IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v13y2020i18p4834-d414183.html
   My bibliography  Save this article

A Coordinated Dispatching Model Considering Generation and Operation Reserve in Wind Power-Photovoltaic-Pumped Storage System

Author

Listed:
  • Dai Cui

    (School of Electrical Engineering, Shenyang University of Technology, Shenyang 100084, China
    State Grid Liaoning Electric Power Co., Ltd., Shenyang 100084, China)

  • Fei Xu

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

  • Weichun Ge

    (School of Electrical Engineering, Shenyang University of Technology, Shenyang 100084, China
    State Grid Liaoning Electric Power Co., Ltd., Shenyang 100084, China)

  • Pengxiang Huang

    (College of Electrical Engineering & New Energy, China Three Gorges University, Yichang 443000, China)

  • Yunhai Zhou

    (College of Electrical Engineering & New Energy, China Three Gorges University, Yichang 443000, China)

Abstract

Large-scale grid integration of renewable energy increases the uncertainty and volatility of power systems, which brings difficulties to output planning and reserve decision-making of power system units. In this paper, we innovatively combined the non-parametric kernel density estimation method and scenario method to describe the uncertainty of renewable energy outputs, and obtained a representative set of renewable energy output scenarios. In addition, we proposed a new method to determine the reserve capacity demand. Further, we derived the quantitative relationship between the reserve demand and the power system reliability index, which was used as the constraint condition of a day-ahead power generation dispatch. Finally, a coordinated dispatching model of power generation and reserve was established, which had the lowest penalty for curtailment of wind power and photovoltaic, as well as the lowest total operating cost for thermal power units, gas power units, and pumped storage power station. By simulating three different working conditions, the proposed model was compared with the traditional deterministic model. Results showed that our proposed method significantly improved system efficiency while maintaining system reliability.

Suggested Citation

  • Dai Cui & Fei Xu & Weichun Ge & Pengxiang Huang & Yunhai Zhou, 2020. "A Coordinated Dispatching Model Considering Generation and Operation Reserve in Wind Power-Photovoltaic-Pumped Storage System," Energies, MDPI, vol. 13(18), pages 1-24, September.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:18:p:4834-:d:414183
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/13/18/4834/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/13/18/4834/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Yumin Xu & Yansheng Lang & Boying Wen & Xiaonan Yang, 2019. "An Innovative Planning Method for the Optimal Capacity Allocation of a Hybrid Wind–PV–Pumped Storage Power System," Energies, MDPI, vol. 12(14), pages 1-14, July.
    2. Jiayu Cheng & Dongliang Duan & Xiang Cheng & Liuqing Yang & Shuguang Cui, 2020. "Probabilistic Microgrid Energy Management with Interval Predictions," Energies, MDPI, vol. 13(12), pages 1-23, June.
    3. Kaplani, E. & Kaplanis, S., 2012. "A stochastic simulation model for reliable PV system sizing providing for solar radiation fluctuations," Applied Energy, Elsevier, vol. 97(C), pages 970-981.
    4. Wang, Wenxiao & Li, Chaoshun & Liao, Xiang & Qin, Hui, 2017. "Study on unit commitment problem considering pumped storage and renewable energy via a novel binary artificial sheep algorithm," Applied Energy, Elsevier, vol. 187(C), pages 612-626.
    5. Miklós Gyalai-Korpos & László Zentkó & Csaba Hegyfalvi & Gergely Detzky & Péter Tildy & Nóra Hegedűsné Baranyai & Gábor Pintér & Henrik Zsiborács, 2020. "The Role of Electricity Balancing and Storage: Developing Input Parameters for the European Calculator for Concept Modeling," Sustainability, MDPI, vol. 12(3), pages 1-26, January.
    6. Jianhua Chen & Wenchuan Wu & Boming Zhang & Bin Wang & Qinglai Guo, 2013. "A Spinning Reserve Allocation Method for Power Generation Dispatch Accommodating Large-Scale Wind Power Integration," Energies, MDPI, vol. 6(10), pages 1-25, October.
    7. Daniel Vázquez Pombo & Florin Iov & Daniel-Ioan Stroe, 2019. "A Novel Control Architecture for Hybrid Power Plants to Provide Coordinated Frequency Reserves," Energies, MDPI, vol. 12(5), pages 1-17, March.
    8. Fu, Yiwei & Lu, Zongxiang & Hu, Wei & Wu, Shuang & Wang, Yiting & Dong, Ling & Zhang, Jietan, 2019. "Research on joint optimal dispatching method for hybrid power system considering system security," Applied Energy, Elsevier, vol. 238(C), pages 147-163.
    9. Soumyadeep Nag & Kwang Y. Lee, 2020. "Network and Reserve Constrained Economic Analysis of Conventional, Adjustable-Speed and Ternary Pumped-Storage Hydropower," Energies, MDPI, vol. 13(16), pages 1-15, August.
    10. Lingxi Zhang & Yutian Zhou & Damian Flynn & Joseph Mutale & Pierluigi Mancarella, 2017. "System-Level Operational and Adequacy Impact Assessment of Photovoltaic and Distributed Energy Storage, with Consideration of Inertial Constraints, Dynamic Reserve and Interconnection Flexibility," Energies, MDPI, vol. 10(7), pages 1-34, July.
    11. Ilias G. Marneris & Pandelis N. Biskas & Anastasios G. Bakirtzis, 2017. "Stochastic and Deterministic Unit Commitment Considering Uncertainty and Variability Reserves for High Renewable Integration," Energies, MDPI, vol. 10(1), pages 1-25, January.
    12. Liu, Hailiang & Brown, Tom & Andresen, Gorm Bruun & Schlachtberger, David P. & Greiner, Martin, 2019. "The role of hydro power, storage and transmission in the decarbonization of the Chinese power system," Applied Energy, Elsevier, vol. 239(C), pages 1308-1321.
    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. Hongbin Zhu & Xiang Gao & Lei Zhao & Xiaoshun Zhang, 2023. "Decomposition-Based Multi-Classifier-Assisted Evolutionary Algorithm for Bi-Objective Optimal Wind Farm Energy Capture," Energies, MDPI, vol. 16(9), pages 1-22, April.
    2. Xian Yang & Ye Cai & Yijia Cao & Shaowei Duan & Liang Tang & Zhijian Jia, 2022. "The Semi-Scheduling Mode of Multi-Energy System Considering Risk–Utility in Day-Ahead Market," Energies, MDPI, vol. 15(21), pages 1-15, November.
    3. Siripha Junlakarn & Radhanon Diewvilai & Kulyos Audomvongseree, 2022. "Stochastic Modeling of Renewable Energy Sources for Capacity Credit Evaluation," Energies, MDPI, vol. 15(14), pages 1-27, July.

    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. Zhang, Menghan & Yang, Zhifang & Lin, Wei & Yu, Juan & Dai, Wei & Du, Ershun, 2021. "Enhancing economics of power systems through fast unit commitment with high time resolution," Applied Energy, Elsevier, vol. 281(C).
    2. Jiang, Sufan & Gao, Shan & Pan, Guangsheng & Zhao, Xin & Liu, Yu & Guo, Yasen & Wang, Sicheng, 2020. "A novel robust security constrained unit commitment model considering HVDC regulation," Applied Energy, Elsevier, vol. 278(C).
    3. Cui, Qi & He, Ling & Han, Guoyi & Chen, Hao & Cao, Juanjuan, 2020. "Review on climate and water resource implications of reducing renewable power curtailment in China: A nexus perspective," Applied Energy, Elsevier, vol. 267(C).
    4. Cervantes, Jairo & Choobineh, Fred, 2018. "Optimal sizing of a nonutility-scale solar power system and its battery storage," Applied Energy, Elsevier, vol. 216(C), pages 105-115.
    5. Toufani, Parinaz & Nadar, Emre & Kocaman, Ayse Selin, 2022. "Short-term assessment of pumped hydro energy storage configurations: Up, down, or closed?," Renewable Energy, Elsevier, vol. 201(P1), pages 1086-1095.
    6. Manzano, J.M. & Salvador, J.R. & Romaine, J.B. & Alvarado-Barrios, L., 2022. "Economic predictive control for isolated microgrids based on real world demand/renewable energy data and forecast errors," Renewable Energy, Elsevier, vol. 194(C), pages 647-658.
    7. Ahmed Alzahrani & Hussain Alharthi & Muhammad Khalid, 2019. "Minimization of Power Losses through Optimal Battery Placement in a Distributed Network with High Penetration of Photovoltaics," Energies, MDPI, vol. 13(1), pages 1-16, December.
    8. Evangelos S. Chatzistylianos & Georgios N. Psarros & Stavros A. Papathanassiou, 2024. "Insights from a Comprehensive Capacity Expansion Planning Modeling on the Operation and Value of Hydropower Plants under High Renewable Penetrations," Energies, MDPI, vol. 17(7), pages 1-29, April.
    9. Wesseh, Presley K. & Benjamin, Nelson I. & Lin, Boqiang, 2022. "The coordination of pumped hydro storage, electric vehicles, and climate policy in imperfect electricity markets: Insights from China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 160(C).
    10. Carlos A. Platero & José A. Sánchez & Christophe Nicolet & Philippe Allenbach, 2019. "Hydropower Plants Frequency Regulation Depending on Upper Reservoir Water Level," Energies, MDPI, vol. 12(9), pages 1-15, April.
    11. Anh Ngoc-Lan Huynh & Ravinesh C. Deo & Duc-Anh An-Vo & Mumtaz Ali & Nawin Raj & Shahab Abdulla, 2020. "Near Real-Time Global Solar Radiation Forecasting at Multiple Time-Step Horizons Using the Long Short-Term Memory Network," Energies, MDPI, vol. 13(14), pages 1-30, July.
    12. Li, Chaoshun & Wang, Wenxiao & Chen, Deshu, 2019. "Multi-objective complementary scheduling of hydro-thermal-RE power system via a multi-objective hybrid grey wolf optimizer," Energy, Elsevier, vol. 171(C), pages 241-255.
    13. Dranka, Géremi Gilson & Ferreira, Paula & Vaz, A. Ismael F., 2021. "A review of co-optimization approaches for operational and planning problems in the energy sector," Applied Energy, Elsevier, vol. 304(C).
    14. Khalilpour, Rajab & Vassallo, Anthony, 2016. "Planning and operation scheduling of PV-battery systems: A novel methodology," Renewable and Sustainable Energy Reviews, Elsevier, vol. 53(C), pages 194-208.
    15. Haobo Shi & Yanping Xu & Baodi Ding & Jinsong Zhou & Pei Zhang, 2023. "Long-Term Solar Power Time-Series Data Generation Method Based on Generative Adversarial Networks and Sunrise–Sunset Time Correction," Sustainability, MDPI, vol. 15(20), pages 1-19, October.
    16. Woo-Jung Kim & Yu-Seok Lee & Yeong-Han Chun & Hae-Seong Jeong, 2022. "Reserve-Constrained Unit Commitment Considering Adjustable-Speed Pumped-Storage Hydropower and Its Economic Effect in Korean Power System," Energies, MDPI, vol. 15(7), pages 1-23, March.
    17. Masoud Agabalaye-Rahvar & Amin Mansour-Saatloo & Mohammad Amin Mirzaei & Behnam Mohammadi-Ivatloo & Kazem Zare & Amjad Anvari-Moghaddam, 2020. "Robust Optimal Operation Strategy for a Hybrid Energy System Based on Gas-Fired Unit, Power-to-Gas Facility and Wind Power in Energy Markets," Energies, MDPI, vol. 13(22), pages 1-21, November.
    18. Rodríguez, Fermín & Martín, Fernando & Fontán, Luis & Galarza, Ainhoa, 2021. "Ensemble of machine learning and spatiotemporal parameters to forecast very short-term solar irradiation to compute photovoltaic generators’ output power," Energy, Elsevier, vol. 229(C).
    19. Huang, Kangdi & Liu, Pan & Kim, Jong-Suk & Xu, Weifeng & Gong, Yu & Cheng, Qian & Zhou, Yong, 2023. "A model coupling current non-adjustable, coming adjustable and remaining stages for daily generation scheduling of a wind-solar-hydro complementary system," Energy, Elsevier, vol. 263(PB).
    20. Xie, Kang & Hui, Hongxun & Ding, Yi & Song, Yonghua & Ye, Chengjin & Zheng, Wandong & Ye, Shuiquan, 2022. "Modeling and control of central air conditionings for providing regulation services for power systems," Applied Energy, Elsevier, vol. 315(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:18:p:4834-:d:414183. 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.