Fan & Wang, Lupan & Yan, Yi & Wang, Haiyang & Zhang, Chenghui, 2022. "A scenario-based two-stage stochastic optimization approach for multi-energy microgrids," Applied Energy, Elsevier, vol. 322(C).
    19. Yunshou Mao & Jiekang Wu & Wenjie Zhang, 2020. "An Effective Operation Strategy for CCHP System Integrated with Photovoltaic/Thermal Panels and Thermal Energy Storage," Energies, MDPI, vol. 13(23), pages 1-20, December.
    20. Ge, Yongkai & Ma, Yue & Wang, Qingrui & Yang, Qing & Xing, Lu & Ba, Shusong, 2023. "Techno-economic-environmental assessment and performance comparison of a building distributed multi-energy system under various operation strategies," Renewable Energy, Elsevier, vol. 204(C), pages 685-696.

    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:219:y:2021:i:c:s0360544220326694. 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.