IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v11y2019i19p5375-d271767.html
   My bibliography  Save this article

Low Carbon Scheduling Optimization of Flexible Integrated Energy System Considering CVaR and Energy Efficiency

Author

Listed:
  • Hang Liu

    (School of Management Engineering, Zhengzhou University of Aeronautics, Zhengzhou 450000, China)

  • Shilin Nie

    (School of Economics and Management, North China Electric Power University, Beijing 102206, China)

Abstract

With the rapid transformation of energy structures, the Integrated Energy System (IES) has developed rapidly. It can meet the complementary needs of various energy sources such as cold, thermal, and electricity in industrial parks; can realize multi-energy complements and centralized energy supplies; and can further improve the use efficiency of energy. However, with the extensive access of renewable energy, the uncertainty and intermittentness of renewable energy power generation will greatly reduce the use efficiency of renewable energy and the supply flexibility of IES so as to increase the operational risk of the system operator. With the goal of minimum sum of the system-operating cost and the carbon-emission penalty cost, this paper analyzes the combined supply of cooling, heating, and power (CCHP) influence on system efficiency, compared with the traditional IES. The flexible modified IES realizes the decoupling of cooling, thermal, and electricity; enhances the flexibility of the IES in a variety of energy supply; at the same time, improves the use efficiency of multi-energy; and reasonably avoids the occurrence of energy loss and resource waste. With the aim of reducing the risk that the access of renewable energy may bring to the IES, this paper introduces the fuzzy c-mean-clustering comprehensive quality (FCM-CCQ) algorithm, which is a novel method superior to the general clustering method and performs cluster analysis on the output scenarios of wind power and photovoltaic. Meanwhile, conditional value at risk (CVaR) theory is added to control the system operation risk, which is rarely applied in the field of IES optimization. The model is simulated in a numerical example, and the results demonstrate that the availability and applicability of the presented model are verified. In addition, the carbon dioxide emission of the traditional operation mode; thermoelectric decoupling operation mode; and cooling, thermal, and electricity decoupling operation mode of the IES decrease successively. The system flexibility is greatly enhanced, and the energy-use rate of the system is improved as a whole. Finally, IES, after its flexible transformation, significantly achieve energy conservation, emission reduction, and environmental protection.

Suggested Citation

  • Hang Liu & Shilin Nie, 2019. "Low Carbon Scheduling Optimization of Flexible Integrated Energy System Considering CVaR and Energy Efficiency," Sustainability, MDPI, vol. 11(19), pages 1-27, September.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:19:p:5375-:d:271767
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/11/19/5375/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/11/19/5375/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Wang, Haichao & Yin, Wusong & Abdollahi, Elnaz & Lahdelma, Risto & Jiao, Wenling, 2015. "Modelling and optimization of CHP based district heating system with renewable energy production and energy storage," Applied Energy, Elsevier, vol. 159(C), pages 401-421.
    2. Jun Dong & Peiwen Yang & Shilin Nie, 2019. "Day-Ahead Scheduling Model of the Distributed Small Hydro-Wind-Energy Storage Power System Based on Two-Stage Stochastic Robust Optimization," Sustainability, MDPI, vol. 11(10), pages 1-27, May.
    3. Mihaela Simionescu & Yuriy Bilan & Stanisław Gędek & Dalia Streimikiene, 2019. "The Effects of Greenhouse Gas Emissions on Cereal Production in the European Union," Sustainability, MDPI, vol. 11(12), pages 1-24, June.
    4. Yang, Yulong & Wu, Kai & Long, Hongyu & Gao, Jianchao & Yan, Xu & Kato, Takeyoshi & Suzuoki, Yasuo, 2014. "Integrated electricity and heating demand-side management for wind power integration in China," Energy, Elsevier, vol. 78(C), pages 235-246.
    5. Shams, Mohammad H. & Shahabi, Majid & Kia, Mohsen & Heidari, Alireza & Lotfi, Mohamed & Shafie-khah, Miadreza & Catalão, João P.S., 2019. "Optimal operation of electrical and thermal resources in microgrids with energy hubs considering uncertainties," Energy, Elsevier, vol. 187(C).
    6. Wang, Dongxiao & Qiu, Jing & Reedman, Luke & Meng, Ke & Lai, Loi Lei, 2018. "Two-stage energy management for networked microgrids with high renewable penetration," Applied Energy, Elsevier, vol. 226(C), pages 39-48.
    7. Liu, Zifa & Chen, Yixiao & Zhuo, Ranqun & Jia, Hongjie, 2018. "Energy storage capacity optimization for autonomy microgrid considering CHP and EV scheduling," Applied Energy, Elsevier, vol. 210(C), pages 1113-1125.
    8. Deng, Zheng-Hong & Qiao, Hong-Hai & Song, Qun & Gao, Li, 2019. "A complex network community detection algorithm based on label propagation and fuzzy C-means," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 519(C), pages 217-226.
    9. Nikoobakht, Ahmad & Aghaei, Jamshid & Fallahzadeh-Abarghouei, Hossein & Hemmati, Rasul, 2019. "Flexible Co-Scheduling of integrated electrical and gas energy networks under continuous and discrete uncertainties," Energy, Elsevier, vol. 182(C), pages 201-210.
    10. Parra, David & Norman, Stuart A. & Walker, Gavin S. & Gillott, Mark, 2017. "Optimum community energy storage for renewable energy and demand load management," Applied Energy, Elsevier, vol. 200(C), pages 358-369.
    11. Lv, Chaoxian & Yu, Hao & Li, Peng & Wang, Chengshan & Xu, Xiandong & Li, Shuquan & Wu, Jianzhong, 2019. "Model predictive control based robust scheduling of community integrated energy system with operational flexibility," Applied Energy, Elsevier, vol. 243(C), pages 250-265.
    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. 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.
    2. Yongzheng Zhang & Chunming Ye & Xiuli Geng, 2022. "A Hesitant Fuzzy Method for Evaluating Risky Cold Chain Suppliers Based on an Improved TODIM," Sustainability, MDPI, vol. 14(16), pages 1-23, August.
    3. Xingyun Yan & Lingyu Wang & Mingzhu Fang & Jie Hu, 2022. "How Can Industrial Parks Achieve Carbon Neutrality? Literature Review and Research Prospect Based on the CiteSpace Knowledge Map," Sustainability, MDPI, vol. 15(1), pages 1-29, December.

    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. Zheng, Jinfu & Zhou, Zhigang & Zhao, Jianing & Wang, Jinda, 2018. "Integrated heat and power dispatch truly utilizing thermal inertia of district heating network for wind power integration," Applied Energy, Elsevier, vol. 211(C), pages 865-874.
    2. Rongxiang Yuan & Jun Ye & Jiazhi Lei & Timing Li, 2016. "Integrated Combined Heat and Power System Dispatch Considering Electrical and Thermal Energy Storage," Energies, MDPI, vol. 9(6), pages 1-17, June.
    3. Wei Wei & Haoyue Jia & Yunfei Mu & Jianzhong Wu & Hongjie Jia, 2019. "A Robust Assessment Model of the Solar Electrical-Thermal Energy Comprehensive Accommodation Capability in a District Integrated Energy System," Energies, MDPI, vol. 12(7), pages 1-26, April.
    4. Hosseini, Seyed Hamid Reza & Allahham, Adib & Walker, Sara Louise & Taylor, Phil, 2021. "Uncertainty analysis of the impact of increasing levels of gas and electricity network integration and storage on Techno-Economic-Environmental performance," Energy, Elsevier, vol. 222(C).
    5. Guelpa, Elisa & Verda, Vittorio, 2021. "Demand response and other demand side management techniques for district heating: A review," Energy, Elsevier, vol. 219(C).
    6. Xiaofeng Guo & Alain Pascal Goumba & Cheng Wang, 2019. "Comparison of Direct and Indirect Active Thermal Energy Storage Strategies for Large-Scale Solar Heating Systems," Energies, MDPI, vol. 12(10), pages 1-18, May.
    7. Hang Liu & Yongcheng Wang & Shilin Nie & Yi Wang & Yu Chen, 2022. "Multistage Economic Scheduling Model of Micro-Energy Grids Considering Flexible Capacity Allocation," Sustainability, MDPI, vol. 14(15), pages 1-29, July.
    8. Xu, Jiuping & Liu, Liying & Wang, Fengjuan, 2022. "Equilibrium strategy-based economic-reliable approach for day-ahead scheduling towards solar-wind-gas hybrid power generation system: A case study from China," Energy, Elsevier, vol. 240(C).
    9. Lv, Chaoxian & Yu, Hao & Li, Peng & Wang, Chengshan & Xu, Xiandong & Li, Shuquan & Wu, Jianzhong, 2019. "Model predictive control based robust scheduling of community integrated energy system with operational flexibility," Applied Energy, Elsevier, vol. 243(C), pages 250-265.
    10. Jun Dong & Shilin Nie & Hui Huang & Peiwen Yang & Anyuan Fu & Jin Lin, 2019. "Research on Economic Operation Strategy of CHP Microgrid Considering Renewable Energy Sources and Integrated Energy Demand Response," Sustainability, MDPI, vol. 11(18), pages 1-22, September.
    11. Àlex Alonso-Travesset & Helena Martín & Sergio Coronas & Jordi de la Hoz, 2022. "Optimization Models under Uncertainty in Distributed Generation Systems: A Review," Energies, MDPI, vol. 15(5), pages 1-40, March.
    12. Jafari, Amirreza & Ganjeh Ganjehlou, Hamed & Khalili, Tohid & Bidram, Ali, 2020. "A fair electricity market strategy for energy management and reliability enhancement of islanded multi-microgrids," Applied Energy, Elsevier, vol. 270(C).
    13. Sadeghian, Omid & Mohammadpour Shotorbani, Amin & Mohammadi-Ivatloo, Behnam & Sadiq, Rehan & Hewage, Kasun, 2021. "Risk-averse maintenance scheduling of generation units in combined heat and power systems with demand response," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
    14. Pia Szichta & Ingela Tietze, 2020. "Sharing Economy in der Elektrizitätswirtschaft: Treiber und Hemmnisse [Title sharing economy in the electricity sector: drivers and barriers]," NachhaltigkeitsManagementForum | Sustainability Management Forum, Springer, vol. 28(3), pages 109-125, December.
    15. Taofeek Afolabi & Hooman Farzaneh, 2023. "Optimal Design and Operation of an Off-Grid Hybrid Renewable Energy System in Nigeria’s Rural Residential Area, Using Fuzzy Logic and Optimization Techniques," Sustainability, MDPI, vol. 15(4), pages 1-33, February.
    16. Nicoleta Mihaela Florea & Roxana Maria Bădîrcea & Ramona Costina Pîrvu & Alina Georgiana Manta & Marius Dalian Doran & Elena Jianu, 2020. "The impact of agriculture and renewable energy on climate change in Central and East European Countries," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 66(10), pages 444-457.
    17. Marco van Dijk & Stefanus Johannes van Vuuren & Giovanna Cavazzini & Chantel Monica Niebuhr & Alberto Santolin, 2022. "Optimizing Conduit Hydropower Potential by Determining Pareto-Optimal Trade-Off Curve," Sustainability, MDPI, vol. 14(13), pages 1-20, June.
    18. 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).
    19. Mansour-Saatloo, Amin & Pezhmani, Yasin & Mirzaei, Mohammad Amin & Mohammadi-Ivatloo, Behnam & Zare, Kazem & Marzband, Mousa & Anvari-Moghaddam, Amjad, 2021. "Robust decentralized optimization of Multi-Microgrids integrated with Power-to-X technologies," Applied Energy, Elsevier, vol. 304(C).
    20. Yu, Kunjie & Liang, J.J. & Qu, B.Y. & Cheng, Zhiping & Wang, Heshan, 2018. "Multiple learning backtracking search algorithm for estimating parameters of photovoltaic models," Applied Energy, Elsevier, vol. 226(C), pages 408-422.

    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:jsusta:v:11:y:2019:i:19:p:5375-:d:271767. 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.