CN116776558A - Fan equipment selection method and system based on wind farm power prediction - Google Patents
Fan equipment selection method and system based on wind farm power prediction Download PDFInfo
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Abstract
The application relates to the technical field of wind power generation, in particular to a fan equipment selection method and system based on wind power plant power prediction, wherein the method comprises the following steps: acquiring historical operation data and historical numerical weather forecast data of a wind power plant; establishing a historical power curve according to the historical operation data and the historical numerical weather forecast data; acquiring real-time numerical weather forecast data of a wind power plant and carrying out refinement treatment to obtain predicted power of a fan; and determining the fan power generation cost according to the fan predicted power and the running state data so as to determine the recommended grade corresponding to the fan equipment according to the fan power generation cost. According to the application, the power of the fan equipment of the wind power plant is predicted, so that the power generation cost of the fan is further predicted, and the corresponding recommended level is determined according to the power generation cost of the fan so as to assist the wind power plant to select the optimal fan equipment, so that the power generation efficiency is improved.
Description
Technical Field
The application relates to the technical field of wind power generation, in particular to a fan equipment selection method and system based on wind power plant power prediction.
Background
The wind power generation capacity increases gradually along with the increase of the whole power consumption proportion of the society, and the correct prediction of the electric quantity has important significance in the aspects of relieving the normal pressure of the peak top of a power grid, reducing the spare capacity of a power system, improving the wind power holding capacity of the power grid and the like, and the wind power prediction is an important technical means for guaranteeing the safe, stable and efficient power generation of wind energy.
In the process of equipment purchasing, most of equipment sources are not clear, so that the selection cannot be performed according to the running conditions of different types of wind power equipment in the wind power station.
Therefore, how to analyze and evaluate the operation efficiency of wind power plant based on the wind power plant power prediction to provide assistance for the plant selection of wind power plant stations is a new need for technical development.
Disclosure of Invention
In view of the above, the application provides a fan equipment selection method and a system based on wind power plant power prediction, which mainly aims to solve the problem of how to analyze and evaluate the operation efficiency of wind power equipment based on wind power plant power prediction so as to provide assistance for equipment selection of a wind power plant.
In one aspect, the application provides a fan equipment selection method based on wind farm power prediction, which comprises the following steps:
acquiring historical operation data and historical numerical weather forecast data of a wind power plant; wherein the historical operating data comprises: average power of the fan; the historical numerical weather forecast data includes: wind direction value, wind speed value, air humidity, air pressure value and air temperature value;
establishing a historical power curve according to the historical operation data and the historical numerical weather forecast data;
acquiring real-time numerical weather forecast data of a wind power plant, and carrying out refinement treatment on the real-time numerical weather forecast data to obtain a predicted wind speed value and a predicted wind direction value of the wind power plant under actual terrain conditions;
applying the predicted wind speed value and the predicted wind direction value to a historical power curve to obtain the predicted power of the fan;
presetting a power prediction period, acquiring preset running state data in the power prediction period, and determining fan power generation cost according to fan predicted power and the running state data so as to determine a recommended level corresponding to fan equipment according to the fan power generation cost;
the preset running state data in the power prediction period comprises the following steps: average running time of the fan, average planned shutdown time of the fan and average load of the fan.
In some embodiments of the present application, when determining fan operating efficiency based on fan predicted power and operating state data, the method comprises:
acquiring real-time fan predicted power in a preset power prediction period, and calculating to obtain fan predicted average power A0 in the preset power prediction period according to the real-time fan predicted power;
obtaining an average fan load B0, and presetting a first preset fan load value B1, a second preset fan load value B2, a third preset fan load value B3 and a fourth preset fan load value B4, wherein B1 is more than B2 is more than B3 is more than B4; presetting a first preset adjustment coefficient b1, a second preset adjustment coefficient b2, a third preset adjustment coefficient b3 and a fourth preset adjustment coefficient b4, wherein 1.2 is more than b1 and more than b2 is more than 1 and more than b3 is more than b4 and more than 0.8;
when B0 is more than or equal to B1, a first preset adjustment coefficient B1 is selected to adjust the predicted average power A0 of the fan, and the predicted average power of the fan after adjustment is A0 x B1;
when B1 is more than B0 and is more than or equal to B2, a second preset adjustment coefficient B2 is selected to adjust the predicted average power A0 of the fan, and the predicted average power of the fan after adjustment is A0B 2;
when B2 is more than B0 and is more than or equal to B3, a third preset adjustment coefficient B3 is selected to adjust the predicted average power A0 of the fan, and the predicted average power of the fan after adjustment is A0 x B3;
when B3 is more than B0 and is more than or equal to B4, a fourth preset adjustment coefficient B4 is selected to adjust the fan predicted average power A0, and the fan predicted average power after adjustment is A0 x B4.
In some embodiments of the present application, after the ith adjustment coefficient bi is selected to adjust the fan predicted average power A0, i=1, 2,3,4, and the adjusted fan predicted average power is obtained as a0×bi, the method further includes:
obtaining a fan average operation duration Ca and a fan average planned outage duration Cb, and calculating to obtain a fan average effective operation duration ratio C0 according to the fan average operation duration Ca and the fan average planned outage duration Cb, wherein C0=Ca/(Ca+Cb);
presetting a first preset effective operation ratio C1, a second preset effective operation ratio C2, a third preset effective operation ratio C3 and a third preset effective operation ratio C4, wherein C1 is more than C2 is more than C3 and more than C4; presetting a first preset adjustment coefficient c1, a second preset adjustment coefficient c2, a third preset adjustment coefficient c3 and a fourth preset adjustment coefficient c4, wherein 1.2 is more than c1 and more than c2 is more than 1 and more than c3 is more than c4 and more than 0.8;
when C0 is more than or equal to C1, selecting a first preset adjustment coefficient C1 to carry out secondary adjustment on the adjusted fan predicted average power A0 and bi, wherein the fan predicted average power after secondary adjustment is A0 and bi C1;
when C1 is more than C0 and is more than or equal to C2, selecting a second preset adjustment coefficient C2 to carry out secondary adjustment on the adjusted fan prediction average power A0 and bi, wherein the fan prediction average power after secondary adjustment is A0 and bi C2;
when C2 is more than C0 and is more than or equal to C3, selecting a third preset adjustment coefficient C3 to carry out secondary adjustment on the adjusted fan prediction average power A0 and bi, wherein the fan prediction average power after secondary adjustment is A0 and bi C3;
when C3 is more than C0 and is more than or equal to C4, selecting a fourth preset adjustment coefficient C4 to carry out secondary adjustment on the adjusted fan prediction average power A0 and bi, wherein the fan prediction average power after secondary adjustment is A0 and bi C4.
In some embodiments of the present application, after the ith adjustment coefficient ci is selected to perform secondary adjustment on the adjusted fan predicted average power a0×bi, i=1, 2,3,4, and obtain the secondary adjusted fan predicted average power a0×bi×ci, the method further includes:
taking the fan predicted average power after secondary adjustment as A0 bi ci as the final predicted average power Ab;
the average input cost D0 of the fan in the power prediction period is preset;
calculating a power prediction period duration Cn according to the fan average operation duration Ca and the fan average planned outage duration Cb, wherein Cn=Ca+Cb;
calculating to obtain the average power generation E0 of the fan in the power prediction period according to the final predicted average power Ab and the power prediction period duration Cn, wherein E0=Ab;
and calculating the average power generation cost F0 in the power prediction period according to the average power generation amount E0 of the fan and the average input cost D0 of the fan, wherein F0=E0/D0.
In some embodiments of the present application, after calculating the average power generation cost F0 in the power prediction period according to the average power generation amount E0 of the fan and the average input cost D0 of the fan, the method further includes:
presetting a first preset power generation cost F1, a second preset power generation cost F2 and a third preset power generation cost F3, wherein F1 is more than F2 and more than F3; presetting a first preset recommended level H1, a second preset recommended level H2 and a third preset recommended level H3, wherein H1 is more than H2 and more than H3;
when F0 is more than or equal to F1, selecting a third preset power generation level H3 as a final recommended level of the fan equipment;
when F1 is more than F0 and is more than or equal to F2, selecting a second preset power generation level H2 as a final recommended level of the fan equipment;
when F2 is more than F0 and more than or equal to F3, the first preset power generation level H1 is selected as the final recommended level of the fan equipment.
In another aspect, the present application provides a fan apparatus selection system based on wind farm power prediction, the system comprising:
the data acquisition unit is used for acquiring historical operation data and historical numerical weather forecast data of the wind power plant and acquiring real-time numerical weather forecast data of the wind power plant; wherein the historical operating data comprises: average power of the fan; the historical numerical weather forecast data includes: wind direction value, wind speed value, air humidity, air pressure value and air temperature value;
the data processing unit is used for establishing a historical power curve according to the historical operation data and the historical numerical weather forecast data, and carrying out refinement treatment on the real-time numerical weather forecast data to obtain a predicted wind speed value and a predicted wind direction value under the actual terrain condition of the wind power plant;
applying the predicted wind speed value and the predicted wind direction value to a historical power curve to obtain the predicted power of the fan;
presetting a power prediction period, acquiring preset running state data in the power prediction period, and determining fan power generation cost according to fan predicted power and the running state data so as to determine a recommended level corresponding to fan equipment according to the fan power generation cost;
the data display unit is used for displaying data according to the recommended level;
the preset running state data in the power prediction period comprises the following steps: average running time of the fan, average planned shutdown time of the fan and average load of the fan.
In some embodiments of the present application, after the data acquisition unit acquires the real-time fan predicted power in the preset power prediction period, the data processing unit calculates the fan predicted average power A0 in the preset power prediction period according to the real-time fan predicted power;
obtaining an average fan load B0, and presetting a first preset fan load value B1, a second preset fan load value B2, a third preset fan load value B3 and a fourth preset fan load value B4, wherein B1 is more than B2 is more than B3 is more than B4; presetting a first preset adjustment coefficient b1, a second preset adjustment coefficient b2, a third preset adjustment coefficient b3 and a fourth preset adjustment coefficient b4, wherein 1.2 is more than b1 and more than b2 is more than 1 and more than b3 is more than b4 and more than 0.8;
when B0 is more than or equal to B1, a first preset adjustment coefficient B1 is selected to adjust the predicted average power A0 of the fan, and the predicted average power of the fan after adjustment is A0 x B1;
when B1 is more than B0 and is more than or equal to B2, a second preset adjustment coefficient B2 is selected to adjust the predicted average power A0 of the fan, and the predicted average power of the fan after adjustment is A0B 2;
when B2 is more than B0 and is more than or equal to B3, a third preset adjustment coefficient B3 is selected to adjust the predicted average power A0 of the fan, and the predicted average power of the fan after adjustment is A0 x B3;
when B3 is more than B0 and is more than or equal to B4, a fourth preset adjustment coefficient B4 is selected to adjust the fan predicted average power A0, and the fan predicted average power after adjustment is A0 x B4.
In some embodiments of the present application, the data processing unit adjusts the fan predicted average power A0 by selecting an ith adjustment coefficient bi, i=1, 2,3,4, obtains the adjusted fan predicted average power as A0 x bi, obtains a fan average operation duration Ca and a fan average planned outage duration Cb, and calculates a fan average effective operation duration ratio C0, c0=ca/(ca+cb) according to the fan average operation duration Ca and the fan average planned outage duration Cb;
presetting a first preset effective operation ratio C1, a second preset effective operation ratio C2, a third preset effective operation ratio C3 and a third preset effective operation ratio C4, wherein C1 is more than C2 is more than C3 and more than C4; presetting a first preset adjustment coefficient c1, a second preset adjustment coefficient c2, a third preset adjustment coefficient c3 and a fourth preset adjustment coefficient c4, wherein 1.2 is more than c1 and more than c2 is more than 1 and more than c3 is more than c4 and more than 0.8;
when C0 is more than or equal to C1, selecting a first preset adjustment coefficient C1 to carry out secondary adjustment on the adjusted fan predicted average power A0 and bi, wherein the fan predicted average power after secondary adjustment is A0 and bi C1;
when C1 is more than C0 and is more than or equal to C2, selecting a second preset adjustment coefficient C2 to carry out secondary adjustment on the adjusted fan prediction average power A0 and bi, wherein the fan prediction average power after secondary adjustment is A0 and bi C2;
when C2 is more than C0 and is more than or equal to C3, selecting a third preset adjustment coefficient C3 to carry out secondary adjustment on the adjusted fan prediction average power A0 and bi, wherein the fan prediction average power after secondary adjustment is A0 and bi C3;
when C3 is more than C0 and is more than or equal to C4, selecting a fourth preset adjustment coefficient C4 to carry out secondary adjustment on the adjusted fan prediction average power A0 and bi, wherein the fan prediction average power after secondary adjustment is A0 and bi C4.
In some embodiments of the present application, after obtaining the secondarily adjusted fan predicted average power as a0×bi×ci, the data processing unit uses the secondarily adjusted fan predicted average power as a0×bi×ci as the final predicted average power Ab;
the average input cost D0 of the fan in the power prediction period is preset;
calculating a power prediction period duration Cn according to the fan average operation duration Ca and the fan average planned outage duration Cb, wherein Cn=Ca+Cb;
calculating to obtain the average power generation E0 of the fan in the power prediction period according to the final predicted average power Ab and the power prediction period duration Cn, wherein E0=Ab;
and calculating the average power generation cost F0 in the power prediction period according to the average power generation amount E0 of the fan and the average input cost D0 of the fan, wherein F0=E0/D0.
In some embodiments of the present application, after the data processing unit calculates the average power generation cost F0 in the power prediction period, the first preset power generation cost F1, the second preset power generation cost F2, and the third preset power generation cost F3 are preset, and F1 > F2 > F3; presetting a first preset recommended level H1, a second preset recommended level H2 and a third preset recommended level H3, wherein H1 is more than H2 and more than H3;
when F0 is more than or equal to F1, selecting a third preset power generation level H3 as a final recommended level of the fan equipment;
when F1 is more than F0 and is more than or equal to F2, selecting a second preset power generation level H2 as a final recommended level of the fan equipment;
when F2 is more than F0 and more than or equal to F3, selecting a first preset power generation level H1 as a final recommended level of the fan equipment;
and the data display unit displays according to the final recommendation level.
Compared with the prior art, the application has the following beneficial effects: according to the method, firstly, historical power curve determination is carried out on fan equipment of a wind power plant, then a power prediction period is preset, fan prediction power is determined according to real-time numerical weather prediction data and the historical power curve of the wind power plant, fan power generation cost is determined according to hierarchical prediction power and preset running state data in the power prediction period, and corresponding recommended grades are determined according to the fan power generation cost so as to assist fan equipment selection. The power of the fan equipment of the wind power plant is predicted, so that the power generation cost of the fan is further predicted, and the corresponding recommended level is determined according to the power generation cost of the fan so as to assist the wind power plant to select the optimal fan equipment, so that the power generation efficiency is improved.
Drawings
Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The drawings are only for purposes of illustrating the preferred embodiments and are not to be construed as limiting the application. In the drawings:
FIG. 1 is a flowchart of a fan device selection method based on wind farm power prediction provided by an embodiment of the application;
FIG. 2 is a functional block diagram of a fan device selection system based on wind farm power prediction according to an embodiment of the present application.
Detailed Description
Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art. It should be noted that, without conflict, the embodiments of the present application and features of the embodiments may be combined with each other. The application will be described in detail below with reference to the drawings in connection with embodiments.
Referring to fig. 1, the embodiment provides a fan device selecting method based on wind farm power prediction, which includes:
s101: acquiring historical operation data and historical numerical weather forecast data of a wind power plant;
wherein the historical operating data comprises: average power of the fan; the historical numerical weather forecast data includes: wind direction value, wind speed value, air humidity, air pressure value and air temperature value;
s102: establishing a historical power curve according to the historical operation data and the historical numerical weather forecast data;
s103: acquiring real-time numerical weather forecast data of a wind power plant, and carrying out refinement treatment on the real-time numerical weather forecast data to obtain a predicted wind speed value and a predicted wind direction value of the wind power plant under actual terrain conditions;
s104: applying the predicted wind speed value and the predicted wind direction value to a historical power curve to obtain the predicted power of the fan;
s105: presetting a power prediction period, acquiring preset running state data in the power prediction period, and determining the power generation cost of the fan according to the fan predicted power and the running state data;
s106: determining a recommended level corresponding to fan equipment according to the fan power generation cost;
the preset running state data in the power prediction period comprises the following steps: average running time of the fan, average planned shutdown time of the fan and average load of the fan.
It can be understood that in this embodiment, by establishing a historical power curve of a fan device of a wind farm, presetting a power prediction period, determining a fan predicted power of the fan device in the power preset period according to the historical power curve, determining a fan power generation cost according to operation state data in the fan predicted power and the power prediction period, determining a recommended level corresponding to the fan device according to the power generation cost, and further providing a basis for suspense when selecting the fan device for a wind farm, and improving the power generation efficiency of the wind farm.
In a specific embodiment of the present application, when judging the operation efficiency of the fan according to the predicted power and the operation state data of the fan, the method includes:
acquiring real-time fan predicted power in a preset power prediction period, and calculating to obtain fan predicted average power A0 in the preset power prediction period according to the real-time fan predicted power;
obtaining an average fan load B0, and presetting a first preset fan load value B1, a second preset fan load value B2, a third preset fan load value B3 and a fourth preset fan load value B4, wherein B1 is more than B2 is more than B3 is more than B4; presetting a first preset adjustment coefficient b1, a second preset adjustment coefficient b2, a third preset adjustment coefficient b3 and a fourth preset adjustment coefficient b4, wherein 1.2 is more than b1 and more than b2 is more than 1 and more than b3 is more than b4 and more than 0.8;
when B0 is more than or equal to B1, a first preset adjustment coefficient B1 is selected to adjust the predicted average power A0 of the fan, and the predicted average power of the fan after adjustment is A0 x B1;
when B1 is more than B0 and is more than or equal to B2, a second preset adjustment coefficient B2 is selected to adjust the predicted average power A0 of the fan, and the predicted average power of the fan after adjustment is A0B 2;
when B2 is more than B0 and is more than or equal to B3, a third preset adjustment coefficient B3 is selected to adjust the predicted average power A0 of the fan, and the predicted average power of the fan after adjustment is A0 x B3;
when B3 is more than B0 and is more than or equal to B4, a fourth preset adjustment coefficient B4 is selected to adjust the fan predicted average power A0, and the fan predicted average power after adjustment is A0 x B4.
It can be understood that in this embodiment, by obtaining the average load of the fan preset in the power prediction period, the average power of the fan is further adjusted according to the average load of the fan, so as to avoid a judgment error caused by that the actual running power of the fan cannot reach the prediction level range due to the load of the fan in the actual running process, thereby affecting the power generation efficiency of the wind farm.
In a specific embodiment of the present application, after the ith adjustment coefficient bi is selected to adjust the fan predicted average power A0, i=1, 2,3,4, and the adjusted fan predicted average power is obtained as a0×bi, the method further includes:
obtaining a fan average operation duration Ca and a fan average planned outage duration Cb, and calculating to obtain a fan average effective operation duration ratio C0 according to the fan average operation duration Ca and the fan average planned outage duration Cb, wherein C0=Ca/(Ca+Cb);
presetting a first preset effective operation ratio C1, a second preset effective operation ratio C2, a third preset effective operation ratio C3 and a third preset effective operation ratio C4, wherein C1 is more than C2 is more than C3 and more than C4; presetting a first preset adjustment coefficient c1, a second preset adjustment coefficient c2, a third preset adjustment coefficient c3 and a fourth preset adjustment coefficient c4, wherein 1.2 is more than c1 and more than c2 is more than 1 and more than c3 is more than c4 and more than 0.8;
when C0 is more than or equal to C1, selecting a first preset adjustment coefficient C1 to carry out secondary adjustment on the adjusted fan predicted average power A0 and bi, wherein the fan predicted average power after secondary adjustment is A0 and bi C1;
when C1 is more than C0 and is more than or equal to C2, selecting a second preset adjustment coefficient C2 to carry out secondary adjustment on the adjusted fan prediction average power A0 and bi, wherein the fan prediction average power after secondary adjustment is A0 and bi C2;
when C2 is more than C0 and is more than or equal to C3, selecting a third preset adjustment coefficient C3 to carry out secondary adjustment on the adjusted fan prediction average power A0 and bi, wherein the fan prediction average power after secondary adjustment is A0 and bi C3;
when C3 is more than C0 and is more than or equal to C4, selecting a fourth preset adjustment coefficient C4 to carry out secondary adjustment on the adjusted fan prediction average power A0 and bi, wherein the fan prediction average power after secondary adjustment is A0 and bi C4.
It can be understood that in this embodiment, the average operation duration of the fan and the average planned outage duration of the fan in the power prediction period are obtained, the average effective operation duration ratio of the fan in the power prediction period is calculated, and then the average power of the fan is predicted and adjusted secondarily through the average effective operation duration ratio of the fan.
In a specific embodiment of the present application, after the ith adjustment coefficient ci is selected to perform secondary adjustment on the adjusted fan prediction average power a0×bi, i=1, 2,3,4, and obtain the secondary adjusted fan prediction average power a0×bi×ci, the method further includes:
taking the fan predicted average power after secondary adjustment as A0 bi ci as the final predicted average power Ab;
the average input cost D0 of the fan in the power prediction period is preset;
calculating a power prediction period duration Cn according to the fan average operation duration Ca and the fan average planned outage duration Cb, wherein Cn=Ca+Cb;
calculating to obtain the average power generation E0 of the fan in the power prediction period according to the final predicted average power Ab and the power prediction period duration Cn, wherein E0=Ab;
and calculating the average power generation cost F0 in the power prediction period according to the average power generation amount E0 of the fan and the average input cost D0 of the fan, wherein F0=E0/D0.
It may be understood that, in this embodiment, by presetting the average input cost of the fan in the power prediction period, the average input cost of the fan may include the basic cost of the fan equipment and the operation maintenance cost of the fan equipment, calculating the average power generation amount of the fan in the power prediction period according to the final predicted average power and the duration of the power prediction period, calculating the average power generation cost in the power prediction period according to the average power generation amount of the fan and the average input cost of the fan, and further using the average power generation cost of the fan equipment in the power prediction period as the recommended index.
In a specific embodiment of the present application, after calculating the average power generation cost F0 in the power prediction period according to the average power generation amount E0 of the fan and the average input cost D0 of the fan, the method further includes:
presetting a first preset power generation cost F1, a second preset power generation cost F2 and a third preset power generation cost F3, wherein F1 is more than F2 and more than F3; presetting a first preset recommended level H1, a second preset recommended level H2 and a third preset recommended level H3, wherein H1 is more than H2 and more than H3;
when F0 is more than or equal to F1, selecting a third preset power generation level H3 as a final recommended level of the fan equipment;
when F1 is more than F0 and is more than or equal to F2, selecting a second preset power generation level H2 as a final recommended level of the fan equipment;
when F2 is more than F0 and more than or equal to F3, the first preset power generation level H1 is selected as the final recommended level of the fan equipment.
It can be appreciated that in this embodiment, by comparing the average power generation cost of the fan device with the preset cost range, further selecting a preset recommended level corresponding to the fan device, and displaying the selected preset recommended level as a final recommended level, a basis is provided for each wind farm station when selecting the fan device, so as to improve the wind power generation rate.
In another aspect, the present application provides a fan apparatus selection system based on wind farm power prediction, the system comprising:
the data acquisition unit is used for acquiring historical operation data and historical numerical weather forecast data of the wind power plant and acquiring real-time numerical weather forecast data of the wind power plant; wherein the historical operating data comprises: average power of the fan; the historical numerical weather forecast data includes: wind direction value, wind speed value, air humidity, air pressure value and air temperature value;
the data processing unit is used for establishing a historical power curve according to the historical operation data and the historical numerical weather forecast data, and carrying out refinement treatment on the real-time numerical weather forecast data to obtain a predicted wind speed value and a predicted wind direction value under the actual terrain condition of the wind power plant;
applying the predicted wind speed value and the predicted wind direction value to a historical power curve to obtain the predicted power of the fan;
presetting a power prediction period, acquiring preset running state data in the power prediction period, and determining fan power generation cost according to fan predicted power and the running state data so as to determine a recommended level corresponding to fan equipment according to the fan power generation cost;
the data display unit is used for displaying data according to the recommended level;
the preset running state data in the power prediction period comprises the following steps: average running time of the fan, average planned shutdown time of the fan and average load of the fan.
In a specific embodiment of the application, after the data acquisition unit acquires the real-time fan predicted power in the preset power prediction period, the data processing unit calculates the fan predicted average power A0 in the preset power prediction period according to the real-time fan predicted power;
obtaining an average fan load B0, and presetting a first preset fan load value B1, a second preset fan load value B2, a third preset fan load value B3 and a fourth preset fan load value B4, wherein B1 is more than B2 is more than B3 is more than B4; presetting a first preset adjustment coefficient b1, a second preset adjustment coefficient b2, a third preset adjustment coefficient b3 and a fourth preset adjustment coefficient b4, wherein 1.2 is more than b1 and more than b2 is more than 1 and more than b3 is more than b4 and more than 0.8;
when B0 is more than or equal to B1, a first preset adjustment coefficient B1 is selected to adjust the predicted average power A0 of the fan, and the predicted average power of the fan after adjustment is A0 x B1;
when B1 is more than B0 and is more than or equal to B2, a second preset adjustment coefficient B2 is selected to adjust the predicted average power A0 of the fan, and the predicted average power of the fan after adjustment is A0B 2;
when B2 is more than B0 and is more than or equal to B3, a third preset adjustment coefficient B3 is selected to adjust the predicted average power A0 of the fan, and the predicted average power of the fan after adjustment is A0 x B3;
when B3 is more than B0 and is more than or equal to B4, a fourth preset adjustment coefficient B4 is selected to adjust the fan predicted average power A0, and the fan predicted average power after adjustment is A0 x B4.
In a specific embodiment of the present application, the data processing unit adjusts the fan prediction average power A0 by selecting an ith adjustment coefficient bi, i=1, 2,3,4, obtains the adjusted fan prediction average power as A0 x bi, obtains a fan average operation duration Ca and a fan average planned outage duration Cb, and calculates a fan average effective operation duration ratio C0, c0=ca/(ca+cb) according to the fan average operation duration Ca and the fan average planned outage duration Cb;
presetting a first preset effective operation ratio C1, a second preset effective operation ratio C2, a third preset effective operation ratio C3 and a third preset effective operation ratio C4, wherein C1 is more than C2 is more than C3 and more than C4; presetting a first preset adjustment coefficient c1, a second preset adjustment coefficient c2, a third preset adjustment coefficient c3 and a fourth preset adjustment coefficient c4, wherein 1.2 is more than c1 and more than c2 is more than 1 and more than c3 is more than c4 and more than 0.8;
when C0 is more than or equal to C1, selecting a first preset adjustment coefficient C1 to carry out secondary adjustment on the adjusted fan predicted average power A0 and bi, wherein the fan predicted average power after secondary adjustment is A0 and bi C1;
when C1 is more than C0 and is more than or equal to C2, selecting a second preset adjustment coefficient C2 to carry out secondary adjustment on the adjusted fan prediction average power A0 and bi, wherein the fan prediction average power after secondary adjustment is A0 and bi C2;
when C2 is more than C0 and is more than or equal to C3, selecting a third preset adjustment coefficient C3 to carry out secondary adjustment on the adjusted fan prediction average power A0 and bi, wherein the fan prediction average power after secondary adjustment is A0 and bi C3;
when C3 is more than C0 and is more than or equal to C4, selecting a fourth preset adjustment coefficient C4 to carry out secondary adjustment on the adjusted fan prediction average power A0 and bi, wherein the fan prediction average power after secondary adjustment is A0 and bi C4.
In a specific embodiment of the present application, after obtaining the average power of fan prediction after secondary adjustment as a0×bi×ci, the data processing unit takes the average power of fan prediction after secondary adjustment as a0×bi×ci as the final average power of prediction Ab;
the average input cost D0 of the fan in the power prediction period is preset;
calculating a power prediction period duration Cn according to the fan average operation duration Ca and the fan average planned outage duration Cb, wherein Cn=Ca+Cb;
calculating to obtain the average power generation E0 of the fan in the power prediction period according to the final predicted average power Ab and the power prediction period duration Cn, wherein E0=Ab;
and calculating the average power generation cost F0 in the power prediction period according to the average power generation amount E0 of the fan and the average input cost D0 of the fan, wherein F0=E0/D0.
In a specific embodiment of the present application, after the data processing unit calculates the average power generation cost F0 in the power prediction period, the first preset power generation cost F1, the second preset power generation cost F2, and the third preset power generation cost F3 are preset, and F1 > F2 > F3; presetting a first preset recommended level H1, a second preset recommended level H2 and a third preset recommended level H3, wherein H1 is more than H2 and more than H3;
when F0 is more than or equal to F1, selecting a third preset power generation level H3 as a final recommended level of the fan equipment;
when F1 is more than F0 and is more than or equal to F2, selecting a second preset power generation level H2 as a final recommended level of the fan equipment;
when F2 is more than F0 and more than or equal to F3, selecting a first preset power generation level H1 as a final recommended level of the fan equipment;
and the data display unit displays according to the final recommendation level.
It can be understood that in this embodiment, the fan predicted power is determined according to the real-time numerical weather forecast data and the historical power curve of the wind farm, the fan power generation cost is determined according to the hierarchical predicted power and the running state data preset in the power prediction period, and the corresponding recommended level is determined according to the fan power generation cost so as to assist the fan equipment to select. The power of the fan equipment of the wind power plant is predicted, so that the power generation cost of the fan is further predicted, and the corresponding recommended level is determined according to the power generation cost of the fan so as to assist the wind power plant to select the optimal fan equipment, so that the power generation efficiency is improved.
It will be appreciated by those skilled in the art that embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
Finally, it should be noted that: the above embodiments are only for illustrating the technical aspects of the present application and not for limiting the same, and although the present application has been described in detail with reference to the above embodiments, it should be understood by those of ordinary skill in the art that: modifications and equivalents may be made to the specific embodiments of the application without departing from the spirit and scope of the application, which is intended to be covered by the claims.
Claims (10)
1. A wind farm power prediction based fan apparatus selection method, comprising:
acquiring historical operation data and historical numerical weather forecast data of the wind power plant; wherein the historical operating data comprises: average power of the fan; the historical numerical weather forecast data includes: wind direction value, wind speed value, air humidity, air pressure value and air temperature value;
establishing a historical power curve according to the historical operation data and the historical numerical weather forecast data;
acquiring real-time numerical weather forecast data of the wind power plant, and carrying out refinement treatment on the real-time numerical weather forecast data to obtain a predicted wind speed value and a predicted wind direction value under the actual topography condition of the wind power plant;
applying the predicted wind speed value and the predicted wind direction value to the historical power curve to obtain the predicted power of the fan;
the method comprises the steps of presetting a power prediction period, obtaining preset running state data in the power prediction period, and determining fan power generation cost according to fan predicted power and the running state data so as to determine a recommended level corresponding to fan equipment according to the fan power generation cost;
wherein, the preset running state data in the power prediction period comprises: average running time of the fan, average planned shutdown time of the fan and average load of the fan.
2. The wind farm power prediction based fan apparatus selection method of claim 1, when determining fan operating efficiency from the fan predicted power and operating state data, comprising:
acquiring real-time fan predicted power in the preset power predicted period, and calculating fan predicted average power A0 in the preset power predicted period according to the real-time fan predicted power;
obtaining an average fan load B0, and presetting a first preset fan load value B1, a second preset fan load value B2, a third preset fan load value B3 and a fourth preset fan load value B4, wherein B1 is more than B2 is more than B3 is more than B4; presetting a first preset adjustment coefficient b1, a second preset adjustment coefficient b2, a third preset adjustment coefficient b3 and a fourth preset adjustment coefficient b4, wherein 1.2 is more than b1 and more than b2 is more than 1 and more than b3 is more than b4 and more than 0.8;
when B0 is more than or equal to B1, a first preset adjustment coefficient B1 is selected to adjust the predicted average power A0 of the fan, and the predicted average power of the fan after adjustment is A0 x B1;
when B1 is more than B0 and is more than or equal to B2, a second preset adjustment coefficient B2 is selected to adjust the predicted average power A0 of the fan, and the predicted average power of the fan after adjustment is A0B 2;
when B2 is more than B0 and is more than or equal to B3, a third preset adjustment coefficient B3 is selected to adjust the predicted average power A0 of the fan, and the predicted average power of the fan after adjustment is A0 x B3;
when B3 is more than B0 and is more than or equal to B4, a fourth preset adjustment coefficient B4 is selected to adjust the fan predicted average power A0, and the fan predicted average power after adjustment is A0 x B4.
3. The wind farm power prediction based fan apparatus selecting method according to claim 2, wherein after selecting the ith adjustment coefficient bi to adjust the fan prediction average power A0, i=1, 2,3,4, obtaining the adjusted fan prediction average power a0×bi, further comprising:
obtaining a fan average operation duration Ca and a fan average planned outage duration Cb, and calculating to obtain a fan average effective operation duration ratio C0 according to the fan average operation duration Ca and the fan average planned outage duration Cb, wherein C0=Ca/(Ca+Cb);
presetting a first preset effective operation ratio C1, a second preset effective operation ratio C2, a third preset effective operation ratio C3 and a third preset effective operation ratio C4, wherein C1 is more than C2 is more than C3 and more than C4; presetting a first preset adjustment coefficient c1, a second preset adjustment coefficient c2, a third preset adjustment coefficient c3 and a fourth preset adjustment coefficient c4, wherein 1.2 is more than c1 and more than c2 is more than 1 and more than c3 is more than c4 and more than 0.8;
when C0 is more than or equal to C1, selecting a first preset adjustment coefficient C1 to carry out secondary adjustment on the adjusted fan predicted average power A0 and bi, wherein the fan predicted average power after secondary adjustment is A0 and bi C1;
when C1 is more than C0 and is more than or equal to C2, selecting a second preset adjustment coefficient C2 to carry out secondary adjustment on the adjusted fan prediction average power A0 and bi, wherein the fan prediction average power after secondary adjustment is A0 and bi C2;
when C2 is more than C0 and is more than or equal to C3, selecting a third preset adjustment coefficient C3 to carry out secondary adjustment on the adjusted fan prediction average power A0 and bi, wherein the fan prediction average power after secondary adjustment is A0 and bi C3;
when C3 is more than C0 and is more than or equal to C4, selecting a fourth preset adjustment coefficient C4 to carry out secondary adjustment on the adjusted fan prediction average power A0 and bi, wherein the fan prediction average power after secondary adjustment is A0 and bi C4.
4. A wind farm power prediction based fan apparatus selection method according to claim 3, wherein after selecting the ith adjustment coefficient ci to perform secondary adjustment on the adjusted fan prediction average power a0×bi, i=1, 2,3,4, obtaining the secondary adjusted fan prediction average power a0×bi×ci, further comprising:
taking the fan predicted average power after secondary adjustment as A0 bi ci as the final predicted average power Ab;
presetting average input cost D0 of a fan in the power prediction period;
calculating a power prediction period duration Cn according to the fan average operation duration Ca and the fan average planned outage duration Cb, wherein Cn=Ca+Cb;
calculating to obtain the average power generation E0 of the fan in the power prediction period according to the final predicted average power Ab and the power prediction period duration Cn, wherein E0=Ab;
and calculating the average power generation cost F0 in the power prediction period according to the average power generation amount E0 of the fan and the average input cost D0 of the fan, wherein F0=E0/D0.
5. The wind farm power prediction based wind turbine plant selection method of claim 4, further comprising, after calculating an average power generation cost F0 in the power prediction period from an average power generation amount E0 of the wind turbine and an average input cost D0 of the wind turbine:
presetting a first preset power generation cost F1, a second preset power generation cost F2 and a third preset power generation cost F3, wherein F1 is more than F2 and more than F3; presetting a first preset recommended level H1, a second preset recommended level H2 and a third preset recommended level H3, wherein H1 is more than H2 and more than H3;
when F0 is more than or equal to F1, selecting a third preset power generation level H3 as a final recommended level of the fan equipment;
when F1 is more than F0 and more than or equal to F2, selecting a second preset power generation level H2 as a final recommended level of the fan equipment;
when F2 is more than F0 and more than or equal to F3, a first preset power generation level H1 is selected as a final recommended level of the fan equipment.
6. A wind farm power prediction based fan device selection system, wherein a wind farm power prediction based fan device selection method according to any of claims 1-5 is applied, comprising:
the data acquisition unit is used for acquiring historical operation data and historical numerical weather forecast data of the wind power plant and acquiring real-time numerical weather forecast data of the wind power plant; wherein the historical operating data comprises: average power of the fan; the historical numerical weather forecast data includes: wind direction value, wind speed value, air humidity, air pressure value and air temperature value;
the data processing unit is used for establishing a historical power curve according to the historical operation data and the historical numerical weather forecast data, and carrying out refinement treatment on the real-time numerical weather forecast data to obtain a predicted wind speed value and a predicted wind direction value under the actual topography condition of the wind power plant;
applying the predicted wind speed value and the predicted wind direction value to the historical power curve to obtain the predicted power of the fan;
presetting a power prediction period, acquiring preset running state data in the power prediction period, and determining fan power generation cost according to the fan predicted power and the running state data so as to determine a recommended level corresponding to fan equipment according to the fan power generation cost;
the data display unit is used for displaying data according to the recommendation level;
wherein, the preset running state data in the power prediction period comprises: average running time of the fan, average planned shutdown time of the fan and average load of the fan.
7. The wind farm power prediction-based fan equipment selection system according to claim 6, wherein after the data acquisition unit acquires the real-time fan prediction power in the preset power prediction period, the data processing unit calculates a fan prediction average power A0 in the preset power prediction period according to the real-time fan prediction power;
obtaining an average fan load B0, and presetting a first preset fan load value B1, a second preset fan load value B2, a third preset fan load value B3 and a fourth preset fan load value B4, wherein B1 is more than B2 is more than B3 is more than B4; presetting a first preset adjustment coefficient b1, a second preset adjustment coefficient b2, a third preset adjustment coefficient b3 and a fourth preset adjustment coefficient b4, wherein 1.2 is more than b1 and more than b2 is more than 1 and more than b3 is more than b4 and more than 0.8;
when B0 is more than or equal to B1, a first preset adjustment coefficient B1 is selected to adjust the predicted average power A0 of the fan, and the predicted average power of the fan after adjustment is A0 x B1;
when B1 is more than B0 and is more than or equal to B2, a second preset adjustment coefficient B2 is selected to adjust the predicted average power A0 of the fan, and the predicted average power of the fan after adjustment is A0B 2;
when B2 is more than B0 and is more than or equal to B3, a third preset adjustment coefficient B3 is selected to adjust the predicted average power A0 of the fan, and the predicted average power of the fan after adjustment is A0 x B3;
when B3 is more than B0 and is more than or equal to B4, a fourth preset adjustment coefficient B4 is selected to adjust the fan predicted average power A0, and the fan predicted average power after adjustment is A0 x B4.
8. The fan equipment selection system based on wind farm power prediction according to claim 7, wherein the data processing unit adjusts the fan prediction average power A0 by selecting an ith adjustment coefficient bi, i=1, 2,3,4, obtains an adjusted fan prediction average power A0 x bi, obtains a fan average operation duration Ca and a fan average planned off-operation duration Cb, and calculates a fan average effective operation duration ratio C0, c0=ca/(ca+cb) according to the fan average operation duration Ca and the fan average planned off-operation duration Cb;
presetting a first preset effective operation ratio C1, a second preset effective operation ratio C2, a third preset effective operation ratio C3 and a third preset effective operation ratio C4, wherein C1 is more than C2 is more than C3 and more than C4; presetting a first preset adjustment coefficient c1, a second preset adjustment coefficient c2, a third preset adjustment coefficient c3 and a fourth preset adjustment coefficient c4, wherein 1.2 is more than c1 and more than c2 is more than 1 and more than c3 is more than c4 and more than 0.8;
when C0 is more than or equal to C1, selecting a first preset adjustment coefficient C1 to carry out secondary adjustment on the adjusted fan predicted average power A0 and bi, wherein the fan predicted average power after secondary adjustment is A0 and bi C1;
when C1 is more than C0 and is more than or equal to C2, selecting a second preset adjustment coefficient C2 to carry out secondary adjustment on the adjusted fan prediction average power A0 and bi, wherein the fan prediction average power after secondary adjustment is A0 and bi C2;
when C2 is more than C0 and is more than or equal to C3, selecting a third preset adjustment coefficient C3 to carry out secondary adjustment on the adjusted fan prediction average power A0 and bi, wherein the fan prediction average power after secondary adjustment is A0 and bi C3;
when C3 is more than C0 and is more than or equal to C4, selecting a fourth preset adjustment coefficient C4 to carry out secondary adjustment on the adjusted fan prediction average power A0 and bi, wherein the fan prediction average power after secondary adjustment is A0 and bi C4.
9. The wind farm power prediction based fan device selection system according to claim 8, wherein the data processing unit obtains a secondarily adjusted fan prediction average power of a0×bi×ci, and then uses the secondarily adjusted fan prediction average power of a0×bi×ci as the final prediction average power Ab;
presetting average input cost D0 of a fan in the power prediction period;
calculating a power prediction period duration Cn according to the fan average operation duration Ca and the fan average planned outage duration Cb, wherein Cn=Ca+Cb;
calculating to obtain the average power generation E0 of the fan in the power prediction period according to the final predicted average power Ab and the power prediction period duration Cn, wherein E0=Ab;
and calculating the average power generation cost F0 in the power prediction period according to the average power generation amount E0 of the fan and the average input cost D0 of the fan, wherein F0=E0/D0.
10. The fan apparatus selection system based on wind farm power prediction according to claim 9, wherein after the data processing unit calculates an average power generation cost F0 in the power prediction period, a first preset power generation cost F1, a second preset power generation cost F2, and a third preset power generation cost F3 are preset, and F1 > F2 > F3; presetting a first preset recommended level H1, a second preset recommended level H2 and a third preset recommended level H3, wherein H1 is more than H2 and more than H3;
when F0 is more than or equal to F1, selecting a third preset power generation level H3 as a final recommended level of the fan equipment;
when F1 is more than F0 and more than or equal to F2, selecting a second preset power generation level H2 as a final recommended level of the fan equipment;
when F2 is more than F0 and more than or equal to F3, selecting a first preset power generation level H1 as a final recommended level of the fan equipment;
and the data display unit displays according to the final recommendation level.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN117452527A (en) * | 2023-12-26 | 2024-01-26 | 贵州省气象台(贵州省气象决策服务中心) | Digital weather intelligent service method and system |
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| CN117452527A (en) * | 2023-12-26 | 2024-01-26 | 贵州省气象台(贵州省气象决策服务中心) | Digital weather intelligent service method and system |
| CN117452527B (en) * | 2023-12-26 | 2024-03-12 | 贵州省气象台(贵州省气象决策服务中心) | Digital weather intelligent service method and system |
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