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

Abstract

An embodiment of the present application provides a method and related equipment for selecting one of three active power signals for a hydro-turbine generator set, relating to the field of hydro-turbine generator set automation technology. The method comprises: obtaining three sets of active power acquisition data, Y1, Y2, and Y3; and determining the optimal active power based on the channel quality of the active power acquisition data. The technical solution of the present application can select and output a unique optimal active power as the final active power of the hydro-turbine generator set to participate in unit control, effectively improving the reliability of active power signal judgment and processing, and resolving problems such as unit startup and shutdown and AGC regulation loss caused by active power signal fluctuation, loss, or failure, resulting from inaccurate judgment and processing.

Description

Technical Field

[0001] The present application relates to the technical field of automation of hydro-generator sets, and in particular to a method for selecting one of three active power signals of a hydro-generator set and related equipment. Background Art

[0002] Active power is a critical parameter for hydroelectric generators. The stability of its measured value directly impacts the generator's start-up and shutdown control, power generation efficiency, and grid frequency balance. Therefore, the stability and reliability of the active power signal are crucial for hydroelectric generators.

[0003] Currently, most hydropower stations are equipped with multiple power sensors to collect the active power signals of the units. These sensors monitor, judge, and process these signals using methods such as "two-choose-one" and "three-choose-two." The "two-choose-one" method primarily uses two active power signals to achieve active / standby redundancy. However, if both active power signals are disconnected or fail simultaneously, the unit's active power signal loses monitoring and control. The "three-choose-two" method primarily selects two sets of active power signals and takes the average value as the actual active power value. However, this method is susceptible to fluctuations in the PT or CT circuits, resulting in frequent switching between the two selected active power signals. Therefore, there is an urgent need for an acquisition system and selection and processing method to improve the stability and reliability of the active power signals of hydro-turbine generator units and further ensure stable operation of the units. Summary of the Invention

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

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

[0006] According to a first aspect of an embodiment of the present application, a method for selecting one of three active power signals of a hydro-generator set is provided, comprising:

[0007] Obtain three groups of active power data, Y1, Y2, and Y3;

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

[0009] When the channel quality of the three sets of active power acquisition data are 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 value deviation of each set of active power acquisition data;

[0010] When the channel quality of at least two groups of active power acquisition data is normal, the optimal active power is determined based on the active power deviation between any two groups of active power acquisition data and the average value deviation of each group of active power acquisition data;

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

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

[0013] When the channel quality of the three groups of active power acquisition data are all normal, the active power deviation between any two groups is calculated to obtain the first active power deviation, the second active power deviation and the third active power deviation;

[0014] Performing 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 calculating the average value deviation under different judgment results based on different judgment results;

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

[0016] In some embodiments of the present application, based on the aforementioned solution, 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 value deviation under different judgment results based on different judgment results, include:

[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, calculating the first type average value deviation of the active power collection data Y1, the first type average value deviation of the active power collection data Y2, and the first type average value deviation of the active power collection data Y3;

[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, calculating the second type of average value deviation of the active power collection data Y2 and the second type of average value deviation of the active power collection 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, calculating the second type of average value deviation of the active power collection data Y1 and the third type of average value deviation of the active power collection 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 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 third type of average value deviation of the active power acquisition data Y1 and the third type of average value deviation of the active power acquisition data Y3 are calculated.

[0021] In some embodiments of the present application, based on the aforementioned solution, the comparison based on the average value 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 smaller than the active power deviation threshold, a size comparison is performed based on the first type of average value deviation of the active power acquisition data Y1, the first type of average value deviation of the active power acquisition data Y2 and the first type of average value deviation of the active power acquisition data Y3, and the active power acquisition data corresponding to the smallest average value deviation 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, a comparison is performed based on the second type of average value deviation of the active power collection data Y2 and the second type of average value deviation of the active power collection data Y3, and the active power collection data corresponding to the smallest average value deviation is taken as the optimal active power;

[0024] 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, a comparison is performed based on the second type of average value deviation of the active power collection data Y1 and the third type of average value deviation of the active power collection data Y2, and the active power collection data corresponding to the smallest average value deviation is taken as the optimal active power;

[0025] 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 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, a size comparison is performed based on the third category average value deviation of the active power acquisition data Y1 and the third category average value deviation of the active power acquisition data Y3, and the active power acquisition data corresponding to the smallest average value deviation is taken as the optimal active power.

[0026] In some embodiments of the present application, based on the aforementioned solution, when the channel quality of at least two 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 value deviation of each set of active power acquisition data includes:

[0027] When the channel quality of at least two groups of active power acquisition data are all normal, the active power deviation between any two groups is calculated to obtain a fourth active power deviation, a fifth active power deviation, and a sixth active power deviation;

[0028] Performing 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 calculating the average value deviation under different judgment results based on different judgment results;

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

[0030] In some embodiments of the present application, based on the aforementioned solution, 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 value deviation under different judgment results based on different judgment results, include:

[0031] When the sixth active power deviation is less than the active power deviation threshold, calculating the second type average value deviation of the active power collection data Y2 and the second type average value deviation of the active power collection data Y3;

[0032] When the fifth active power deviation is less than the active power deviation threshold, calculating the third type average value deviation of the active power collection data Y1 and the third type average value deviation of the active power collection data Y3;

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

[0034] In some embodiments of the present application, based on the aforementioned solution, the comparison based on the average value deviation to obtain the optimal active power includes:

[0035] When the sixth active power deviation is less than the active power deviation threshold, comparing the second type of average value deviation of the active power acquisition data Y2 and the second type of average value deviation of the active power acquisition data Y3, and taking the active power acquisition data corresponding to the smallest average value deviation as the optimal active power;

[0036] When the fifth active power deviation is less than the active power deviation threshold, comparing the third type average value deviation of the active power acquisition data Y1 and the third type average value deviation of the active power acquisition data Y3, and taking the active power acquisition data corresponding to the smallest average value deviation as the optimal active power;

[0037] When the fourth active power deviation is smaller than the active power deviation threshold, a size comparison is performed based on the second type of average value deviation of the active power acquisition data Y1 and the third type of average value deviation of the active power acquisition data Y2, and the active power acquisition data corresponding to the smallest average value deviation is taken as the optimal active power.

[0038] According to a second aspect of an embodiment of the present application, a device for selecting one of three active power signals of a hydro-generator set is provided, comprising:

[0039] The acquisition unit is used to obtain three groups of active power acquisition data, namely Y1, Y2 and Y3;

[0040] A confirmation unit, configured to confirm the optimal active power based on the channel quality of the active power acquisition data;

[0041] Wherein, the confirmation unit includes:

[0042] The first confirmation subunit is configured to, when the channel qualities of the three groups of active power acquisition data are all normal, determine the optimal active power based on the active power deviation between any two groups of active power acquisition data and the average value deviation of each group of active power acquisition data;

[0043] The second confirmation subunit is configured to, when the channel quality of at least two groups of active power acquisition data is normal, confirm the optimal active power according to the active power deviation between any two groups of active power acquisition data and the average value deviation of each group of active power acquisition data;

[0044] The third confirmation subunit is configured to confirm the optimal active power based on the channel quality of the active power collection data when the channel quality of at least one group of active power collection data is normal.

[0045] According to a third aspect of the embodiments of the present application, a computer-readable storage medium is provided, wherein the storage medium stores computer instructions, and when the computer instructions are executed on a computer, the computer is caused to execute the method according to the first aspect.

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

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

[0048] The processor is configured to call the computer instructions stored in the memory so that the electronic device executes the method according to the first aspect.

[0049] The technical solution of the present application can select and output the only optimal active power as the final active power of the hydro-turbine generator set to participate in the control of the unit, effectively improving the reliability of active power signal judgment and processing, and solving problems such as unit start-up and shutdown and AGC adjustment out of control due to inaccurate judgment and processing of active power signal fluctuations, loss or failure of the hydro-turbine generator set.

[0050] It should be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] The accompanying drawings are incorporated into and constitute a part of the specification, illustrating embodiments consistent with the present application and, together with the specification, explaining the principles of the present application. Obviously, the drawings described below are only some embodiments of the present application, and those skilled in the art can derive other drawings based on these drawings without inventive effort. In the drawings:

[0052] Figure 1 A schematic flow chart of a method for selecting one of three active power signals of a hydro-generator set according to an embodiment of the present application is shown;

[0053] Figure 2 FIG2 shows a flow chart of step S200 according to an embodiment of the present application;

[0054] Figure 3 A block diagram of a device for selecting one out of three active power signals of a hydro-generator set according to an embodiment of the present application is shown;

[0055] Figure 4 A block diagram of an electronic device according to an embodiment of the present application is shown;

[0056] Figure 5A schematic diagram of the structure of a computer system suitable for implementing an electronic device according to an embodiment of the present application is shown. DETAILED DESCRIPTION

[0057] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example 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 so that this application will be thorough and complete and will fully convey the concepts of the example embodiments to those skilled in the art.

[0058] In addition, described feature, structure or characteristic can be combined in one or more embodiments in any suitable manner.In the following description, many specific details are provided so as to provide a full understanding of the embodiments of the present application. However, it will be appreciated by those skilled in the art that the technical scheme of the present application can be put into practice without one or more of the specific details, or other methods, components, devices, steps etc. can be adopted. In other cases, known methods, devices, implementations or operations are not shown or described in detail to avoid blurring the various aspects of the application.

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

[0060] The flowcharts shown in the accompanying drawings are for illustrative purposes only and do not necessarily include all contents and operations / steps, nor must they be executed in the order described. For example, some operations / steps may be decomposed, while others may be combined or partially combined. Therefore, the actual execution order may vary depending on the actual situation.

[0061] It should be noted that the terms "first," "second," and the like in the specification and claims of this application and the accompanying drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or precedence. It should be understood that the terms used in this manner are interchangeable where appropriate, such that the embodiments of the present application described herein can be implemented in an order other than that illustrated or described.

[0062] To make the objectives, technical solutions, and advantages of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts shall fall within the scope of protection of the present invention.

[0063] The following will describe some embodiments of the present application in detail with reference to the accompanying drawings. In the absence of conflict, the following embodiments and features therein may be combined with each other.

[0064] See also Figure 1 , shows a flow chart of a method for selecting one of three active power signals of a hydro-generator set according to an embodiment of the present application.

[0065] like Figure 1 As shown, a method for selecting one of three active power signals of a hydro-generator set is presented, including steps S100 to S200.

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

[0067] It can be understood that, in this embodiment, three groups of active power acquisition data are obtained by random selection.

[0068] Continue to refer Figure 1 , step S200, confirming the optimal active power based on the channel quality of the active power acquisition data.

[0069] For details, see Figure 2 , step S200 includes:

[0070] Step S210: When the channel qualities of the three sets of active power acquisition data are 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 value deviation of each set of active power acquisition data;

[0071] Step S220, determining the optimal active power by calculating the active power deviation between the rate collected data and the average value deviation of each group of active power collected data;

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

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

[0074] In some feasible embodiments, based on the above solution, when the channel quality of the three sets of active power acquisition data are all normal, determining the optimal active power according to the active power deviation between any two sets of active power acquisition data and the average value deviation of each set of active power acquisition data includes:

[0075] When the channel quality of the three groups of active power acquisition data are all normal, the active power deviation between any two groups is calculated to obtain the first active power deviation, the second active power deviation and the third active power deviation;

[0076] Performing 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 calculating the average value deviation under different judgment results based on different judgment results;

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

[0078] Exemplarily, the calculation process of 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 the active power acquisition data Y2, specifically:

[0080] Diff1 = |Y1-Y2|.

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

[0082] Diff2 = |Y1-Y3|.

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

[0084] Diff3 = |Y2-Y3|.

[0085] In some feasible embodiments, based on the above solution, 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 value deviation under different judgment results based on different judgment results, include:

[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, calculating the first type average value deviation of the active power collection data Y1, the first type average value deviation of the active power collection data Y2, and the first type average value deviation of the active power collection data Y3;

[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] According to the active power acquisition data Y3 and the average value of the active power acquisition data Y1 and Y3, the third type of average deviation AVED3'' of the active power acquisition data Y3 is obtained, specifically:

[0111] AVED3″=|Y3-(Y1+Y3) / 2|.

[0112] In some feasible embodiments, based on the above solution, the comparison based on the average value deviation to obtain the optimal active power includes:

[0113] When the first active power deviation, the second active power deviation and the third active power deviation are all smaller than the active power deviation threshold, a size comparison is performed based on the first type of average value deviation of the active power acquisition data Y1, the first type of average value deviation of the active power acquisition data Y2 and the first type of average value deviation of the active power acquisition data Y3, and the active power acquisition data corresponding to the smallest average value deviation 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, a comparison is performed based on the second type of average value deviation of the active power acquisition data Y2 and the second type of average value deviation of the active power acquisition data Y3, and the active power acquisition data corresponding to the smallest average value deviation is taken as the optimal active power;

[0115] 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, a comparison is performed based on the second type of average value deviation of the active power collection data Y1 and the third type of average value deviation of the active power collection data Y2, and the active power collection data corresponding to the smallest average value deviation is taken as the optimal active power;

[0116] 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 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, a size comparison is performed based on the third category average value deviation of the active power acquisition data Y1 and the third category average value deviation of the active power acquisition data Y3, and the active power acquisition data corresponding to the smallest average value deviation is taken as the optimal active power.

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

[0118] Similarly, AVED2′ and AVED3′ are compared. If the value of AVED2′ is the smallest, the active power acquisition data Y2 is confirmed as the optimal active power. If the value of AVED3′ is the smallest, the active power acquisition data Y3 is confirmed as the optimal active power.

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

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

[0121] In some feasible embodiments, based on the above solution, when the channel quality of at least two 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 value deviation of each set of active power acquisition data includes:

[0122] When the channel quality of at least two groups of active power acquisition data are all normal, the active power deviation between any two groups is calculated to obtain a fourth active power deviation, a fifth active power deviation, and a sixth active power deviation;

[0123] Performing 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 calculating the average value deviation under different judgment results based on different judgment results;

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

[0125] Exemplarily, the calculation process of the fourth active power deviation, the fifth active power deviation, and the sixth active power deviation is as follows:

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

[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, the determination is made 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 average deviation under different determination results is calculated respectively, 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] Calculate 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 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, comparing the second type of average value deviation of the active power acquisition data Y2 and the second type of average value deviation of the active power acquisition data Y3, and taking the active power acquisition data corresponding to the smallest average value deviation as the optimal active power;

[0154] When the fifth active power deviation is less than the active power deviation threshold, comparing the third type average value deviation of the active power acquisition data Y1 and the third type average value deviation of the active power acquisition data Y3, and taking the active power acquisition data corresponding to the smallest average value deviation as the optimal active power;

[0155] When the fourth active power deviation is smaller than the active power deviation threshold, a size comparison is performed based on the second type of average value deviation of the active power acquisition data Y1 and the third type of average value deviation of the active power acquisition data Y2, and the active power acquisition data corresponding to the smallest average value deviation is taken as the optimal active power.

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

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

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

[0159] In summary, the technical solution of the present application effectively improves the reliability of active power signal acquisition, judgment and processing, effectively reduces the risk of fluctuation, loss or failure of the unit's active power signal due to single sensor failure and PT and CT circuit fluctuations, and solves the problems of inaccurate judgment and processing after fluctuation, loss or failure of the active power signal of the hydro-turbine generator set, resulting in unit start-up and shutdown and AGC adjustment out of control.

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

[0161] Step S1: Acquire three sets of active power acquisition 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 from the three groups of collected active powers, 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 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 deviation AVED2 > AVED3. If so, execute step T23; otherwise, execute step T24.

[0168] 5. Execute step T23 to determine whether the average 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 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 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 of the two sets of collected active powers through a three - way selection, and finally output a unique 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 deviation: AVED2′ = |Y2 - (Y2 + Y3) / 2|, AVED3′ = |Y3 - (Y2 + Y3) / 2|.

[0184] 19. Execute step G22 to determine whether the average 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 deviation: AVED1″ = |Y1 - (Y1 + Y3) / 2|, AVED3″ = |Y3 - (Y1 + Y3) / 2|.

[0187] 22. Execute step G32 to determine whether the average 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 deviation: AVED1′ = |Y1 - (Y1 + Y2) / 2|, AVED2″ = |Y2 - (Y1 + Y2) / 2|.

[0190] 25. Execute step G42 to determine whether the average 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 group of data channel qualities is normal. If so, enter step S41; otherwise, end the process.

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

[0193] 26. Execute step B1 to determine whether the quality of the first group 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 channel quality of the second group of active power data Y2 is normal. If so, 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 device of the present application, which can be used to implement a method for selecting one of three active power signals of a hydro-generator set in the above embodiment of the present application. For details not disclosed in the embodiment of the device of the present application, please refer to the embodiment of the method of the above application.

[0196] Reference Figure 3 As shown, according to one embodiment of the present application, a device 300 for selecting one of three active power signals of a hydro-generator set includes:

[0197] The acquisition unit 301 is used to acquire three groups of active power acquisition data, namely Y1, Y2 and Y3;

[0198] A confirmation unit 302 is configured to determine the optimal active power based on the channel quality of the active power acquisition data;

[0199] Wherein, the confirmation unit includes:

[0200] The first confirmation subunit is configured to, when the channel qualities of the three groups of active power acquisition data are all normal, determine the optimal active power based on the active power deviation between any two groups of active power acquisition data and the average value deviation of each group of active power acquisition data;

[0201] The second confirmation subunit is configured to, when the channel quality of at least two groups of active power acquisition data is normal, confirm the optimal active power according to the active power deviation between any two groups of active power acquisition data and the average value deviation of each group of active power acquisition data;

[0202] The third confirmation subunit is configured to confirm the optimal active power based on the channel quality of the active power collection data when the channel quality of at least one group of active power collection data is normal.

[0203] like Figure 4 As shown, an embodiment of the present application 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, the steps of the above-mentioned three-selection method for the active power signal of a hydro-turbine generator set are implemented.

[0204] Since the electronic device introduced in this embodiment is the device used to implement a three-choice selection device for active power signals of a hydro-turbine generator set in the embodiment of this application, based on the method introduced in the embodiment of this application, technical personnel in this field can understand the specific implementation method of the electronic device of this embodiment and its various variations. Therefore, how the electronic device implements the method in the embodiment of this application will not be introduced in detail here. As long as the equipment used by technical personnel in this field to implement the method in the embodiment of this application falls within the scope of protection of this application.

[0205] During the specific implementation process, when the computer program 411 is executed by the processor, any implementation method in the embodiments corresponding to the first aspect can be implemented.

[0206] Figure 5 A schematic diagram of the structure of a computer system suitable for implementing an electronic device according to an embodiment of the present application is shown.

[0207] It should be noted that Figure 5 The computer system 500 of the electronic device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0208] like Figure 5 As shown, the computer system 500 includes a central processing unit (CPU) 501, which can perform various appropriate actions and processes according to the program stored in the read-only memory (ROM) 502 or the program loaded from the storage part 508 to the random access memory (RAM) 503, such as executing the method described in the above embodiment. Various programs and data required for system operation are also stored in the RAM 503. The CPU 501, ROM 502 and RAM 503 are connected to each other 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 the I / O interface 505: an input section 506 including a keyboard, a mouse, and the like; an output section 507 including devices such as a cathode ray tube (CRT), a liquid crystal display (LCD), and a speaker; a storage section 508 including a hard disk; and a communication section 509 including a network interface card such as a LAN (Local Area Network) card or a modem. The communication section 509 performs communication processing via a network such as the Internet. A drive 510 is also connected to the I / O interface 505 as needed. Removable media 511, such as a magnetic disk, an optical disk, a magneto-optical disk, or a semiconductor memory, is installed in the drive 510 as needed, so that computer programs read therefrom can be installed into the storage section 508 as needed.

[0210] In particular, according to an embodiment of the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present application includes a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network via the communication portion 509, and / or installed from a removable medium 511. When the computer program is executed by the central processing unit (CPU) 501, the various functions defined in the system of the present application are executed.

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

[0212] The flowcharts and block diagrams in the accompanying drawings illustrate the possible implementation architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present application. Among them, each box in the flowchart or block diagram can represent a module, program segment, or part of the code, and the above-mentioned module, program segment, or part of the code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in an order different from that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flowchart, and the combination of boxes in the block diagram or flowchart, can be implemented with a dedicated hardware-based system that performs the specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0213] The units involved in the embodiments described in this application may be implemented by software or hardware, and the units described may also be set in a processor. In some cases, the names of these units do not constitute limitations on the units themselves.

[0214] As another aspect, the present application further provides a computer program product or computer program, comprising 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 method for selecting one of three active power signals of a hydro-generator set as described in the above-described embodiment.

[0215] As another aspect, the present application also provides a computer-readable medium, which may be included in the electronic device described in the above embodiments, or may exist independently and not incorporated into the electronic device. The computer-readable medium carries one or more programs, which, when executed by the electronic device, enable the electronic device to implement the method for selecting one of three active power signals of a hydro-turbine generator set described in the above embodiments.

[0216] It should be noted that, although several modules or units of the device for action execution are mentioned in the above detailed description, this division is not mandatory. In fact, according to the embodiment of the application, the features and functions of two or more modules or units described above can be concretized in one module or unit. On the contrary, the features and functions of one module or unit described above can be further divided into multiple modules or units to be concretized.

[0217] Through the description of the above embodiments, it is easy for those skilled in the art to understand that the example embodiments described herein can be implemented by software or by combining software with necessary hardware. Therefore, the technical solution according to the embodiments of the present application can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, and includes several instructions to enable a computing device (which can be a personal computer, a server, a touch terminal, or a network device, etc.) to execute the method according to the embodiments of the present application.

[0218] Those skilled in the art will readily appreciate other embodiments of the present application after considering the specification and practicing the embodiments disclosed herein. This application is intended to cover any variations, uses, or adaptations of the present application that follow the general principles of the present application and include common knowledge or customary techniques in the art that are not disclosed in this application. 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 the scope thereof. The scope of this application is limited only by the appended claims.

Claims

1. A method for selecting one of three active power signals of a hydro-generator set, characterized in that: include: Obtain three groups of active power data, Y1, Y2, and Y3; Based on the channel quality of active power acquisition data, the optimal active power is determined, including: When the channel quality of the three sets of active power acquisition data are 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 value deviation of each set of active power acquisition data; When the channel quality of at least two groups of active power acquisition data is normal, the optimal active power is determined based on the active power deviation between any two groups of active power acquisition data and the average value deviation of each group of active power acquisition data; When the channel quality of at least one set of active power acquisition data is normal, the optimal active power is determined based on the channel quality of the active power acquisition data; When the channel qualities of the three groups of active power acquisition data are all normal, the optimal active power is determined according to the active power deviation between any two groups of active power acquisition data and the average value deviation of each group of active power acquisition data, including: When the channel quality of the three groups of active power acquisition data are all normal, the active power deviation between any two groups is calculated to obtain the first active power deviation, the second active power deviation and the third active power deviation; Performing 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 calculating the average value deviation under different judgment results based on different judgment results; Comparing the average value deviations to obtain the optimal active power; When the channel quality of at least two groups of active power acquisition data is normal, determining the optimal active power according to the active power deviation between any two groups of active power acquisition data and the average value deviation of each group of active power acquisition data includes: When the channel quality of at least two groups of active power acquisition data are all normal, the active power deviation between any two groups is calculated to obtain a fourth active power deviation, a fifth active power deviation, and a sixth active power deviation; Performing 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 calculating the average value deviation under different judgment results based on different judgment results; The optimal active power is obtained by comparing the deviations from the average values.

2. The method according to claim 1, characterized in that The judging based on the first active power deviation, the second active power deviation, the third active power deviation and the active power deviation threshold, and respectively calculating the average value deviation under different judgment results based on different judgment results, include: 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, calculating the first type average value deviation of the active power collection data Y1, the first type average value deviation of the active power collection data Y2, and the first type average value deviation of the active power collection data Y3; 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, calculating the second type of average value deviation of the active power collection data Y2 and the second type of average value deviation of the active power collection 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, calculating the second type of average value deviation of the active power collection data Y1 and the third type of average value deviation of the active power collection 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, the third type of average value deviation of the active power acquisition data Y1 and the third type of average value deviation of the active power acquisition data Y3 are calculated.

3. The method according to claim 2, characterized in that The comparing based on the average value 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 smaller than the active power deviation threshold, comparing the first type average value deviation of the active power acquisition data Y1, the first type average value deviation of the active power acquisition data Y2, and the first type average value deviation of the active power acquisition data Y3, and taking the active power acquisition data corresponding to the smallest average value deviation 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, a comparison is performed based on the second type of average value deviation of the active power collection data Y2 and the second type of average value deviation of the active power collection data Y3, and the active power collection data corresponding to the smallest average value deviation is taken as the optimal active power; 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, a comparison is performed based on the second type of average value deviation of the active power collection data Y1 and the third type of average value deviation of the active power collection data Y2, and the active power collection data corresponding to the smallest average value deviation is taken as the optimal active power; 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 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, a size comparison is performed based on the third category average value deviation of the active power acquisition data Y1 and the third category average value deviation of the active power acquisition data Y3, and the active power acquisition data corresponding to the smallest average value deviation is taken as the optimal active power.

4. The method according to claim 1, wherein The judging based on the fourth active power deviation, the fifth active power deviation, the sixth active power deviation and the active power deviation threshold, and respectively calculating the average value deviation under different judgment results based on different judgment results, include: When the sixth active power deviation is less than the active power deviation threshold, calculating the second type average value deviation of the active power collection data Y2 and the second type average value deviation of the active power collection data Y3; When the fifth active power deviation is less than the active power deviation threshold, calculating the third type average value deviation of the active power collection data Y1 and the third type average value deviation of the active power collection data Y3; When the fourth active power deviation is less than the active power deviation threshold, the second type average value deviation of the active power collection data Y1 and the third type average value deviation of the active power collection data Y2 are calculated.

5. The method according to claim 4, characterized in that The comparing based on the average value deviation to obtain the optimal active power includes: When the sixth active power deviation is less than the active power deviation threshold, comparing the second type of average value deviation of the active power acquisition data Y2 and the second type of average value deviation of the active power acquisition data Y3, and taking the active power acquisition data corresponding to the smallest average value deviation as the optimal active power; When the fifth active power deviation is less than the active power deviation threshold, comparing the third type average value deviation of the active power acquisition data Y1 and the third type average value deviation of the active power acquisition data Y3, and taking the active power acquisition data corresponding to the smallest average value deviation as the optimal active power; When the fourth active power deviation is smaller than the active power deviation threshold, a size comparison is performed based on the second type of average value deviation of the active power acquisition data Y1 and the third type of average value deviation of the active power acquisition data Y2, and the active power acquisition data corresponding to the smallest average value deviation is taken as the optimal active power.

6. A device for selecting one out of three active power signals of a hydro-generator set, applied to the method according to any one of claims 1 to 5, characterized in that: include: The acquisition unit is used to obtain three groups of active power acquisition data, namely Y1, Y2 and Y3; A confirmation unit, configured to confirm the optimal active power based on the channel quality of the active power acquisition data; Wherein, the confirmation unit includes: The first confirmation subunit is configured to, when the channel qualities of the three groups of active power acquisition data are all normal, determine the optimal active power based on the active power deviation between any two groups of active power acquisition data and the average value deviation of each group of active power acquisition data; The second confirmation subunit is configured to, when the channel quality of at least two groups of active power acquisition data is normal, confirm the optimal active power according to the active power deviation between any two groups of active power acquisition data and the average value deviation of each group of active power acquisition data; The third confirmation subunit is configured to confirm the optimal active power based on the channel quality of the active power collection data when the channel quality of at least one group of active power collection data is normal.

7. A computer-readable storage medium, characterized in that The storage medium stores computer instructions, which, when executed on a computer, enable the computer to execute the method according to any one of claims 1 to 5.

8. An electronic device, characterized in that: include: memory and processor; The memory is used to store computer instructions; The processor is configured to call the computer instructions stored in the memory so that the electronic device executes the method according to any one of claims 1 to 5.

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