CN102566551B - Data mining-based method for analyzing thermal power plant operation index optimal target value - Google Patents
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Abstract
The invention relates to a data mining-based method for analyzing a thermal power plant operation index optimal target value. Operation working conditions of a unit are divided according to external working conditions of the unit operation, wherein the working conditions include loads, coal qualities, and circulating water temperatures and the like; on the basis of unit operation massive historical data accumulated by a thermal power plant, by employing a data mining algorithm, operation optimal values of all important parameters on the similar operation working conditions of the unit are found out according to performance indexes including stability, economy and environmental protection and the like; and on the basis of data accumulation and continuous data updating, operation optical values of all operation parameters of the unit are found out and tracked on different working conditions of the unit. And moreover, a concrete method according to which a thermal power plant operation index optimal value is employed as a target value of an evaluation index so as to realize operation evaluation and real-time guidance functions is provided.
Description
Technical field
The invention belongs to technical field of power systems, be specifically related to a kind of analytical approach of thermal power plant operation index optimal target value.
Background technology
The analysis and calculation of thermal power plant's operating index desired value is the most key step and the of paramount importance link of thermal power plant's operation performance appraisal system, it provides the operational factor of the current optimized operation state of reflection unit and the desired value of performance index, provides the foundation and foundation for operation Optimum Operation instructs.There is no the support of correct applicable operating index desired value, operation performance appraisal has also just lost meaning.
Each operating index of unit has a running optimal value (desired value), the optimum value that unit can reach under current service condition, the ideal value that should reach in order to obtain maximum economic benefit in other words conj.or perhaps.Degree of closeness between instantaneous value and the desired value of index can quantitative response operation level height.Therefore, desired value is to weigh the benchmark of unit operation level, also be that operating index moves fine or not evaluation criterion, operations staff should operate, optimize operation as target to dwindle deviation between instantaneous value and desired value, and operation performance appraisal is also the height of evaluating operations staff's operation level with this inclined to one side extent degree.
Unit operation target goals value comprises each operational factor of the current optimized running state of unit and the optimization target values of performance index, it provides optimum operating mode and the parameter control mode of unit under different external condition (as load, fuel, external environment condition etc.) for operations staff, operation optimization target values is based upon on existing equipment basis and (comprises therrmodynamic system structure, equipment running status etc.), mainly adjust realization by operation, its object makes unit move in optimum state exactly always.
From the relation of unit operating index desired value and unit operation situation, unit operation index can be divided into two classes: the first kind is that it doesn't matter for the desired value of unit operation index and the load of unit, such as main stripping temperature, reheat steam temperature degree, while only having its numerical value to be design load, the performance driving economy of unit is best.Therefore, can think the design load that the desired value of these indexs provides for manufacturing plant.Equations of The Second Kind is that unit operation index changes along with the variation of unit operation operating mode, relevant with therrmodynamic system architectural feature with unit load, environment temperature, such as station service power consumption rate, flue gas oxygen content, exhaust gas temperature, main vapour pressure.These indexs can reach optimal value by the adjustment of equipment and parameter.
The desired value of unit operation index is very doubt in theory in fact, turns to target because it is actually with unit heat consumption index optimum, the Multi-dimensional constraint optimizing problem on unit operation performance state space.Generally adopt at present following numerical value as unit operation target goals value, and different classes of index adopts different desired values:
(1) design basis value.The state that can reach during corresponding to unit design, the design conditions data under typical load and the environment temperature providing according to manufacturer, obtain the reference value under different load and condition by model of fit and experimental formula.
(2) maintenance reference value.The state that can reach after maintenance corresponding to unit, obtains the reference value under different load and condition according to thermal performance test after unit maintenance.
(3) calculate and should reach value.Under specific load and condition, carry out that performance is calculated and variable working condition calculates and desirable should reach value according to performance computation model and variable working condition computation model.
Adopt design basis value, maintenance reference value, calculate should reach value as the desired value of unit operation index time, all there are some problems: while adopting design basis value, only in the time that the practical operation situation of unit is similar to design conditions, just reasonable relatively, otherwise not too appropriate; Adopt maintenance when reference value, after maintenance, the in the initial stage of that effect is better, and working time, elongated rear desired value can change to some extent; Adopt and calculate should reach value time, although be correct in theory, result of calculation is subject to the impact of model, and in service being often difficult to reaches.
Summary of the invention
For solving the problems referred to above that occur in prior art, the invention discloses a kind of analytical approach of the thermal power plant operation index optimal target value based on data mining, described method adopts the desired value of index running optimal value as thermal power plant's operating index.The state that the running optimal value reflection unit of index can reach under optimum operating mode and operational factor, based on data mining technology, the working condition data such as index and load, environment temperature in a large amount of operation history data being carried out to profound level analysis obtains, be a series of optimal values of unit optimal operational condition under reflection different load and external condition, thereby obtain confidence level and the higher target goals value of accuracy.
Fired power generating unit is a very complicated process industry system, and its operation optimization problem is the focus that Thermal Power Generation Industry is paid close attention to always.The key problem that operation is optimized is to determine unit operation parameter optimal objective value, to instruct operation by post-installation review.Operational factor optimal objective value has reflected the lower optimal parameter that can reach of the current operating condition condition of unit and operating mode.
The present invention specifically by the following technical solutions.
A kind of analytical approach of the thermal power plant operation index optimal target value based on data mining, the unit operation mass historical data of described analytical approach based on thermal power plant's accumulation, find out the optimal operational condition under the similar operating condition of unit, described analytical approach comprises the steps:
Step 1: thermal power unit operation operating mode is divided, unit operation operating mode is carried out to clustering by three external condition parameters such as load, ature of coal and circulating water temperatures, three external condition parameters are respectively got an operating condition of a demarcation interval composition;
Step 2: definition Fossil-fired Unit Performance index, comprises the 3 class indexs such as stability, economy, the feature of environmental protection;
Step 3: based on being stored in thermal power unit operation parameter in real time historical database and the mass historical data of performance index, utilize the clustering method of data mining technology, the one group of operational parameter value that therefrom searches out performance index optimum under each operating mode is the optimal objective value under this operating mode as operational factor, and the time of described desired value and cluster data is saved in database;
Step 4: the initial value of the operational factor using the described desired value of fired power generating unit definite in step 3 under corresponding operating mode, As time goes on the variation of thermal power unit operation operating mode, timing utilizes the data clusters analytical approach of data mining technology, the one group of operational parameter value that searches out the performance index optimum under each operating mode is the up-to-date optimal objective value under this operating mode as operational factor, and the time of up-to-date optimal objective value and cluster data is saved in database; Simultaneously, by this up-to-date optimal objective value and the optimal objective value, the i.e. historical optimal objective value comparison that search out with the last timing moment under operating mode, if up-to-date optimal objective value is better than historical optimal objective value, use up-to-date optimal objective value to substitute the historical optimal objective value under this operating mode, the current optimal objective value as thermal power unit operation parameter under this operating mode.
Step 5: the historical optimal objective value for each operational factor preserving in step 3 and step 4 under each operating mode, reject and exceed the described historical optimal objective value of setting the time limit.
The present invention has following characteristics and beneficial effect:
(1) the magnanimity production run historical data based on unit reality, these data are unit and equipment the objectively responding of (such as ature of coal, environment temperature, circulating water temperature etc.) actual motion state under different service conditions;
(2) adopt data mining technology and method, in the production run historical data of unit magnanimity, automatically the means of calculating by software, have found out the optimal operational condition under the similar operating condition of unit, have determined the optimal value of each index under these service conditions;
(3) by accumulation and the software of production run data, the data of new accumulation are constantly carried out to timing optimizing, constantly update optimal data storehouse, assurance unit index operational objective value is followed the tracks of the objective running optimal value of unit all the time, the nearly running optimal value of not disconnecting, provides credible, operating index desired value accurately for real time execution performance appraisal and real time execution instruct.
(4) the production run historical data of the overall process of this computing method based on unit, adopt data mining technology to analyze mass data, excavate out unit (such as ature of coal, environment temperature, circulating water temperature etc.) actual motion state under different service conditions, reflect the objective moving law of reality of unit, avoided the impact of the human factors such as artificial target setting value.
Accompanying drawing explanation
Fig. 1 is the thermal power plant's operation optimal objective value analytical approach process flow diagram that the present invention is based on data mining.
Embodiment
Below in conjunction with Figure of description, technical scheme of the present invention is described in further details.
Carrying out the real time execution performance appraisal of unit and real time execution while instructing, adopt which type of mathematical model to make the operating index desired value calculating there is high as far as possible confidence level and accuracy, it is a more difficult problem, because the desired value of each index is not only relevant with operating condition, load and the design parameter of unit, also there is relation with the factor such as equipment state and environmental baseline, only have and correctly and all sidedly consider various influence factors, just can draw the desired value conforming to the actual situation.
At present, the calculating of operating index desired value generally adopts curve fitting method and method of interpolation.
(1) curve fitting method
Under a certain load, can get operational parameter value under the optimum operating condition desired value as index, in time, between the change curve of index parameter and the change curve of unit load, present certain funtcional relationship, so can simulate by the method for numerical analysis the desired value curve of index, these curves are functions of unit load.
(2) method of interpolation
Interpolation calculation index operating index desired value, first need to obtain the desired value (Xi of index under each load condition condition, Yi), wherein: Xi represents load variation, Yi represents target goals value variable, the value of i, depending on the computational accuracy of actual needs, is then used the method for numerical interpolation to try to achieve target goals value.
The process flow diagram that is illustrated in figure 1 the computing method of the thermal power plant operation index optimal target value based on data mining disclosed by the invention, concrete steps are as follows:
(1) thermal power unit operation operating mode is divided, unit operation operating mode is carried out to clustering by three external condition parameters such as load, ature of coal, circulating water temperatures, set up the operating mode storehouse of system, mainly comprise desired value of the parameters under the operating mode number of each operating mode, the upper and lower bound value (numerical range of working condition parameter) of each working condition parameter, each operating mode number etc.
For load parameter, adopt K-averaging method to carry out discretize, clustering to meeting parameter, such as the load parameter of certain 600MW unit is divided into ..., [377,410], [410,440], [440,475], [475,511] ... a such a interval, three external condition parameters are respectively got an operating condition of an interval composition;
For ature of coal parameter, its characteristic is characterized by net calorific value, moisture, three amounts of fugitive constituent (analysis data), in order to simplify the calculating in operating mode storehouse, first these three amounts are carried out discretize and different combinations are classified according to general regulation, be divided into poor, in, good, four classifications (or interval).
For circulating water temperature, it generally, between 0 to 40 ℃, is divided into 8 temperature ranges by it from low to high continuously, 5 ℃ of each temperature range scopes.
Assembled arrangement is carried out in each interval for above load, ature of coal, three external condition parameters of circulating water temperature, forms whole operating mode storehouse, comprises between operating mode number, loading zone, ature of coal interval, circulating water temperature interval, each operating index desired value etc.
(2) definition Fossil-fired Unit Performance index, comprises the 3 class indexs such as stability, economy, the feature of environmental protection; ;
For every class performance index, based on the operating mode storehouse of setting up in (1) step, calculate respectively the optimal objective value under unit operating index each operating mode in the time that such performance index are optimum.
(3) based on being stored in thermal power unit operation parameter in real time historical database and the mass historical data of performance index, utilize the clustering method of data mining technology, the one group of operational parameter value that therefrom searches out performance index optimum under each operating mode is the desired value under this operating mode as operational factor, and the time of desired value and cluster data is saved in database;
(4) initial value under corresponding operating mode using the desired value of each class performance index of unit definite in (3), As time goes on the variation of thermal power unit operation duty parameter, adopt timing (such as every month) executing data to excavate and data clusters analytic process, extract the up-to-date optimal value of each unit operation index under each operating mode, and the time of up-to-date optimal value and cluster data is saved in database; Meanwhile, by this up-to-date optimal value and with the historical optimal value comparison under operating mode, if be better than the latter, substitute the optimal value under this operating mode, as new operational factor desired value.
(5): for the historical optimal value of each operating index preserving in step 3 and step 4, carry out every year after large light maintenance at unit, reject some out-of-date historical datas, only need to retain the historical data of a period of time (such as nearest 3 years), thereby guarantee the ageing of historical optimal value.
The present invention obtains can further include on the basis of the optimal objective value of Present Thermal Power unit operation parameter under each operating mode following steps in above-mentioned steps (5):
The current operating condition of the calculating in real time of operation Performance Management System and decision-making system, according to the operating mode of current operating condition number and performance index type, from operating mode storehouse, inquire about the optimal objective value of each operating index, desired value using these optimal objective values as performance assessment criteria, carries out the examination scoring of index.
The height of operations staff's operation level is evaluated in operation performance appraisal with the deviation size between instantaneous value and the desired value of index.Unit is in actual motion, operational factor is often in continuous fluctuation status, operational factor can not be adjusted to desired value remains unchanged, but allow operational factor to fluctuate in some scopes, therefore, operational factor generally has four " attention lines " such as upper economic line, lower economic line, upper safety line, lower safety lines, and these four lines are that index has been divided several examinations interval, also can as required interval division be obtained carefullyyer, carry out more fine-grained examination.
Examine in arranging of standards of grading in index, the score difference that each is interval, the upper and lower safety line of the proportion by subtraction interval score in addition that obtains in upper and lower economic line interval wants high, simultaneously, upper and lower economic line interval is also often optimum interval, and upper and lower safety line interval is in addition also often early warning interval.In actual applications, the desired value of a lot of indexs changes with the variation of operating mode, corresponding upper and lower economic line, upper and lower safety line also change with the variation of operating mode, curve rather than straight line often, article four, the numerical value that line is corresponding need to calculate according to real-time working condition condition by various algorithms, such as adopting curve fitting method, experimental formula method, Lagrange's interpolation etc.
Claims (3)
1. the analytical approach of the thermal power plant operation index optimal target value based on data mining, the unit operation mass historical data of described analytical approach based on thermal power plant's accumulation, find out the optimal operational condition under the similar operating condition of unit, described analytical approach comprises the steps:
Step 1: thermal power unit operation operating mode is divided, unit operation operating mode is carried out to clustering by load, ature of coal and three external condition parameters of circulating water temperature, three external condition parameters are respectively got an operating condition of a demarcation interval composition; Wherein, for load parameter, adopt K-averaging method to carry out discretize, clustering; For ature of coal parameter, its characteristic is levied by net calorific value, moisture, three scales of fugitive constituent, and these three amounts are carried out discretize and different combinations is classified according to general regulation; For circulating water temperature, it generally, between 0 to 40 ℃, is divided into 8 temperature ranges by it from low to high continuously, 5 ℃ of each temperature range scopes;
Step 2: definition Fossil-fired Unit Performance index, comprises stability, economy, the feature of environmental protection 3 class indexs;
Step 3: based on being stored in thermal power unit operation parameter in real time historical database and the mass historical data of performance index, utilize the clustering method of data mining technology, the one group of operational parameter value that therefrom searches out performance index optimum under each operating mode is the optimal objective value under this operating mode as operational factor, and the time of described optimal objective value and cluster data is saved in database;
Step 4: the initial value of the operational factor using the described optimal objective value of fired power generating unit definite in step 3 under corresponding operating mode, As time goes on the variation of thermal power unit operation operating mode, timing utilizes the data clusters analytical approach of data mining technology, the one group of operational parameter value that searches out the performance index optimum under each operating mode is the up-to-date optimal objective value under this operating mode as operational factor, and the time of up-to-date optimal objective value and cluster data is saved in database; Simultaneously, by this up-to-date optimal objective value and the optimal objective value, the i.e. historical optimal objective value comparison that search out with the last timing moment under operating mode, if up-to-date optimal objective value is better than historical optimal objective value, use up-to-date optimal objective value to substitute the historical optimal objective value under this operating mode, the current optimal objective value as thermal power unit operation parameter under this operating mode;
Step 5: the historical optimal objective value for each operational factor preserving in step 3 and step 4 under each operating mode, reject and exceed the described historical optimal objective value of setting the time limit;
Step 6: the current operating condition of the calculating in real time of operation Performance Management System and decision-making system, according to the operating mode of current operating condition number and performance index type, from operating mode storehouse, inquire about the optimal objective value of each operating index, desired value using these optimal objective values as performance assessment criteria, carry out the examination scoring of index: the height of operations staff's operation level is evaluated in operation performance appraisal with the deviation size between instantaneous value and the desired value of thermal power unit operation index, thermal power unit operation parameter is provided with to upper economic line, lower economic line, upper safety line, four of lower safety lines " attention line ", article four, the numerical value that " attention line " is corresponding need to adopt curve fitting method, experimental formula method or Lagrange's interpolation calculate according to real-time working condition condition, divide the different examination intervals that obtain score value based on described four " attention lines ".
2. the analytical approach of the thermal power plant operation index optimal target value based on data mining according to claim 1, is characterized in that:
In described step 5, when described setting, be limited to 3 years or 2 years.
3. the analytical approach of the thermal power plant operation index optimal target value based on data mining according to claim 1, is characterized in that:
Described in step 4 timing time be limited to one month.
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