CN103093056B - The optimization system of a kind of power station Design of Hydraulic Turbine and method - Google Patents
The optimization system of a kind of power station Design of Hydraulic Turbine and method Download PDFInfo
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Abstract
The present invention is optimization method and the system of a kind of power station Design of Hydraulic Turbine, and optimization method is: according to the characteristic parameter that power station is given, recall parameter data storehouse and model database, obtains the first of each parts of Turbine Flow Passage and establishes result; Stability emulation is carried out to full runner, calculates the weight of different stability factor of influence in each parts, draw optimization suggestion for revision and the measure of each parts of runner, send and preserve Optimum Design Results.The system realizing the method comprises: overall process module, simulation algorithm model, weight analysis module, data memory module, factor of influence index storehouse and method base.Present invention achieves integrated forecasting and the assessment of the biological factors affecting hydraulic turbine stability energy, the design that designer is closed at Design of Hydraulic Turbine and the optimum combo of each parts of runner shortens the time, and then also improves the stability of Power Station Turbine group and factory building.
Description
Technical field
The present invention relates to optimization system and the method for the design of a kind of hydraulic, the optimization system of a kind of power station Design of Hydraulic Turbine and method specifically.
Background technology
The stability indicator of the hydraulic turbine, efficiency index and cavitation index be three large performance index of the hydraulic turbine.Whether hydraulic turbine stability is related to unit can safe operation, and relationship between efficiency is to the producing level of flow energy, and cavitation is not only related to the life-span of unit but also can affects the stable of the hydraulic turbine to a certain extent.In construction of hydropower facilities project, only have unit operation to stablize, power benefit that efficiency is high and anti-Cavitation the is good hydraulic turbine can have.
At present, the efficiency of the hydraulic turbine can reach more than 90%, and the performance of anti-cavitation also improves a lot.But along with the raising of single-machine capacity, the increase of machine packet size, the problem that serious vibration and leaf destruction etc. affect hydraulic turbine stability energy displays gradually, not only have impact on the normal operation in power station, even constitutes a threat to the safety of factory building.And the content that hydraulic turbine stability is contained is very wide, from waterpower influence factor, just include pressure fluctuation that vortex rope causes, eddy current and cavitation, add that different stability factor of influence there are differences in the influence degree of each parts of different Power Station Turbine runners and the position of appearance.Therefore, the stability problem of the hydraulic turbine more and more receives the concern of people, and hydraulic stability has also become another criterion of large-scale mixed turbine design.
For the discussion of above-mentioned hydraulic turbine stability waterpower influence factor and affect diversity judgement analysis at each parts of runner, comprehensively traditional manual method impossible consider, must the modern technologies such as computer technology, Fluid Mechanics Computation analytical technology and database technology could make comprehensively hydraulic turbine stability problem, science, effective analysis and judgement.In existing hydraulic turbine optimal design, develop the software package of hydraulic turbine type design, but can not to the turbine parameter just established, model structures etc. carry out optimization; And in the runner of the hydraulic turbine, only have pressure fluctuation can to measure as quantities, but the large cost of this surveying work amount is also high.And owing to also not having the complete law of similitude between model and prototype, also just making to utilize the measurement forecast pressure of model to pulse after design can't completely as the foundation of prototype to hydraulic turbine stability.
Therefore, if each hydraulic factors affecting hydraulic turbine stability energy is considered, and Predicting and analysis affects the most serious runner position of the significant effects Summing Factor of hydraulic turbine stability on one system, just can contribute to designer and better be optimized design to the hydraulic turbine.
Summary of the invention
Technical matters to be solved by this invention is, overcome the shortcoming of prior art, optimization method and the system of a kind of power station Design of Hydraulic Turbine are provided, can the design and optimization of Turbin Type Selection and runner be gathered in one, the hydraulic turbine can be realized from the one-stop design being just set to global optimization, ensureing high efficiency while, substantially increase the stability of this hydraulic turbine, and greatly reduce the generation of cavitation.
The technical scheme that the present invention solves above technical matters is:
An optimization system for power station Design of Hydraulic Turbine, comprising: the overall process module communicated to connect mutually, simulation algorithm model, weight analysis module, data memory module, factor of influence index storehouse and method base;
Overall process module, for other modules in calling system, realizes each intermodule communication and connects;
Simulation algorithm model comprise: three-dimensional non-steady turbulent pressure submodule, three-dimensional non-steady turbulence flow flied submodule and three-dimensional non-steady cavitation two-phase turbulence submodule, they are respectively used to the simulation calculation that spiral case inlet to draft tube exports the pressure of this full runner, flow field and cavitation;
Weight analysis module comprises: pressure fluctuation weight submodule, eddy current weight submodule and cavitation weight submodule, they are respectively used to the data samples such as the pressure of each measuring point in runner on analysis section, velocity and cavity component and calculate in not recurrence in the same time, show that three factors of influence are in cross sections not " contribution " in the same time, and then draw the most serious position that the most important factor that affects hydraulic turbine stability and the Different Effects factor occur in each flow path features;
Data memory module comprises: parameter database and model database, they are respectively used to store historical parametric data (hydraulic turbine each type selecting parameter and runner model) and model data (each number of element types size of runner and digital model figure), and the first of storage of water turbine establishes data and corresponding optimum results;
Factor of influence index storehouse, for utilizing variable importance projection index to calculate lot of domestic and foreign historical summary, the index storehouse of relevant three factors of influence set up, for determining that three factors are at each section synchronization t
p" contribution " size;
Method base is the database that the empirical documentation that there is hydraulic turbine stability problem according to solution lot of domestic and foreign is set up, and for after weight analysis completes, offers an opinion to the parameter and model structure revising each parts of runner and provides other ancillary method.
The optimization method of a kind of power station Design of Hydraulic Turbine carries out according to the following steps:
(i) according to the characteristic parameter of the given maximum head in power station, minimum head, design head, installed capacity and unit number of units, parameter database in calling data memory module and model database, obtain the first of spiral case in the hydraulic turbine, stator and draft tube and establish result, described model, physical dimension and performance parameter of just establishing result to comprise each parts;
(ii) read the first of the hydraulic turbine and establish result, call simulation algorithm model, whether the ratio according to maximum head and minimum head is greater than 1.4, if be greater than 1.4, then carries out to hydraulic turbine stability factor of influence vortex rope, eddy current and cavitation the simulation calculation that spiral case inlet exports to draft tube; If be less than 1.4, then the simulation calculation that spiral case inlet exports to draft tube is carried out to hydraulic turbine stability factor of influence vortex rope and eddy current;
(iii) after completing simulation calculation, call weight analysis module and factor of influence index storehouse, calculate and determine " contribution rate " of each parts of runner in the Different Effects factor, drawing hydraulic turbine stability weight analysis result, namely affect the most important factor of hydraulic turbine stability;
(iv) according to weight analysis result, called side Faku County and model database determination suggestion for revision, if need revise at the beginning of the hydraulic turbine and establish model, and model-free is optional in model bank, what then automatically enter model database establishes unit certainly, carry out artificial amendment, and result is sent to power station data memory module;
(v) by Optimum Design Results by data memory module stored in corresponding database, user can according to the data storage attribute in each database, Automatic inquirying and obtain the type selecting of the hydraulic turbine and the optimum results of runner design.
Like this, the present invention is according to the given characteristic parameter such as maximum head, minimum head, design head, installed capacity, unit number of units in power station, parameter database in calling data memory module and model database, obtain the first of parts such as spiral case in the hydraulic turbine, stator, draft tube and establish result.Read parameter and the model data of the hydraulic turbine to be optimized, call simulation algorithm model, selectively stability prediction and calculation is carried out to full runner, that is: judge whether the ratio of maximum head and minimum head is greater than 1.4, determine whether also to select three-dimensional non-steady cavitation two-phase turbulence submodule.After simulation calculation completes, call weight analysis module, passing to corresponding weight submodule in the data do not calculated in the same time.At each weight submodule, by each measuring point on cross sections at t
1to t
pdata are not in the same time as sample, based on the homing method in genetic algorithm, and the regression equation of Time Created and sample data, and then calculate each measuring point from t
1to t
pthe deviation in each moment, and to measuring point different in each section at synchronization t
pdeviation be averaged.Then, call factor of influence index storehouse, determine that three factors of influence are at each section synchronization t
p" contribution ", the cumulative weight distribution that can obtain each section Different Effects factor is carried out in not " contribution " in the same time.Finally, consider the weight analysis result of each section, just can draw the most important factor affecting hydraulic turbine stability, also can analyze the most serious position that a certain factor of influence occurs in each flow path features simultaneously.Complete after hydraulic turbine stability can predict, called side Faku County and model database, draw suggestion for revision and the measure of each parts optimum combination of decision-making runner, and final optimization pass result sent and be saved in data memory module.
The technical scheme that the present invention limits further is:
The optimization system of aforesaid power station Design of Hydraulic Turbine, the information of each module is shared mutually by the management interface arranged in systems in which.
The optimization method of aforesaid power station Design of Hydraulic Turbine, step (iii) in, calculate and determine that " contribution rate " of each parts of runner in the Different Effects factor are specially: before the simulation calculation of full runner being carried out to different stability factor of influence, making the several analysis section n perpendicular to each component axes in advance
1, n
2, n
3... .n
i, each section gets several measuring point m
1, m
2, m
3... .m
j, and each measuring point can record t
1, t
2, t
3... .t
pnot simulation calculation data in the same time, comprise pressure, velocity and cavity component; After simulation calculation completes, call weight analysis module, the data do not calculated in the same time are passed to corresponding weight submodule; At each weight submodule, by each measuring point on cross sections at t
1to t
pdata are not in the same time as sample, based on the homing method in genetic algorithm, and the regression equation of Time Created and sample data, and then calculate each measuring point from t
1to t
pthe deviation in each moment, and to measuring point different in each section at synchronization t
pdeviation be averaged; Introduce factor of influence index storehouse, determine that three factors are at a certain moment t of each section
p" contribution ", the cumulative weight distribution that can obtain each section Different Effects factor is carried out in not " contribution " in the same time; Consider the weight analysis result of each section, draw the most important factor affecting hydraulic turbine stability.
The optimization method of aforesaid power station Design of Hydraulic Turbine, step (i) in, the first result of establishing obtaining spiral case in the hydraulic turbine, stator and draft tube is specially one of following two kinds of methods: (1) the direct database from data memory module obtains; (2) carried out just establishing to the hydraulic turbine at the unit of certainly establishing of two databases by designer.
The invention has the beneficial effects as follows: (1) the design and optimization of Turbin Type Selection and runner is gathered in one, the hydraulic turbine can be realized from the one-stop design being just set to global optimization; (2) the introducing of weight analysis calculating, achieve considering of the Different Effects factor of hydraulic turbine stability, more can draw the contribution rate of each parts of runner under the Different Effects factor in all directions, so for designer realize each parts of runner optimum combination design foundation is provided; (3) whole process of optimization is integrated in a system and carries out, and convenient to use, surveying work amount is little, and cost is low; (4) achieve integrated forecasting and the assessment of the biological factors affecting hydraulic turbine stability energy, the design that designer is closed at Design of Hydraulic Turbine and the optimum combo of each parts of runner shortens the time, and then also improve the stability of Power Station Turbine group and factory building, ensureing high efficiency while, substantially increase the stability of this hydraulic turbine, and greatly reduce the generation of cavitation.
Accompanying drawing explanation
Fig. 1 is that system of the present invention connects block diagram.
The process flow diagram of Fig. 2 for establishing at the beginning of each parts of embodiment of the present invention power station Turbine Flow Passage.
Fig. 3 is the process flow diagram of method of the present invention.
Embodiment
Embodiment 1
Embodiment 1: for a certain power station, utilizes the present invention to carry out the optimization of each parts of Turbine Flow Passage.The optimization system of the present embodiment power station Design of Hydraulic Turbine connects as shown in Figure 1, and power station hydraulic turbine Optimum Design System comprises: overall process module 201, simulation algorithm model 202, weight analysis module 203, data memory module 204, factor of influence index storehouse 205 and method base 206;
Wherein, overall process module 201, for other modules of calling system, realizes " cooperation " of each intermodule.
Simulation algorithm model 202 comprises: three-dimensional non-steady turbulent flow (pressure) submodule 2021, three-dimensional non-steady turbulent flow (flow field) submodule 2022, three-dimensional non-steady cavitation two-phase turbulence submodule 2023.They are respectively used to the simulation calculation that spiral case inlet to draft tube exports the pressure of this full runner, flow field and cavitation.
Weight analysis module 203 comprises: pressure fluctuation weight submodule 2031, eddy current weight submodule 2032 and cavitation weight submodule 2033.They are respectively used to the data samples such as the pressure of each measuring point in runner on analysis section, velocity and cavity component and calculate in not recurrence in the same time, show that three factors of influence are in cross sections not " contribution " in the same time, and then draw the most serious position that the most important factor that affects hydraulic turbine stability and the Different Effects factor occur in each flow path features.
Data memory module 204 comprises: parameter database 2041 and model database 2042.They are respectively used to store historical parametric data (hydraulic turbine each type selecting parameter and runner model) and model data (each number of element types size of runner and digital model figure), and the first of storage of water turbine establishes data and corresponding optimum results.Meanwhile, described parameter database and model database all have from establishing unit, and designer can the parameter of the designed, designed hydraulic turbine and structural model.
Factor of influence index storehouse 205 utilizes variable importance projection index to calculate lot of domestic and foreign historical summary, the index storehouse of relevant three factors of influence set up.For determining that three factors are at each section synchronization t
p" contribution " size.
Method base 206 is databases that the empirical documentation that there is hydraulic turbine stability problem according to solution lot of domestic and foreign is set up.After judging according to weight analysis, the parameter, model structure etc. of each parts of amendment runner are offered an opinion and provide other ancillary method.
Native system is the system for power station Turbine Flow Passage optimal design, can realize user and can change into the management of the data that computing machine describes and stores, and the information of each module is shared mutually by the management interface in system.
The optimization method flow process of the present embodiment power station Design of Hydraulic Turbine as shown in Figure 3,
(1) according to the characteristic parameter 301 (see table 1) such as maximum head, minimum head, design head, installed capacity, unit number of units that this power station is given, the flow process of establishing at the beginning of each parts of power station Turbine Flow Passage as shown in Figure 2, recall parameter data storehouse 302 and model database 303, obtain the first of parts such as spiral case in the hydraulic turbine, stator, draft tube and establish result 304.
Table 1
| Maximum head | Design head | Minimum head | Unit number of units | Installed capacity |
| 79.5 | 60 | 50.5 | 3 | 75 |
The each parts of its main flow paths first set result as:
Spiral case form adopts metal spiral case, and cornerite is 345 degree; Seat ring: diameter * is high=3980*1800mm; Base ring: diameter * is high=2940*170mm; Water distributor is of a size of: diameter * is high=and 3350*2045mm, blade is traditional runner bucket; Draft tube adopts curved elbow (elbow of draft tube two sections: diameter * is high=7880*5050*4000mm; Draft tube cone: diameter * is high=2950*1861mm); Runner: diameter * is high=2500*1450mm.Performance parameter through backstage can be calculated: to exert oneself be 24.5%, efficiency is 93.8%, cavitation performance is 0.120, operation characteristic is 0.90.
Complete the first of the hydraulic turbine and establish 305.And just establish result to be sent to data memory module 306 by above-mentioned.
(3) read that this hydraulic turbine is above-mentioned just establishes result 401, call simulation algorithm model 402, due to the ratio (being specially 1.574) 403 of maximum head and minimum head, so export to spiral case inlet to draft tube the total calculation 404 and 405 that this full runner carries out pressure, flow field and cavitation;
(4) after completing simulation calculation, continue to call weight analysis module 406, the data calculated at different time (comprising pressure, velocity, cavity component) are passed to corresponding weight submodule.At each weight submodule, by each measuring point on cross sections at t
1to t
pdata are not in the same time as sample, based on the homing method in genetic algorithm, and the regression equation 407 of Time Created and sample data, and then calculate each measuring point from t
1to t
pthe deviation in each moment, and to measuring point different in each section at synchronization t
pdeviation be averaged.Then, introduce the factor of influence index storehouse 408 of relevant three factors of influence set up by lot of domestic and foreign historical summary data respectively, determine that three factors are at each section synchronization t
p" contribution ", the cumulative weight distribution that can obtain each section Different Effects factor is carried out in not " contribution " in the same time.Finally, consider the weight analysis result of each section, draw the most important factor affecting hydraulic turbine stability, also analyze the most serious position 409 that a certain factor of influence occurs in each flow path features simultaneously.
Weight analysis result is: the weight of pressure fluctuation, eddy current and cavitation three hydraulic turbine factors of influence respectively 64%, 15% and 21%.Wherein, pressure fluctuation happening part is at draft tube, stator, runner, and weight contribution is respectively 56%, 9%, 27%; Eddy current happening part is in the head of blade and the back side, the middle part of draft tube and the outlet of runner, and weight contribution is respectively 72%, 13%, 15%; And the position that cavitation occurs is in the middle part of runner bucket pressure face, runner bucket suction surface, draft tube, weight contribution is respectively 37%, 51%, 12%.
Determine the prediction 410 of stability.
(5) according to the weight analysis result of above-mentioned steps (4), called side Faku County 411 and model database 412, draw the suggestion for revision 413 that the optimum combo of each parts of decision-making runner is closed, as follows:
1): draft cone is retrofited.The bottom of draft cone prototype is installed additional a streamlined cone of round end, near length to outlet of rotary wheel.
2): draft tube is retrofited.The height of draft tube cone is increased 109% to former height; Inlet diameter simultaneously by suitably increasing discharge diameter of runner and reduction ell makes cone angle increase to 105% of prototype.
3): change prototype blade into negative incidence blade.
4): effectively reduce specific speed, 225 are reduced to by original 235.
5): to air admission to main shaft central hole, air compensation is 0.35% of rated flow.
In above-mentioned suggestion for revision 2) because of in model database model-free optional, so automatically enter model database certainly establish unit, carry out artificial Change In Design; And suggestion for revision 1) and 3) can directly select by model database.
(6) send and preserve Optimum Design Results 414: by the Optimum Design Results of above-mentioned type selecting and each parts of runner by data memory module stored in corresponding database, user can according to the memory attribute of each database, Automatic inquirying and the acquisition type selecting of the hydraulic turbine and the optimum results of runner design.
Find through test: above-mentioned optimum results, ensureing high efficiency while, substantially increases the stability of this hydraulic turbine, and greatly reduces the generation of cavitation.
In addition to the implementation, the present invention can also have other embodiments.All employings are equal to the technical scheme of replacement or equivalent transformation formation, all drop on the protection domain of application claims.
Claims (3)
1. an optimization system for power station Design of Hydraulic Turbine, is characterized in that: comprising: the overall process module communicated to connect mutually, simulation algorithm model, weight analysis module, data memory module, factor of influence index storehouse and method base;
Described overall process module, for other modules in calling system, realizes each intermodule communication and connects;
Described simulation algorithm model comprises: three-dimensional non-steady turbulent pressure submodule, three-dimensional non-steady turbulence flow flied submodule and three-dimensional non-steady cavitation two-phase turbulence submodule, and they are respectively used to the simulation calculation that spiral case inlet to draft tube exports the pressure of this full runner, flow field and cavitation;
Described weight analysis module comprises: pressure fluctuation weight submodule, eddy current weight submodule and cavitation weight submodule, they are respectively used to the pressure of each measuring point in runner on analysis section, velocity and cavity component data sample and calculate in not recurrence in the same time, show that these three factors of influence of pressure, velocity and cavity component are in cross sections not " contribution " in the same time, and then draw the most serious position that the most important factor that affects hydraulic turbine stability and the Different Effects factor occur in each flow path features;
Described data memory module comprises: parameter database and model database, they are respectively used to store historical parametric data and model data, and the supplemental characteristic in the first optimum results establishing data and correspondence of the hydraulic turbine and model data are also stored to described parameter database and model database respectively; Described historical parametric data is each type selecting parameter of the hydraulic turbine and runner model, and described model data is each number of element types size of runner and digital model figure;
Described factor of influence index storehouse, for utilizing variable importance projection index, lot of domestic and foreign historical summary is calculated, the index storehouse of the pressure set up, velocity and cavity component three factors of influence, for determining three factors " contribution " size at each section synchronization;
Described method base is the database that the empirical documentation that there is hydraulic turbine stability problem according to solution lot of domestic and foreign is set up, and for after weight analysis completes, offers an opinion to the parameter and model structure revising each parts of runner;
The optimization method of described power station Design of Hydraulic Turbine, carries out according to the following steps:
(i) according to the characteristic parameter of the given maximum head in power station, minimum head, design head, installed capacity and unit number of units, parameter database in calling data memory module and model database, obtain the first of spiral case in the hydraulic turbine, stator and draft tube and establish result, described model, physical dimension and performance parameter of just establishing result to comprise each parts;
(ii) read the first of the hydraulic turbine and establish result, call simulation algorithm model, whether the ratio according to maximum head and minimum head is greater than 1.4, if be greater than 1.4, then carries out to hydraulic turbine stability factor of influence vortex rope, eddy current and cavitation the simulation calculation that spiral case inlet exports to draft tube; If be less than 1.4, then the simulation calculation that spiral case inlet exports to draft tube is carried out to hydraulic turbine stability factor of influence vortex rope and eddy current;
(iii) after completing simulation calculation, call weight analysis module and factor of influence index storehouse, calculate and determine " contribution rate " of each parts of runner in the Different Effects factor, drawing hydraulic turbine stability weight analysis result, namely affect the most important factor of hydraulic turbine stability;
(iv) according to weight analysis result, called side Faku County and model database determination suggestion for revision, if need revise at the beginning of the hydraulic turbine and establish model, and model-free is optional in model bank, what then automatically enter model database establishes unit certainly, carry out artificial amendment, and the result of amendment is sent to data memory module;
(v) by step, (iv) middle amendment result is stored in the parameter database in data memory module and model database, and user can according to the data storage attribute in each database, Automatic inquirying and the acquisition type selecting of the hydraulic turbine and the optimum results of runner design;
Described step (iii) in, calculate and determine that " contribution rate " of each parts of runner in the Different Effects factor are specially: before the simulation calculation of full runner being carried out to different stability factor of influence, making the several analysis section n perpendicular to each component axes in advance
1, n
2, n
3... .n
i, each section gets several measuring point m
1, m
2, m
3... .m
j, and each measuring point can record t
1, t
2, t
3... .t
pnot simulation calculation data in the same time, comprise pressure, velocity and cavity component; After simulation calculation completes, call weight analysis module, the data do not calculated in the same time are passed to corresponding weight submodule; At each weight submodule, by each measuring point on cross sections at t
1to t
pdata are not in the same time as sample, based on the homing method in genetic algorithm, and the regression equation of Time Created and sample data, and then calculate each measuring point from t
1to t
pthe deviation of each moment pressure, velocity and cavity component, and to measuring point different in each section at synchronization t
pdeviation be averaged; Introduce factor of influence index storehouse, determine that each factor is at a certain moment t of each section
p" contribution ", the cumulative weight distribution that can obtain each section Different Effects factor is carried out in not " contribution " in the same time; Consider the weight analysis result of each section, draw the most important factor affecting hydraulic turbine stability.
2. the optimization system of power station as claimed in claim 1 Design of Hydraulic Turbine, is characterized in that: the information of described each module is shared mutually by the management interface arranged in systems in which.
3. the optimization system of power station as claimed in claim 1 Design of Hydraulic Turbine, it is characterized in that: described step (i) in, the first result of establishing obtaining spiral case in the hydraulic turbine, stator and draft tube is specially one of following two kinds of methods: (1) directly obtain from the parameter database data memory module and model database; (2) carried out just establishing to the hydraulic turbine at the unit of certainly establishing of parameter database and model database by designer.
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