IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v13y2020i5p1073-d326758.html
   My bibliography  Save this article

Optimal Dispatch Strategy for a Flexible Integrated Energy Storage System for Wind Power Accommodation

Author

Listed:
  • Yunhai Zhou

    (College of Electrical Engineering & New Energy, China Three Gorges University, Yichang 443000, China
    Hubei Provincial Key Laboratory for Operation and Control of Cascaded Hydropower Station, China Three Gorges University, Yichang 443000, China)

  • Pinchao Zhao

    (College of Electrical Engineering & New Energy, China Three Gorges University, Yichang 443000, China
    Hubei Provincial Key Laboratory for Operation and Control of Cascaded Hydropower Station, China Three Gorges University, Yichang 443000, China)

  • Fei Xu

    (Department of Electrical Engineering, Tsinghua University, Beijing 100084, China)

  • Dai Cui

    (Jinzhou Power Supply Company, Liaoning Electric Power Co., Ltd., Shenyang 121000, China
    School of Electrical Engineering, Shenyang University of Technology, Shenyang 110870, China)

  • Weichun Ge

    (Jinzhou Power Supply Company, Liaoning Electric Power Co., Ltd., Shenyang 121000, China
    School of Electrical Engineering, Shenyang University of Technology, Shenyang 110870, China)

  • Xiaodong Chen

    (Jinzhou Power Supply Company, Liaoning Electric Power Co., Ltd., Shenyang 121000, China)

  • Bo Gu

    (Jinzhou Power Supply Company, Liaoning Electric Power Co., Ltd., Shenyang 121000, China)

Abstract

The application of the large-capacity energy storage and heat storage devices in an integrated energy system with a high proportion of wind power penetration can improve the flexibility and wind power accommodation capacity of the system. However, the efficiency and cost of the flexible resource should also be taken into consideration when improving the new energy accommodation capacity. Based on these considerations, the authors try to construct a joint optimal scheduling model for day-ahead energy storage and heat storage that considers flexibility. The power supplies and devices will be modeled separately, which enables a universal applicability. The objective function is the minimum cost and wind curtailment. Various practical constraints are taken into account. The mixed integer programming and software GLPK is used to program and solve. The actual operation data of a provincial power grid in northern China is used to conduct simulation analysis in four different working conditions. The results show that the model can maintain economical efficiency under different working conditions. In addition, it can adjust and dispatch various power supplies and devices efficiently, significantly improving wind power accommodation of the system.

Suggested Citation

  • Yunhai Zhou & Pinchao Zhao & Fei Xu & Dai Cui & Weichun Ge & Xiaodong Chen & Bo Gu, 2020. "Optimal Dispatch Strategy for a Flexible Integrated Energy Storage System for Wind Power Accommodation," Energies, MDPI, vol. 13(5), pages 1-18, March.
  • Handle: RePEc:gam:jeners:v:13:y:2020:i:5:p:1073-:d:326758
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/13/5/1073/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/13/5/1073/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Leśko, Michał & Bujalski, Wojciech & Futyma, Kamil, 2018. "Operational optimization in district heating systems with the use of thermal energy storage," Energy, Elsevier, vol. 165(PA), pages 902-915.
    2. Yanhong Luo & Zhenxing Yin & Dongsheng Yang & Bowen Zhou, 2019. "A New Wind Power Accommodation Strategy for Combined Heat and Power System Based on Bi-Directional Conversion," Energies, MDPI, vol. 12(13), pages 1-16, June.
    3. Shahbaz Hussain & Mohammed Al-Hitmi & Salman Khaliq & Asif Hussain & Muhammad Asghar Saqib, 2019. "Implementation and Comparison of Particle Swarm Optimization and Genetic Algorithm Techniques in Combined Economic Emission Dispatch of an Independent Power Plant," Energies, MDPI, vol. 12(11), pages 1-15, May.
    4. Kia, Mohsen & Nazar, Mehrdad Setayesh & Sepasian, Mohammad Sadegh & Heidari, Alireza & Siano, Pierluigi, 2017. "Optimal day ahead scheduling of combined heat and power units with electrical and thermal storage considering security constraint of power system," Energy, Elsevier, vol. 120(C), pages 241-252.
    5. Shi, Jie & Wang, Luhao & Lee, Wei-Jen & Cheng, Xingong & Zong, Xiju, 2019. "Hybrid Energy Storage System (HESS) optimization enabling very short-term wind power generation scheduling based on output feature extraction," Applied Energy, Elsevier, vol. 256(C).
    6. Wu, Wei & Lin, Boqiang, 2018. "Application value of energy storage in power grid: A special case of China electricity market," Energy, Elsevier, vol. 165(PB), pages 1191-1199.
    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. Yu, Haiquan & Zhou, Jianxin & Si, Fengqi & Nord, Lars O., 2022. "Combined heat and power dynamic economic dispatch considering field operational characteristics of natural gas combined cycle plants," Energy, Elsevier, vol. 244(PA).
    2. 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.

    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. Guelpa, Elisa, 2021. "Impact of thermal masses on the peak load in district heating systems," Energy, Elsevier, vol. 214(C).
    2. Guo, Yurun & Wang, Shugang & Wang, Jihong & Zhang, Tengfei & Ma, Zhenjun & Jiang, Shuang, 2024. "Key district heating technologies for building energy flexibility: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PB).
    3. Misaghian, M.S. & Saffari, M. & Kia, M. & Heidari, A. & Shafie-khah, M. & Catalão, J.P.S., 2018. "Tri-level optimization of industrial microgrids considering renewable energy sources, combined heat and power units, thermal and electrical storage systems," Energy, Elsevier, vol. 161(C), pages 396-411.
    4. Xinyu Zhao & Yunxiao Zhang & Xueying Cui & Le Wan & Jinlong Qiu & Erfa Shang & Yongchang Zhang & Haisen Zhao, 2023. "Wavelet Packet-Fuzzy Optimization Control Strategy of Hybrid Energy Storage Considering Charge–Discharge Time Sequence," Sustainability, MDPI, vol. 15(13), pages 1-17, July.
    5. Vandermeulen, Annelies & Van Oevelen, Tijs & van der Heijde, Bram & Helsen, Lieve, 2020. "A simulation-based evaluation of substation models for network flexibility characterisation in district heating networks," Energy, Elsevier, vol. 201(C).
    6. Ji, Huichao & Wang, Haixin & Yang, Junyou & Feng, Jiawei & Yang, Yongyue & Okoye, Martin Onyeka, 2021. "Optimal schedule of solid electric thermal storage considering consumer behavior characteristics in combined electricity and heat networks," Energy, Elsevier, vol. 234(C).
    7. Li, Yanbin & Zhang, Feng & Li, Yun & Wang, Yuwei, 2021. "An improved two-stage robust optimization model for CCHP-P2G microgrid system considering multi-energy operation under wind power outputs uncertainties," Energy, Elsevier, vol. 223(C).
    8. Xiao, Jucheng & He, Guangyu & Fan, Shuai & Zhang, Siyuan & Wu, Qing & Li, Zuyi, 2020. "Decentralized transfer of contingency reserve: Framework and methodology," Applied Energy, Elsevier, vol. 278(C).
    9. Egging-Bratseth, Ruud & Kauko, Hanne & Knudsen, Brage Rugstad & Bakke, Sara Angell & Ettayebi, Amina & Haufe, Ina Renate, 2021. "Seasonal storage and demand side management in district heating systems with demand uncertainty," Applied Energy, Elsevier, vol. 285(C).
    10. Lin, Boqiang & Wu, Wei, 2021. "The impact of electric vehicle penetration: A recursive dynamic CGE analysis of China," Energy Economics, Elsevier, vol. 94(C).
    11. Kia, M. & Shafiekhani, M. & Arasteh, H. & Hashemi, S.M. & Shafie-khah, M. & Catalão, J.P.S., 2020. "Short-term operation of microgrids with thermal and electrical loads under different uncertainties using information gap decision theory," Energy, Elsevier, vol. 208(C).
    12. Huijia Yang & Weiguang Fan & Guangyu Qin & Zhenyu Zhao, 2021. "A Fuzzy-ANP Approach for Comprehensive Benefit Evaluation of Grid-Side Commercial Storage Project," Energies, MDPI, vol. 14(4), pages 1-17, February.
    13. Jicheng Fang & Yifei Wang & Zhen Lei & Qingshan Xu, 2022. "Control Strategy and Performance Analysis of Electrochemical Energy Storage Station Participating in Power System Frequency Regulation: A Case Study of the Jiangsu Power Grid," Sustainability, MDPI, vol. 14(15), pages 1-31, July.
    14. Lu, Shuai & Gu, Wei & Zhou, Jinhui & Zhang, Xuesong & Wu, Chenyu, 2018. "Coordinated dispatch of multi-energy system with district heating network: Modeling and solution strategy," Energy, Elsevier, vol. 152(C), pages 358-370.
    15. Stanislav Chicherin & Vladislav Mašatin & Andres Siirde & Anna Volkova, 2020. "Method for Assessing Heat Loss in A District Heating Network with A Focus on the State of Insulation and Actual Demand for Useful Energy," Energies, MDPI, vol. 13(17), pages 1-15, September.
    16. Shams, Mohammad H. & Shahabi, Majid & Khodayar, Mohammad E., 2018. "Stochastic day-ahead scheduling of multiple energy Carrier microgrids with demand response," Energy, Elsevier, vol. 155(C), pages 326-338.
    17. Wang, Qi & Miao, Cairan & Tang, Yi, 2022. "Power shortage support strategies considering unified gas-thermal inertia in an integrated energy system," Applied Energy, Elsevier, vol. 328(C).
    18. Golmohamadi, Hessam & Larsen, Kim Guldstrand & Jensen, Peter Gjøl & Hasrat, Imran Riaz, 2022. "Integration of flexibility potentials of district heating systems into electricity markets: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 159(C).
    19. Zhang, Youjun & Hao, Junhong & Ge, Zhihua & Zhang, Fuxiang & Du, Xiaoze, 2021. "Optimal clean heating mode of the integrated electricity and heat energy system considering the comprehensive energy-carbon price," Energy, Elsevier, vol. 231(C).
    20. Yu, Xiaobing & Duan, Yuchen & Luo, Wenguan, 2022. "A knee-guided algorithm to solve multi-objective economic emission dispatch problem," Energy, Elsevier, vol. 259(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:13:y:2020:i:5:p:1073-:d:326758. 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.