IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v16y2023i24p7940-d1295521.html
   My bibliography  Save this article

Optimal Configuration Analysis Method of Energy Storage System Based on “Equal Area Criterion”

Author

Listed:
  • Yizheng Li

    (Key Laboratory of Smart Grid of Ministry of Education, Tianjin University, Tianjin 300072, China
    State Grid Economic and Technological Research Institute Co., Ltd., Beijing 102209, China)

  • Yuan Zeng

    (Key Laboratory of Smart Grid of Ministry of Education, Tianjin University, Tianjin 300072, China)

  • Zhidong Wang

    (State Grid Economic and Technological Research Institute Co., Ltd., Beijing 102209, China)

  • Lang Zhao

    (State Grid Economic and Technological Research Institute Co., Ltd., Beijing 102209, China)

  • Yao Wang

    (Economic and Technological Research Institute of State Grid Shanxi Electric Power Co., Ltd., Taiyuan 030021, China)

Abstract

In order to solve the problem of randomness and volatility caused by the rapid growth of renewable energy (RE), energy storage systems (ESSs)—as an important means of regulation—can effectively improve the flexible regulation capacity of power systems utilizing a high proportion of RE. Most of the current ESS capacity configuration procedures are carried out based on the typical scenario method or time series production simulation. This method tends to determine the size of the ESS configuration through multiple trial simulations. Uncertainty of simulation prediction data can result in the existence of an excess capacity or lack of configured capacity. In addition, this method reflects the ESS demand under specific targets, but it fails to fully utilize RE generation characteristics. The configuration process lacks the mathematical mechanism of RE consumption, and the calculation process is too complicated. In view of the shortcomings of traditional ESS optimal configuration methods, this paper examines the mathematical mechanism of RE consumption and proposes the ESS optimal configuration analysis method based on “equal area criterion”. First, the principle of RE consumption is analyzed and the “RE consumption characteristic curve” is proposed according to RE characteristics. In addition, a working principle diagram of RE consumption, including ESS, is constructed to visually show the consumption capacity of RE and the working position of ESS. Then, the ESS optimal configuration process, based on the “equal area criterion”, is proposed to achieve an accurate match between ESS capacity demand and RE consumption targets. Finally, the power grid of a region in China is taken as an example. We prove that the proposed method can save 1.41 × 10 3 MWh of ESS capacity and provide a more “mathematical” and “convenient” systematic solution for RE consumption and ESS optimization compared to the production simulation method.

Suggested Citation

  • Yizheng Li & Yuan Zeng & Zhidong Wang & Lang Zhao & Yao Wang, 2023. "Optimal Configuration Analysis Method of Energy Storage System Based on “Equal Area Criterion”," Energies, MDPI, vol. 16(24), pages 1-29, December.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:24:p:7940-:d:1295521
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/16/24/7940/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/16/24/7940/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Feng, Cong & Zhang, Jie & Zhang, Wenqi & Hodge, Bri-Mathias, 2022. "Convolutional neural networks for intra-hour solar forecasting based on sky image sequences," Applied Energy, Elsevier, vol. 310(C).
    2. Takele Ferede Agajie & Ahmed Ali & Armand Fopah-Lele & Isaac Amoussou & Baseem Khan & Carmen Lilí Rodríguez Velasco & Emmanuel Tanyi, 2023. "A Comprehensive Review on Techno-Economic Analysis and Optimal Sizing of Hybrid Renewable Energy Sources with Energy Storage Systems," Energies, MDPI, vol. 16(2), pages 1-26, January.
    3. Mohammad Mehdi Davari & Hossein Ameli & Mohammad Taghi Ameli & Goran Strbac, 2022. "Impact of Local Emergency Demand Response Programs on the Operation of Electricity and Gas Systems," Energies, MDPI, vol. 15(6), pages 1-20, March.
    Full references (including those not matched with items on IDEAS)

    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. Paletta, Quentin & Arbod, Guillaume & Lasenby, Joan, 2023. "Omnivision forecasting: Combining satellite and sky images for improved deterministic and probabilistic intra-hour solar energy predictions," Applied Energy, Elsevier, vol. 336(C).
    2. Lilla Barancsuk & Veronika Groma & Dalma Günter & János Osán & Bálint Hartmann, 2024. "Estimation of Solar Irradiance Using a Neural Network Based on the Combination of Sky Camera Images and Meteorological Data," Energies, MDPI, vol. 17(2), pages 1-25, January.
    3. Larbi Chrifi-Alaoui & Saïd Drid & Mohammed Ouriagli & Driss Mehdi, 2023. "Overview of Photovoltaic and Wind Electrical Power Hybrid Systems," Energies, MDPI, vol. 16(12), pages 1-35, June.
    4. Spyros Giannelos & Stefan Borozan & Marko Aunedi & Xi Zhang & Hossein Ameli & Danny Pudjianto & Ioannis Konstantelos & Goran Strbac, 2023. "Modelling Smart Grid Technologies in Optimisation Problems for Electricity Grids," Energies, MDPI, vol. 16(13), pages 1-15, June.
    5. Liu, Jingxuan & Zang, Haixiang & Cheng, Lilin & Ding, Tao & Wei, Zhinong & Sun, Guoqiang, 2023. "A Transformer-based multimodal-learning framework using sky images for ultra-short-term solar irradiance forecasting," Applied Energy, Elsevier, vol. 342(C).
    6. Takele Ferede Agajie & Armand Fopah-Lele & Isaac Amoussou & Ahmed Ali & Baseem Khan & Om Prakash Mahela & Ramakrishna S. S. Nuvvula & Divine Khan Ngwashi & Emmanuel Soriano Flores & Emmanuel Tanyi, 2023. "Techno-Economic Analysis and Optimization of Hybrid Renewable Energy System with Energy Storage under Two Operational Modes," Sustainability, MDPI, vol. 15(15), pages 1-31, July.
    7. Masoumeh Sharifpour & Mohammad Taghi Ameli & Hossein Ameli & Goran Strbac, 2023. "A Resilience-Oriented Approach for Microgrid Energy Management with Hydrogen Integration during Extreme Events," Energies, MDPI, vol. 16(24), pages 1-18, December.
    8. Zhou, Guangzhao & Guo, Zanquan & Sun, Simin & Jin, Qingsheng, 2023. "A CNN-BiGRU-AM neural network for AI applications in shale oil production prediction," Applied Energy, Elsevier, vol. 344(C).
    9. Georgios Yiasoumas & Lazar Berbakov & Valentina Janev & Alessandro Asmundo & Eneko Olabarrieta & Andrea Vinci & Giovanni Baglietto & George E. Georghiou, 2023. "Key Aspects and Challenges in the Implementation of Energy Communities," Energies, MDPI, vol. 16(12), pages 1-24, June.
    10. Katarzyna Piwowar-Sulej & Mariusz Sołtysik & Szymon Jarosz & Ryszard Pukała, 2023. "The Linkage between Renewable Energy and Project Management: What Do We Already Know, and What Are the Future Directions of Research?," Energies, MDPI, vol. 16(12), pages 1-26, June.
    11. José Luis Muñoz-Pincheira & Lautaro Salazar & Felipe Sanhueza & Armin Lüer-Villagra, 2024. "Temporal Complementarity Analysis of Wind and Solar Power Potential for Distributed Hybrid Electric Generation in Chile," Energies, MDPI, vol. 17(8), pages 1-23, April.
    12. Paletta, Quentin & Hu, Anthony & Arbod, Guillaume & Lasenby, Joan, 2022. "ECLIPSE: Envisioning CLoud Induced Perturbations in Solar Energy," Applied Energy, Elsevier, vol. 326(C).
    13. Huang, Xiaoqiao & Liu, Jun & Xu, Shaozhen & Li, Chengli & Li, Qiong & Tai, Yonghang, 2023. "A 3D ConvLSTM-CNN network based on multi-channel color extraction for ultra-short-term solar irradiance forecasting," Energy, Elsevier, vol. 272(C).
    14. Isaac Amoussou & Emmanuel Tanyi & Lajmi Fatma & Takele Ferede Agajie & Ilyes Boulkaibet & Nadhira Khezami & Ahmed Ali & Baseem Khan, 2023. "The Optimal Design of a Hybrid Solar PV/Wind/Hydrogen/Lithium Battery for the Replacement of a Heavy Fuel Oil Thermal Power Plant," Sustainability, MDPI, vol. 15(15), pages 1-29, July.
    15. Liu, Jingxuan & Zang, Haixiang & Ding, Tao & Cheng, Lilin & Wei, Zhinong & Sun, Guoqiang, 2023. "Harvesting spatiotemporal correlation from sky image sequence to improve ultra-short-term solar irradiance forecasting," Renewable Energy, Elsevier, vol. 209(C), pages 619-631.
    16. Muhammad Waqas & Mohsin Jamil & Ashraf Ali Khan, 2024. "Hybrid Power System Design and Dynamic Modeling for Enhanced Reliability in Remote Natural Gas Pipeline Control Stations," Energies, MDPI, vol. 17(7), pages 1-24, April.

    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:24:p:7940-:d:1295521. 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.