Joint Optimal Flood Control Operation of Large Scale Mixed Reservoirs
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MATEC Web of Conferences 246, 01088 (2018) https://doi.org/10.1051/matecconf/201824601088 ISWSO 2018 Joint optimal flood control operation of large scale mixed reservoirs Gang Zha1,2, Jianzhong Zhou1,2,a,Lu Chen1,2, Quansen Wang1,2, Chengwei Lu1,2,Xin Yang1,2 , Ling Dai1,2 and Chao Zhou3 1School of Hydropower and Information Engineering, Huazhong University of Science and Technology, Wuhan 430074, PR China 2Hubei Key Laboratory of Digital Valley Science and Technology, Huazhong University of Science and Technology, PR China 3Changjiang Institute of Survey, Planning, Design and Research, 430010 Wuhan, China Abstract. With the reservoir construction gradually completed, joint operation of reservoir groups is an important measure to realize reservoir flood control potential,but when the river basin is large, the flood channel routing and time-lag cannot be simplified, in addition, the curse of dimensionality is very difficult for model solving With the expansion of the number of reservoirs. These factors restrict the application of joint operation of large scale mixed reservoirs.In this study, The DP-POA cyclic iterative algorithm which is based on large scale system decomposed-coordinating method was proposed to solve the optimal problem considering the flood routing and time-lag.The upper Yangtze River is selected as a case study. 6 reservoirs, including the Three Gorges Reservoir(TGR)、Xiangjiaba Reservoir(XJB)、Xiluodu Reservoir (XLD)、 Pubugou Reservoir (PBG)、Goupitan Reservoir (GPT) and Tingzikou Reservoir (TZK)are taken into accounts.Compared with current operation of reservoirs independent,results demonstrate that the method can effectively reduce the maximum operating water level of TGR and flood diversion in the lower reaches of the TGR. Therefore, the safety of the flood control points along the river has been largely improved based on the proposed method. 1 Introduction is also more and more long, so that these factors which can be ignored in small watershed area become very Flood disaster is one of the most damaging natural important ; Third, There are hydraulic connections disasters, due to its high frequency and enormous between series reservoirs, so that many methods that can destruction strength[1]. Reservoir is an effective be applied to parallel reservoirs without hydraulic engineering measure for flood control and disaster connections are not suitable for series reservoirs ; Last reduction. Optimization techniques for planning, design, but not least, the increasing number of reservoirs and the and management of complex water resources systems complex hydraulic connections between reservoirs make have longstanding use in water resources engineering [2]. it difficult to find feasible initial solutions, which have a such as linear programming [3], dynamic programming great impact on the convergence of algorithms such as (DP)[4], nonlinear programming [5], and folded dynamic POA. These problems bring great challenges to the programming (FDP) [6]. A variety of common operating modeling and solving of the joint flood control operation rules have been derived for single-purpose reservoirs in of large-scale mixed reservoir group. series and in parallel[7]. Labadie[8] discusses the For the above problems, A DP-POA cyclic iterative technological challenges and rewards of integrated algorithm based on large system decomposition and optimization of reservoir systems. coordination theory is proposed. The upper Yangtze Flood management reservoirs regulate inflows to River is selected as a case study. 6 reservoirs, including reduce downstream flood damages[9]. These methods the Three Gorges Reservoir(TGR) 、 Xiangjiaba have been applied to small scale reservoir groups and Reservoir(XJB)、Xiluodu Reservoir (XLD)、Pubugou achieved effective results. However, with the increase of Reservoir (PBG) 、 Goupitan Reservoir (GPT) and the number of reservoirs and the increase of catchment area, some factors that can be ignored in the small Tingzikou Reservoir (TZK) are taken into accounts. reservoir groups become more and more influential and Compared with current operation of reservoirs independent,results demonstrate that the method can cannot be ignored. First, The time required for the model calculation increases rapidly with the increase of the effectively reduce the maximum operating water level of TGR and flood diversion in the lower reaches of the number of reservoirs so that it is eventually unacceptable, for example, DP cannot be applied to joint flood control TGR. Therefore, the safety of the flood control points of more than four reservoirs because of the dimension along the river has been largely improved based on the proposed method. disaster problem ; Second, With the increase of river length, the phenomenon of flood peak attenuation and loss is more and more serious, and the propagation delay a Corresponding author:Jianzhong Zhou: [email protected] © The Authors, published by EDP Sciences. This is an open access article distributed under the terms of the Creative Commons Attribution License 4.0 (http://creativecommons.org/licenses/by/4.0/). MATEC Web of Conferences 246, 01088 (2018) https://doi.org/10.1051/matecconf/201824601088 ISWSO 2018 2 Methodology combined to be one objective by using weight method, The final objective function is shown below: As shown in Fig. 1,The algorithm includes the following steps : First, Simplify the series reservoirs into a virtual NTMTZZmax− 1 minFa=+++Δ min( (ii bQcQdQt22 ) (e )) reservoir ; Second, establish joint flood control iitijtjjtj21− ,,,(1) itjt====1111ZZii Operating model; Third, from upstream to downstream, where F is Objective function value;i is the number from tributary to main stream, DP algorithm is used to reservoir;N is the total number of reservoir;t is operating calculate reservoir optimization one by one and obtain period number;j is the number of flood control points;M the initial solution of reservoir group joint operation ; Z max Fourth, taking the DP algorithm as the initial solution, is the total number of flood control points; i is Z 1 the POA algorithm considering phenomenon of flood maximum operate level of reservoir i; i is the Z 2 peak attenuation and loss is used to solve the joint flood allowable minimum water level of reservoir i; i is the control model ;Fifth The calculation results of virtual ai reservoirs are decomposed into serial reservoirs. allowable maximum water level of reservoir i; is the Weight coefficient of the maximum adjusted flood level Q of reservoir i; t,i is the ohtflow of the reservoir i at b peroid t; i is the weight coefficient of the squared Q outflow of reservoir i; tj, is the ohtflow of the flood c control point i at peroid t; j is the weight coefficient of Qe the squared outflow of flood control point i; tj, is the value exceed the safe flow of the flood control point i at Δ d peroid t; t is the length of operating period; j is the weight coefficient of the value exceed the safe flow of the flood control point j. 2.1.2 Constraints (1) The lowest and the highest water level constraints: min≤≤ max Zit,,,ZZ it it (2) where Zi,t is the ith reservoir i water level at period t; Z min Z max it, and it, are the ith reservoir allowable minimum and maximum water level at period t. (2) The water balance constraint: =+−Δ VVit,,1,, it− () IQ it it t (3) V V where it, and it,-1 are the ith reservoir storage status at I Q the beginning and the end of time period t; it, and it, are the ith reservoir inflow and outflow; Δt is the peroid interval. (3) The minimum outflow and the outflow capacity Figure 1. Algorithm flow chart constraints: min≤≤ max QQQit,,, it it (4) Q Qmin 2.1 Operating model where it, is the ith reservoir outflow at time t; it, and Qmax Based on the flood control demand and the flood control it, are the ith reservoir allowable minimum and capability of the basin, the integrated flood control maximum outflow at time t; model of reservoir group is established. (4) The outflow amplitude constraint: −≤Δ QQit,,1 it− Q i (5) ΔQ 2.1.1 Objective function where i is the ith reservoir allowable amplitude of outflow. The joint flood control operation of large-scale reservoir (5) Limits of discharge for downstream flood control often involves multiple objectives.(1) the excess flood point capacity of flood control points is the least;(2) the =+Δ≤’ max maximum adjusted flood level of the reservoir is lowest qQjt,, it qq t j (6) to reduce flood risk;(3) minimum sum of squares of flow q where jt, is the discharge at time t for the jth flood at flood control points;(4) minimum sum of squares of Q’ outflow of reservoir. The above four objectives are control point downstream. it, is the discharge of the ith reservoir considering the flood routing at the jth flood 2 MATEC Web of Conferences 246, 01088 (2018) https://doi.org/10.1051/matecconf/201824601088 ISWSO 2018 Δq located in Dadu River which is the tributary of the control points, and t is the inflow in the interval zones between the ith reservoir and the flood control point Minjiang River, Flood control aim of Pubugou reservoir q max is to ensure that Chengkun railway meet flood control downstream. j is the allowed maximum discharge for standards and cooperate with other reservoirs to reduce the jth flood control point downstream. flood losses of river basin; Tingzikou reservoir is located in Jialing River, Flood control aim of Pubugou 2.2 Flood channel routing reservoir is to ensure that Langzhou meet flood control standards and cooperate with other reservoirs to reduce This paper uses Muskingum method to calculate flood flood losses of river basin; Goupitan reservoir is routing : located in Wujiang River, Flood control aim of Goupitan = + + O2 C0 I 2 C1 I1 C2 O1 (7) reservoir is to ensure that Sinan meet flood control where standards and cooperate with other reservoirs to reduce flood losses of river basin.