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CN-116070386-B - Intelligent design and evaluation method and system for water network engineering

CN116070386BCN 116070386 BCN116070386 BCN 116070386BCN-116070386-B

Abstract

The invention discloses an intelligent design and evaluation method and system for water network engineering, wherein the method comprises the following steps of S1, acquiring data of water network engineering reconstruction nodes; S2, constructing a node water supply characteristic evaluation model according to data of the water network engineering reconstruction nodes, and determining a reconstruction direction, S3, constructing and selecting a proper reconstruction scheme according to the node water supply characteristic evaluation model, and calculating relevant parameters and control conditions required by the reconstruction scheme to obtain a reconstruction model, and S4, constructing a control model related to the reconstruction model to realize intelligent reconstruction of the water network engineering. The invention provides the characteristic evaluation of the water supply network engineering, forms the transformation benefit evaluation mechanism of the water supply network engineering, builds a matched control system under the working guidance of the evaluation mechanism, and not only realizes the intelligent operation of the water network system, but also achieves the aim of intensive utilization of water resources and efficient development of water energy.

Inventors

  • SHANG YIZI
  • LI XIAOFEI
  • SHANG LING
  • GONG JIAGUO
  • YE YUNTAO
  • JIANG YUNZHONG

Assignees

  • 中国水利水电科学研究院

Dates

Publication Date
20260512
Application Date
20230302

Claims (8)

  1. 1. The intelligent design and evaluation method for the water network engineering is characterized by comprising the following steps of: S1, acquiring data of a water network engineering reconstruction node; s2, constructing a node water supply characteristic evaluation model according to data of the water network engineering reconstruction node, and determining a reconstruction direction; S3, constructing and selecting a proper reconstruction scheme according to the node water supply characteristic evaluation model, and calculating related parameters and control conditions required by the reconstruction scheme to obtain a reconstruction model; s4, constructing a control model related to the transformation model, and realizing intelligent transformation of the water network engineering; Wherein constructing the node water supply characteristic evaluation model comprises: According to the formula: Obtaining the importance degree of the current category index Quality value of water supply characteristic Scoring process parameters under weight influence Wherein, the method comprises the steps of, Representing the maximum value of a value interval specified by the current category; Representing the minimum value of a value interval specified by the current category; A scoring value representing a percentage of each of the sub-categories j of the current category i, totaling k, s representing that the current scoring value is the s-th of the k values; a constant indicating a pass of the score; representing the weight obtained by the subjective weighting method, Representing the weight obtained by the entropy method; According to the formula: obtaining normalized water supply guarantee index And a water supply network engineering external environment safety index EEI, wherein, Indicating that the water supply network engineering has no fault; indicating reservoir water storage and drainage failure; Indicating instability of channel diversion and diversion control; representing a water distribution imbalance of the water diversion outlet; representing a set of values for which PI has not been normalized; the comparison of the water supply characteristic performance values under the continuous prediction after the node transformation is represented; Representing administrative area; representing a predicted duration span; represents the value conversion coefficient of the water supply network engineering, GFI is a service value index and GSI is an intensity index of water supply and water consumption; According to the formula: obtaining the operation safety index ESI of the water supply network engineering, wherein, Represents the joint probability density of the random variables of the node population, N represents the node number of the bayesian network, Representing a parameter set, d representing samples in the sample set, X representing a vector composed of random variables, and X representing corresponding elements in the vector; Representing the weight allocation under each category; Corresponding node ; Representing a risk state engineering safety characterization constant; Engineering safety characterization constants representing daily operational state risks; And U represents the node of the u-th Bayesian network; Represent the first A plurality of nodes; Represent the first A plurality of nodes; Represent the first The categories.
  2. 2. The intelligent water network engineering design and evaluation method according to claim 1, wherein the step S2 comprises the following steps: s2-1, performing principal component analysis according to data of the water network engineering reconstruction nodes to obtain data from which subjective influences are removed; S2-2, performing principal component analysis on the data with subjective influences removed to obtain a data set; s2-3, constructing a node water supply characteristic evaluation model; S2-4, evaluating the data in the data set by using the node water supply characteristic evaluation model, and determining the transformation direction.
  3. 3. The intelligent water network engineering design and evaluation method according to claim 2, wherein the step S2-3 comprises the following steps: S2-3-1, according to the formula: Obtaining average water supply performance pjxn and average difference pjcy, wherein N is the number of databases, namely the number of categories; The data quantity is the quantity of data in the category I, B represents the performance metric value corresponding to the sub-category j in the category I, I represents j+1 sub-categories in the category I; S2-3-3, constructing an confusion matrix comprising a false positive class, a false negative class and a true class according to the actual measurement value and the predicted value of the evaluation information class, wherein the true class represents that the water supply characteristic corresponds to an influence element in the evaluation class accurately; s2-3-3, according to the formula: Obtaining harmonic mean value FM of precision and recall rate, carrying out transformation benefit evaluation, wherein, Representing the number of real classes; Representing the number of false positive classes; representing the number of elements in the confusion matrix corresponding to the false negative class; JD represents precision ZHL represents recall; S2-3-4, according to the formula: Obtaining the influence evaluation of the continuity of the transformed nodes Wherein, the method comprises the steps of, A quality value representing a water supply characteristic prior to prediction; A quality value representing the predicted water supply characteristic; Representing the temporal prediction variable under the influence of persistence, A predicted constant indicative of a negative water supply characteristic under a delayed action, The lg represents the logarithm of the bottom 10; s2-3-5, according to the formula: obtaining the average water supply service value of the current node Wherein, the method comprises the steps of, The water supply service value of a single node under the category i; The service value is supplied to the whole current node; An area representing a current class of water supply radiation range; representing the value coefficient under class i; s2-3-6, according to the formula: the sensitivity coefficient MX is obtained, wherein, The initial value of the service value before node transformation is set; The service value after node transformation is predicted and adjusted; representing a value coefficient of the performance of the given water supply characteristic before the integral transformation of the node under the category i; representing the value coefficient of the performance characteristics of the established water supply after the integral reconstruction of the nodes under the category i; s2-3-7, according to the formula: Obtaining a water supply safety index WPSI, wherein, 、 、 Respectively represent 、 、 Weights of (2); S2-3-8, according to the water supply safety index WPSI, the sensitivity coefficient MX and the average water supply service value of the current node Impact evaluation of continuity after modification of modified nodes Harmonic mean FM of precision and recall, importance of current class index Quality value of water supply characteristic Scoring process parameters under weight influence The average water supply performance pjxn and the average difference pjcy construct a node water supply characteristic assessment model.
  4. 4. The intelligent water network engineering design and evaluation method according to claim 3, wherein the specific implementation manner of the step S3 is as follows: s3-1, constructing four reconstruction schemes, and selecting an optimal reconstruction scheme according to a node water supply characteristic evaluation model; S3-2, calculating key parameters and control limiting conditions of each scheme, and selecting corresponding key parameters and control limiting conditions according to the optimal modification scheme; s3-3, constructing a reconstruction model according to the key parameters and the control limiting conditions of the optimal reconstruction scheme.
  5. 5. The intelligent water network engineering design and evaluation method according to claim 4, wherein the four modification schemes in the step S3-1 are respectively as follows: The water supply-power generation parallel linkage control device and system gate control water delivery channel modification scheme comprises an upstream water network main flow or reservoir, a drainage channel, a control gate, a generator set, a stilling pool, a downstream river channel and a water diversion gate, wherein the upstream water network main flow or reservoir flows to the drainage channel and the drainage channel, the drainage channel and the upstream water network main flow or reservoir control water flow through the water diversion gate, the drainage channel and the drainage channel are distributed in parallel, water in the drainage channel flows to the generator set through the control gate, water in the generator set and the drainage channel flow to be collected into the stilling pool, and water in the stilling pool flows to the downstream river channel; the water supply-power generation series linkage control device and the gate control water delivery channel modification scheme of the system comprise a reservoir or a water network main flow channel, a gate, a channel, a cross flow unit, an overflow weir, a water diversion gate, a downstream channel and a plurality of water diversion channels, wherein the gate is used for controlling the water flow of the reservoir or the water network main flow channel to enter the channel; The inverted siphon throttle gate linkage control device and the gate control water pipeline modification scheme of the system comprise a channel, an inlet gate, a front tank, an inverted siphon, an outlet gate and a downstream channel, wherein the speed of water flow of the channel to the front tank is controlled through the inlet gate; The complex water network diversion water port linkage control device and the system are improved in scheme that the complex water network diversion water port linkage control device comprises a water network main flow canal, a regulating tank, a plurality of control gates and a plurality of diversion ports corresponding to the control gates, wherein the water network main flow canal and the regulating tank are connected through the gates, and the regulating tank and the plurality of diversion ports are connected through the corresponding control gates.
  6. 6. The intelligent water network engineering design and evaluation method according to claim 5, wherein the key parameters and control constraints of the four modification schemes of step S3-2 include the following parameters: channel ultra-high design parameters, overflow weir parameters, reservoir capacity, stilling pool, regulating pool parameters, long-distance water diversion device parameters, water diversion ports and gate parameters and control limiting conditions, wherein: The channel ultra-high design parameters comprise an ultra-high value required by the flow scale and extra ultra-high required by the zero flow water level; The reservoir capacity, the stilling pool and the regulating pool parameters comprise overflow weir parameters, total water head of a water diversion main channel in a water supply network engineering system, water depth required by the stilling pool to realize the stilling function, water quantity change coefficient of diversion, flow required by a diversion port under the condition of water supply guarantee, regulating pool volume required under the condition of insufficient water supply, storage capacity required by the regulating pool under the condition of excessive water supply, maximum water diversion capacity, regulating pool capacity, ultrahigh regulating pool length of the regulating pool, width of the regulating pool and reservoir capacity when reservoir capacity samples accord with normal distribution and reservoir capacity when reservoir capacity samples do not accord with normal distribution; the parameters of the overflow weir comprise that the top width is set to be 4m, wherein, the earth-rock weir is provided with an impermeable body of 0.6m, 20m is taken between transverse seams, the safety coefficient K is more than or equal to 3 by using a shearing-resistant formula, the main tensile stress of stress deformation is less than 0.2MPa, and the conditions of the height and the width of the stilling pool are simultaneously met; The parameters and control rules of the long-distance water diversion device comprise energy loss of a water body with unit weight of a siphon pipeline in a unit flow, linear distance of an inverted siphon pipeline, control rules of total water head of a pipeline with high pressure at a certain point of the pipeline, pressure lines, basic equations of the inverted siphon pipeline, turbulence quantity generation items of coupling condition processing results of the pipeline and a sluice under unsteady flow dispersion and turbulence energy generation items of a step average value; The water diversion port and gate parameters comprise gate passing flow, total flow, water diversion flow of the water diversion port, sensitivity index of the water diversion port, hydraulic sensitivity index before and after the gate of the current gate and overflow of the diversion main channel; The control constraints include a system of basic equations for unsteady flow computation, continuous equations in an eccentric format, incremental linearization, improved conversion of momentum equations, control equations, and conditional constraint solving time domain finite difference equations.
  7. 7. The intelligent water network engineering design and evaluation method according to claim 6, wherein the specific implementation manner of the step S4 is as follows: S4-1, acquiring real-time monitoring data of a water network system according to various hydrologic monitoring stations laid out and distributed in the existing water network engineering; S4-2, a data processing system is arranged on the monitoring station, interference and noise are removed from the real-time monitoring data, and a current water network state monitoring data set which is consistent with the data and is relevant to the data is obtained through fuzzification processing, so that instant feedback is formed; S4-3, establishing a predictive control mode of the water flow state of the water network according to the instant feedback result, the set water supply of the water network, the water quantity target of the water receiving side and the expected water supply process path; S4-4, obtaining an adjusted predictive fuzzy control model by adopting a control effect fuzzy evaluation and feedback correction method according to the established predictive control mode, and realizing intelligent reconstruction of the nodes.
  8. 8. A system applied to the intelligent design and evaluation method of the water network engineering according to any one of claims 1-7, which is characterized by comprising a data acquisition module, a node water supply characteristic evaluation module, a reconstruction model construction module and a control module; The data acquisition module is used for acquiring data of the water network engineering reconstruction node; the node water supply characteristic evaluation module is used for constructing a node water supply characteristic evaluation model according to the data of the water network engineering reconstruction node and determining the reconstruction direction; The reconstruction model construction module is used for constructing and selecting a proper reconstruction scheme according to the node water supply characteristic evaluation model and calculating related parameters and control conditions required by the reconstruction scheme to obtain a reconstruction model; And the control module is used for constructing a control model related to the transformation model and realizing intelligent transformation of the water network engineering.

Description

Intelligent design and evaluation method and system for water network engineering Technical Field The invention relates to the fields of intelligent water conservancy, water network engineering and intelligent control, in particular to an intelligent design and evaluation method and system for water network engineering. Background The hydraulic engineering which is manually built on the basis of natural river and lake water systems, has the functions of diversion, water use and stable operation and serves multiple objects is generally called complex water supply engineering, and almost all canal systems buildings such as mountain reservoir, plain reservoir, water delivery open channel, hydropower station, tunnel, aqueduct, inverted siphon, river diversion sluice, pump station, flood control dike and the like are included. If the guiding ideas of safe water delivery, accurate monitoring and scientific scheduling are implemented, the water supply engineering can be operated efficiently, economically and scientifically. The traditional water supply network engineering can meet the application of water regulation of the most basic self-water supply side, diversion by canal system, water diversion of the water receiving side through a plurality of branch channels and the like, but because hardware, equipment, devices and structural design are single, a control management system is still equipped according to the traditional water supply technology, real-time automatic scheduling cannot be realized, flexible progress cannot be realized, and the system stability of the whole water supply engineering is insufficient. Not only causes the waste of water resources and energy sources, but also increases the water supply cost, and further does not meet the requirements on reasonable development of water resources and improvement of application benefits. In particular to aspects of water condition water regulation, control regulation, engineering safety and the like of a plurality of water supply objects, and the water supply system has the characteristics of randomness, multi-objective property, real-time property and the like of water demand target changes, and realizes reliable operation difficulty by more complicated water supply. The existing control decision system has the problems that the current situation is inaccurate in judgment, the model parameter calculation is limited, the fusion of a business function system and an actual model in control is insufficient, a channel control system lacks a buffer space, the accumulation and superposition of deviation and error in the control process exist, the connection and coordination of different working conditions are insufficient, the gate control is complex in mutual restriction on the channel hydrodynamic process, the flow and water level change is obvious due to the downstream tail water of a generator set, the control effect does not meet the timeliness and the refinement requirement, and the like. In a comprehensive view, the joint control of the multipoint gates of the current channel system has less work in the aspects of device design, structural layout, state measurement and identification, control mechanism and driving, digital twin application, fine decision coordination and engagement and the like. To realize scientific configuration of water resources, partition, grading and balanced distributed multipoint linkage control is required to be constructed, the interconnection layout of regional water supply is perfected, the requirements of water use, irrigation, diversion, ecology and the like are considered, and the water energy is further developed and utilized. But still face the following difficulties: (1) The existing water supply network engineering has the defects of standard and guide in installation, operation and maintenance, especially lacks the selection of devices and the design method thereof in the system architecture, and has inaccurate facility selection and irregular installation, thereby causing difficult layout and construction of proposed engineering measures. Not only is the compact structural requirement difficult to realize, but also the water level can not be quickly and quickly stabilized in a short distance, and the natural river can not be matched with the natural river to form natural-social binary fusion, so that the control and practical applicability are insufficient. Even in the intelligent transformation process, because the evaluation mechanism of the water supply network engineering lacks judgment driven by functional requirements and the control effect is set based on the certainty of actual requirements, the construction of the regional intelligent water network is not accurately positioned and the foundation is not accurate, the layout and construction of proposed engineering measures are difficult, and the practical method and path are deficient. (2) On one hand, the traditional hardware device is difficult to control