CN116433073A - Wind power plant operation efficiency evaluation method, device, equipment and medium - Google Patents
Wind power plant operation efficiency evaluation method, device, equipment and medium Download PDFInfo
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Abstract
The disclosure relates to the technical field of wind farm operation efficiency evaluation, and in particular relates to a wind farm operation efficiency evaluation method, device, equipment and medium, wherein a basic statistical index corresponding to a wind farm is determined according to historical operation data of the wind farm, and the historical operation data at least comprises: wind tower data, laser radar wind data, data acquisition and monitoring control system data, production operation management system data, power control system data and wind turbine generator design data; after the basic statistical indexes corresponding to the wind power plant are determined, determining the high-order statistical indexes corresponding to the wind power plant based on the basic statistical indexes; and determining target efficiency evaluation parameters corresponding to the wind power plant according to the high-order statistical indexes and all first wind power plant statistical parameters corresponding to the high-order statistical indexes, wherein the target efficiency evaluation parameters are used for evaluating the operation efficiency of the wind power plant. By adopting the method, the evaluation accuracy of the wind farm operation efficiency can be improved.
Description
Technical Field
The disclosure relates to the technical field of wind farm operation efficiency evaluation, in particular to a wind farm operation efficiency evaluation method, device, equipment and medium.
Background
The wind power plant operation efficiency evaluation is used for quantitatively evaluating the actual operation condition of the in-service wind power plant and tracing the generation performance loss root of the wind power plant, so that the space can be increased for the operation management and technical transformation performance of the wind power plant, the generation efficiency of the wind power plant is improved, and the operation cost of the wind power plant in the life cycle is reduced.
In the prior art, different power generation enterprises collect more single wind farm operation data, and each power generation enterprise adopts a respective wind farm operation efficiency evaluation method, so that the wind farm operation efficiency is evaluated based on the more single wind farm operation data, however, the problem of low evaluation accuracy of the wind farm operation efficiency exists in the prior art.
Disclosure of Invention
Based on the above, it is necessary to provide a method, a device, equipment and a medium for evaluating the operation efficiency of a wind farm according to the above technical problems. According to historical operation data corresponding to wind power plants and comprising various data, basic statistical indexes corresponding to the wind power plants can be determined, the problem of single evaluation data in the prior art is solved, after the high-order statistical indexes are further determined according to the basic statistical indexes, target efficiency evaluation parameters of each wind power plant are calculated by using the high-order statistical indexes and all first wind power plant statistical parameters corresponding to the high-order statistical indexes, so that evaluation of operation efficiency of each wind power plant is realized, and each power generation enterprise is prevented from evaluating by adopting a respective wind power plant operation efficiency evaluation method in the prior art, so that evaluation accuracy of wind power plant operation efficiency is improved.
In a first aspect of the embodiments of the present disclosure, a method for evaluating operation efficiency of a wind farm is provided, where the method includes:
according to historical operation data of a wind power plant, determining a basic statistical index corresponding to the wind power plant, wherein the historical operation data at least comprises: wind tower data, laser radar wind data, data acquisition and monitoring control system data, production operation management system data, power control system data and wind turbine generator design data;
after determining a basic statistical index corresponding to the wind power plant, determining a higher-order statistical index corresponding to the wind power plant based on the basic statistical index;
and determining a target efficiency evaluation parameter corresponding to the wind power plant according to the high-order statistical index and all first wind power plant statistical parameters corresponding to the high-order statistical index, wherein the target efficiency evaluation parameter is used for evaluating the operation efficiency of the wind power plant.
In one embodiment, before determining the basic statistical index corresponding to the wind farm according to the historical operation data of the wind farm, the method further includes:
in a preset period, according to a preset duration, statistics is carried out on historical operation data corresponding to the wind power plant;
Wherein the preset duration is less than the preset period.
In one embodiment, the base statistical indicator comprises: design performance, accessibility performance, actual performance, performance loss, energy consumption level, network performance, and security achievement score;
the high-order statistical indicators include design level indicators, maintenance level indicators, operation level indicators, and safety level indicators.
In one embodiment, after determining the basic statistical indicator corresponding to the wind farm, determining the higher-order statistical indicator corresponding to the wind farm based on the basic statistical indicator includes:
and determining each first wind power plant statistical parameter corresponding to a design level index, a maintenance level index, an operation level index and a safety level index included in the high-order statistical index based on at least one second wind power plant statistical parameter corresponding to the design performance, the reachable performance, the actual performance, the performance loss, the energy consumption degree, the network-related performance and the safety standard score respectively.
In one embodiment, the determining, according to the high-order statistical index and all the first wind farm statistical parameters corresponding to the high-order statistical index, the target performance evaluation parameter corresponding to the wind farm includes:
Acquiring first target weights respectively corresponding to all first wind power plant statistical parameters included in the design level index, the maintenance level index, the operation level index and the safety level index;
acquiring second target weights corresponding to the design level index, the maintenance level index, the operation level index and the safety level index respectively;
and determining target efficiency evaluation parameters corresponding to the wind power plant according to the first wind power plant statistical parameters, the first target weights corresponding to the first wind power plant statistical parameters, and the second target weights corresponding to the design level index, the maintenance level index, the operation level index and the safety level index.
In one embodiment, the obtaining the first target weights corresponding to all the first wind farm statistical parameters included in the design level indicator, the maintenance level indicator, the operation level indicator, and the safety level indicator includes:
calculating first target weights corresponding to all the first wind farm statistical parameters respectively through an analytic hierarchy process;
obtaining the second target weights respectively corresponding to the design level index, the maintenance level index, the operation level index and the safety level index, including:
And calculating second target weights respectively corresponding to the design level index, the maintenance level index, the operation level index and the safety level index through an analytic hierarchy process.
In one embodiment, the target performance evaluation parameter is used to evaluate the operational performance of the wind farm, comprising:
obtaining target efficiency evaluation parameters corresponding to a plurality of wind power plants in a preset range;
calculating average efficiency evaluation parameters corresponding to the wind power plants in a preset range according to target efficiency evaluation parameters corresponding to the wind power plants respectively;
and evaluating each wind power plant within a preset range according to the average efficiency evaluation parameter and the target efficiency evaluation parameter corresponding to each wind power plant.
In a second aspect of the embodiments of the present disclosure, there is provided a wind farm operation efficiency evaluation device, the device including:
the base statistical index determining module is used for determining a base statistical index corresponding to a wind power plant according to historical operation data of the wind power plant, wherein the historical operation data at least comprises: wind tower data, laser radar wind data, data acquisition and monitoring control system data, production operation management system data, power control system data and wind turbine generator design data;
The high-order statistical index determining module is used for determining the high-order statistical index corresponding to the wind power plant based on the basic statistical index after determining the basic statistical index corresponding to the wind power plant;
the target efficiency evaluation parameter determining module is configured to determine a target efficiency evaluation parameter corresponding to the wind farm according to the high-order statistical index and all the first wind farm statistical parameters corresponding to the high-order statistical index, where the target efficiency evaluation parameter is used to evaluate operation efficiency of the wind farm.
In a third aspect of the disclosed embodiments, there is provided an electronic device, including:
one or more processors;
storage means for storing one or more programs,
the one or more programs, when executed by the one or more processors, cause the one or more processors to implement the method of any of the first aspects.
In a fourth aspect, embodiments of the present disclosure provide a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements a method according to any of the first aspects.
Compared with the prior art, the technical scheme provided by the embodiment of the disclosure has the following advantages:
The disclosure provides a wind farm operation efficiency evaluation method, device, equipment and medium, which determine a basic statistical index corresponding to a wind farm according to historical operation data of the wind farm, wherein the historical operation data at least comprises: wind tower data, laser radar wind data, data acquisition and monitoring control system data, production operation management system data, power control system data and wind turbine generator design data; after the basic statistical indexes corresponding to the wind power plant are determined, determining the high-order statistical indexes corresponding to the wind power plant based on the basic statistical indexes; and determining target efficiency evaluation parameters corresponding to the wind power plant according to the high-order statistical indexes and all first wind power plant statistical parameters corresponding to the high-order statistical indexes, wherein the target efficiency evaluation parameters are used for evaluating the operation efficiency of the wind power plant. In the process, the basic statistical index corresponding to the wind power plant can be determined according to the historical operation data corresponding to the wind power plant and comprising various data, the problem of single evaluation data in the prior art is solved, and after the high-order statistical index is further determined according to the basic statistical index, the target efficiency evaluation parameters of each wind power plant are calculated by utilizing the high-order statistical index and all the first wind power plant statistical parameters corresponding to the high-order statistical index, so that the evaluation of the operation efficiency of each wind power plant is realized, and each power generation enterprise is prevented from evaluating by adopting a respective wind power plant operation efficiency evaluation method in the prior art, so that the evaluation accuracy of the operation efficiency of the wind power plant is improved.
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The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the disclosure and together with the description, serve to explain the principles of the disclosure.
In order to more clearly illustrate the embodiments of the present disclosure or the solutions in the prior art, the drawings that are required for the description of the embodiments or the prior art will be briefly described below, and it will be obvious to those skilled in the art that other drawings can be obtained from these drawings without inventive effort.
Fig. 1 is a schematic flow chart of a method for evaluating operation efficiency of a wind farm according to an embodiment of the disclosure;
fig. 2 is a schematic structural diagram of a wind farm operation efficiency evaluation device according to an embodiment of the present disclosure;
fig. 3 is an internal structural diagram of an electronic device provided in an embodiment of the present disclosure.
Detailed Description
In order that the above objects, features and advantages of the present disclosure may be more clearly understood, a further description of aspects of the present disclosure will be provided below. It should be noted that, without conflict, the embodiments of the present disclosure and features in the embodiments may be combined with each other.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present disclosure, but the present disclosure may be practiced otherwise than as described herein; it will be apparent that the embodiments in the specification are only some, but not all, embodiments of the disclosure.
The terms first, second and the like in the description and in the claims, are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged, where appropriate, such that embodiments of the disclosure may be practiced in sequences other than those illustrated and described herein, and that the objects identified by "first," "second," etc. are generally of the same type and are not limited to the number of objects, e.g., the first object may be one or more. Furthermore, in the description and claims, "and/or" means at least one of the connected objects, and the character "/", generally means that the associated object is an "or" relationship.
In the prior art, when wind farm operation efficiency evaluation is performed for different power generation enterprises, each power generation enterprise depends on single wind farm operation data, for example, only depends on data acquisition and monitoring control system (supervisory control and data acquisition, SCADA) data, and each power generation enterprise realizes the evaluation of wind farm operation efficiency based on the single wind farm operation data according to respective wind farm operation efficiency evaluation methods, and the wind farm operation data to be evaluated is single, and the wind farm operation efficiency evaluation methods have no universality, so that the evaluation of wind farm operation efficiency cannot be accurately realized.
Based on the above problems, the present disclosure provides a wind farm operation efficiency evaluation method, device, equipment and medium, by determining a basic statistical index corresponding to a wind farm according to historical operation data of the wind farm, where the historical operation data at least includes: wind tower data, laser radar wind data, data acquisition and monitoring control system data, production operation management system data, power control system data and wind turbine generator design data; after the basic statistical indexes corresponding to the wind power plant are determined, determining the high-order statistical indexes corresponding to the wind power plant based on the basic statistical indexes; and determining target efficiency evaluation parameters corresponding to the wind power plant according to the high-order statistical indexes and all first wind power plant statistical parameters corresponding to the high-order statistical indexes, wherein the target efficiency evaluation parameters are used for evaluating the operation efficiency of the wind power plant. In the process, the basic statistical index corresponding to the wind power plant can be determined according to the historical operation data corresponding to the wind power plant and comprising various data, the problem of single evaluation data in the prior art is solved, and after the high-order statistical index is further determined according to the basic statistical index, the target efficiency evaluation parameters of each wind power plant are calculated by utilizing the high-order statistical index and all the first wind power plant statistical parameters corresponding to the high-order statistical index, so that the evaluation of the operation efficiency of each wind power plant is realized, and each power generation enterprise is prevented from evaluating by adopting a respective wind power plant operation efficiency evaluation method in the prior art, so that the evaluation accuracy of the operation efficiency of the wind power plant is improved.
For more detailed description of the present solution, the following description will be given by way of example with reference to fig. 1, and it will be understood that the steps involved in fig. 1 may include more steps or fewer steps when actually implemented, and the order of these steps may also be different, so as to enable the wind farm operation efficiency evaluation method provided in the embodiments of the present application.
Fig. 1 is a flow chart of a wind farm operation efficiency evaluation method according to an embodiment of the present disclosure. The method of the embodiment is executed by a wind farm operation efficiency evaluation device applied to electronic equipment, and the device can be realized by adopting a hardware/software mode. As shown in fig. 1, the wind farm operation efficiency evaluation method specifically includes the following steps:
s11: and determining a basic statistical index corresponding to the wind power plant according to the historical operation data of the wind power plant.
Wherein, the historical operating data at least comprises: wind tower data, laser radar wind data, data acquisition and monitoring control system data, production operation management system data, power control system data and wind turbine generator design data.
The wind tower data includes, but is not limited to, air temperature, air pressure, humidity, different elevation layer wind speeds and wind direction. Laser radar anemometry data includes, but is not limited to, different elevation layer wind speeds and wind directions. Data acquisition and monitoring control system data includes, but is not limited to, pitch angle and active power. The production operation management system data comprises, but is not limited to, a fault unit, a fault start time and a fault end time corresponding to the fault unit, a fixed check start time and a fixed check end time corresponding to the fixed check unit, and the power control system data comprises, but is not limited to, a power limiting unit, a power limiting start time and a power limiting end time corresponding to the power limiting unit, power limiting power, active fluctuation, response time and voltage drop times. The present disclosure is not particularly limited, and those skilled in the art may set the present disclosure according to actual circumstances.
Specifically, for each wind power plant, according to collected historical operation data corresponding to each wind power plant, such as wind tower data, laser radar wind measurement data, data collection and monitoring control system data, production operation management system data, power control system data and wind turbine generator design data, basic statistical indexes corresponding to the wind power plant are determined.
Optionally, on the basis of the foregoing embodiments, in some embodiments of the present disclosure, the foregoing basic statistical indicators include design performance, reachability performance, actual performance, performance loss, energy consumption level, grid-related performance, and safety achievement score, and the design performance, reachability performance, actual performance, performance loss, energy consumption level, grid-related performance, and safety achievement score included for the basic statistical indicators include one or more second wind farm statistical parameters, respectively.
For example, the second wind farm statistical parameter included for the design performance may be, for example, the effective wind energy, and the design power generation. The second wind farm statistical parameter included for the achievable performance may be, for example, the achievable generation amount. The second wind farm statistical parameters included for the actual performance may be, for example, the actual power generation amount, and the operation maintenance fee. The second wind farm statistical parameter included for the performance loss may be, for example, a fault loss power, a fixed check loss power, a scheduled limit loss power, and other loss power due to different causes of off-farm transmission line faults, power system faults, bad weather such as lightning, freezing, typhoons, etc. The second wind farm statistical parameter included for the energy consumption level may be, for example, the comprehensive farm power consumption and the outgoing line loss power. The second wind farm statistical parameter included for the grid-related performance may be, for example, active fluctuation, response time, low voltage drop times, etc. The second wind farm statistical parameters included in the safety standard score may be, for example, a production facility system safety level standard score, a fire safety level standard score, a labor and operation environment safety level standard score, and a safety management level standard score, but are not limited thereto, and the present disclosure is not particularly limited thereto, and may be set by those skilled in the art according to actual conditions.
Further, in some embodiments of the present disclosure, an implementation manner of S11 may be that, according to collected historical operation data corresponding to each wind farm, design performance, reachable performance, actual performance, performance loss, energy consumption degree, grid-related performance and safety standard score corresponding to the basic statistical index corresponding to the wind farm are determined, where the design performance, reachable performance, actual performance, performance loss, energy consumption degree, grid-related performance and safety standard score correspond to each second wind farm statistical parameter.
For example, the second wind farm statistical parameter included in the design performance may be, for example, effective wind energy, and is calculated and determined according to historical operation data of the wind farm, such as the number of wind turbines in a statistical period, the number of wind speed data, the air density at each moment, the swept area of the wind turbine of each wind turbine and the equivalent wind speed of the wind turbine of each wind turbine at different moments. The effective wind energy may be defined by the following expression:
wherein N represents the number of wind turbines, T represents the number of wind speed data, ρ (T) represents the air density at the T-th moment, and A i The method comprises the steps of representing the wind wheel swept area of an ith wind turbine, wherein Vi (t) represents the wind wheel equivalent wind speed of the ith wind turbine at the t moment, and Deltat represents the time interval of historical operation data measuring points.
The design power generation amount may be specifically defined by the following expression:
wherein, the liquid crystal display device comprises a liquid crystal display device,
represents the hub altitude incoming wind speed, f of the ith wind turbine generator and the t moment 0 i () And (5) representing an ith wind turbine generator system power curve.
It should be noted that, for a specific calculation manner of the design performance, the reachable performance, the actual performance, the performance loss, the energy consumption degree, the network-related performance and other second wind farm statistical parameters corresponding to the safe standard-reaching scores respectively, reference may be made to the prior art, and this disclosure is not specifically limited, and is not repeated here.
S12: after the basic statistical index corresponding to the wind power plant is determined, the high-order statistical index corresponding to the wind power plant is determined based on the basic statistical index.
Optionally, on the basis of the foregoing embodiments, in some embodiments of the present disclosure, the high-order statistics include a design level indicator, a maintenance level indicator, an operation level indicator, and a safety level indicator, and the high-order statistics include one or more first wind farm statistical parameters respectively.
For example, the first wind farm statistical parameter included for the design level indicator may be, for example, a design wind energy utilization rate, and the first wind farm statistical parameter included for the maintenance level indicator may be, for example, a maintenance performance coefficient, a failure loss coefficient, and a fixed inspection loss coefficient. The first wind farm statistical parameter included for the operation level index may be, for example, an operation performance coefficient, a scheduling electricity limiting loss coefficient, other loss coefficients, a comprehensive farm electricity utilization rate, an outgoing line loss rate, a power operation maintenance fee, a maximum active fluctuation, an average response time, a low voltage ride through performance, and a prediction error. The first wind farm statistical parameter included in the safety level index may be, for example, a production facility system safety factor, a fire safety factor, a labor and work environment safety factor, and a safety management level factor, but is not limited thereto, and the present disclosure is not particularly limited thereto, and may be set by those skilled in the art according to actual situations.
Optionally, in connection with the foregoing embodiments, in some embodiments of the present disclosure, an implementation manner of determining, based on the basic statistical indicator, a higher-order statistical indicator corresponding to the wind farm may be:
s121: and determining the first wind power plant statistical parameters respectively corresponding to the design level index, the maintenance level index, the operation level index and the safety level index included by the high-order statistical index based on the at least one second wind power plant statistical parameter respectively corresponding to the design performance, the accessibility performance, the actual performance, the performance loss, the energy consumption degree, the network-related performance and the safety standard-reaching score.
Specifically, in a preset period, the collected historical operation data of the wind power plant are used for calculating one or more second wind power plant statistical parameters corresponding to basic statistical indexes of the wind power plant, including design performance, accessibility performance, actual performance, performance loss, energy consumption degree, network-related performance and safety standard-reaching score, and calculating each first wind power plant statistical parameter corresponding to a design level index, a maintenance level index, an operation level index and a safety level index included in the high-order statistical indexes.
Illustratively, in connection with the above embodiment, for a first wind farm statistical parameter, such as a designed wind energy utilization rate, included in a design level index in the high-order statistical index, the first wind farm statistical parameter, such as a designed power generation amount of a wind farm and an effective wind energy, included in the basic statistical index, may be calculated and determined, and may be specifically defined by the following expression:
Wherein E is 0 Representing the designed generating capacity of the wind power plant, and E represents the effective wind energy.
It should be noted that, for the specific calculation manner of the other first wind farm statistical parameters corresponding to the design level index, the maintenance level index, the operation level index and the safety level index, which are included in the high-order statistical index, reference may be made to the prior art, and this disclosure is not specifically limited, and is not repeated herein.
S13: and determining target efficiency evaluation parameters corresponding to the wind power plant according to the high-order statistical indexes and all first wind power plant statistical parameters corresponding to the high-order statistical indexes.
The target efficiency evaluation parameter is used for evaluating the operation efficiency of the wind power plant.
Specifically, after determining the high-order statistical index corresponding to the wind farm, determining the target efficiency evaluation parameter corresponding to the wind farm according to the high-order statistical index and all the first wind farm statistical parameters respectively corresponding to the high-order statistical index such as the design level index, the maintenance level index, the operation level index and the safety level index, so as to realize the evaluation of the operation efficiency of the wind farm by using the target efficiency evaluation parameter.
In this way, according to the method for evaluating the operation efficiency of the wind farm provided by the embodiment, the basic statistical index corresponding to the wind farm is determined according to the historical operation data of the wind farm, where the historical operation data at least includes: wind tower data, laser radar wind data, data acquisition and monitoring control system data, production operation management system data, power control system data and wind turbine generator design data; after the basic statistical indexes corresponding to the wind power plant are determined, determining the high-order statistical indexes corresponding to the wind power plant based on the basic statistical indexes; and determining target efficiency evaluation parameters corresponding to the wind power plant according to the high-order statistical indexes and all first wind power plant statistical parameters corresponding to the high-order statistical indexes, wherein the target efficiency evaluation parameters are used for evaluating the operation efficiency of the wind power plant. In the process, the basic statistical index corresponding to the wind power plant can be determined according to the historical operation data corresponding to the wind power plant and comprising various data, the problem of single evaluation data in the prior art is solved, and after the high-order statistical index is further determined according to the basic statistical index, the target efficiency evaluation parameters of each wind power plant are calculated by utilizing the high-order statistical index and all the first wind power plant statistical parameters corresponding to the high-order statistical index, so that the evaluation of the operation efficiency of each wind power plant is realized, and each power generation enterprise is prevented from evaluating by adopting a respective wind power plant operation efficiency evaluation method in the prior art, so that the evaluation accuracy of the operation efficiency of the wind power plant is improved.
Optionally, on the basis of the above embodiment, in some embodiments of the disclosure, before performing S11, further includes:
s10: and in a preset period, according to the preset duration, counting historical operation data corresponding to the wind power plant.
Wherein the preset duration is less than the preset period. The preset period is a period parameter set for counting historical operation data corresponding to the wind power plant, and a large amount of historical operation data corresponding to the wind power plant can be obtained by setting the preset period, and the preset period can be, for example, one month or one quarter, but is not limited to, the present disclosure is not particularly limited, and a person skilled in the art can set according to practical situations.
The preset duration refers to a measurement point time interval for collecting historical operation data corresponding to the wind power plant in a preset period, and the preset duration may be, for example, 10 minutes, that is, the historical operation data corresponding to the wind power plant is collected once every ten minutes, but is not limited thereto, the disclosure is not particularly limited, and a person skilled in the art may set according to actual situations.
In this way, according to the method for evaluating the wind farm operation efficiency provided by the embodiment, through the process, a large amount of historical operation data corresponding to the wind farm can be collected through setting the preset period and the preset duration, so that the subsequent evaluation of the wind farm operation efficiency based on the large amount of historical operation data is facilitated.
Alternatively, based on the above embodiments, in some embodiments of the disclosure, one implementation of S13 may be:
s131: and acquiring first target weights respectively corresponding to all the first wind power plant statistical parameters included in the design level index, the maintenance level index, the operation level index and the safety level index.
The first target weight refers to a corresponding parameter value given to different first wind farm statistical parameters because the different first wind farm statistical parameters have different degrees of influence on wind farm operation efficiency in the wind farm operation efficiency evaluation process, that is, the first target weight is used for measuring the degree of influence of the different first wind farm statistical parameters on wind farm operation efficiency evaluation.
Alternatively, based on the above embodiments, in some embodiments of the disclosure, one implementation of S131 may be:
s1311: and calculating first target weights corresponding to all the first wind farm statistical parameters respectively through an analytic hierarchy process.
The analytic hierarchy process is a subjective weight assignment mode, wherein the subjective weight assignment is a weighting method for determining the weight of each index by comparing the importance degree of each index based on the knowledge experience or preference of a decision maker.
The specific calculation process for the above-mentioned analytic hierarchy process is as follows: firstly, decomposing a decision problem into different hierarchical structures according to the sequence of a total target, each layer of sub-targets and an evaluation criterion, then comparing and scoring the importance of the same level of factors two by using a scaling method such as a satty 1-9 scaling method to obtain positive and negative interaction matrixes of different levels, finally, after the weights of the factors are obtained according to the positive and negative interaction matrixes, carrying out consistency check on the positive and negative interaction matrixes, and when the positive and negative interaction matrixes are determined to meet consistency, determining that the weights of the current factors are final weights. And when the positive and negative interaction matrixes are determined to not meet the consistency, reassigning and correcting are needed until the consistency check is passed.
The method comprises the steps of decomposing data into different layers according to a hierarchical analysis method, namely determining all first wind power plant statistical parameters as sub-criterion layers, comparing all first wind power plant statistical parameters included in the sub-criterion layers by two by utilizing a scaling method such as a satty 1-9 scaling method to obtain a positive and negative interaction matrix of the sub-criterion layers, carrying out product operation on each row of elements of the positive and negative interaction matrix, calculating square root values corresponding to the product of each row of elements, and carrying out normalization processing to obtain weights respectively corresponding to all first wind power plant statistical parameters included in the sub-criterion layers, further carrying out consistency check on the positive and negative interaction matrix, and determining that the weights respectively corresponding to all current first wind power plant statistical parameters are first target weights when the positive and negative interaction matrix corresponding to the sub-criterion layers meets the consistency check.
S132: and obtaining second target weights corresponding to the design level index, the maintenance level index, the operation level index and the safety level index respectively.
The second target weight is used for measuring the influence degree of the design level index, the maintenance level index, the operation level index and the safety level index on the wind power plant operation efficiency evaluation.
Alternatively, based on the above embodiments, in some embodiments of the disclosure, one implementation of S131 may be:
s1321: and calculating second target weights corresponding to the design level index, the maintenance level index, the operation level index and the safety level index respectively through an analytic hierarchy process.
For the specific implementation procedure of S1321, refer to the implementation procedure of S1311 in the foregoing embodiment, and will not be repeated here.
S133: and determining target efficiency evaluation parameters corresponding to the wind power plant according to all the first wind power plant statistical parameters, first target weights corresponding to all the first wind power plant statistical parameters respectively, and second target weights corresponding to the design level index, the maintenance level index, the operation level index and the safety level index respectively.
Specifically, according to an analytic hierarchy process, after first target weights corresponding to all the first wind farm statistical parameters are calculated, and second target weights corresponding to the level indexes, the maintenance level indexes, the operation level indexes and the safety level indexes are designed, target efficiency evaluation parameters corresponding to the wind farm are determined according to all the first wind farm statistical parameters, the first target weights corresponding to all the first wind farm statistical parameters, the second target weights corresponding to the design level indexes, the maintenance level indexes, the operation level indexes and the safety level indexes.
Alternatively, based on the above embodiments, in some embodiments of the present disclosure, the target performance evaluation parameter may be specifically defined by the following expression:
wherein, the high-order evaluation index comprises a design level index, a maintenance level index, an operation level index and a safety level index, then w i Representing a second target weight corresponding to the ith higher-order statistical index, n i The number of the first wind power plant statistical parameters included in the ith high-order evaluation index is the number of the first wind power plant statistical parameters; mu (mu) ij Is the ithA first target weight corresponding to a j-th first wind power plant statistical parameter in the high-order evaluation index; η (eta) ij And the statistical parameter is the j first wind farm statistical parameter in the i higher-order evaluation index.
In this way, according to the method for evaluating the operation efficiency of the wind farm provided by the embodiment, through the above process, the target efficiency evaluation parameter for evaluating the operation efficiency of the wind farm is obtained, so that the accuracy of evaluating the operation efficiency of the wind farm is improved.
Optionally, on the basis of the foregoing embodiments, in some embodiments of the present disclosure, one implementation of the target performance evaluation parameter for evaluating the operation performance of the wind farm may be:
and acquiring target efficiency evaluation parameters corresponding to the wind power plants in a preset range.
The preset range may be, for example, the same area, for example, an area corresponding to one province, but is not limited thereto, and the disclosure is not particularly limited thereto, and may be set by those skilled in the art according to actual situations.
And calculating average efficiency evaluation parameters corresponding to the wind power plants in a preset range according to the target efficiency evaluation parameters corresponding to the wind power plants.
And evaluating each wind power plant in a preset range according to the average efficiency evaluation parameter and the target efficiency evaluation parameter corresponding to each wind power plant.
Specifically, target efficiency evaluation parameters corresponding to a plurality of wind power plants in a preset range are obtained, average calculation is carried out on the target efficiency evaluation parameters corresponding to the wind power plants in the preset range, average efficiency evaluation parameters corresponding to the wind power plants in the preset range are obtained, and then each wind power plant in the preset range is evaluated according to the average efficiency evaluation parameters and the target efficiency evaluation parameters corresponding to each wind power plant in the preset range.
In this way, the method for evaluating the operation efficiency of the wind power plant provided by the embodiment can realize the operation efficiency of a plurality of wind power plants in a preset range through the process, and is convenient for users and enterprises to manage.
The embodiment of the disclosure also provides a wind farm operation efficiency evaluation device, which is used for executing any wind farm operation efficiency evaluation method provided by the embodiment, and has the corresponding beneficial effects of the wind farm operation efficiency evaluation method.
Fig. 2 is a schematic structural diagram of a wind farm operation efficiency evaluation device according to an embodiment of the present disclosure, including: a basic statistical index determination module 11, a higher-order statistical index determination module 12 and a target efficacy evaluation parameter determination module 13.
The base statistical index determining module 11 is configured to determine a base statistical index corresponding to a wind farm according to historical operation data of the wind farm, where the historical operation data at least includes: wind tower data, laser radar wind data, data acquisition and monitoring control system data, production operation management system data, power control system data and wind turbine generator design data;
a higher-order statistical index determining module 12, configured to determine a higher-order statistical index corresponding to the wind farm based on the basic statistical index after determining the basic statistical index corresponding to the wind farm;
the target performance evaluation parameter determining module 13 is configured to determine a target performance evaluation parameter corresponding to the wind farm according to the high-order statistical indicator and at least one first wind farm statistical parameter corresponding to the high-order statistical indicator, where the target performance evaluation parameter is used to evaluate an operation performance of the wind farm.
In the above embodiment, the apparatus further includes: the statistics module is used for counting historical operation data corresponding to the wind power plant according to preset duration in a preset period; wherein the preset duration is less than the preset period.
In the above embodiment, the basic statistical index includes: design performance, accessibility performance, actual performance, performance loss, energy consumption level, network performance, and security achievement score;
the high-order statistical indicators include design level indicators, maintenance level indicators, operation level indicators, and safety level indicators.
In the foregoing embodiment, the higher-order statistical indicator determining module 12 is specifically configured to determine, based on at least one second wind farm statistical parameter corresponding to the design performance, the reachability performance, the actual performance, the performance loss, the energy consumption degree, the grid-related performance, and the safety standard reaching score, each of the first wind farm statistical parameters corresponding to the design level indicator, the maintenance level indicator, the operation level indicator, and the safety level indicator included in the higher-order statistical indicator.
In the above embodiment, the target performance evaluation parameter determining module 13 is specifically configured to obtain first target weights corresponding to all the first wind farm statistical parameters included in the design level indicator, the maintenance level indicator, the operation level indicator, and the safety level indicator, respectively;
Acquiring second target weights corresponding to the design level index, the maintenance level index, the operation level index and the safety level index respectively;
and determining target efficiency evaluation parameters corresponding to the wind power plant according to the first wind power plant statistical parameters, the first target weights corresponding to the first wind power plant statistical parameters, and the second target weights corresponding to the design level index, the maintenance level index, the operation level index and the safety level index.
In the above embodiment, the target performance evaluation parameter determining module 13 is specifically further configured to calculate, by using a hierarchical analysis method, first target weights corresponding to all the first wind farm statistical parameters respectively; and calculating second target weights respectively corresponding to the design level index, the maintenance level index, the operation level index and the safety level index through an analytic hierarchy process.
In the above embodiment, the apparatus further includes: the evaluation module is used for acquiring target efficiency evaluation parameters corresponding to the wind power plants in a preset range; calculating average efficiency evaluation parameters corresponding to the wind power plants in a preset range according to target efficiency evaluation parameters corresponding to the wind power plants respectively; and evaluating each wind power plant within a preset range according to the average efficiency evaluation parameter and the target efficiency evaluation parameter corresponding to each wind power plant.
In this way, the base statistical index determining module is configured to determine, according to historical operation data of a wind farm, a base statistical index corresponding to the wind farm, where the historical operation data at least includes: wind tower data, laser radar wind data, data acquisition and monitoring control system data, production operation management system data, power control system data and wind turbine generator design data; the high-order statistical index determining module is used for determining the high-order statistical index corresponding to the wind power plant based on the basic statistical index after determining the basic statistical index corresponding to the wind power plant; the target efficiency evaluation parameter determining module is used for determining target efficiency evaluation parameters corresponding to the wind power plant according to the high-order statistical index and at least one first wind power plant statistical parameter corresponding to the high-order statistical index, wherein the target efficiency evaluation parameters are used for evaluating the operation efficiency of the wind power plant. In the process, the basic statistical index corresponding to the wind power plant can be determined according to the historical operation data corresponding to the wind power plant and comprising various data, the problem of single evaluation data in the prior art is solved, and after the high-order statistical index is further determined according to the basic statistical index, the target efficiency evaluation parameters of each wind power plant are calculated by utilizing the high-order statistical index and all the first wind power plant statistical parameters corresponding to the high-order statistical index, so that the evaluation of the operation efficiency of each wind power plant is realized, and each power generation enterprise is prevented from evaluating by adopting a respective wind power plant operation efficiency evaluation method in the prior art, so that the evaluation accuracy of the operation efficiency of the wind power plant is improved.
Fig. 3 is a schematic structural diagram of an electronic device according to an embodiment of the present disclosure, and as shown in fig. 3, the electronic device includes a processor 310, a memory 320, an input device 330, and an output device 340; the number of processors 310 in the computer device may be one or more, one processor 310 being taken as an example in fig. 3; the processor 310, the memory 320, the input device 330 and the output device 340 in the electronic device may be connected by a bus or other means, in fig. 3 by way of example.
The memory 320 is a computer readable storage medium, and may be used to store a software program, a computer executable program, and modules, such as program instructions/modules corresponding to the methods in the embodiments of the present invention. The processor 310 executes various functional applications of the computer device and data processing, i.e., implements the methods provided by embodiments of the present invention, by running software programs, instructions, and modules stored in the memory 320.
The input device 330 may be used to receive input numeric or character information and to generate key signal inputs related to user settings and function control of the electronic device, which may include a keyboard, mouse, etc. The output device 340 may include a display device such as a display screen.
The disclosed embodiments also provide a storage medium containing computer executable instructions which, when executed by a computer processor, are used to implement the methods provided by the embodiments of the present invention, the method comprising:
according to historical operation data of a wind power plant, determining a basic statistical index corresponding to the wind power plant, wherein the historical operation data at least comprises: wind tower data, laser radar wind data, data acquisition and monitoring control system data, production operation management system data, power control system data and wind turbine generator design data;
after determining a basic statistical index corresponding to the wind power plant, determining a higher-order statistical index corresponding to the wind power plant based on the basic statistical index;
and determining a target efficiency evaluation parameter corresponding to the wind power plant according to the high-order statistical index and all first wind power plant statistical parameters corresponding to the high-order statistical index, wherein the target efficiency evaluation parameter is used for evaluating the operation efficiency of the wind power plant.
Of course, the storage medium containing computer executable instructions provided in the embodiments of the present invention is not limited to the method operations described above, and may also perform related operations in the method provided in any embodiment of the present invention.
From the above description of embodiments, it will be clear to a person skilled in the art that the present invention may be implemented by means of software and necessary general purpose hardware, but of course also by means of hardware, although in many cases the former is a preferred embodiment. Based on such understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art in the form of a software product, which may be stored in a computer readable storage medium, such as a floppy disk, a Read-Only Memory (ROM), a random access Memory (Random Access Memory, RAM), a FLASH Memory (FLASH), a hard disk or an optical disk of a computer, etc., and include several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the method according to the embodiments of the present invention.
It should be noted that in this document, relational terms such as "first" and "second" and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
The foregoing is merely a specific embodiment of the disclosure to enable one skilled in the art to understand or practice the disclosure. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the disclosure. Thus, the present disclosure is not intended to be limited to the embodiments shown and described herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (10)
1. A method for evaluating the operational efficiency of a wind farm, the method comprising:
according to historical operation data of a wind power plant, determining a basic statistical index corresponding to the wind power plant, wherein the historical operation data at least comprises: wind tower data, laser radar wind data, data acquisition and monitoring control system data, production operation management system data, power control system data and wind turbine generator design data;
after determining a basic statistical index corresponding to the wind power plant, determining a higher-order statistical index corresponding to the wind power plant based on the basic statistical index;
and determining a target efficiency evaluation parameter corresponding to the wind power plant according to the high-order statistical index and all first wind power plant statistical parameters corresponding to the high-order statistical index, wherein the target efficiency evaluation parameter is used for evaluating the operation efficiency of the wind power plant.
2. The method according to claim 1, wherein before determining the base statistical indicator corresponding to the wind farm according to the historical operation data of the wind farm, the method further comprises:
in a preset period, according to a preset duration, statistics is carried out on historical operation data corresponding to the wind power plant;
wherein the preset duration is less than the preset period.
3. The method of claim 1, wherein the base statistical indicator comprises: design performance, accessibility performance, actual performance, performance loss, energy consumption level, network performance, and security achievement score;
the high-order statistical indicators include design level indicators, maintenance level indicators, operation level indicators, and safety level indicators.
4. A method according to claim 3, wherein after determining the base statistical indicator corresponding to the wind farm, determining the higher-order statistical indicator corresponding to the wind farm based on the base statistical indicator comprises:
and determining each first wind power plant statistical parameter corresponding to a design level index, a maintenance level index, an operation level index and a safety level index included in the high-order statistical index based on at least one second wind power plant statistical parameter corresponding to the design performance, the reachable performance, the actual performance, the performance loss, the energy consumption degree, the network-related performance and the safety standard score respectively.
5. The method of claim 4, wherein determining the target performance evaluation parameter corresponding to the wind farm according to the high-order statistical indicator and all the first wind farm statistical parameters corresponding to the high-order statistical indicator comprises:
acquiring first target weights respectively corresponding to all first wind power plant statistical parameters included in the design level index, the maintenance level index, the operation level index and the safety level index;
acquiring second target weights corresponding to the design level index, the maintenance level index, the operation level index and the safety level index respectively;
and determining target efficiency evaluation parameters corresponding to the wind power plant according to the first wind power plant statistical parameters, the first target weights corresponding to the first wind power plant statistical parameters, and the second target weights corresponding to the design level index, the maintenance level index, the operation level index and the safety level index.
6. The method of claim 5, wherein the obtaining the first target weights for all the first wind farm statistical parameters included in the design level indicator, the maintenance level indicator, the operation level indicator, and the safety level indicator includes respectively includes:
Calculating first target weights corresponding to all the first wind farm statistical parameters respectively through an analytic hierarchy process;
obtaining the second target weights respectively corresponding to the design level index, the maintenance level index, the operation level index and the safety level index, including:
and calculating second target weights respectively corresponding to the design level index, the maintenance level index, the operation level index and the safety level index through an analytic hierarchy process.
7. The method of claim 1, wherein the target performance evaluation parameter is used to evaluate an operational performance of the wind farm, comprising:
obtaining target efficiency evaluation parameters corresponding to a plurality of wind power plants in a preset range;
calculating average efficiency evaluation parameters corresponding to the wind power plants in a preset range according to target efficiency evaluation parameters corresponding to the wind power plants respectively;
and evaluating each wind power plant within a preset range according to the average efficiency evaluation parameter and the target efficiency evaluation parameter corresponding to each wind power plant.
8. A wind farm operational effectiveness evaluation device, the device comprising:
the base statistical index determining module is used for determining a base statistical index corresponding to a wind power plant according to historical operation data of the wind power plant, wherein the historical operation data at least comprises: wind tower data, laser radar wind data, data acquisition and monitoring control system data, production operation management system data, power control system data and wind turbine generator design data;
The high-order statistical index determining module is used for determining the high-order statistical index corresponding to the wind power plant based on the basic statistical index after determining the basic statistical index corresponding to the wind power plant;
the target efficiency evaluation parameter determining module is configured to determine a target efficiency evaluation parameter corresponding to the wind farm according to the high-order statistical index and all the first wind farm statistical parameters corresponding to the high-order statistical index, where the target efficiency evaluation parameter is used to evaluate operation efficiency of the wind farm.
9. An electronic device, comprising:
one or more processors;
storage means for storing one or more programs,
the one or more programs, when executed by the one or more processors, cause the one or more processors to implement the steps of the wind farm operational performance evaluation method of any of claims 1 to 7.
10. A computer-readable storage medium, on which a computer program is stored, characterized in that the program, when being executed by a processor, implements the steps of the wind farm operation performance evaluation method according to any of claims 1 to 7.
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| CN107563564A (en) * | 2017-09-14 | 2018-01-09 | 重庆大学 | A kind of efficiency estimation method of wind power plant scheduling process |
| CN108764755A (en) * | 2018-06-12 | 2018-11-06 | 华北电力大学 | A kind of wind power plant operation benefits synthesis real-time estimating method |
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