Abstract
Compared to conventional operating rules (CORs) for multiple reservoirs in a basin, joint flood control operation can reduce flood loss in downstream cities. The CORs adopted for most reservoirs ignore among–basin coordination, leading to incomplete consideration of the problem of the compensation effect between the reservoir flood control storage capacity (FCSC) and uneven flood composition distribution. A parameterization–simulation–optimization framework was applied in this study to design reservoir joint optimized flood control operating charts (OFCOCs) and analyse the compensation effect between reservoirs. The non–fixed FCSC nodes method and guaranteed output were respectively adopted to bound the end water levels in reservoirs with low inflow but high FCSC values or those adopting dynamic flood limited water level (DFLWL) return to the flood limited water level (FLWL). Choosing the Xijiang River basin (XRB) as an example, the optimized OFCOC designed in this study achieved a better peak–cutting effect than that of the CORs. The peak–cutting rate of the OFCOC was 5.77%, while that of the CORs was 3.41%. Adoption of the non–fixed FCSC nodes method and guaranteed output could meet the constraint of water level return to the FLWL. Reasonable operating chart design could provide a guideline for scientific flood control.
Similar content being viewed by others
Availability of Data and Materials
The observed data used in this study are not publicly accessible. These data have been collected and supported by the Hydrological Center of Guangxi Zhuang Autonomous Region. Anyone who wish to use these data should contact Lihua Chen and Hang Chen to obtain permission.
References
Afshar MH (2013) Extension of the constrained particle swarm optimization algorithm to optimal operation of multi-reservoirs system. Int J Elec Power 51:71–81. https://doi.org/10.1016/j.ijepes.2013.02.035
Bayesteh M, Azari A (2021) Stochastic Optimization of reservoir operation by applying hedging rules. J Water Res Plan Man 147(2). https://doi.org/10.1061/(ASCE)WR.1943-5452.0001312
Chang J, Wang X, Li Y, Wang Y, Zhang H (2018) Hydropower plant operation rules optimization response to climate change. Energy 160:886–897. https://doi.org/10.1016/j.energy.2018.07.066
Che D, Mays LW (2015) Development of an optimization/simulation model for real-time flood-control operation of river-reservoirs systems. Water Resour Manag 29(11):3987–4005. https://doi.org/10.1007/s11269-015-1041-8
Chen L, Teng X, Pan Z, Liu W (2019) Composition and encountering law of floods at Wuzhou station from main stream and tributaries in Xijiang River Basin. J China Hydrol 39(6):80–84. https://doi.org/10.19797/j.cnki.1000-0852.20180296 (in Chinese)
Cheng CT, Chau KW (2002) Three-person multi-objective conflict decision in reservoir flood control. Eur J Oper Res 142(3):625–631. https://doi.org/10.1016/S0377-2217(01)00319-8
Ethteram M, Mousavi S, Karami H, Farzin S, Deo R, Othman FB, Chau K, Sarkamaryan S, Singh VP, El-Shafie A (2018) Bat algorithm for dam-reservoir operation. Environ Earth Sci 77:510. https://doi.org/10.1007/s12665-018-7662-5
Guo X, Qin T, Lei X, Jiang Y, Wang H (2016) Advances in derivation method for multi-reservoir joint operation policy. J Hydroelectr Eng 35(1):19–27. https://doi.org/10.11660/slfdxb.20160103 (in Chinese)
He S, Guo S, Yin J, Liao Z, Li H, Liu Z (2022) A novel impoundment framework for a mega reservoir system in the upper Yangtze River basin. Appl Energ 305:117792. https://doi.org/10.1016/j.apenergy.2021.117792
Hossain MS, El-Shafie A, Mahzabin MS, Zawawi MH (2018) System performances analysis of reservoir optimization-simulation model in application of artificial bee colony algorithm. Neural Comput Appl 30(7):2101–2112. https://doi.org/10.1007/s00521-016-2798-2
Jahandideh-Tehrani M, Bozorg-Haddad O, Loaiciga HA (2019) Application of non-animal-inspired evolutionary algorithms to reservoir operation: an overview. Environ Monit Assess 191(7):1–21. https://doi.org/10.1007/s10661-019-7581-2
Jiang Z, Liu P, Ji C, Zhang H, Chen Y (2019) Ecological flow considered multi-objective storage energy operation chart optimization of large-scale mixed reservoirs. J Hydrol 577:123949. https://doi.org/10.1016/j.jhydrol.2019.123949
Kennedy J, Eberhart R (1995) Particle swarm optimization. Proc IEEE Int Conf Neural Netw 4:1942–1948. https://doi.org/10.1109/ICNN.1995.488968
Lei X, Zhang J, Wang H, Wang M, Khu S, Li Z, Tan Q (2018) Deriving mixed reservoir operating rules for flood control based on weighted non-dominated sorting genetic algorithm II. J Hydrol 564:967–983. https://doi.org/10.1016/j.jhydrol.2018.07.075
Li A, Zhang J, Zhong Z, Ding Y (2013) Study on joint flood control operation for leading reservoirs in the upper Changjiang River. J Hydraul Eng 44(1):59–66. https://doi.org/10.13243/j.cnki.slxb.2013.01.013 (in Chinese)
Macian-Sorribes H, Pulido-Velazquez M (2020) Inferring efficient operating rules in multireservoir water resource systems: A review. Wiley Interdiscip Rev Water 7(1):e1400. https://doi.org/10.1002/wat2.1400
Moeini R, Babaei M (2017) Constrained improved particle swarm optimization algorithm for optimal operation of large scale reservoir: proposing three approaches. Evol Syst 8(4):287–301. https://doi.org/10.1007/s12530-017-9192-x
Pan Z, Chen L, Teng X (2020) Research on joint flood control operation rule of parallel reservoir group based on aggregation-decomposition method. J Hydrol 590:125479. https://doi.org/10.1016/j.jhydrol.2020.125479
Prakash O, Srinivasan K, Sudheer KP (2015) Adaptive multi-objective simulation-optimization framework for dynamic flood control operation in a river-reservoir system. Hydrol Res 46(6):893–911. https://doi.org/10.2166/nh.2015.171
Rahimi H, Ardakani MK, Ahmadian M, Tang X (2020) Multi-reservoir utilization planning to optimize hydropower energy and flood control simultaneously. Environ Process 7:41–52. https://doi.org/10.1007/s40710-019-00404-8
Rani D, Moreira MM (2010) Simulation-Optimization Modeling: A survey and potential application in reservoir systems operation. Water Resour Manag 24(6):1107–1138. https://doi.org/10.1007/s11269-009-9488-0
Saadatpour M, Javaheri S, Afshar A, Solis SS (2021) Optimization of selective withdrawal systems in hydropower reservoir considering water quality and quantity aspects. Expert Syst Appl. https://doi.org/10.1016/j.eswa.2021.115474
Soghrati F, Moeini R (2020) Deriving optimal operation of reservoir proposing improved artificial bee colony algorithm: standard and constrained versions. J Hydroinform 22(2):263–280. https://doi.org/10.2166/hydro.2019.125
Tan Q, Wang X, Liu P, Lei X, Cai S, Wang H, Ji Y (2017) The dynamic control bound of flood limited water level considering capacity compensation regulation and flood spatial pattern uncertainty. Water Resour Manag 31(1):143–158. https://doi.org/10.1007/s11269-016-1515-3
Turgeon A (1980) Optimal operation of multireservoir power systems with stochastic inflows. Water Resour Res 16(2):275–283. https://doi.org/10.1029/WR016i002p00275
Yang G, Guo S, Liu P, Li L, Liu Z (2017) Multiobjective cascade reservoir operation rules and uncertainty analysis based on PA-DDS algorithm. J Water Resour Plan Manag 143(7):04017025. https://doi.org/10.1061/(ASCE)WR.1943-5452.0000773
Zhang J, Li Z, Wang X, Lei X, Liu P, Feng M, Khu S, Wang H (2019) A novel method for deriving reservoir operating rules based on flood classification-aggregation-decomposition. J Hydrol 568:722–734. https://doi.org/10.1016/j.jhydrol.2018.10.032
Zhong P, Kong Y, Wang X, Xu B, Wang Y (2014) Study on method for estimation of dynamic control bounds of flood limited water level in cascade reservoirs. J Hydroelectr Eng 33(5):36–43 (in Chinese)
Zhu D, Mei Y, Xu X, Liu Z, Wu Z, Cai H (2021) Optimal operation of a parallel multireservoir system for flood control using a stagewise compensation method. Water Resour Manag 35(6):1689–1710. https://doi.org/10.1007/s11269-021-02803-9
Acknowledgements
We appreciate the contributions of the editor and anonymous reviewers whose comments and suggestions significantly improved this article.
Funding
This research was financially supported by the National Natural Science Foundation of China (grant numbers 52069002 and 51669003) and Nanning Communications Asset Management CO., LTD (Grant number NNJZ-NWDC–(2021) –12).
Author information
Authors and Affiliations
Contributions
Conceptualization: LH C and X T; Data curation: LH C and J Y; Methodology: J T and X T; Software: J T; Writing–original draft: LH C, J Y and H C; Writing–review & editing: LH C, H C and XF L.
Corresponding author
Ethics declarations
Ethical Approval
All authors have seen and agreed with the contents of the manuscript and are looking forward to publishing this paper on “Water Resources Management” journal.
Consent to Participate
All authors provided explicit consent to participate in this work.
Consent to Publish
All authors gave explicit consent to publish this manuscript.
Competing Interest
The authors declare that they have no financial interests.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Appendix
Appendix
Rights and permissions
About this article
Cite this article
Chen, L., Yu, J., Teng, J. et al. Optimizing Joint Flood Control Operating Charts for Multi–reservoir System Based on Multi–group Piecewise Linear Function. Water Resour Manage 36, 3305–3325 (2022). https://doi.org/10.1007/s11269-022-03202-4
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11269-022-03202-4