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Value of Medium-range Precipitation Forecasts in Inflow Prediction and Hydropower Optimization

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  • Guolei Tang
  • Huicheng Zhou
  • Ningning Li
  • Feng Wang
  • Yajun Wang
  • Deping Jian

Abstract

This paper presents an inflow-forecasting model and a Piecewise Stochastic Dynamic Programming model (PSDP) to investigate the value of the Quantitative Precipitation Forecasts (QPFs) comprehensively. Recently medium-range quantitative precipitation forecasts are addressed to improve inflow forecasts accuracy. Revising the Ertan operation, a simple hydrological model is proposed to predict 10-day average inflow into the Ertan dam using GFS-QPFs of 10-day total precipitation during wet season firstly. Results show that the reduction of average absolute errors (ABE) is of the order of 15% and the improvement in other statistics is similar, compared with those from the currently used AR model. Then an improved PSDP is proposed to generate monthly or 10-day operating policies to incorporate forecasts with various lead-times as hydrologic state variables. Finally performance of the PSDP is compared with alternative SDP models to evaluate the value of the GFS-QPFs in hydropower generation. The simulation results demonstrate that including the GFS-QPFs is beneficial to the Ertan reservoir inflow forecasting and hydropower generation dispatch. Copyright Springer Science+Business Media B.V. 2010

Suggested Citation

  • Guolei Tang & Huicheng Zhou & Ningning Li & Feng Wang & Yajun Wang & Deping Jian, 2010. "Value of Medium-range Precipitation Forecasts in Inflow Prediction and Hydropower Optimization," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 24(11), pages 2721-2742, September.
    • Handle: RePEc:spr:waterr:v:24:y:2010:i:11:p:2721-2742
    DOI: 10.1007/s11269-010-9576-1
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    Citations

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    Cited by:

    1. Majid Dehghani & Hossein Riahi-Madvar & Farhad Hooshyaripor & Amir Mosavi & Shahaboddin Shamshirband & Edmundas Kazimieras Zavadskas & Kwok-wing Chau, 2019. "Prediction of Hydropower Generation Using Grey Wolf Optimization Adaptive Neuro-Fuzzy Inference System," Energies, MDPI, vol. 12(2), pages 1-20, January.
    2. Pedram Pishgah Hadiyan & Ramtin Moeini & Eghbal Ehsanzadeh & Monire Karvanpour, 2022. "Trend Analysis of Water Inflow Into the Dam Reservoirs Under Future Conditions Predicted By Dynamic NAR and NARX Models," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(8), pages 2703-2723, June.
    3. Qiao-feng Tan & Guo-hua Fang & Xin Wen & Xiao-hui Lei & Xu Wang & Chao Wang & Yi Ji, 2020. "Bayesian Stochastic Dynamic Programming for Hydropower Generation Operation Based on Copula Functions," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(5), pages 1589-1607, March.
    4. Wang, Chong & Ju, Ping & Wu, Feng & Pan, Xueping & Wang, Zhaoyu, 2022. "A systematic review on power system resilience from the perspective of generation, network, and load," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(C).
    5. Lu, Di & Wang, Bende & Wang, Yaodong & Zhou, Huicheng & Liang, Qiuhua & Peng, Yong & Roskilly, Tony, 2015. "Optimal operation of cascade hydropower stations using hydrogen as storage medium," Applied Energy, Elsevier, vol. 137(C), pages 56-63.
    6. Wei Xu & Xiaoli Zhang & Anbang Peng & Yue Liang, 2020. "Deep Reinforcement Learning for Cascaded Hydropower Reservoirs Considering Inflow Forecasts," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(9), pages 3003-3018, July.
    7. Jie Chen & François Brissette, 2015. "Combining Stochastic Weather Generation and Ensemble Weather Forecasts for Short-Term Streamflow Prediction," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(9), pages 3329-3342, July.
    8. Pao-Shan Yu & Tao-Chang Yang & Chen-Min Kuo & Yi-Tai Wang, 2014. "A Stochastic Approach for Seasonal Water-Shortage Probability Forecasting Based on Seasonal Weather Outlook," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(12), pages 3905-3920, September.

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