Plant-network-river-lake integrated dispatching method and system based on butterfly optimization algorithm

Abstract

The invention discloses a factory network river-lake integrated scheduling method and system based on a butterfly optimization algorithm, and solves the problems that resource scheduling is not systematic and the optimization effect is poor in urban water environment management. The method comprises the following steps: firstly, collecting and sorting data information such as a rain sewage pipe network, pump gate characteristics and a water system in a research area, constructing one-dimensional and two-dimensional hydrodynamic models, and simulating dynamic behaviors of a drainage system; on the basis, a meta-heuristic butterfly optimization algorithm is adopted to construct an optimization scheduling model, and an optimization scheme conforming to a scheduling target is generated through the steps of population initialization, fitness calculation, iterative search of an optimal solution and the like. In the optimization process, scheduling parameters are adjusted in combination with real-time monitoring data, and the effectiveness and practicability of the scheme are ensured.

Description

Technical Field

[0001] The present invention belongs to the field of urban water environment management, and in particular relates to a plant-grid-river-lake integrated dispatching method and system based on a butterfly optimization algorithm. Background Art

[0002] At present, the water resource dispatching and control in cities is mostly carried out around a certain link in sewage treatment plants, drainage networks, urban lakes and canals, and rarely from the level of complete plant-network-river-lake integration; and even if some cities have built an integrated dispatching system, there is a lack of a dispatching scheme providing method that can assist managers in making intelligent decisions. Therefore, the technology of the present invention aims to disclose a plant-network-river-lake integrated dispatching method and system based on a butterfly optimization algorithm, which is used to assist in the integrated dispatching of urban water environment, and provides an optimization algorithm for generating a preferred dispatching scheme.

[0003] There are two main types of existing technical solutions for integrated dispatching of power plants, grids, rivers and lakes: One type is to conduct single-module or joint dispatch of plant networks, rivers and lakes based on monitoring data, combined with historical dispatch plans, dispatch procedures or the experience and quality of managers. The quality of dispatch plans and dispatch results depends to a large extent on the quality of the practitioners themselves and the richness of the historical records of the dispatch management center.

[0004] The other type is to use common single-objective or multi-objective optimization algorithms to provide optimization solutions through algorithm calculations. However, due to the limitations of the algorithm itself, in some cases, due to poor algorithm convergence or insufficient algorithm robustness, it may not be possible to provide a correct optimized scheduling solution, which has poor practicality.

[0005] Disadvantages of existing technology: One is that the scheduling effect is unclear: because there is no systematic scheduling simulation and calculation, and no comparison and trial calculation of a large number of scheduling plans, it is difficult for the dispatching personnel to know the impact of the scheduling operation on the entire drainage system, and it is unclear whether there is a better scheduling plan.

[0006] The second type is that even if scheduling simulation and optimized scheduling calculation are adopted, the algorithm effect of optimized scheduling may not be good: one part is directly calculated and compared through random generation of solutions, without clear optimization direction and algorithm logic; the other part is limited by the poor convergence and robustness of the algorithm itself, and the optimized calculation may not be able to give a normal and reasonable optimized scheduling solution. Summary of the invention

[0007] The technical problem to be solved by the present invention is to provide a method and system for integrated dispatching of power plants, networks, rivers and lakes based on the butterfly optimization algorithm. The present invention creates a dispatching model that can be built based on the integrated dispatching model of power plants, networks, rivers and lakes. The dispatching scheme is trial-calculated and determined through a meta-heuristic algorithm (butterfly optimization algorithm) that has been newly proposed and verified in recent years. The dispatching control operation and maintenance management personnel are provided with a dispatching scheme that has been verified and optimized by the system, which assists in dealing with the problem that managers have difficulty in making decisions and determining dispatching schemes due to the complexity of the integrated dispatching system, thereby improving the operational efficiency of management units and the level of smart urban management.

[0008] In order to solve the above technical problems, the technical solution adopted by the present invention is: A method for integrated dispatching of power plants, grids, rivers and lakes based on butterfly optimization algorithm, the steps are as follows: S1. Determine the research area, collect and organize the data and information in the research area, including rainwater and sewage pipe network data, rainwater and sewage catchment area data, historical data of drainage households, hydraulic characteristics data of pumps and gates, water system hydraulic data, historical dispatching data and dispatching procedures; the water system hydraulic data is the water system hydraulic data of lakes, canals or open channels; organize the data and information into formatted data content; S2. Based on the one-dimensional hydrodynamic model and the two-dimensional hydrodynamic model of the pipeline, and according to the formatted data content obtained in step S1, a power plant network river-lake integrated scheduling model of the scheduling and research area is constructed. The power plant network river-lake integrated scheduling model is used to dynamically calculate and evaluate the results of scheduling control; S3, based on the plant-grid-river-lake integrated dispatching model constructed in step S2, an optimization dispatching model is constructed according to the meta-heuristic butterfly algorithm, and the optimization dispatching model is used to calculate and generate an optimization dispatching plan that meets the dispatching target; S4. Based on the optimization scheduling model constructed in step S3, according to the set optimization target, combined with the real-time monitoring data of the pipeline network liquid level meter, river and lake water level meter and pump gate monitoring device, the optimization scheduling calculation is performed to obtain the scheduling plan and scheduling calculation results that meet the optimization target, and the key data in the plant network river and lake scheduling link are displayed. The scheduling plan of the optimization target is the optimal plan; the optimal plan is compared with the plan set by the dispatcher or the plan generated by the default scheduling procedure, and the optimal plan record is saved in the system for the dispatcher to use and learn.

[0009] Preferably, the content of the profile information includes: (1) Data on the rainwater and sewage pipe network mainly include the structure, material, burial depth, and topological information of inspection well nodes of the rainwater and sewage pipe network; (2) Pump-gate hydraulic characteristics data include pump-gate properties and gate pump design information: gate size, gate shape, gate flow capacity, pump energy efficiency curve and pump QH curve; (3) Rainwater and sewage catchment zoning data and water system hydraulic data, including GIS data on rainwater and sewage zoning in the study area, lake and river connectivity and water system vector data, and underwater topography and DEM data of lakes and canals; (4) Historical data of drainage households, historical dispatching information and dispatching procedures, including historical sewage drainage monitoring data of major drainage households, rainfall monitoring data, and pipeline network liquid level data at the time of rainfall.

[0010] Preferably, the sub-steps of step S2 are: Step S2.1, constructing a one-dimensional hydrodynamic model of a pipe channel and a two-dimensional hydrodynamic model of a lake and a river respectively, and transmitting data through the pipe channel hydrodynamic model and the two-dimensional hydrodynamic model in the calculation to connect the calculation data of the two models; Step S2.2, the drainage forecast data and rainfall forecast data of the drainage users are used to provide boundary conditions for the integrated scheduling model, and the real-time monitoring data of river and lake water levels and pipeline network liquid levels are used to provide initial conditions. Based on the scheduling parameters of different pumps, gates and pipeline networks as input variables of the model, the plant network, river and lake integrated scheduling model is calculated and the results are obtained.

[0011] Preferably, the method for constructing the one-dimensional hydrodynamic model in step S2.1 is as follows: (1) Based on the rainwater and sewage pipe network data, catchment area data, and water system hydraulic data, the pipe network topology and pipe network attributes in the study area are written into a structured data file. The relevant geographic elevation and burial depth information are written into the file according to the pipe network topology and node coordinates. The location of the gate pump and its connection relationship with the pipe network are expressed in the data file to form a parameter input file of the pipe network grid and attributes in the study area. (2) Based on the canal hydrodynamic model, combined with the pump-sluice hydrodynamic curve or relationship, fill in the relevant parameters in the model formula according to the parameter input file for calculation; The pipe hydrodynamic model used is developed based on the one-dimensional Saint-Venant shallow water equations, which can be used to describe the unsteady flow evolution process of one-dimensional open channels and underground pipe networks. The equations are composed of the continuity equation and the momentum equation, which are expressed as: ; ; Where: A is the area of ​​the water-passing section of the river / pipeline (㎡); x is the distance (m); y is the water depth of the river / pipeline (m). The liquid level and water level can be calculated based on the buried depth of the pipeline or the geographical elevation of the open channel; g is the acceleration of gravity (m / s 2 ); S f is the friction slope coefficient.

[0012] The pump-sluice hydrodynamic model used consists of a gate model and a pump station model; Gate model: By dividing the gate flow process into orifice flow and weir flow process, the hydrodynamic calculation of the gate can be performed; Among them, when the quotient of the gate opening e and the water depth H0 in front of the gate (e / H0) is less than 0.65, it is regarded as orifice flow, and the formula of orifice flow process can be expressed as: ; In the formula, Q0 represents the orifice flow rate, σ represents the flooding coefficient; m represents the comprehensive orifice flow coefficient; b represents the width of the water-passing section (m); e represents the gate opening (m); and g represents the acceleration of gravity. When the quotient of the gate opening e and the water depth H0 in front of the gate (e / H0) is greater than 0.65, it is regarded as weir flow. The formula of weir flow process can be expressed as: ; Where Q1 represents the weir flow rate, C w Represents the weir flow coefficient.

[0013] Pump station model: Based on the hydraulic characteristic curve of the pump, considering that the flow rate of the pump station changes continuously with the head difference between the inlet and outlet nodes, the flow value of the corresponding head difference of the pump is obtained by linear interpolation.

[0014] Preferably, the method for constructing the two-dimensional hydrodynamic model of lakes and rivers in step S2.1 is as follows: (1) Based on the lake-river connectivity, water system data, underwater topography, and DEM data collected and collated in step 1, combined with GIS satellite maps and vector data, the scope of the river and lake model in the study area is determined, and an unstructured triangular unit finite element mesh is constructed. Values ​​are assigned to each mesh node based on the underwater topography and DEM data; (2) Combined with the collected GIS data on the connection between pipeline networks and rivers and lakes, the coordinates of the connection points between pipelines and rivers and lakes are sorted out, and the points of adjacent nodes of the coordinates are defined as data exchange points, which are used to transfer the one-dimensional pipeline hydraulic calculation results and the two-dimensional river and lake hydraulic calculation results; (3) Based on the real-time monitoring data, the initial water depth and water level data are assigned to each grid node. Based on the terrain elevation at the grid node, the rainfall runoff data and the pipe calculation results are used as the boundary input of the model to perform two-dimensional hydraulic calculations: The two-dimensional hydrodynamic model of rivers and lakes used is developed and constructed based on the two-dimensional Saint-Venant shallow water equations, which can be used to describe the flow characteristics and processes of two-dimensional rivers and lakes. The equations consist of the continuity equation and the momentum equation, and their conservation form can be expressed as: ; ; ; Where x and y represent the two directions of the Cartesian coordinates; t represents time; g represents gravitational acceleration; h represents water depth; u and v represent the vertical average velocity in the x and y directions, respectively; E(U) and G(U) represent interface fluxes; S(U) represents the source term; z b represents the bottom elevation; n represents the bottom roughness.

[0015] Preferably, in step S3, the steps of constructing an optimization scheduling model based on the meta-heuristic butterfly algorithm are as follows: Step S3.1: Initialize the position x of each butterfly in the population i , population size N, maximum number of iterations T, dimensional space D, sensory modality c, power index a and dynamic transition probability p; Step S3.2: Calculate the position of each butterfly based on the integrated dispatching model of the power plant, grid, river and lake, obtain key data indicators, and calculate the fragrance coefficient fitness f of each butterfly based on the data indicators. i , select the current optimal fitness f g and its corresponding position g, and generate a random number r between [0,1]; Step S3.3, if r < p, then a global search is performed on the butterflies in the dimensional space, and the butterflies gather towards the individuals with the strongest fragrance (highest fitness). Otherwise, a local search is performed, and the butterfly individuals move randomly; Step S3.4, calculate the fitness of each butterfly's position after the position update, and update the optimal position; Step S3.5: Determine whether the end condition is met. If so, the algorithm ends and the optimal solution obtained by the algorithm is output. If not, go to step 2.

[0016] Preferably, the position of the butterfly is a scheduling scheme containing the parameters of each schedulable facility; the dimensional space contains all possible scheduling situations of the schedulable facilities, and its boundary is the scheduling range of each schedulable facility; the calculation formulas of each function in the optimization scheduling model are as follows: For the fragrance coefficient fitness, the calculation formula is: ; Where I i represents the stimulus intensity, which is represented by x in the present invention. i The result of normalizing the optimization target value calculated by the scheduling plan; For the dynamic conversion probability, at the tth iteration, its calculation formula is: ; In the formula, represents the dynamic conversion probability under the tth iteration; For the case of r<p in step 3-3, at the tth iteration, the butterfly position update calculation formula is: ; For the case of r ≥ p, at the tth iteration, the butterfly position update calculation formula is: ; In the formula, x i ,x j ,x k Respectively represent the positions of the i, j, and k butterflies.

[0017] Preferably, in step S4, the steps of performing optimization scheduling calculation and obtaining a scheduling solution that meets the optimization target are as follows: Step S4.1, sort out the real-time monitored pipe network liquid level data, river and lake water level data, and pump and gate facility working condition data and input them into the integrated dispatching model of the plant network and rivers and lakes to ensure that the model can be directly calculated based on the rainfall forecast data and the given dispatching parameters; Step S4.2, define the optimization target, consider the liquid level of the prone point of the pipeline network as the optimization target, the lower the liquid level, the better the scheduling plan; Step S4.3, execute the optimization scheduling model calculation based on step three. After the calculation is completed, the calculation results are processed and sorted to obtain the results of the optimization scheduling plan, including the pipeline network liquid level, river and lake water level, pump and gate scheduling process data, etc.

[0018] A plant-grid-river-lake integrated dispatching system based on a butterfly optimization algorithm adopts the plant-grid-river-lake integrated dispatching method based on a butterfly optimization algorithm.

[0019] A computer device, characterized in that it comprises: one or more processors; The processor is used to store one or more programs; When the one or more programs are executed by the one or more processors, a plant-grid-river-lake integrated scheduling method based on a butterfly optimization algorithm as described in any one of claims 1 to 8 is implemented. The present invention can achieve the following beneficial effects: 1. The present invention can perform optimization scheduling calculations based on monitoring data, scheduling parameters and forecast data and display the results. It can calculate the optimized scheduling plan through the optimization algorithm. The plan can improve the optimization target compared with the previous plan or personnel experience, and can provide experience for the scheduling personnel, effectively improving the intelligent management level of the scheduling management unit.

[0020] 2. By introducing the butterfly optimization algorithm, managers can be assisted to make more intelligent and scientific decisions. This not only improves the quality of the scheduling plan, but also reduces the dependence on the experience and quality of practitioners. The butterfly optimization algorithm is used to calculate and determine the scheduling plan. Compared with traditional manual scheduling or automatic scheduling based on simple algorithms, the present invention can find the optimal solution more quickly and accurately, thereby improving the operating efficiency of the entire system.

[0021] 3. The present invention realizes an integrated process from monitoring to analysis to optimization by integrating multiple data sources (such as pipe network level gauges, river and lake water level gauges, pump and gate monitoring devices, etc.), which helps to promote the development of urban management towards intelligence and enhance the comprehensive management capabilities of the city.

[0022] 4. Through the construction and optimization calculation of the integrated model of the plant network, river and lake, the limited urban water resources can be more reasonably allocated and utilized, reducing waste and improving resource utilization. The optimal dispatching plan is recorded and saved in the system for dispatchers to use and learn, which can not only accumulate experience and knowledge, but also continuously improve the dispatching strategy to form a virtuous circle. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] The present invention will be further described below in conjunction with the accompanying drawings and embodiments: Figure 1 It is a flow chart of the present invention; Figure 2 This is a schematic diagram of the flow chart of the optimization scheduling model of the present invention; Figure 3 This is a schematic diagram of the integrated dispatching model of the power plant, network, river and lake of the present invention; Figure 4 This is a schematic curve diagram of the optimization scheduling calculation results of the present invention (liquid level changes at prone points). DETAILED DESCRIPTION

[0024] The preferred solution is Figures 1 to 4 As shown, a method and system for integrated dispatching of power plants, grids, rivers and lakes based on butterfly optimization algorithm, S1. Determine the research area, collect and organize the data and information in the research area, including rainwater and sewage pipe network data, rainwater and sewage catchment area data, historical data of drainage households, hydraulic characteristics data of pumps and gates, water system hydraulic data, historical dispatching data and dispatching procedures; the water system hydraulic data is the water system hydraulic data of lakes, canals or open channels; organize the data and information into formatted data content; The content of the information includes: (1) Data on the rainwater and sewage pipe network mainly include the structure, material, burial depth, and topological information of inspection well nodes of the rainwater and sewage pipe network; (2) Pump-gate hydraulic characteristics data include pump-gate properties and gate pump design information: gate size, gate shape, gate flow capacity, pump energy efficiency curve and pump QH curve; (3) Rainwater and sewage catchment zoning data and water system hydraulic data, including GIS data on rainwater and sewage zoning in the study area, lake and river connectivity and water system vector data, and underwater topography and DEM data of lakes and canals; (4) Historical data of drainage households, historical dispatching information and dispatching procedures, including historical sewage drainage monitoring data of major drainage households (areas), rainfall monitoring data, and pipeline network liquid level data at the time of rainfall.

[0025] S2. Based on the one-dimensional hydrodynamic model and the two-dimensional hydrodynamic model of the pipeline, and according to the formatted data content obtained in step S1, a power plant network river-lake integrated scheduling model of the scheduling and research area is constructed. The power plant network river-lake integrated scheduling model is used to dynamically calculate and evaluate the results of scheduling control; Step S2.1, constructing a one-dimensional hydrodynamic model of a pipe channel and a two-dimensional hydrodynamic model of a lake and a river respectively, and transmitting data through the pipe channel hydrodynamic model and the two-dimensional hydrodynamic model in the calculation to connect the calculation data of the two models; Step S2.2, the drainage forecast data and rainfall forecast data of the drainage users are used to provide boundary conditions for the integrated scheduling model, and the real-time monitoring data of river and lake water levels and pipeline network liquid levels are used to provide initial conditions. Based on the scheduling parameters of different pumps, gates and pipeline networks as input variables of the model, the plant network, river and lake integrated scheduling model is calculated and the results are obtained.

[0026] Furthermore, the one-dimensional hydrodynamic model in step S2.1 is constructed as follows: (1) Based on the rainwater and sewage pipe network data, catchment area data, and water system hydraulic data, the pipe network topology and pipe network attributes in the study area are written into a structured data file. The relevant geographic elevation and burial depth information are written into the file according to the pipe network topology and node coordinates. The location of the gate pump and its connection relationship with the pipe network are expressed in the data file to form a parameter input file of the pipe network grid and attributes in the study area. (2) Based on the canal hydrodynamic model, combined with the pump-sluice hydrodynamic curve or relationship, fill in the relevant parameters in the model formula according to the parameter input file for calculation; The pipe hydrodynamic model used is developed based on the one-dimensional Saint-Venant shallow water equations, which can be used to describe the unsteady flow evolution process of one-dimensional open channels and underground pipe networks. The equations are composed of the continuity equation and the momentum equation, which are expressed as: ; ; Where: A is the area of ​​the water-passing section of the river / pipeline (㎡); x is the distance (m); y is the water depth of the river / pipeline (m). The liquid level and water level can be calculated based on the buried depth of the pipeline or the geographical elevation of the open channel; g is the acceleration of gravity (m / s 2 ); S f is the friction slope coefficient.

[0027] The pump-sluice hydrodynamic model used consists of a gate model and a pump station model; Gate model: By dividing the gate flow process into orifice flow and weir flow process, the hydrodynamic calculation of the gate can be performed; Among them, when the quotient of the gate opening e and the water depth H0 in front of the gate (e / H0) is less than 0.65, it is regarded as orifice flow, and the formula of orifice flow process can be expressed as: ; In the formula, Q0 represents the orifice flow rate, σ represents the flooding coefficient; m represents the comprehensive orifice flow coefficient; b represents the width of the water-passing section (m); e represents the gate opening (m); and g represents the acceleration of gravity. When the quotient of the gate opening e and the water depth H0 in front of the gate (e / H0) is greater than 0.65, it is regarded as weir flow. The formula of weir flow process can be expressed as: ; Where Q1 represents the weir flow rate, C w Represents the weir flow coefficient.

[0028] Pump station model: Based on the hydraulic characteristic curve of the pump, considering that the flow rate of the pump station changes continuously with the head difference between the inlet and outlet nodes, the flow value of the corresponding head difference of the pump is obtained by linear interpolation.

[0029] Furthermore, the method for constructing the two-dimensional hydrodynamic model of lakes and rivers in step S2.1 is as follows: (1) Based on the lake-river connectivity, water system data, underwater topography, and DEM data collected and collated in step 1, combined with GIS satellite maps and vector data, the scope of the river and lake model in the study area is determined, and an unstructured triangular unit finite element mesh is constructed. Values ​​are assigned to each mesh node based on the underwater topography and DEM data; (2) Combined with the collected GIS data on the connection between pipeline networks and rivers and lakes, the coordinates of the connection points between pipelines and rivers and lakes are sorted out, and the points of adjacent nodes of the coordinates are defined as data exchange points, which are used to transfer the one-dimensional pipeline hydraulic calculation results and the two-dimensional river and lake hydraulic calculation results; (3) Based on the real-time monitoring data, the initial water depth and water level data are assigned to each grid node. Based on the terrain elevation at the grid node, the rainfall runoff data and the pipe calculation results are used as the boundary input of the model to perform two-dimensional hydraulic calculations: The two-dimensional hydrodynamic model of rivers and lakes used is developed and constructed based on the two-dimensional Saint-Venant shallow water equations, which can be used to describe the flow characteristics and processes of two-dimensional rivers and lakes. The equations consist of the continuity equation and the momentum equation, and their conservation form can be expressed as: ; ; ; Where x and y represent the two directions of the Cartesian coordinates; t represents time; g represents gravitational acceleration; h represents water depth; u and v represent the vertical average velocity in the x and y directions, respectively; E(U) and G(U) represent interface fluxes; S(U) represents the source term; z b represents the bottom elevation; n represents the bottom roughness.

[0030] S3, based on the plant-grid-river-lake integrated dispatching model constructed in step S2, an optimization dispatching model is constructed according to the meta-heuristic butterfly algorithm (BOA), and the optimization dispatching model is used to calculate and generate an optimization dispatching plan that meets the dispatching objectives; The steps to build an optimization scheduling model based on the meta-heuristic butterfly algorithm are as follows: Step S3.1: Initialize the position x of each butterfly in the population i , population size N, maximum number of iterations T, dimensional space D, sensory modality c, power index a and dynamic transition probability p; Step S3.2: Calculate the position of each butterfly based on the integrated dispatching model of the power plant, grid, river and lake, obtain key data indicators, and calculate the fragrance coefficient fitness f of each butterfly based on the data indicators. i , select the current optimal fitness f g and its corresponding position g, and generate a random number r between [0,1]; Step S3.3, if r < p, then a global search is performed on the butterflies in the dimensional space, and the butterflies gather towards the individuals with the strongest fragrance (highest fitness). Otherwise, a local search is performed, and the butterfly individuals move randomly; Step S3.4, calculate the fitness of each butterfly's position after the position update, and update the optimal position; Step S3.5: Determine whether the end condition is met. If so, the algorithm ends and the optimal solution obtained by the algorithm is output. If not, go to step 2.

[0031] Furthermore, the position of the butterfly is the scheduling scheme containing the parameters of each dispatchable facility; the dimensional space contains all possible scheduling situations of the dispatchable facilities, and its boundary is the scheduling range of each dispatchable facility; the calculation formulas of each function in the optimization scheduling model are as follows: For the fragrance coefficient fitness, the calculation formula is: ; Where I i represents the stimulus intensity, which is represented by x in the present invention. i The result of normalizing the optimization target value calculated by the scheduling plan; For the dynamic conversion probability, at the tth iteration, its calculation formula is: ; In the formula, represents the dynamic conversion probability under the tth iteration; For the case of r<p in step 3-3, at the tth iteration, the butterfly position update calculation formula is: ; For the case of r ≥ p, at the tth iteration, the butterfly position update calculation formula is: ; In the formula, x i ,x j ,x k Respectively represent the positions of the i, j, and k butterflies.

[0032] S4. Based on the optimization scheduling model constructed in step S3, according to the set optimization target, combined with the real-time monitoring data of the pipeline network liquid level meter, river and lake water level meter and pump gate monitoring device, the optimization scheduling calculation is performed to obtain the scheduling plan and scheduling calculation results that meet the optimization target, and the key data in the plant network river and lake scheduling link are displayed. The scheduling plan of the optimization target is the optimal plan; the optimal plan is compared with the plan set by the dispatcher or the plan generated by the default scheduling procedure, and the optimal plan record is saved in the system for the dispatcher to use and learn.

[0033] The steps to perform optimal scheduling calculation and obtain a scheduling solution that meets the optimization objectives are as follows: Step S4.1, sort out the real-time monitored pipe network liquid level data, river and lake water level data, and pump and gate facility working condition data and input them into the integrated dispatching model of the plant network and rivers and lakes to ensure that the model can be directly calculated based on the rainfall forecast data and the given dispatching parameters; Step S4.2, define the optimization target, consider the liquid level of the prone point of the pipeline network as the optimization target, the lower the liquid level, the better the scheduling plan; Step S4.3, execute the optimization scheduling model calculation based on step three. After the calculation is completed, the calculation results are processed and sorted to obtain the results of the optimization scheduling plan, including the pipeline network liquid level, river and lake water level, pump and gate scheduling process data, etc.

[0034] A plant-grid-river-lake integrated dispatching system based on a butterfly optimization algorithm adopts the plant-grid-river-lake integrated dispatching method based on a butterfly optimization algorithm.

[0035] A computer device, characterized in that it comprises: one or more processors; The processor is used to store one or more programs; When the one or more programs are executed by the one or more processors, a plant-grid-river-lake integrated scheduling method based on a butterfly optimization algorithm as described in any one of claims 1 to 8 is implemented.

[0036] Embodiment 1: In a certain plain city, due to the long history of the city, there are a large number of canals, open channels and lakes in the urban area, and there are many underground pipe networks and pump gates in the urban area. It is difficult for the management personnel of the dispatching center to timely carry out the integrated dispatching of the plant network, rivers and lakes according to the real-time situation and provide feedback to the on-site staff. Affected by short-term rainfall, the urban area is prone to overflow of inspection wells, causing a series of problems in urban water safety, water ecology and water environment. In order to better carry out dispatching simulation and efficiently complete dispatching decisions, the dispatching management unit of the city adopts the technical route and specific implementation example provided by the present invention to improve its own management level.

[0037] In this embodiment, after communicating with the dispatch center staff, the study area was determined to be the central urban area of ​​the city. Through field surveys and visits, the pipe network pump gate data of the central urban area was collected and sorted out, including the structure, material, burial depth, and topology information of the inspection well nodes of the rainwater and sewage pipe network; Collected and organized the hydraulic characteristics data of the water treatment plant's pump gates, including pump gate attributes and pump gate design information, gate size, gate shape, gate flow capacity, water pump energy efficiency curve, water pump head flow curve and other data; Collected and organized the rainwater and sewage catchment zoning data, river and lake water system data, including rainwater and sewage zoning GIS vector data, river and lake connectivity and water system vector data, river and lake underwater topography, and adjacent area DEM data; Historical drainage household data, dispatching information, and dispatching procedure data were collected and organized, including historical sewage drainage monitoring data of major drainage households in the central urban area, rainfall monitoring data, and pipe network liquid level record data during rainfall.

[0038] Based on the collected and organized data, a numerical model for the integrated dispatch of power plants, networks, rivers and lakes in the central urban area of ​​the city was constructed in this embodiment, which mainly includes a one-dimensional hydrodynamic model of pipelines and canals and a two-dimensional hydrodynamic model of rivers and lakes.

[0039] The method for constructing the one-dimensional hydrodynamic model of the pipe channel in this embodiment is as follows: Based on the collected and collated pipe network data, catchment area data and water system data, the pipe network topology and pipe network attributes of the study area are written into a structured data file, and the relevant geographic elevation and burial depth information are written into the file according to the pipe network topology and node coordinates, and the location of the gate pump and the connection relationship with the pipe network are expressed in the data file to form a parameter input file of the pipe network grid and attributes in the study area; based on the pipe channel hydrodynamic model, combined with the pump gate hydrodynamic curve or relationship, according to the parameter input file, the relevant parameters in the model formula are filled in for calculation. In this embodiment, the calculation formula and method used are as follows: The one-dimensional Saint-Venant shallow water equations were developed and constructed to describe the unsteady flow evolution process of one-dimensional open channels and underground pipe networks. The equations consist of the continuity equation and the momentum equation, which can be expressed as: ; ; Where: A is the area of ​​the water-passing section of the river / pipeline (㎡), which is given by the collected pipe structure information; x is the distance (m), which is obtained through the topological structure between the calculation nodes during calculation; y is the water depth of the river / pipeline (m), and the liquid level and water level can be calculated according to the buried depth of the pipeline or the geographical elevation of the open channel; g is the acceleration of gravity (m / s 2 ), in this implementation, we take 9.81; S f is the friction slope coefficient. In this embodiment, different coefficients are used according to different pipeline and channel characteristics.

[0040] The pump-gate hydrodynamic model used in this embodiment consists of a gate model and a pump station model; Gate model: By dividing the gate flow process into orifice flow and weir flow process, the hydrodynamic calculation of the gate can be performed; Among them, when the quotient of the gate opening e and the water depth H0 in front of the gate (e / H0) is less than 0.65, it is regarded as orifice flow, and the formula of orifice flow process can be expressed as: ; Wherein, Q0 represents the orifice flow rate, σ represents the flooding coefficient; m represents the comprehensive orifice flow coefficient, which is 0.38 in this embodiment; b represents the width of the water-passing section (m); e represents the gate opening (m), which has different upper limits according to different gates in this embodiment; g represents the acceleration of gravity; When the quotient of the gate opening e and the water depth H0 in front of the gate (e / H0) is greater than 0.65, it is regarded as weir flow. The formula of weir flow process can be expressed as: ; Where Q1 represents the weir flow rate, C w It represents the weir flow coefficient, and in this embodiment, the value is 0.7.

[0041] Pump station model: Based on the hydraulic characteristic curves of pumps at different powers, considering that the flow rate of the pump station changes continuously with the head difference between the inlet and outlet nodes, the flow value of the pump corresponding to the head difference is obtained by linear interpolation.

[0042] The method for constructing the two-dimensional hydrodynamic model of rivers and lakes in this embodiment is as follows: Based on the collected and collated lake and river connectivity, water system data, underwater topography and DEM data, combined with GIS satellite maps and vector data, the scope of the river and lake model in the study area is determined, and an unstructured triangular unit finite element mesh is constructed, and each node of the mesh is assigned a value based on the underwater topography and DEM data; Combined with the collected GIS data on the connection between the pipe network and the river and lake, the coordinates of the connection between the pipe and the river and the lake are sorted out, and the node points adjacent to the coordinates are defined as data exchange points for transmitting the one-dimensional pipe hydraulic calculation results and the two-dimensional river and lake hydraulic calculation results. In this embodiment, the transmitted result is the flow rate Q; According to the real-time monitoring data, the initial water depth and water level data are assigned to each grid node. Based on the terrain elevation on the grid node, the rainfall runoff data and the pipe calculation results are used as the boundary input of the model to perform two-dimensional hydraulic calculations: Specifically, the two-dimensional hydrodynamic model of rivers and lakes used is developed and constructed based on the two-dimensional Saint-Venant shallow water equations, which can be used to describe the flow characteristics and processes of two-dimensional rivers and lakes. The equations consist of the continuity equation and the momentum equation, and their conservation form can be expressed as: ; ; ; Where x and y represent the two directions of the Cartesian coordinates; t represents time; g represents gravitational acceleration; h represents water depth; u and v represent the vertical average velocity in the x and y directions, respectively; E(U) and G(U) represent interface fluxes; S(U) represents the source term; z b represents the bottom elevation; n represents the bottom roughness. In this embodiment, different parameters are set according to different river and lake landforms.

[0043] Relying on the integrated dispatching model of the power plant, grid, river and lake constructed in this embodiment, in the execution of dispatching and dispatching calculation, the variables in the dispatching scheme that can be given are mainly the opening and closing rules of each pump gate, including when the liquid level in the forewater pool reaches a certain level to start the pump, when the pump is shut down, when the water level in front of and behind the gate reaches a certain level to open or close the gate, and the change process of the gate opening. According to the control content and dispatching allowable boundaries in the dispatching scheme, an optimization dispatching model is constructed based on the meta-heuristic butterfly algorithm to calculate and generate an optimization dispatching scheme that meets the dispatching objectives.

[0044] In this embodiment, the values ​​of the variables in the scheduling scheme are integrated and defined as the butterfly position x i Before building the model and performing the calculation, the position x of each butterfly in the population is initialized by random distribution. i ; Define the population size N=1000, define the maximum number of iterations T=200, define the dimensional space D according to the extreme value range of the scheduling scheme variable, define the sensory mode c=0.01, define the power exponent a=0.1, and the dynamic conversion probability p is given by the formula calculation formula, which is 0.5 at the initial time.

[0045] For the dynamic conversion probability, at the tth iteration, its calculation formula is: ; In the formula, represents the dynamic conversion probability under the tth iteration; For the fragrance coefficient fitness in BOA, the calculation formula is: ; Where I i represents the stimulus intensity, which is represented by x in this embodiment. i After the dispatching plan executes the integrated dispatching calculation of the plant network and the river and lake, the calculated optimization target value (in this embodiment, the liquid level value h of the pipe network prone to flooding) is node )The result after normalization calculation using sigmoid function, the specific expression is: ; After initialization, the position of each butterfly is calculated based on the integrated dispatching model of the power plant, grid, river and lake constructed in this embodiment to obtain key data indicators. According to the data indicators, the fragrance coefficient fitness f of each butterfly is calculated. i , select the current optimal fitness f g And its corresponding position g, and generate a random number r between [0,1].

[0046] If r < p, a global search is performed in the dimensional space according to the following formula. The butterflies gather towards the individuals with the strongest fragrance (highest fitness). In the tth iteration, the calculation formula for the butterfly position update is:

[0047] On the contrary, if r ≥ p, a local search is performed and the individual butterflies move randomly. In the tth iteration, the calculation formula for the butterfly position update is: ; In the formula, x i , x j , x kThey represent the positions of the i, j, and k butterflies respectively, and i, j, and k are different.

[0048] After each position update, the fitness of each butterfly's position is calculated and the optimal position is updated. It is determined whether the end condition is met. If it is met, the algorithm ends and the optimal solution obtained by the algorithm is output. If it is not met, the search and position update will continue until the end condition is met and the calculated optimal scheduling plan is obtained.

[0049] In this embodiment, based on the above-constructed plant network river-lake integrated model and optimized scheduling model, according to the real-time monitoring data of the pipeline liquid level, river and lake water level and pump and gate working conditions, drainage prediction data, combined with rainfall forecast data, the pipeline liquid level of several flooding-prone points is taken as the optimization target and converted into the parameters of the optimization algorithm through the sigmoid function, and then the optimization algorithm calculates the optimized scheduling scheme and the results of the integrated scheduling calculation; through visualization tools and systems, automatic data post-processing and data analysis are performed to obtain various statistical indicators after optimized scheduling, which can significantly improve the goal of reducing the liquid level at the flooding-prone points compared with the scheduling scheme formed manually based on historical experience.

[0050] In this embodiment, dispatchers can use the optimized dispatching plan calculated and given by the technology of the present invention based on future medium- and short-term rainfall forecast data, combined with current pipeline liquid level monitoring data, river and lake water level monitoring data, pump and gate working conditions and other information, to quickly respond and complete dispatching consultation decisions, thereby supporting targeted optimization of dispatching plan strategy layout and implementation, greatly improving work efficiency and reducing time costs.

[0051] The above embodiments are only preferred technical solutions of the present invention and should not be regarded as limiting the present invention. The protection scope of the present invention shall be the technical solutions recorded in the claims, including equivalent replacement solutions of the technical features in the technical solutions recorded in the claims. That is, equivalent replacement improvements within this scope are also within the protection scope of the present invention.

Claims

1. A method for integrated dispatching of power plants, grids, rivers and lakes based on butterfly optimization algorithm, characterized in that The following methods are included: S1. Determine the research area, collect and organize the data and information in the research area, including rainwater and sewage pipe network data, rainwater and sewage catchment area data, historical data of drainage households, hydraulic characteristics data of pumps and gates, water system hydraulic data, historical dispatching data and dispatching procedures; the water system hydraulic data is the water system hydraulic data of lakes, canals or open channels; organize the data and information into formatted data content; S2. Based on the one-dimensional hydrodynamic model and the two-dimensional hydrodynamic model of the pipeline, and according to the formatted data content obtained in step S1, a power plant network river-lake integrated scheduling model of the scheduling and research area is constructed. The power plant network river-lake integrated scheduling model is used to dynamically calculate and evaluate the results of scheduling control; S3, based on the plant-grid-river-lake integrated dispatching model constructed in step S2, an optimization dispatching model is constructed according to the meta-heuristic butterfly algorithm, and the optimization dispatching model is used to calculate and generate an optimization dispatching plan that meets the dispatching target; S4. Based on the optimization scheduling model constructed in step S3, according to the set optimization target, combined with the real-time monitoring data of the pipeline network liquid level meter, river and lake water level meter and pump gate monitoring device, the optimization scheduling calculation is performed to obtain the scheduling plan and scheduling calculation results that meet the optimization target, and the key data in the plant network river and lake scheduling link are displayed. The scheduling plan of the optimization target is the optimal plan; the optimal plan is compared with the plan set by the dispatcher or the plan generated by the default scheduling procedure, and the optimal plan record is saved in the system for the dispatcher to use and learn.

2. The integrated dispatching method of power plant, grid, river and lake based on butterfly optimization algorithm according to claim 1 is characterized by: The content of the information includes: (1) Data on the rainwater and sewage pipe network mainly include the structure, material, burial depth, and topological information of inspection well nodes of the rainwater and sewage pipe network; (2) Pump-gate hydraulic characteristics data include pump-gate properties and gate pump design information: gate size, gate shape, gate flow capacity, pump energy efficiency curve and pump QH curve; (3) Rainwater and sewage catchment zoning data and water system hydraulic data, including GIS data on rainwater and sewage zoning in the study area, lake and river connectivity and water system vector data, and underwater topography and DEM data of lakes and canals; (4) Historical data of drainage households, historical dispatching information and dispatching procedures, including historical sewage drainage monitoring data of major drainage households, rainfall monitoring data, and pipeline network liquid level data at the time of rainfall.

3. The integrated dispatching method of power plant, grid, river and lake based on butterfly optimization algorithm according to claim 1 is characterized by: The sub-steps of step S2 are: Step S2.1, constructing a one-dimensional hydrodynamic model of a pipe channel and a two-dimensional hydrodynamic model of a lake and a river respectively, and transmitting data through the pipe channel hydrodynamic model and the two-dimensional hydrodynamic model in the calculation to connect the calculation data of the two models; Step S2.2, the drainage forecast data and rainfall forecast data of the drainage users are used to provide boundary conditions for the integrated scheduling model, and the real-time monitoring data of river and lake water levels and pipeline network liquid levels are used to provide initial conditions. Based on the scheduling parameters of different pumps, gates and pipeline networks as input variables of the model, the plant network, river and lake integrated scheduling model is calculated and the results are obtained.

4. The integrated dispatching method of power plant, grid, river and lake based on butterfly optimization algorithm according to claim 3 is characterized by: The one-dimensional hydrodynamic model in step S2.1 is constructed as follows: (1) Based on the data of rainwater and sewage pipe networks, catchment area division data, and water system hydraulic data, the pipe network topology and pipe network attributes in the study area are written into a structured data file. The relevant geographic elevation and burial depth information are written into the file according to the pipe network topology and node coordinates. The location of the sluice pump and its connection relationship with the pipe network are expressed in the data file to form a parameter input file of the pipe network grid and attributes in the study area. (2) Based on the canal hydrodynamic model, combined with the pump-sluice hydrodynamic curve or relationship, fill in the relevant parameters in the model formula according to the parameter input file for calculation; The pipe hydrodynamic model used is developed based on the one-dimensional Saint-Venant shallow water equations, which can be used to describe the unsteady flow evolution process of one-dimensional open channels and underground pipe networks. The equations are composed of the continuity equation and the momentum equation, which are expressed as: ； ； Where: A is the area of ​​the water-passing section of the river / pipeline; x is the distance; y is the water depth of the river / pipeline. The liquid level and water level can be calculated based on the buried depth of the pipeline or the geographical elevation of the open channel; g is the acceleration of gravity; S f is the friction slope coefficient; The pump-sluice hydrodynamic model used consists of a gate model and a pump station model; Gate model: By dividing the gate flow process into orifice flow and weir flow process, the hydrodynamic calculation of the gate can be performed; Among them, when the quotient of the gate opening e and the water depth H0 in front of the gate is less than 0.65, it is regarded as orifice flow, and the formula of orifice flow process can be expressed as: ； In the formula, Q0 represents the orifice flow rate, σ represents the flooding coefficient; m represents the comprehensive orifice flow coefficient; b represents the width of the water-passing section; e represents the gate opening; and g represents the acceleration of gravity. When the quotient of the gate opening e and the water depth H0 in front of the gate is greater than 0.65, it is regarded as weir flow. The formula for the weir flow process is expressed as: ； Where Q1 represents the weir flow rate, C w represents the weir flow coefficient; Pump station model: Based on the hydraulic characteristic curve of the pump, considering that the flow rate of the pump station changes continuously with the head difference between the inlet and outlet nodes, the flow value of the corresponding head difference of the pump is obtained by linear interpolation.

5. The integrated dispatching method of power plant, grid, river and lake based on butterfly optimization algorithm according to claim 3 is characterized by: The construction method of the two-dimensional hydrodynamic model of lakes and rivers in step S2.1 is as follows: (1) Based on the collected and collated lake-river connectivity, water system data, underwater topography, and DEM data, combined with GIS satellite maps and vector data, the scope of the river and lake model in the study area is determined, and an unstructured triangular unit finite element mesh is constructed. The nodes of the mesh are assigned values ​​based on the underwater topography and DEM data; (2) Combined with the collected GIS data on the connection between pipeline networks and rivers and lakes, the coordinates of the connection points between pipelines and rivers and lakes are sorted out, and the points of adjacent nodes of the coordinates are defined as data exchange points, which are used to transfer the one-dimensional pipeline hydraulic calculation results and the two-dimensional river and lake hydraulic calculation results; (3) Based on the real-time monitoring data, the initial water depth and water level data are assigned to each grid node. Based on the terrain elevation at the grid node, the rainfall runoff data and the pipe calculation results are used as the boundary input of the model to perform two-dimensional hydraulic calculations: The two-dimensional hydrodynamic model of rivers and lakes used is developed and constructed based on the two-dimensional Saint-Venant shallow water equations, which can be used to describe the flow characteristics and processes of two-dimensional rivers and lakes. The equations consist of the continuity equation and the momentum equation, and their conservation form can be expressed as: ； ； ； Where x and y represent the two directions of the Cartesian coordinates; t represents time; g represents gravitational acceleration; h represents water depth; u and v represent the vertical average velocity in the x and y directions, respectively; E(U) and G(U) represent interface fluxes; S(U) represents the source term; z b represents the bottom elevation; n represents the bottom roughness.

6. The integrated dispatching method of power plant, grid, river and lake based on butterfly optimization algorithm according to claim 1 is characterized by: In step S3, the steps of constructing an optimization scheduling model based on the meta-heuristic butterfly algorithm are as follows: Step S3.1: Initialize the position x of each butterfly in the population i , population size N, maximum number of iterations T, dimensional space D, sensory modality c, power index a and dynamic transition probability p; Step S3.2: Calculate the position of each butterfly based on the integrated dispatching model of the power plant, grid, river and lake, obtain key data indicators, and calculate the fragrance coefficient fitness f of each butterfly based on the data indicators. i , select the current optimal fitness f g and its corresponding position g, and generate a random number r between [0,1]; Step S3.3, if r < p, then a global search is performed on the butterflies in the dimensional space, and the butterflies gather towards the individuals with the strongest fragrance. Otherwise, a local search is performed, and the individual butterflies move randomly; Step S3.4, calculate the fitness of each butterfly's position after the position update, and update the optimal position; Step S3.5: Determine whether the end condition is met. If so, the algorithm ends and the optimal solution obtained by the algorithm is output. If not, go to step S3.

2.

7. The integrated dispatching method of power plant, grid, river and lake based on butterfly optimization algorithm according to claim 6 is characterized by: The position of the butterfly is the scheduling scheme containing the parameters of each dispatchable facility; the dimensional space contains all possible scheduling situations of the dispatchable facilities, and its boundary is the scheduling range of each dispatchable facility; the calculation formulas of each function in the optimization scheduling model are as follows: For the fragrance coefficient fitness, the calculation formula is: ； Where I i represents the stimulus intensity, which is represented by x in the present invention. i The result of normalizing the optimization target value calculated by the scheduling plan; For the dynamic conversion probability, at the tth iteration, its calculation formula is: ； In the formula, represents the dynamic conversion probability under the tth iteration; For the case of r<p in step 3-3, at the tth iteration, the butterfly position update calculation formula is: ； For the case of r ≥ p, at the tth iteration, the butterfly position update calculation formula is: ； In the formula, x i ,x j ,x k Respectively represent the positions of the i, j, and k butterflies.

8. The integrated dispatching method of power plant, grid, river and lake based on butterfly optimization algorithm according to claim 1 is characterized by: Step S4, the steps of performing optimization scheduling calculation and obtaining a scheduling solution that meets the optimization target are as follows: Step S4.1, sort out the real-time monitored pipe network liquid level data, river and lake water level data, and pump and gate facility working condition data and input them into the integrated dispatching model of the plant network and rivers and lakes to ensure that the model can be directly calculated based on the rainfall forecast data and the given dispatching parameters; Step S4.2, define the optimization target, consider the liquid level of the prone point of the pipeline network as the optimization target, the lower the liquid level, the better the scheduling plan; Step S4.3, execute the optimization scheduling model calculation based on step S3. After the calculation is completed, the calculation results are processed and sorted to obtain the results of the optimization scheduling plan, including the pipeline network liquid level, river and lake water level, and pump and gate scheduling process data.

9. A plant-grid-river-lake integrated dispatching system based on butterfly optimization algorithm, characterized by: A plant-grid-river-lake integrated scheduling method based on a butterfly optimization algorithm according to any one of claims 1 to 8 is adopted.

10. A computer device, characterized in that: include: one or more processors; The processor is used to store one or more programs; When the one or more programs are executed by the one or more processors, a plant-grid-river-lake integrated scheduling method based on a butterfly optimization algorithm as described in any one of claims 1 to 8 is implemented.

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