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A New Fluctuation Index: Characteristics and Application to Hydro-Wind Systems

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  • Xianxun Wang

    (State Key Laboratory of Water Resource and Hydropower Engineering Science, Wuhan University, Wuhan 430072, Hubei, China
    Hubei Collaborative Innovation Center for Water Resources Security, Wuhan 430072, Hubei, China)

  • Yadong Mei

    (State Key Laboratory of Water Resource and Hydropower Engineering Science, Wuhan University, Wuhan 430072, Hubei, China
    Hubei Collaborative Innovation Center for Water Resources Security, Wuhan 430072, Hubei, China)

  • Hao Cai

    (State Key Laboratory of Water Resource and Hydropower Engineering Science, Wuhan University, Wuhan 430072, Hubei, China
    Hubei Collaborative Innovation Center for Water Resources Security, Wuhan 430072, Hubei, China)

  • Xiangyu Cong

    (POWERCHINA Kunming Engineering Corporation Limited, Kunming 650051, Yunnan, China)

Abstract

Hydro-wind system output fluctuations are the primary factors used to assess the effects of hydropower on power companies compensating for wind power intermittency. Considering that most fluctuation indices can only characterize one aspect of fluctuations, namely, the quantitative or contour variations, we present a new index that uses the standard deviation (SD) and rotation angle to detect the quantitative variations and contour changes, respectively. Herein, the new index is compared with commonly used indices, specifically, the first-order difference, SD, and Richards-Baker flashiness indices. The results of tests performed using various processes and disposals show that: (1) when dealing with the process by moving average, repeating or overlay disposal, the new index performs comparably to the other indices, while when dealing with the process by zooming disposal, it more fully describes the fluctuation characteristics by taking both quantitative and contour variations into consideration; (2) when the new index is used to characterize the hydro-wind output fluctuations with different resources and capacities, the outcomes coincide with the mechanisms of hydro-wind systems. This study presents a new way to characterize the fluctuation of hydro-wind output.

Suggested Citation

  • Xianxun Wang & Yadong Mei & Hao Cai & Xiangyu Cong, 2016. "A New Fluctuation Index: Characteristics and Application to Hydro-Wind Systems," Energies, MDPI, vol. 9(2), pages 1-17, February.
    • Handle: RePEc:gam:jeners:v:9:y:2016:i:2:p:114-:d:64022
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    References listed on IDEAS

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    1. Huaichang Ge & Qinglai Guo & Hongbin Sun & Bin Wang & Boming Zhang & Wenchuan Wu, 2014. "A Load Fluctuation Characteristic Index and Its Application to Pilot Node Selection," Energies, MDPI, vol. 7(1), pages 1-15, January.
    2. Javier Marcos & Iñigo De la Parra & Miguel García & Luis Marroyo, 2014. "Control Strategies to Smooth Short-Term Power Fluctuations in Large Photovoltaic Plants Using Battery Storage Systems," Energies, MDPI, vol. 7(10), pages 1-27, October.
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    Cited by:

    1. Wang, Xianxun & Virguez, Edgar & Xiao, Weihua & Mei, Yadong & Patiño-Echeverri, Dalia & Wang, Hao, 2019. "Clustering and dispatching hydro, wind, and photovoltaic power resources with multiobjective optimization of power generation fluctuations: A case study in southwestern China," Energy, Elsevier, vol. 189(C).
    2. Kangping Wang & Pengjiang Ge & Naixin Duan & Jili Wang & Jinli Lv & Meng Liu & Bin Wang, 2023. "The Multi-Objective Optimal Scheduling of the Water–Wind–Light Complementary System Based on an Improved Pigeon Flock Algorithm," Energies, MDPI, vol. 16(19), pages 1-18, September.
    3. Wang, Xianxun & Mei, Yadong & Kong, Yanjun & Lin, Yuru & Wang, Hao, 2017. "Improved multi-objective model and analysis of the coordinated operation of a hydro-wind-photovoltaic system," Energy, Elsevier, vol. 134(C), pages 813-839.
    4. Hong Pan & Zhengliang Luo & Chenyang Hang & Yuan Zheng & Fang Feng & Xiaonan Zheng, 2024. "Optimization of Load Distribution Method for Hydropower Units Based on Output Fluctuation Constraint and Double-Layer Nested Model," Mathematics, MDPI, vol. 12(5), pages 1-17, February.
    5. Xinshuo Zhang & Guangwen Ma & Weibin Huang & Shijun Chen & Shuai Zhang, 2018. "Short-Term Optimal Operation of a Wind-PV-Hydro Complementary Installation: Yalong River, Sichuan Province, China," Energies, MDPI, vol. 11(4), pages 1-19, April.
    6. Han, Shuang & Zhang, Lu-na & Liu, Yong-qian & Zhang, Hao & Yan, Jie & Li, Li & Lei, Xiao-hui & Wang, Xu, 2019. "Quantitative evaluation method for the complementarity of wind–solar–hydro power and optimization of wind–solar ratio," Applied Energy, Elsevier, vol. 236(C), pages 973-984.
    7. Xianxun Wang & Lihua Chen & Qijuan Chen & Yadong Mei & Hao Wang, 2018. "Model and Analysis of Integrating Wind and PV Power in Remote and Core Areas with Small Hydropower and Pumped Hydropower Storage," Energies, MDPI, vol. 11(12), pages 1-24, December.
    8. Zida Song & Quan Liu & Zhigen Hu & Chunsheng Zhang & Jinming Ren & Zhexin Wang & Jianhai Tian, 2020. "Construction Diversion Risk Assessment for Hydropower Development on Sediment-Rich Rivers," Energies, MDPI, vol. 13(4), pages 1-20, February.
    9. Jie Li & Linjun Shi & Hao Fu, 2023. "Multi-Objective Short-Term Optimal Dispatching of Cascade Hydro–Wind–Solar–Thermal Hybrid Generation System with Pumped Storage Hydropower," Energies, MDPI, vol. 17(1), pages 1-20, December.
    10. Xiong, Hualin & Egusquiza, Mònica & Alberg Østergaard, Poul & Pérez-Díaz, Juan I. & Sun, Guoxiu & Egusquiza, Eduard & Patelli, Edoardo & Xu, Beibei & Duan, Hongjiang & Chen, Diyi & Luo, Xingqi, 2021. "Multi-objective optimization of a hydro-wind-photovoltaic power complementary plant with a vibration avoidance strategy," Applied Energy, Elsevier, vol. 301(C).

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