One-out-of-three selection method for active power signals of hydro-turbine generator set, and related device

Abstract

The embodiments of the present application relate to the technical field of automation of hydro-turbine generator sets. Provided are a one-out-of-three selection method for active power signals of a hydro-turbine generator set, and a related device. The method comprises: acquiring a total of three pieces of collected active power data, i.e., Y1, Y2 and Y3; and on the basis of the channel quality situations of the collected active power data, determining an optimal active power. By means of the technical solution of the present application, a unique optimal active power can be selected and output as a final active power of a hydro-turbine generator set to participate in generator set control, thereby effectively improving the reliability of determination and processing of active power signals, and solving the problems such as the startup / shutdown and AGC regulation of a hydro-turbine generator set being out of control due to inaccurate determination and processing after fluctuations, loss or failures of active power signals.

Description

A method for selecting one of three active power signals for a hydro-generator unit and related equipment Technical Field

[0001] This application relates to the field of hydro-generator automation technology, and more specifically, to a method for selecting one of three active power signals for a hydro-generator and related equipment. Background Technology

[0002] Currently, under the national strategy of "carbon peaking and carbon neutrality," hydropower, as one of the clean energy sources, is still in a stage of vigorous development. Active power, as one of the important parameters of hydro-generator units, directly affects the start-up and shutdown control, power generation efficiency, and grid frequency balance of the generator units, depending on the stability of its measured value. Therefore, the stability and reliability of the active power signal are crucial for hydro-generator units.

[0003] Currently, most hydropower stations are equipped with multiple power sensors to collect active power signals from the generating units, and employ methods such as "two-to-one" and "three-to-two" to monitor, judge, and process these signals. The "two-to-one" method primarily achieves redundancy by using two active power signals; however, its drawback is that if both signals are simultaneously disconnected or fail, the generating unit's active power signal loses monitoring and control. The "three-to-two" method selects the average of two active power signals as the actual active power value; however, this method is susceptible to fluctuations in the PT or CT circuits, leading to frequent switching between the selected two sets of signals. Therefore, there is an urgent need for a data acquisition system and a selection and processing method to improve the stability and reliability of the active power signals from hydro-generator units, further ensuring the stable operation of the units. Summary of the Invention

[0004] The embodiments of this application provide a three-way selection method and related equipment for active power signals of a hydro-generator set, in order to solve the technical problems existing in the prior art.

[0005] Other features and advantages of this application will become apparent from the following detailed description, or may be learned in part from practice of this application.

[0006] According to a first aspect of the embodiments of this application, a three-way selection method for active power signals of a hydro-generator set is provided, including:

[0007] Acquire three sets of active power data: Y1, Y2, and Y3.

[0008] Based on the channel quality of the active power acquisition data, the optimal active power is determined, including:

[0009] When the channel quality of all three sets of active power acquisition data is normal, the optimal active power is determined based on the active power deviation between any two sets of active power acquisition data and the average deviation of each set of active power acquisition data.

[0010] When at least two sets of active power acquisition data have normal channel quality, the optimal active power is determined based on the active power deviation between any two sets of active power acquisition data and the average deviation of each set of active power acquisition data.

[0011] When at least one set of active power acquisition data channels has normal quality, the optimal active power is determined based on the channel quality of the active power acquisition data.

[0012] In some embodiments of this application, based on the aforementioned scheme, when the channel quality of all three sets of active power acquisition data is normal, determining the optimal active power based on the active power deviation between any two sets of active power acquisition data and the average deviation of each set of active power acquisition data includes:

[0013] Assuming that the channel quality of all three sets of active power acquisition data is normal, calculate the active power deviation between any two sets to obtain the first active power deviation, the second active power deviation, and the third active power deviation.

[0014] The judgment is made based on the first active power deviation, the second active power deviation, the third active power deviation and the active power deviation threshold, and the average deviation under different judgment results is calculated based on different judgment results.

[0015] The optimal active power is obtained by comparing the deviations of the average values.

[0016] In some embodiments of this application, based on the aforementioned scheme, the judgment based on the first active power deviation, the second active power deviation, the third active power deviation, and the active power deviation threshold, and the calculation of the average deviation under different judgment results, includes:

[0017] When the first active power deviation, the second active power deviation, and the third active power deviation are all less than the active power deviation threshold, the first type of average deviation of active power acquisition data Y1, the first type of average deviation of active power acquisition data Y2, and the first type of average deviation of active power acquisition data Y3 are calculated.

[0018] When the third active power deviation is less than the active power deviation threshold and the second active power deviation is greater than the active power deviation threshold, or when the third active power deviation is less than the active power deviation threshold and the first active power deviation is greater than the active power deviation threshold, calculate the second type of average deviation of active power acquisition data Y2 and the second type of average deviation of active power acquisition data Y3.

[0019] When the first active power deviation is less than the active power deviation threshold and the second active power deviation is greater than the active power deviation threshold, or when the first active power deviation is less than the active power deviation threshold and the third active power deviation is greater than the active power deviation threshold, calculate the second type of average deviation of active power acquisition data Y1 and the third type of average deviation of active power acquisition data Y2.

[0020] When the second active power deviation is less than the active power deviation threshold and the first active power deviation is greater than the active power deviation threshold, or when the second active power deviation is less than the active power deviation threshold and the third active power deviation is greater than the active power deviation threshold, calculate the third type average deviation of active power acquisition data Y1 and the third type average deviation of active power acquisition data Y3.

[0021] In some embodiments of this application, based on the foregoing scheme, the step of comparing the average deviation to obtain the optimal active power includes:

[0022] When the first active power deviation, the second active power deviation, and the third active power deviation are all less than the active power deviation threshold, the active power data corresponding to the smallest average deviation of active power data Y1, the first average deviation of active power data Y2, and the first average deviation of active power data Y3 are compared, and the active power data is taken as the optimal active power.

[0023] When the third active power deviation is less than the active power deviation threshold and the second active power deviation is greater than the active power deviation threshold, or when the third active power deviation is less than the active power deviation threshold and the first active power deviation is greater than the active power deviation threshold, the second type average deviation of active power acquisition data Y2 and the second type average deviation of active power acquisition data Y3 are compared, and the active power acquisition data corresponding to the smallest average deviation is taken as the optimal active power.

[0024] If the first active power deviation is less than the active power deviation threshold and the second active power deviation is greater than the active power deviation threshold, or if the first active power deviation is less than the active power deviation threshold and the third active power deviation is greater than the active power deviation threshold, the second type average deviation of active power acquisition data Y1 and the third type average deviation of active power acquisition data Y2 are compared, and the active power acquisition data corresponding to the smallest average deviation is taken as the optimal active power.

[0025] If the second active power deviation is less than the active power deviation threshold and the first active power deviation is greater than the active power deviation threshold, or if the second active power deviation is less than the active power deviation threshold and the third active power deviation is greater than the active power deviation threshold, the active power data corresponding to the smallest average deviation is selected as the optimal active power based on a comparison of the third type average deviation of active power data Y1 and the third type average deviation of active power data Y3.

[0026] In some embodiments of this application, based on the foregoing scheme, the step of determining the optimal active power based on the active power deviation between any two sets of active power acquisition data and the average deviation of each set of active power acquisition data when at least two sets of active power acquisition data have normal channel quality includes:

[0027] Under the condition that the channel quality of at least two sets of active power acquisition data is normal, calculate the active power deviation between any two sets to obtain the fourth active power deviation, the fifth active power deviation and the sixth active power deviation.

[0028] Judgments are made based on the fourth active power deviation, the fifth active power deviation, the sixth active power deviation, and the active power deviation threshold. The average deviation under different judgment results is calculated based on the different judgment results.

[0029] The optimal active power is obtained by comparing the deviations of the average values.

[0030] In some embodiments of this application, based on the aforementioned scheme, the judgment based on the fourth active power deviation, the fifth active power deviation, the sixth active power deviation, and the active power deviation threshold, and the calculation of the average deviation under different judgment results, includes:

[0031] When the sixth active power deviation is less than the active power deviation threshold, calculate the second type average deviation of active power acquisition data Y2 and the second type average deviation of active power acquisition data Y3.

[0032] When the fifth active power deviation is less than the active power deviation threshold, calculate the third type average deviation of active power acquisition data Y1 and the third type average deviation of active power acquisition data Y3.

[0033] When the fourth active power deviation is less than the active power deviation threshold, the second type of average deviation of active power acquisition data Y1 and the third type of average deviation of active power acquisition data Y2 are calculated.

[0034] In some embodiments of this application, based on the foregoing scheme, the step of comparing the average deviation to obtain the optimal active power includes:

[0035] When the sixth active power deviation is less than the active power deviation threshold, the second type average deviation of active power acquisition data Y2 and the second type average deviation of active power acquisition data Y3 are compared, and the active power acquisition data corresponding to the smallest average deviation is taken as the optimal active power.

[0036] When the fifth active power deviation is less than the active power deviation threshold, the magnitude of the third type average deviation of active power acquisition data Y1 and the third type average deviation of active power acquisition data Y3 are compared, and the active power acquisition data corresponding to the smallest average deviation is taken as the optimal active power.

[0037] When the fourth active power deviation is less than the active power deviation threshold, the second type of average deviation of active power acquisition data Y1 and the third type of average deviation of active power acquisition data Y2 are compared, and the active power acquisition data corresponding to the smallest average deviation is taken as the optimal active power.

[0038] According to a second aspect of the embodiments of this application, a three-way selection device for active power signals of a hydro-generator set is provided, comprising:

[0039] The acquisition unit is used to acquire three sets of active power data: Y1, Y2, and Y3.

[0040] The confirmation unit is used to confirm the optimal active power based on the channel quality status of the active power acquisition data.

[0041] The confirmation unit includes:

[0042] The first confirmation subunit is used to determine the optimal active power based on the active power deviation between any two sets of active power acquisition data and the average deviation of each set of active power acquisition data when the channel quality of all three sets of active power acquisition data is normal.

[0043] The second confirmation subunit is used to determine the optimal active power based on the active power deviation between any two sets of active power acquisition data and the average deviation of each set of active power acquisition data when the channel quality of at least two sets of active power acquisition data is normal.

[0044] The third confirmation subunit is used to determine the optimal active power based on the channel quality of the active power acquisition data when at least one set of active power acquisition data channels are of normal quality.

[0045] According to a third aspect of the embodiments of this application, a computer-readable storage medium is provided, the storage medium storing computer instructions that, when executed on a computer, cause the computer to perform the method as described in the first aspect.

[0046] According to a fourth aspect of the embodiments of this application, an electronic device is provided, including: a memory and a processor;

[0047] The memory is used to store computer instructions;

[0048] The processor is configured to invoke computer instructions stored in the memory, causing the electronic device to execute the method described in the first aspect.

[0049] The technical solution of this application can select and output a unique optimal active power as the final active power of the hydro-generator unit to participate in the unit control, which effectively improves the reliability of active power signal judgment and processing, and solves the problems of unit start-up and shutdown and AGC regulation failure caused by inaccurate judgment and processing of active power signal fluctuation, loss or failure.

[0050] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and do not limit this application. Attached Figure Description

[0051] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application. It is obvious that the drawings described below are merely some embodiments of this application, and those skilled in the art can obtain other drawings based on these drawings without any inventive effort. In the drawings:

[0052] Figure 1 shows a flowchart illustrating a three-way selection method for active power signals of a hydro-generator set according to an embodiment of this application;

[0053] Figure 2 shows a flowchart of step S200 according to an embodiment of this application;

[0054] Figure 3 shows a block diagram of a three-way selection device for active power signals of a hydro-generator set according to an embodiment of this application;

[0055] Figure 4 shows a block diagram of an electronic device according to one embodiment of the present application;

[0056] Figure 5 shows a schematic diagram of the structure of a computer system suitable for implementing the electronic device of the present application. Detailed Implementation

[0057] Exemplary embodiments will now be described more fully with reference to the accompanying drawings. However, these exemplary embodiments can be implemented in many forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided to make this application more comprehensive and complete, and to fully convey the concept of the exemplary embodiments to those skilled in the art.

[0058] Furthermore, the described features, structures, or characteristics can be combined in any suitable manner in one or more embodiments. Numerous specific details are provided in the following description to give a thorough understanding of embodiments of this application. However, those skilled in the art will recognize that the technical solutions of this application can be practiced without one or more of the specific details, or other methods, components, apparatuses, steps, etc., can be employed. In other instances, well-known methods, apparatuses, implementations, or operations are not shown or described in detail to avoid obscuring various aspects of this application.

[0059] The block diagrams shown in the accompanying drawings are merely functional entities and do not necessarily correspond to physically independent entities. That is, these functional entities can be implemented in software, in one or more hardware modules or integrated circuits, or in different network and / or processor devices and / or microcontroller devices.

[0060] The flowcharts shown in the accompanying drawings are merely illustrative and do not necessarily include all content and operations / steps, nor do they necessarily have to be performed in the described order. For example, some operations / steps can be broken down, while others can be combined or partially combined; therefore, the actual execution order may change depending on the specific circumstances.

[0061] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such uses of these terms can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described.

[0062] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of the embodiments of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this invention, and not all of them. Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this invention.

[0063] The following detailed description of some embodiments of this application will be provided in conjunction with the accompanying drawings. Unless otherwise specified, the following embodiments and features can be combined with each other.

[0064] Referring to Figure 1, a flowchart illustrating a three-way selection method for active power signals of a hydro-generator set according to an embodiment of this application is shown.

[0065] Figure 1 illustrates a three-way selection method for active power signals of a hydro-generator unit, including steps S100 to S200.

[0066] Step S100: Acquire three sets of active power data: Y1, Y2, and Y3.

[0067] It is understood that in this embodiment, three sets of active power data are acquired by random selection.

[0068] Referring to Figure 1, in step S200, the optimal active power is determined based on the channel quality of the active power acquisition data.

[0069] Specifically, referring to Figure 2, step S200 includes:

[0070] Step S210: When the channel quality of the three sets of active power acquisition data is all normal, the optimal active power is determined based on the active power deviation between any two sets of active power acquisition data and the average deviation of each set of active power acquisition data.

[0071] Step S220: The optimal active power is determined by the active power deviation between the active power data and the average deviation of each group of active power data.

[0072] Step S230: When at least one set of active power acquisition data channels has normal quality, the optimal active power is determined based on the channel quality of the active power acquisition data.

[0073] It should be noted that, provided that at least one set of active power acquisition data has normal channel quality, the active power acquisition data with normal channel quality among the three sets of active power acquisition data will be taken as the optimal active power.

[0074] In some feasible embodiments, based on the aforementioned scheme, when the channel quality of all three sets of active power acquisition data is normal, the optimal active power is determined according to the active power deviation between any two sets of active power acquisition data and the average deviation of each set of active power acquisition data, including:

[0075] Assuming that the channel quality of all three sets of active power acquisition data is normal, calculate the active power deviation between any two sets to obtain the first active power deviation, the second active power deviation, and the third active power deviation.

[0076] The judgment is made based on the first active power deviation, the second active power deviation, the third active power deviation and the active power deviation threshold, and the average deviation under different judgment results is calculated based on different judgment results.

[0077] The optimal active power is obtained by comparing the deviations of the average values.

[0078] For example, the calculation process for the first active power deviation, the second active power deviation, and the third active power deviation is as follows:

[0079] (1) The first active power deviation Diff1 is calculated based on the active power acquisition data Y1 and Y2, specifically as follows:

[0080] Diff1 = |Y1 - Y2|.

[0081] (2) The second active power deviation Diff2 is calculated based on the active power acquisition data Y1 and Y3, specifically as follows:

[0082] Diff2 = |Y1 - Y3|.

[0083] (3) The third active power deviation Diff3 is calculated based on the active power acquisition data Y2 and Y3, specifically as follows:

[0084] Diff3 = |Y2-Y3|.

[0085] In some feasible embodiments, based on the aforementioned scheme, the judgment based on the first active power deviation, the second active power deviation, the third active power deviation, and the active power deviation threshold, and the calculation of the average deviation under different judgment results, includes:

[0086] When the first active power deviation, the second active power deviation, and the third active power deviation are all less than the active power deviation threshold, the first type of average deviation of active power acquisition data Y1, the first type of average deviation of active power acquisition data Y2, and the first type of average deviation of active power acquisition data Y3 are calculated.

[0087] When the third active power deviation is less than the active power deviation threshold and the second active power deviation is greater than the active power deviation threshold, or when the third active power deviation is less than the active power deviation threshold and the first active power deviation is greater than the active power deviation threshold, calculate the second type of average deviation of the active power acquisition data Y2 and the second type of average deviation of the active power acquisition data Y3;

[0088] When the first active power deviation is less than the active power deviation threshold and the second active power deviation is greater than the active power deviation threshold, or when the first active power deviation is less than the active power deviation threshold and the third active power deviation is greater than the active power deviation threshold, calculate the second type of average deviation of the active power acquisition data Y1 and the third type of average deviation of the active power acquisition data Y2;

[0089] When the second active power deviation is less than the active power deviation threshold and the first active power deviation is greater than the active power deviation threshold, or when the second active power deviation is less than the active power deviation threshold and the third active power deviation is greater than the active power deviation threshold, calculate the third type of average deviation of the active power acquisition data Y1 and the third type of average deviation of the active power acquisition data Y3.

[0090] Exemplarily, when Diff1 < W and Diff2 < W and Diff3 < W, where W represents the active power deviation threshold, the calculation process of the average deviation is as follows:

[0091] Obtain the first type of average deviation AVED1 of the active power acquisition data Y1 according to the active power acquisition data Y1 and the average value of the three groups of active power acquisition data Y1, Y2, and Y3. Specifically:

[0092] AVED1 = |Y1 - (Y1 + Y2 + Y3) / 3|.

[0093] Obtain the first type of average deviation AVED2 of the active power acquisition data Y2 according to the active power acquisition data Y2 and the average value of the three groups of active power acquisition data Y1, Y2, and Y3. Specifically:

[0094] AVED2 = |Y2 - (Y1 + Y2 + Y3) / 3|.

[0095] Obtain the first type of average deviation AVED3 of the active power acquisition data Y3 according to the active power acquisition data Y3 and the average value of the three groups of active power acquisition data Y1, Y2, and Y3. Specifically:

[0096] AVED3 = |Y3 - (Y1 + Y2 + Y3) / 3|。

[0097] When Diff3 < W and Diff1 > W, or Diff3 < W and Diff2 > W, the calculation process of the average deviation is as follows:

[0098] According to the active power acquisition data Y2 and the average value of the active power acquisition data Y2 and Y3, the second type of average deviation AVED2' of the active power acquisition data Y2 is obtained, specifically:

[0099] AVED2' = |Y2 - (Y2 + Y3) / 2|。

[0100] According to the active power acquisition data Y3 and the average value of the active power acquisition data Y2 and Y3, the second type of average deviation AVED3' of the active power acquisition data Y3 is obtained, specifically:

[0101] AVED3' = |Y3 - (Y2 + Y3) / 2|。

[0102] When Diff1 < W and Diff2 > W, or Diff1 < W and Diff3 > W, the calculation process of the average deviation is as follows:

[0103] According to the active power acquisition data Y1 and the average value of the active power acquisition data Y1 and Y2, the second type of average deviation AVED1' of the active power acquisition data Y1 is obtained, specifically:

[0104] AVED1' = |Y1 - (Y1 + Y2) / 2|。

[0105] According to the active power acquisition data Y2 and the average value of the active power acquisition data Y1 and Y2, the third type of average deviation AVED2'' of the active power acquisition data Y2 is obtained, specifically:

[0106] AVED2'' = |Y2 - (Y1 + Y2) / 2|。

[0107] When Diff2 < W and Diff1 > W, or Diff2 < W and Diff3 > W, the calculation process of the average deviation is as follows:

[0108] According to the active power acquisition data Y1 and the average value of the active power acquisition data Y1 and Y3, the third type of average deviation AVED1'' of the active power acquisition data Y1 is obtained, specifically:

[0109] AVED1'' = |Y1 - (Y1 + Y3) / 2|。

[0110] The third type of mean deviation AVED3″ of the active power acquisition data Y3 is calculated based on the average values ​​of the active power acquisition data Y1 and Y3. Specifically:

[0111] AVED3″=|Y3-(Y1+Y3) / 2|.

[0112] In some feasible embodiments, based on the foregoing scheme, the step of obtaining the optimal active power by comparing the average deviation includes:

[0113] When the first active power deviation, the second active power deviation, and the third active power deviation are all less than the active power deviation threshold, the active power data corresponding to the smallest average deviation of active power data Y1, the first average deviation of active power data Y2, and the first average deviation of active power data Y3 are compared, and the active power data is taken as the optimal active power.

[0114] When the third active power deviation is less than the active power deviation threshold and the second active power deviation is greater than the active power deviation threshold, or when the third active power deviation is less than the active power deviation threshold and the first active power deviation is greater than the active power deviation threshold, the second type average deviation of active power acquisition data Y2 and the second type average deviation of active power acquisition data Y3 are compared, and the active power acquisition data corresponding to the smallest average deviation is taken as the optimal active power.

[0115] If the first active power deviation is less than the active power deviation threshold and the second active power deviation is greater than the active power deviation threshold, or if the first active power deviation is less than the active power deviation threshold and the third active power deviation is greater than the active power deviation threshold, the second type average deviation of active power acquisition data Y1 and the third type average deviation of active power acquisition data Y2 are compared, and the active power acquisition data corresponding to the smallest average deviation is taken as the optimal active power.

[0116] If the second active power deviation is less than the active power deviation threshold and the first active power deviation is greater than the active power deviation threshold, or if the second active power deviation is less than the active power deviation threshold and the third active power deviation is greater than the active power deviation threshold, the active power data corresponding to the smallest average deviation is selected as the optimal active power based on a comparison of the third type average deviation of active power data Y1 and the third type average deviation of active power data Y3.

[0117] For example, AVED1, AVED2, and AVED3 are compared. If AVED1 is the smallest among the three, the active power data Y1 is confirmed as the optimal active power. If AVED2 is the smallest among the three, the active power data Y2 is confirmed as the optimal active power. If AVED3 is the smallest among the three, the active power data Y3 is confirmed as the optimal active power.

[0118] Similarly, compare the values ​​of AVED2′ and AVED3′. If the value of AVED2′ is the smallest, then the active power data Y2 is confirmed as the optimal active power. If the value of AVED3′ is the smallest, then the active power data Y3 is confirmed as the optimal active power.

[0119] Compare the values ​​of AVED1′ and AVED2″. If AVED1′ is the smallest, the active power data Y1 is confirmed as the optimal active power. If AVED2″ is the smallest, the active power data Y2 is confirmed as the optimal active power.

[0120] Compare the values ​​of AVED1″ and AVED3″. If the value of AVED1″ is the smallest, the active power data Y1 is confirmed as the optimal active power. If the value of AVED3″ is the smallest, the active power data Y3 is confirmed as the optimal active power.

[0121] In some feasible embodiments, based on the aforementioned scheme, when at least two sets of active power acquisition data have normal channel quality, determining the optimal active power based on the active power deviation between any two sets of active power acquisition data and the average deviation of each set of active power acquisition data includes:

[0122] Under the condition that the channel quality of at least two sets of active power acquisition data is all normal, calculate the active power deviation between any two sets to obtain the fourth active power deviation, the fifth active power deviation and the sixth active power deviation.

[0123] Judgments are made based on the fourth active power deviation, the fifth active power deviation, the sixth active power deviation, and the active power deviation threshold. The average deviation under different judgment results is calculated based on the different judgment results.

[0124] The optimal active power is obtained by comparing the deviations of the average values.

[0125] For example, the calculation process for the fourth, fifth, and sixth active power deviations is as follows:

[0126] (1) The fourth active power deviation Diff4 is calculated based on the active power acquisition data Y1 and Y2, specifically as follows:

[0127] Diff4 = |Y1 - Y2|.

[0128] (2) Calculate the fifth active power deviation Diff5 based on the active power acquisition data Y1 and the active power acquisition data Y3, specifically:

[0129] Diff5 = |Y1 - Y3|.

[0130] (3) Calculate the sixth active power deviation Diff6 based on the active power acquisition data Y2 and the active power acquisition data Y3, specifically:

[0131] Diff6 = |Y2 - Y3|.

[0132] It should be noted that the fourth active power deviation is essentially the same as the first active power deviation, so their calculation methods are the same. In this application, since the first active power deviation and the fourth active power deviation exist in different steps, for the sake of easy distinction, they are respectively named the first active power deviation and the fourth active power deviation. The same reason applies to the fifth active power deviation and the second active power deviation, as well as the sixth active power deviation and the third active power deviation.

[0133] In some feasible embodiments, based on the foregoing solution, judge based on the fourth active power deviation, the fifth active power deviation, the sixth active power deviation and the active power deviation threshold, and calculate the average deviation under different judgment results based on different judgment results, including:

[0134] When the sixth active power deviation is less than the active power deviation threshold, calculate the second type of average deviation of the active power acquisition data Y2 and the second type of average deviation of the active power acquisition data Y3;

[0135] When the fifth active power deviation is less than the active power deviation threshold, calculate the third type of average deviation of the active power acquisition data Y1 and the third type of average deviation of the active power acquisition data Y3;

[0136] When the fourth active power deviation is less than the active power deviation threshold, calculate the second type of average deviation of the active power acquisition data Y1 and the third type of average deviation of the active power acquisition data Y2.

[0137] Exemplarily, when Diff6 < W, where W represents the active power deviation threshold, the calculation process of the average deviation is as follows:

[0138] Obtain the second type of average deviation AVED2' of the active power acquisition data Y2 based on the active power acquisition data Y2 and the average value of the active power acquisition data Y2 and Y3, specifically:

[0139] AVED2' = |Y2 - (Y2 + Y3) / 2|.

[0140] The second type of average deviation AVED3' of the active power acquisition data Y3 is obtained based on the active power acquisition data Y3 and the average value of the active power acquisition data Y2 and Y3, specifically:

[0141] AVED3' = |Y3 - (Y2 + Y3) / 2|.

[0142] When Diff5 < W, the calculation process of the average deviation is as follows:

[0143] The third type of average deviation AVED1'' of the active power acquisition data Y1 is obtained based on the active power acquisition data Y1 and the average value of the active power acquisition data Y1 and Y3, specifically:

[0144] AVED1'' = |Y1 - (Y1 + Y3) / 2|.

[0145] The third type of average deviation AVED3'' of the active power acquisition data Y3 is obtained based on the active power acquisition data Y3 and the average value of the active power acquisition data Y1 and Y3, specifically:

[0146] AVED3'' = |Y3 - (Y1 + Y3) / 2|.

[0147] When Diff4 < W, the calculation process of the average deviation is as follows:

[0148] The second type of average deviation AVED1' of the active power acquisition data Y1 is obtained based on the active power acquisition data Y1 and the average value of the active power acquisition data Y1 and Y2, specifically:

[0149] AVED1' = |Y1 - (Y1 + Y2) / 2|.

[0150] The third type of average deviation AVED2'' of the active power acquisition data Y2 is obtained based on the active power acquisition data Y2 and the average value of the active power acquisition data Y1 and Y2, specifically:

[0151] AVED2'' = |Y2 - (Y1 + Y2) / 2|.

[0152] In some feasible embodiments, based on the foregoing solution, comparing based on the average deviation to obtain the optimal active power includes:

[0153] When the sixth active power deviation is less than the active power deviation threshold, the second type average deviation of active power acquisition data Y2 and the second type average deviation of active power acquisition data Y3 are compared, and the active power acquisition data corresponding to the smallest average deviation is taken as the optimal active power.

[0154] When the fifth active power deviation is less than the active power deviation threshold, the magnitude of the third type average deviation of active power acquisition data Y1 and the third type average deviation of active power acquisition data Y3 are compared, and the active power acquisition data corresponding to the smallest average deviation is taken as the optimal active power.

[0155] When the fourth active power deviation is less than the active power deviation threshold, the second type of average deviation of active power acquisition data Y1 and the third type of average deviation of active power acquisition data Y2 are compared, and the active power acquisition data corresponding to the smallest average deviation is taken as the optimal active power.

[0156] For example, AVED2′ and AVED3′ are compared. If the value of AVED2′ is the smallest, the active power data Y2 is confirmed as the optimal active power. If the value of AVED3′ is the smallest, the active power data Y3 is confirmed as the optimal active power.

[0157] Compare the values ​​of AVED1′ and AVED2″. If AVED1′ is the smallest, the active power data Y1 is confirmed as the optimal active power. If AVED2″ is the smallest, the active power data Y2 is confirmed as the optimal active power.

[0158] Compare the values ​​of AVED1″ and AVED3″. If the value of AVED1″ is the smallest, the active power data Y1 is confirmed as the optimal active power. If the value of AVED3″ is the smallest, the active power data Y3 is confirmed as the optimal active power.

[0159] In summary, the technical solution of this application effectively improves the reliability of active power signal acquisition, judgment and processing, effectively reduces the risk of active power signal fluctuation, loss or failure due to single sensor failure and PT and CT circuit fluctuation, and solves the problems of inaccurate judgment and processing after active power signal fluctuation, loss or failure of hydro-generator unit, which leads to unit start-up and shutdown and AGC regulation failure.

[0160] Below is a specific implementation process for this method:

[0161] Step S1: Acquire three sets of active power data Y1, Y2, and Y3.

[0162] Step S2: Determine whether the quality of all three groups of data channels is normal. If the quality of all three groups of data channels is normal, proceed to step S21; otherwise, execute step S3.

[0163] Step S21: When the quality of all three groups of data channels is normal, select one of the three groups of active powers collected and finally output the only optimal active power. Specifically:

[0164] 1. Execute step T1 to calculate the active power deviation between any two groups: Diff1 = |Y1 - Y2|, Diff2 = |Y1 - Y3|, Diff3 = |Y2 - Y3|.

[0165] 2. Execute step T2 to determine whether the active power deviation between any two groups is within the threshold W, that is, whether Diff1 < W and Diff2 < W and Diff2 < W exist. If so, execute step T21; otherwise, execute step T3.

[0166] 3. Execute step T21 to calculate the average value deviation: AVED1 = |Y1 - (Y1 + Y2 + Y3) / 3|, AVED2 = |Y2 - (Y1 + Y2 + Y3) / 3|, AVED3 = |Y3 - (Y1 + Y2 + Y3) / 3|.

[0167] 4. Execute step T22 to determine whether the average value deviation AVED2 > AVED3. If so, execute step T23; otherwise, execute step T24.

[0168] 5. Execute step T23 to determine whether the average value deviation AVED1 > AVED3. If so, output the optimal active power as Y3 and the process ends; otherwise, output the optimal active power as Y1 and the process ends.

[0169] 6. Execute step T24 to determine whether the average value deviation AVED2 < AVED1. If so, output the optimal active power as Y2 and the process ends; otherwise, output the optimal active power as Y1 and the process ends.

[0170] 7. Execute step T3 to determine whether the deviation Diff3 < W and Diff1 > W or Diff2 > W. If so, execute step T31; otherwise, execute step T4.

[0171] 8. Execute step T31 to calculate the average value deviation: AVED2′ = |Y2 - (Y2 + Y3) / 2|, AVED3′ = |Y3 - (Y2 + Y3) / 2|.

[0172] 9. Execute step T32 to determine whether the average value deviation AVED2′ > AVED3′. If so, output the optimal active power as Y3 and end the process; otherwise, output the optimal active power as Y2 and end the process.

[0173] 10. Execute step T4 to determine whether the deviation Diff1 < W and Diff2 > W or Diff3 > W. If so, execute step T41; otherwise, execute step T5.

[0174] 11. Execute step T41 to calculate the average value deviation: AVED1′ = |Y1 - (Y1 + Y2) / 2|, AVED2″ = |Y2 - (Y1 + Y2) / 2|.

[0175] 12. Execute step T42 to determine whether the average value deviation AVED1′ > AVED2″. If so, output the optimal active power as Y2 and end the process; otherwise, output the optimal active power as Y1 and end the process.

[0176] 13. Execute step T5 to determine whether the deviation Diff2 < W and Diff1 > W or Diff3 > W. If so, execute step T51; otherwise, end the process.

[0177] 14. Execute step T51 to calculate the average value deviation: AVED1″ = |Y1 - (Y1 + Y3) / 2|, AVED3″ = |Y3 - (Y1 + Y3) / 2|.

[0178] 15. Execute step T52 to determine whether the average value deviation AVED1″ > AVED3″. If so, output the optimal active power as Y3 and end the process; otherwise, output the optimal active power as Y1 and end the process.

[0179] Step S3: Determine whether at least two groups of data channel qualities are normal. If so, enter step S31; otherwise, execute step S4.

[0180] Step S31: In the case where at least two groups of data channel qualities are normal, select one from the three collected active powers, and finally output the only optimal active power. Specifically:

[0181] 16. Execute step G1 to calculate the active power deviation between any two groups: Diff4 = |Y1 - Y2|, Diff5 = |Y1 - Y3|, Diff6 = |Y2 - Y3|.

[0182] 17. Execute step G2 to determine whether the active power deviation Diff6 is within the threshold W, that is, whether Diff6 < W. If so, execute step G21; otherwise, execute step G3.

[0183] 18. Execute step G21 to calculate the average value deviation: AVED2′ = |Y2 - (Y2 + Y3) / 2|, AVED3′ = |Y3 - (Y2 + Y3) / 2|.

[0184] 19. Execute step G22 to determine whether the average value deviation AVED2′ > AVED3′. If so, output the optimal active power as Y3 and end the process; otherwise, output the optimal active power as Y2 and end the process.

[0185] 20. Execute step G3 to determine whether the active power deviation Diff5 is within the threshold W, that is, whether Diff5 < W. If so, execute step G31; otherwise, execute step G4.

[0186] 21. Execute step G31 to calculate the average value deviation: AVED1″ = |Y1 - (Y1 + Y3) / 2|, AVED3″ = |Y3 - (Y1 + Y3) / 2|.

[0187] 22. Execute step G32 to determine whether the average value deviation AVED1″ > AVED3″. If so, output the optimal active power as Y3 and end the process; otherwise, output the optimal active power as Y1 and end the process.

[0188] 23. Execute step G4 to determine whether the active power deviation Diff4 is within the threshold W, that is, whether Diff4 < W. If so, execute step G41; otherwise, end the process.

[0189] 24. Execute step G41 to calculate the average value deviation: AVED1′ = |Y1 - (Y1 + Y2) / 2|, AVED2″ = |Y2 - (Y1 + Y2) / 2|.

[0190] 25. Execute step G42 to determine whether the average value deviation AVED1′ > AVED2″. If so, output the optimal active power as Y2 and end the process; otherwise, output the optimal active power as Y1 and end the process.

[0191] Step S4: Determine whether at least one set of data channel quality is normal. If so, enter step S41; otherwise, end the process.

[0192] Step S41: In the case where at least one set of data channel quality is normal, select one out of the three sets of collected active power signals, and finally output the only optimal active power. Specifically:

[0193] 26. Execute step B1 to determine whether the quality of the first set of active power data Y1 channel is normal. If so, output the optimal active power as Y1 and end the process; otherwise, execute step B2.

[0194] 27. Execute step B2 to determine whether the quality of the active power data Y2 channel in the second group is normal. If yes, output the optimal active power as Y2 and the process ends; otherwise, output the optimal active power as Y3 and the process ends.

[0195] The following describes an embodiment of the apparatus described in this application, which can be used to execute a three-way selection method for active power signals of a hydro-generator set as described in the above embodiments of this application. For details not disclosed in the apparatus embodiments of this application, please refer to the embodiments of the method described in the above applications.

[0196] Referring to FIG3, a three-way selection device 300 for active power signals of a hydro-generator set according to an embodiment of the present application includes:

[0197] Acquisition unit 301 is used to acquire three sets of active power data: Y1, Y2, and Y3.

[0198] The confirmation unit 302 is used to confirm the optimal active power based on the channel quality status of the active power acquisition data.

[0199] The confirmation unit includes:

[0200] The first confirmation subunit is used to determine the optimal active power based on the active power deviation between any two sets of active power acquisition data and the average deviation of each set of active power acquisition data when the channel quality of all three sets of active power acquisition data is normal.

[0201] The second confirmation subunit is used to determine the optimal active power based on the active power deviation between any two sets of active power acquisition data and the average deviation of each set of active power acquisition data when the channel quality of at least two sets of active power acquisition data is normal.

[0202] The third confirmation subunit is used to determine the optimal active power based on the channel quality of the active power acquisition data when at least one set of active power acquisition data channels are of normal quality.

[0203] As shown in Figure 4, this application embodiment also provides an electronic device 400, including a memory 410, a processor 420, and a computer program 411 stored in the memory 410 and executable on the processor. When the processor 420 executes the computer program 411, it implements the steps of the above-mentioned method for selecting one of three active power signals of a hydro-generator set.

[0204] Since the electronic device described in this embodiment is the device used to implement the active power signal three-to-one selection device of a hydro-generator set in the embodiments of this application, those skilled in the art can understand the specific implementation method and various variations of the electronic device in this embodiment based on the method described in the embodiments of this application. Therefore, how the electronic device implements the method in the embodiments of this application will not be described in detail here. Any device used by those skilled in the art to implement the method in the embodiments of this application is within the scope of protection of this application.

[0205] In practice, when the computer program 411 is executed by the processor, it can implement any of the embodiments corresponding to the first aspect.

[0206] Figure 5 shows a schematic diagram of the structure of a computer system suitable for implementing the electronic device of the present application.

[0207] It should be noted that the computer system 500 of the electronic device shown in Figure 5 is only an example and should not impose any limitations on the functionality and scope of use of the embodiments of this application.

[0208] As shown in Figure 5, the computer system 500 includes a Central Processing Unit (CPU) 501, which can perform various appropriate actions and processes based on programs stored in Read-Only Memory (ROM) 502 or programs loaded from storage portion 508 into Random Access Memory (RAM) 503, such as performing the methods described in the above embodiments. The RAM 503 also stores various programs and data required for system operation. The CPU 501, ROM 502, and RAM 503 are interconnected via a bus 504. An Input / Output (I / O) interface 505 is also connected to the bus 504.

[0209] The following components are connected to I / O interface 505: an input section 506 including a keyboard, mouse, etc.; an output section 507 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and speakers, etc.; a storage section 508 including a hard disk, etc.; and a communication section 509 including a network interface card such as a LAN (Local Area Network) card, modem, etc. The communication section 509 performs communication processing via a network such as the Internet. A drive 510 is also connected to I / O interface 505 as needed. Removable media 511, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., are installed on drive 510 as needed so that computer programs read from them can be installed into storage section 508 as needed.

[0210] Specifically, according to embodiments of this application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of this application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication section 509, and / or installed from removable medium 511. When the computer program is executed by central processing unit (CPU) 501, it performs various functions defined in the system of this application.

[0211] It should be noted that the computer-readable medium shown in the embodiments of this application can be a computer-readable signal medium or a computer-readable storage medium, or any combination of the two. A computer-readable storage medium can be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), flash memory, optical fiber, portable compact disc read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this application, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In this application, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such transmitted data signals can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. The computer-readable signal medium can also be any computer-readable medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to wireless, wired, etc., or any suitable combination thereof.

[0212] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. Each block in a flowchart or block diagram may represent a module, segment, or portion of code, which contains one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0213] The units described in the embodiments of this application can be implemented in software or hardware, and the described units can also be located in a processor. The names of these units do not necessarily limit the specific unit itself.

[0214] In another aspect, this application also provides a computer program product or computer program including computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the three-way selection method for active power signals of a hydro-generator set described in the above embodiments.

[0215] In another aspect, this application also provides a computer-readable medium, which may be included in the electronic device described in the above embodiments; or it may exist independently and not assembled into the electronic device. The computer-readable medium carries one or more programs, which, when executed by the electronic device, cause the electronic device to implement the three-way selection method for active power signals of a hydro-generator set described in the above embodiments.

[0216] It should be noted that although several modules or units for the device used to perform actions have been mentioned in the detailed description above, this division is not mandatory. In fact, according to the embodiments of this application, the features and functions of two or more modules or units described above can be embodied in one module or unit. Conversely, the features and functions of one module or unit described above can be further divided and embodied by multiple modules or units.

[0217] Through the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein can be implemented by software or by combining software with necessary hardware. Therefore, the technical solutions according to the embodiments of this application can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (such as a CD-ROM, USB flash drive, external hard drive, etc.) or on a network, including several instructions to cause a computing device (such as a personal computer, server, touch terminal, or network device, etc.) to execute the method according to the embodiments of this application.

[0218] Other embodiments of this application will readily conceive of by those skilled in the art upon consideration of the specification and practice of the embodiments disclosed herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein. It should be understood that this application is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this application is limited only by the appended claims.

Claims

1. A three-way selection method for active power signals of a hydro-generator unit, characterized in that, include: Acquire three sets of active power data: Y1, Y2, and Y3. Based on the channel quality of the active power acquisition data, the optimal active power is determined, including: When the channel quality of all three sets of active power acquisition data is normal, the optimal active power is determined based on the active power deviation between any two sets of active power acquisition data and the average deviation of each set of active power acquisition data. When at least two sets of active power acquisition data have normal channel quality, the optimal active power is determined based on the active power deviation between any two sets of active power acquisition data and the average deviation of each set of active power acquisition data. When at least one set of active power acquisition data channels has normal quality, the optimal active power is determined based on the channel quality of the active power acquisition data.

2. The method according to claim 1, characterized in that, When the channel quality of all three sets of active power acquisition data is normal, the optimal active power is determined based on the active power deviation between any two sets of active power acquisition data and the average deviation of each set of active power acquisition data, including: Assuming that the channel quality of all three sets of active power acquisition data is normal, calculate the active power deviation between any two sets to obtain the first active power deviation, the second active power deviation, and the third active power deviation. The judgment is made based on the first active power deviation, the second active power deviation, the third active power deviation and the active power deviation threshold, and the average deviation under different judgment results is calculated based on different judgment results. The optimal active power is obtained by comparing the deviations of the average values.

3. The method according to claim 2, characterized in that, The judgment is based on the first active power deviation, the second active power deviation, the third active power deviation, and the active power deviation threshold. The average deviation under different judgment results is calculated, including: When the first active power deviation, the second active power deviation, and the third active power deviation are all less than the active power deviation threshold, the first type of average deviation of active power acquisition data Y1, the first type of average deviation of active power acquisition data Y2, and the first type of average deviation of active power acquisition data Y3 are calculated. When the third active power deviation is less than the active power deviation threshold and the second active power deviation is greater than the active power deviation threshold, or when the third active power deviation is less than the active power deviation threshold and the first active power deviation is greater than the active power deviation threshold, calculate the second type of average deviation of active power acquisition data Y2 and the second type of average deviation of active power acquisition data Y3. When the first active power deviation is less than the active power deviation threshold and the second active power deviation is greater than the active power deviation threshold, or when the first active power deviation is less than the active power deviation threshold and the third active power deviation is greater than the active power deviation threshold, calculate the second type of average deviation of active power acquisition data Y1 and the third type of average deviation of active power acquisition data Y2. When the second active power deviation is less than the active power deviation threshold and the first active power deviation is greater than the active power deviation threshold, or when the second active power deviation is less than the active power deviation threshold and the third active power deviation is greater than the active power deviation threshold, calculate the third type average deviation of active power acquisition data Y1 and the third type average deviation of active power acquisition data Y3.

4. The method according to claim 3, characterized in that, The process of comparing the average deviation to obtain the optimal active power includes: When the first active power deviation, the second active power deviation, and the third active power deviation are all less than the active power deviation threshold, the magnitude of the first type of average deviation of active power acquisition data Y1, the first type of average deviation of active power acquisition data Y2, and the first type of average deviation of active power acquisition data Y3 are compared, and the active power acquisition data corresponding to the smallest average deviation is taken as the optimal active power. When the third active power deviation is less than the active power deviation threshold and the second active power deviation is greater than the active power deviation threshold, or when the third active power deviation is less than the active power deviation threshold and the first active power deviation is greater than the active power deviation threshold, the second type average deviation of active power acquisition data Y2 and the second type average deviation of active power acquisition data Y3 are compared, and the active power acquisition data corresponding to the smallest average deviation is taken as the optimal active power. If the first active power deviation is less than the active power deviation threshold and the second active power deviation is greater than the active power deviation threshold, or if the first active power deviation is less than the active power deviation threshold and the third active power deviation is greater than the active power deviation threshold, the second type average deviation of active power acquisition data Y1 and the third type average deviation of active power acquisition data Y2 are compared, and the active power acquisition data corresponding to the smallest average deviation is taken as the optimal active power. If the second active power deviation is less than the active power deviation threshold and the first active power deviation is greater than the active power deviation threshold, or if the second active power deviation is less than the active power deviation threshold and the third active power deviation is greater than the active power deviation threshold, the active power data corresponding to the smallest average deviation is selected as the optimal active power based on a comparison of the third type average deviation of active power data Y1 and the third type average deviation of active power data Y3.

5. The method according to claim 1, characterized in that, When at least two sets of active power acquisition data have normal channel quality, the optimal active power is determined based on the active power deviation between any two sets of active power acquisition data and the average deviation of each set of active power acquisition data, including: Under the condition that the channel quality of at least two sets of active power acquisition data is normal, calculate the active power deviation between any two sets to obtain the fourth active power deviation, the fifth active power deviation and the sixth active power deviation. Judgments are made based on the fourth active power deviation, the fifth active power deviation, the sixth active power deviation, and the active power deviation threshold. The average deviation under different judgment results is calculated based on the different judgment results. The optimal active power is obtained by comparing the deviations of the average values.

6. The method according to claim 5, characterized in that, The judgment is based on the fourth active power deviation, the fifth active power deviation, the sixth active power deviation, and the active power deviation threshold. The average deviation under different judgment results is calculated, including: When the sixth active power deviation is less than the active power deviation threshold, calculate the second type average deviation of active power acquisition data Y2 and the second type average deviation of active power acquisition data Y3. When the fifth active power deviation is less than the active power deviation threshold, calculate the third type average deviation of active power acquisition data Y1 and the third type average deviation of active power acquisition data Y3. When the fourth active power deviation is less than the active power deviation threshold, the second type of average deviation of active power acquisition data Y1 and the third type of average deviation of active power acquisition data Y2 are calculated.

7. The method according to claim 6, characterized in that, The process of comparing the average deviation to obtain the optimal active power includes: When the sixth active power deviation is less than the active power deviation threshold, the second type average deviation of active power acquisition data Y2 and the second type average deviation of active power acquisition data Y3 are compared, and the active power acquisition data corresponding to the smallest average deviation is taken as the optimal active power. When the fifth active power deviation is less than the active power deviation threshold, the magnitude of the third type average deviation of active power acquisition data Y1 and the third type average deviation of active power acquisition data Y3 are compared, and the active power acquisition data corresponding to the smallest average deviation is taken as the optimal active power. When the fourth active power deviation is less than the active power deviation threshold, the second type of average deviation of active power acquisition data Y1 and the third type of average deviation of active power acquisition data Y2 are compared, and the active power acquisition data corresponding to the smallest average deviation is taken as the optimal active power.

8. A three-way selection device for active power signals of a hydro-generator set, characterized in that, include: The acquisition unit is used to acquire three sets of active power data: Y1, Y2, and Y3. The confirmation unit is used to confirm the optimal active power based on the channel quality status of the active power acquisition data. The confirmation unit includes: The first confirmation subunit is used to determine the optimal active power based on the active power deviation between any two sets of active power acquisition data and the average deviation of each set of active power acquisition data when the channel quality of all three sets of active power acquisition data is normal. The second confirmation subunit is used to determine the optimal active power based on the active power deviation between any two sets of active power acquisition data and the average deviation of each set of active power acquisition data when the channel quality of at least two sets of active power acquisition data is normal. The third confirmation subunit is used to determine the optimal active power based on the channel quality of the active power acquisition data when at least one set of active power acquisition data channels are of normal quality.

9. A computer-readable storage medium, characterized in that, The storage medium stores computer instructions that, when executed on a computer, cause the computer to perform the method as described in any one of claims 1-7.

10. An electronic device, characterized in that, include: Memory and processor; The memory is used to store computer instructions; The processor is configured to invoke computer instructions stored in the memory, causing the electronic device to perform the method as described in any one of claims 1-7.

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