Energy-saving optimization method and system for power distribution switch control equipment based on data fusion

Abstract

The present application relates to the technical field of equipment energy-saving control, and particularly relates to a power distribution switch control equipment energy-saving optimization method and system based on data fusion, which imports control record data and equipment parameter data of control equipment into an equipment control difficulty analysis model to analyze the control difficulty of the control equipment; imports switch operation data and current operation state data of the power distribution switch into an operation stability analysis model to analyze the operation stability of the power distribution switch; constructs an equipment energy-saving benefit evaluation model, imports the control difficulty analysis result of the control equipment and the operation stability analysis result of the power distribution switch into the equipment energy-saving benefit evaluation model to evaluate the energy-saving benefit of the control equipment; and adjusts the energy-saving mode according to the energy-saving benefit evaluation result of the control equipment. The energy-saving mode parameters can be accurately and dynamically optimized, the energy-saving and equipment operation can be balanced, and the adaptability and energy-saving effect of the energy-saving mode can be improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of device energy-saving control, and particularly relates to a power distribution switch control device energy-saving optimization method and system based on data fusion. BACKGROUND

[0002] In the operation process of a power distribution system, reasonable adaptation of an energy-saving mode is crucial for device energy efficiency and safety. Among them, the power distribution switch control device, as a key node in the power distribution link and energy-saving regulation process, its running state will be affected by multiple factors. Under different energy-saving modes, the triggering conditions and execution timing of control operation instructions such as start-stop, power regulation, etc. of the power distribution switch control device are significantly different, thereby affecting the running state of the power distribution switch control device; in terms of control operation frequency, the frequency of opening and closing of the power distribution switch and the fluctuation of the duration of continuous operation are greatly different between peak load period and valley period, high-frequency control operation will accelerate the mechanical wear and electrical aging of the device, and low-frequency operation may also accumulate hidden faults due to long-term device standby, which will further affect the running state of the power distribution switch control device; at the same time, multiple loss forms such as Joule heat loss, hysteresis loss, and eddy current loss also dynamically change with the running condition and affect the running state of the power distribution switch control device at any time. These factors are intertwined and interact with each other, so that the running state of the power distribution switch control device under the action of multiple factors has serious energy efficiency problems. Therefore, to improve the energy efficiency of the power distribution switch control device, through fine energy-saving mode regulation, while meeting the demand for power supply, the device energy consumption and operation and maintenance cost are reduced to the greatest extent, which has become the research focus of the prior art.

[0003] However, the prior art only focuses on the number of operations or simple timing when optimizing the energy-saving of the power distribution switch control device, ignores the disorder of control operation type distribution, control frequency fluctuation, and the complex influence of manual and automatic control on control device control difficulty and control device energy-saving optimization, and fails to effectively fuse the synergistic effect of control behavior interference and device inherent loss. Further, the energy-saving mode and the actual running demand are poorly adapted, which cannot realize optimal energy-saving benefits while ensuring device stability, thereby threatening the energy-saving upgrade and safe operation of the power distribution system.

[0004] In order to solve these problems, the present application designs a power distribution switch control device energy-saving optimization method and system based on data fusion. SUMMARY

[0005] In order to overcome the defects and deficiencies existing in the prior art, the application provides an energy-saving optimization method and system for a power distribution switch control device based on data fusion, which comprehensively analyzes the control difficulty of the control device and the operation stability of the power distribution switch, realizes accurate evaluation of the energy-saving benefit of the control device, and adjusts and optimizes the energy-saving mode according to the energy-saving benefit evaluation result of the control device. The energy-saving mode parameters can be accurately and dynamically optimized, the energy saving and device operation are balanced, and the adaptability and energy-saving effect of the energy-saving mode are improved.

[0006] In order to achieve the above purpose, the application adopts the following technical solutions:

[0007] In the first aspect, the application embodiment provides an energy-saving optimization method for a power distribution switch control device based on data fusion, which comprises the following steps:

[0008] S1, obtaining switch operation data and current operation state data of the power distribution switch, and obtaining control record data and device parameter data of the control device;

[0009] S2, importing the control record data and the device parameter data of the control device into a device control difficulty analysis model to analyze the control difficulty of the control device;

[0010] S3, importing the switch operation data and the current operation state data of the power distribution switch into an operation stability analysis model to analyze the operation stability of the power distribution switch;

[0011] S4, constructing a control device energy-saving benefit evaluation model, importing the control difficulty analysis result of the control device and the operation stability analysis result of the power distribution switch into the control device energy-saving benefit evaluation model, and evaluating the energy-saving benefit of the control device;

[0012] S5, adjusting the energy-saving mode according to the energy-saving benefit evaluation result of the control device.

[0013] In the preferred technical solution of the application, the control difficulty of the control device is analyzed in step S2, which comprises the following specific steps:

[0014] S21, extracting the control record data and the device parameter data of the control device under the current energy-saving mode;

[0015] S22, constructing a device control difficulty analysis model based on the control record data and the device parameter data of the control device under the current energy-saving mode, analyzing the control difficulty of the control device under the current energy-saving mode, and obtaining the control difficulty analysis result of the control device under the current energy-saving mode;

[0016] The control difficulty calculation formula is:

[0017] ;

[0018] In the formula, Kn is the control difficulty of the control device in the current energy-saving mode, fz is the control operation complexity analysis result of the control device in the current energy-saving mode, fb is the control frequency fluctuation level analysis result of the control device in the current energy-saving mode, ps is the manual control times of the control device in the current energy-saving mode, and pt is the total control times of the control device in the current energy-saving mode.

[0019] In the preferred technical scheme of the present application, the construction process of the device control difficulty analysis model in step S22 comprises the following specific steps:

[0020] S221, based on the control record data and the device parameter data of the control device in the current energy-saving mode, the control operation complexity of the control device in the current energy-saving mode is analyzed to obtain the control operation complexity analysis result of the control device in the current energy-saving mode;

[0021] S222, based on the control record data of the control device in the current energy-saving mode, the control frequency fluctuation level of the control device in the current energy-saving mode is analyzed to obtain the control frequency fluctuation level analysis result of the control device in the current energy-saving mode.

[0022] In the preferred technical scheme of the present application, the analysis of the operation stability of the power distribution switch in step S3 comprises the following specific steps:

[0023] S31, the switch operation data and the current running state data of the power distribution switch in the current energy-saving mode are extracted;

[0024] S32, based on the switch operation data and the current running state data of the power distribution switch in the current energy-saving mode, an operation stability analysis model is constructed to analyze the operation stability of the power distribution switch in the current energy-saving mode, and the operation stability analysis result of the power distribution switch in the current energy-saving mode is obtained;

[0025] In the formula, Yw is the operation stability of the power distribution switch in the current energy-saving mode, gr is the control behavior interference degree analysis result of the control device generated in the running process of the power distribution switch in the current energy-saving mode, and sh is the running loss degree analysis result of the power distribution switch in the current energy-saving mode.

[0026] ;

[0027] In the formula, Yw is the operation stability of the power distribution switch in the current energy-saving mode, gr is the control behavior interference degree analysis result of the control device generated in the running process of the power distribution switch in the current energy-saving mode, and sh is the running loss degree analysis result of the power distribution switch in the current energy-saving mode.

[0028] In the preferred technical scheme of the present application, the construction process of the operation stability analysis model in step S32 comprises the following specific steps:

[0029] S321, based on the switch operation data and the current operation state data of the power distribution switch in the current energy-saving mode, analyze the interference degree of the control action of the control device in the running process of the power distribution switch in the current energy-saving mode, and obtain the interference degree analysis result of the control action of the control device in the running process of the power distribution switch in the current energy-saving mode.

[0030] S322, based on the switch operation data and the current operation state data of the power distribution switch in the current energy-saving mode, analyze the interference degree of the control action of the control device in the running process of the power distribution switch in the current energy-saving mode, and obtain the interference degree analysis result of the control action of the control device in the running process of the power distribution switch in the current energy-saving mode.

[0031] In the preferred technical scheme of the present application, the control device energy-saving benefit evaluation model is constructed in step S4, which comprises the following specific steps:

[0032] S41, extract the control difficulty degree analysis result of the control device in the current energy-saving mode and the running stability analysis result of the power distribution switch;

[0033] S42, according to the control difficulty degree analysis result of the control device in the current energy-saving mode and the running stability analysis result of the power distribution switch, evaluate the energy-saving benefit of the control device in the current energy-saving mode;

[0034] The evaluation formula of the energy-saving benefit of the control device is:

[0035] ;

[0036] In the formula, NX is the energy-saving benefit of the control device in the current energy-saving mode, Kn is the control difficulty degree analysis result of the control device in the current energy-saving mode, and Yw is the running stability analysis result of the power distribution switch in the current energy-saving mode.

[0037] In the preferred technical scheme of the present application, the control device energy-saving benefit evaluation result is obtained in step S5, which comprises the following specific steps:

[0038] S51, obtain the energy-saving benefit evaluation result of the control device in all energy-saving modes;

[0039] S52, obtain the energy-saving benefit evaluation result of the control device in all energy-saving modes; when the energy-saving benefit evaluation result of the control device in the energy-saving mode is the largest, the energy-saving mode corresponding to the largest energy-saving benefit evaluation result is taken as the optimal energy-saving mode, and the energy-saving mode of the power distribution switch control device is adjusted to the optimal energy-saving mode.

[0040] Secondly, the present application also provides a power distribution switch control device energy-saving optimization system based on data fusion, which comprises:

[0041] A data acquisition module is configured to acquire switch operation data and current operation state data of the power distribution switch, and acquire control record data and device parameter data of the control device;

[0042] A control difficulty analysis module is configured to import the control record data and the device parameter data of the control device into a device control difficulty analysis model, and analyze the control difficulty of the control device;

[0043] An operation stability analysis module is configured to import the switch operation data and the current operation state data of the power distribution switch into an operation stability analysis model, and analyze the operation stability of the power distribution switch;

[0044] An energy saving benefit evaluation module is configured to construct a control device energy saving benefit evaluation model, import the control difficulty analysis result of the control device and the operation stability analysis result of the power distribution switch into the control device energy saving benefit evaluation model, and evaluate the energy saving benefit of the control device;

[0045] An energy saving mode adjustment module is configured to adjust the energy saving mode according to the energy saving benefit evaluation result of the control device;

[0046] A control module is configured to control the operation of the data acquisition module, the control difficulty analysis module, the operation stability analysis module, the energy saving benefit evaluation module and the energy saving mode adjustment module.

[0047] Compared with the prior art, the present application has the following advantages and beneficial effects:

[0048] The control record data and the device parameter data of the control device are imported into the device control difficulty analysis model to analyze the control difficulty of the control device; the switch operation data and the current operation state data of the power distribution switch are imported into the operation stability analysis model to analyze the operation stability of the power distribution switch; the control device energy saving benefit evaluation model is constructed, the control difficulty analysis result of the control device and the operation stability analysis result of the power distribution switch are imported into the control device energy saving benefit evaluation model to evaluate the energy saving benefit of the control device; and the energy saving mode is adjusted according to the energy saving benefit evaluation result of the control device. The energy saving mode parameters can be accurately and dynamically optimized, the energy saving and the device operation can be balanced, and the adaptability and the energy saving effect of the energy saving mode can be improved. BRIEF DESCRIPTION OF DRAWINGS

[0049] Other features, objects and advantages of the present application will become more apparent from the following detailed description of non-limiting embodiments with reference to the attached drawings:

[0050] Figure 1 FIG. 1 is a schematic diagram of the overall process of the power distribution switch control device energy saving optimization method based on data fusion of the present application;

[0051] Figure 2 Workflow diagram for step S2 in the power distribution switch control device energy-saving optimization method based on data fusion of the present application;

[0052] Figure 3 Workflow diagram for step S3 in the power distribution switch control device energy-saving optimization method based on data fusion of the present application;

[0053] Figure 4 Structural schematic diagram of the power distribution switch control device energy-saving optimization system based on data fusion of the present application. DETAILED DESCRIPTION

[0054] The technical solutions of the present application will be described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the embodiments and specific features in the embodiments are detailed descriptions of the technical solutions of the present application, and not limitations of the technical solutions of the present application. In the case of no conflict, the technical features in the embodiments and the embodiments can be combined with each other.

[0055] Embodiment 1:

[0056] As shown in the figure, the embodiment provides a power distribution switch control device energy-saving optimization method based on data fusion, which specifically includes the following steps: Figure 1

[0057] S1, obtaining switch operation data and current operation state data of the power distribution switch, and obtaining control record data and device parameter data of the control device;

[0058] S2, importing the control record data and the device parameter data of the control device into a device control difficulty analysis model to analyze the control difficulty of the control device;

[0059] S3, importing the switch operation data and the current operation state data of the power distribution switch into a running stability analysis model to analyze the running stability of the power distribution switch;

[0060] S4, constructing a control device energy-saving benefit evaluation model, importing the control difficulty analysis result of the control device and the running stability analysis result of the power distribution switch into the control device energy-saving benefit evaluation model, and evaluating the energy-saving benefit of the control device;

[0061] S5, adjusting the energy-saving mode according to the energy-saving benefit evaluation result of the control device.

[0062] In this embodiment, as shown in the figure, the control difficulty of the control device is analyzed in step S2, which includes the following specific steps: Figure 2

[0063] ​​S21. Extract the control record data and equipment parameter data of the controlled equipment under the current energy-saving mode;

[0064] S22. Based on the control record data and equipment parameter data of the control equipment under the current energy-saving mode, construct an analysis model for the degree of difficulty in controlling the equipment, analyze the degree of difficulty in controlling the equipment under the current energy-saving mode, and obtain the analysis results of the degree of difficulty in controlling the equipment under the current energy-saving mode.

[0065] The formula for calculating the degree of difficulty in control is as follows:

[0066] ;

[0067] In the formula, Kn represents the degree of difficulty in controlling the device under the current energy-saving mode, fz represents the analysis result of the complexity of the control operation of the device under the current energy-saving mode, fb represents the analysis result of the control frequency fluctuation level of the device under the current energy-saving mode, ps represents the number of manual control operations of the device under the current energy-saving mode, and pt represents the total number of control operations of the device under the current energy-saving mode.

[0068] For example, this embodiment comprehensively considers the impact of control operation complexity and control frequency fluctuation level on the degree of control difficulty, and introduces the proportion of manual control to modify the calculation formula for control difficulty. Different operation types and execution time deviations determine the complexity of the control logic, which is the basis for measuring control difficulty. Therefore, this embodiment introduces fz as a parameter in the calculation formula to reflect the impact of control operation complexity on control difficulty. The stability of the control frequency is related to the operating rhythm of the control equipment; large fluctuations in the control frequency increase the control difficulty of the equipment. Therefore, this embodiment introduces fb to reflect the impact of control frequency fluctuation level on control difficulty. Furthermore, this embodiment adopts... This method calculates the synergistic effect of normalized control operation complexity and control frequency fluctuation level, accurately reflecting their combined contribution to the control difficulty. It avoids a single factor dominating the calculation results, ensuring adaptability of control operation complexity and control frequency fluctuation level across different magnitudes. Furthermore, it makes the calculation results more consistent with the difficulty judgment logic of multi-factor coupling in actual control operation scenarios. Specifically, this embodiment introduces the ratio of manual control counts to total control counts to reflect the impact of human intervention on control difficulty. In this embodiment, a high proportion of manual operation means that the control logic of the control equipment is more difficult to automate and more complex to coordinate. Using the ratio of manual control counts to total control counts as a correction term further refines the assessment of control difficulty, thereby comprehensively and accurately quantifying the control difficulty of the control equipment under the current energy-saving mode.

[0069] In the embodiment, the process of constructing the device control difficulty analysis model in step S22 includes the following specific steps:

[0070] S221, based on the control record data and the device parameter data of the control device in the current energy-saving mode, analyzing the control operation complexity of the control device in the current energy-saving mode, and obtaining the control operation complexity analysis result of the control device in the current energy-saving mode;

[0071] The control operation complexity calculation formula is:

[0072] ;

[0073] In the formula, fz is the control operation complexity of the control device in the current energy-saving mode, n is the number of control operation types of the control device in the current energy-saving mode in the device parameter data, pi is the ratio of the number of the i-th control operation of the control device in the current energy-saving mode in the control record data to the total number of control operations, tci is the difference between the average execution time of the i-th control operation of the control device in the current energy-saving mode in the control record data and the design standard time, and stc is the standard deviation of the execution time of all control operations of the control device in the current energy-saving mode in the control record data.

[0074] For example, the embodiment analyzes the control operation complexity from two dimensions of operation type distribution and operation time deviation. By introducing information entropy The operation type distribution is calculated, and pi is the ratio of the number of the i-th control operation, and the greater the entropy value, the more dispersed and disordered the control operation type distribution, which can reflect the complexity of the control operation in the control operation type level. Further, the embodiment divides by The entropy value is normalized, which can make the entropy values under different control operation types comparable and make the result in the interval of 0 to 1, so as to facilitate subsequent combined analysis with other factors. is the sum of the differences between the average execution time of each operation and the design standard time, which can reflect the cumulative influence of the operation time deviation, and stc is the standard deviation of the execution time of all operations, which can reflect the dispersion degree of the execution time fluctuation, is the quantification of the influence of the time deviation fluctuation, and by multiplying 1 and the operation type distribution item , the influence of the time deviation can be integrated into the calculation of the overall control operation complexity, which can reflect that the greater the execution time deviation, the more significant the relative fluctuation, and the stronger the amplification effect on the control operation complexity. Using information entropy The disorder of discrete events can be effectively described, thereby satisfying the quantification of the complexity of the operation type distribution; the time length deviation is introduced to reflect the actual working condition that the deviation of the operation execution time length from the design standard increases the control difficulty, and the complexity of the control operation is reflected by comprehensively analyzing the complexity of the operation type distribution and the fluctuation of the time length deviation, which can comprehensively cover the complexity factors of the control operation in the type distribution and the time sequence execution, and accurately quantize the complexity of the control operation.

[0075] S222, based on the control record data of the control device in the current energy saving mode, analyzing the control frequency fluctuation level of the control device in the current energy saving mode to obtain a control frequency fluctuation level analysis result of the control device in the current energy saving mode;

[0076] The control frequency fluctuation level calculation formula is:

[0077]

[0078] In the formula, fb is the control frequency fluctuation level of the control device in the current energy saving mode, M is the number of historical running cycles of the control device in the current energy saving mode in the control record data, fm is the control frequency in the mth historical running cycle of the control device in the current energy saving mode in the control record data, is the average value of the control frequency in all historical running cycles of the control device in the current energy saving mode in the control record data, fmax and fmin are the maximum value and the minimum value of the control frequency in all historical running cycles of the control device in the current energy saving mode in the control record data, respectively.

[0079] Exemplarily, the embodiment analyzes the control frequency fluctuation level from the discrete degree and the extreme value difference of the frequency. is the coefficient of variation of the control frequency, which can eliminate the influence of different control frequency averages, thereby accurately reflecting the discrete fluctuation degree of the control frequency around the average value and reflecting the stability of the control frequency. Further, the embodiment introduces the hyperbolic tangent function to describe the influence of the relative average value of the frequency extreme value difference, the larger the extreme value difference is, the closer the function value is to 1, and the more obvious the amplification effect on the control frequency fluctuation level is. Therefore, the embodiment considers that the maximum and minimum value difference of the control frequency in the actual control will significantly affect the running rhythm and coordination difficulty of the control device, and therefore, the influence of the maximum and minimum value difference of the control frequency based on the nonlinear characteristics of the hyperbolic tangent function is reasonably reflected. Meanwhile, dividing by is normalized, so that the control frequency fluctuation with different averages is comparable, thereby achieving accurate quantization of the regular fluctuation and extreme difference of the control frequency, and realizing accurate calculation of the influence of the control frequency fluctuation level on the control difficulty.

[0080] In the embodiment, as​Figure 3 As shown, the operation stability of the power distribution switch in step S3 is analyzed, including the following specific steps:

[0081] S31, extract the switch operation data and current operating state data of the power distribution switch under the current energy saving mode;

[0082] S32, based on the switch operation data and current operating state data of the power distribution switch under the current energy saving mode, construct an operation stability analysis model, analyze the operation stability of the power distribution switch under the current energy saving mode, and obtain the operation stability analysis result of the power distribution switch under the current energy saving mode;

[0083] Wherein, the operation stability calculation formula of the power distribution switch is:

[0084]

[0085] In the formula, Yw is the operation stability of the power distribution switch under the current energy saving mode, gr is the control behavior interference degree analysis result of the control device generated in the operation process of the power distribution switch under the current energy saving mode, and sh is the operation loss degree analysis result of the power distribution switch under the current energy saving mode.

[0086] Exemplarily, the embodiment evaluates the operation stability of the power distribution switch based on the control behavior interference degree and the operation loss degree. The embodiment takes the sum of the control behavior interference degree and the operation loss degree as an exponential term after taking negative, and calculates the operation stability of the power distribution switch, which can reflect that the greater the control behavior interference and the more the operation loss, the lower the operation stability: the control behavior interference degree and the operation loss degree will destroy the stable operation state of the power distribution switch in actual working conditions. The embodiment uses exponential function, which can effectively distinguish the difference of the operation stability of the power distribution switch under different interference and loss degree, and when the interference and loss are small, the operation stability of the power distribution switch rises rapidly and tends to 1; when the interference and loss are large, the operation stability of the power distribution switch decreases sharply and tends to 0, which can meet the law of the operation stability of the power distribution switch changing with the interference and loss, so as to intuitively and accurately quantify the operation stability of the power distribution switch under the current energy saving mode.

[0087] In the embodiment, the construction process of the operation stability analysis model in step S32 includes the following specific steps:

[0088] S321, based on the switch operation data and current operating state data of the power distribution switch under the current energy saving mode, analyze the control behavior interference degree generated by the control device in the operation process of the power distribution switch under the current energy saving mode, and obtain the control behavior interference degree analysis result of the control device generated in the operation process of the power distribution switch under the current energy saving mode;

[0089] ​Wherein, the control behavior interference degree calculation formula is:

[0090] ;

[0091] In the formula, gr is the control behavior interference degree of the control device in the operation process of the power distribution switch in the current energy-saving mode, sf is the standard deviation of the control frequency of the control device in all historical operation cycles in the current energy-saving mode, T is the total duration of all historical operation cycles of the control device of the power distribution switch in the current energy-saving mode in the switch operation data, u is the rated voltage value of the power distribution switch end in the switch operation data, and ut is the real-time voltage value of the power distribution switch end in all historical operation cycles in the current energy-saving mode in the current operation state data.

[0092] For example, the embodiment comprehensively analyzes the influence of control frequency and voltage fluctuation on the control behavior interference degree. The average control frequency is used to reflect the average rhythm of the control behavior, the frequency fluctuation degree is reflected by the control frequency standard deviation, and the voltage fluctuation degree is reflected by The control frequency stability is quantified, and the more stable the control frequency is, the greater the interference degree is, which means that the control behavior is more stable. Further, the embodiment also analyzes the control behavior interference degree combined with the voltage fluctuation. When the voltage fluctuation is large, the interference degree will also increase. Among them, is the time integral of the voltage deviation, which is used to measure the cumulative influence of the voltage fluctuation, and the voltage relative fluctuation level is quantified by dividing the product of the time and the rated voltage. Based on the above content, the embodiment combines the control frequency characteristics and the voltage fluctuation characteristics in the form of product, which can reflect that the control behavior of the control device will interfere with the operation of the power distribution switch by affecting parameters such as voltage, and the frequency instability and large voltage fluctuation will increase the interference degree, so as to accurately quantify the interference degree of the control behavior on the operation of the power distribution switch.

[0093] S322, based on the switch operation data and the current operation state data of the power distribution switch in the current energy-saving mode, analyzing the operation loss degree of the power distribution switch in the current energy-saving mode, and obtaining the operation loss degree analysis result of the power distribution switch in the current energy-saving mode;

[0094] Wherein, the operation loss degree calculation formula is:

[0095] ;

[0096] In the formula, sh is the operation loss degree of the power distribution switch in the current energy-saving mode, M is the number of historical operation cycles of the control device in the current energy-saving mode, is the average carrying current value of the power distribution switch in the mth historical operation cycle in the current energy-saving mode in the current operation state data, is the average value of the contact resistance of the power distribution switch in all historical running periods in the current energy-saving mode in the current running state data, Pe is the rated loss power of the power distribution switch terminal in the switch running data, Ty is the average running temperature of the internal conductive loop of the power distribution switch in all historical running periods in the current energy-saving mode in the current running state data, and Tmax is the maximum value of the safe running temperature of the internal conductive loop of the power distribution switch in the switch running data.

[0097] Exemplarily, the embodiment analyzes the running loss degree of the power distribution switch in the current energy-saving mode from three dimensions of current, resistance and temperature. The current heat loss is the core of the running loss of the power distribution switch. Based on the Joule's law, the embodiment adopts The current heat loss reflects the cumulative degree of the running loss of the power distribution switch. By summing a plurality of running periods and dividing the product of M and the rated loss power, the loss is normalized and averaged, so that the running loss degree calculation result can reflect the average loss degree relative to the rated loss in different running periods. Further, temperature rise accelerates equipment aging and increases loss. The embodiment introduces , which can reflect the influence of temperature on the running loss. The higher the temperature, the closer to the safe maximum value, the faster the running loss degree of the power distribution switch. Based on the above, the embodiment can comprehensively quantify the running loss degree of the power distribution switch in the current energy-saving mode.

[0098] In the embodiment, the control device energy-saving benefit evaluation model is constructed in step S4, including the following specific steps:

[0099] S41, extracting the control difficulty analysis result of the control device in the current energy-saving mode and the running stability analysis result of the power distribution switch obtained by analysis;

[0100] S42, according to the control difficulty analysis result of the control device in the current energy-saving mode and the running stability analysis result of the power distribution switch, evaluating the energy-saving benefit of the control device in the current energy-saving mode;

[0101] The evaluation formula of the energy-saving benefit of the control device is:

[0102] ;

[0103] In the formula, NX is the energy-saving benefit of the control device in the current energy-saving mode, Kn is the control difficulty analysis result of the control device in the current energy-saving mode, and Yw is the running stability analysis result of the power distribution switch in the current energy-saving mode.

[0104] Exemplarily, the embodiment evaluates the energy saving benefit by the ratio of the running stability and the control difficulty degree, and in combination with the hyperbolic tangent function. The output value of the hyperbolic tangent function can be controlled between -1 and 1, and in the embodiment, since the running stability and the control difficulty degree are both non-negative values, the calculation result of the energy saving benefit can be between 0 and 1, and the greater the calculation result is, the better the energy saving benefit is. The ratio of the running stability and the control difficulty degree reflects the trade-off between the running stability and the control difficulty degree when the embodiment evaluates the energy saving benefit, and when the running stability is high and the control difficulty degree is low, the ratio is large, and the energy saving benefit is good; otherwise, the energy saving benefit is poor. The embodiment selects the hyperbolic tangent function, which can map the ratios of different orders of magnitude to a reasonable interval by using the nonlinear compression characteristics of the input, so as to highlight the difference of the energy saving benefit under different energy saving modes, and at the same time, avoid the excessive influence of extreme values on the energy saving benefit, so as to simply and effectively evaluate the energy saving benefit of the control device under the current energy saving mode, and reflect the comprehensive benefit of the energy saving mode in ensuring the running stability while controlling the difficulty.

[0105] In the embodiment, the energy saving mode is adjusted according to the energy saving benefit evaluation result of the control device in step S5, including the following specific steps:

[0106] S51, obtaining the energy saving benefit evaluation result of the control device under all energy saving modes;

[0107] S52, obtaining the energy saving mode corresponding to the maximum energy saving benefit evaluation result of the control device in the energy saving benefit evaluation result of the control device under all energy saving modes as the optimal energy saving mode, and adjusting the energy saving mode of the power distribution switch control device to the optimal energy saving mode.

[0108] Embodiment 2:

[0109] As shown in Figure 4 , the embodiment provides a power distribution switch control device energy saving optimization system based on data fusion, which comprises:

[0110] a data acquisition module for acquiring switch running data and current running state data of the power distribution switch, and control record data and device parameter data of the control device;

[0111] a control difficulty degree analysis module for importing the control record data and the device parameter data of the control device into a device control difficulty degree analysis model to analyze the control difficulty degree of the control device;

[0112] a running stability analysis module for importing the switch running data and the current running state data of the power distribution switch into a running stability analysis model to analyze the running stability of the power distribution switch;

[0113] The energy-saving benefit evaluation module is configured to build a control device energy-saving benefit evaluation model, import the control difficulty analysis result of the control device and the operation stability analysis result of the power distribution switch into the control device energy-saving benefit evaluation model, and evaluate the energy-saving benefit of the control device.

[0114] The energy-saving mode adjustment module is configured to adjust the energy-saving mode according to the energy-saving benefit evaluation result of the control device.

[0115] The control module is configured to control the operation of the data acquisition module, the control difficulty analysis module, the operation stability analysis module, the energy-saving benefit evaluation module, and the energy-saving mode adjustment module.

[0116] The steps of implementing the functions of the parameters and the unit modules in the above-mentioned data fusion-based power distribution switch control device energy-saving optimization system of the present application can refer to the parameters and steps in the above-mentioned data fusion-based power distribution switch control device energy-saving optimization method, and will not be repeated here.

[0117] Each embodiment in the present application is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other. Each embodiment mainly describes the differences from other embodiments. In particular, the Internet of Things device and medium embodiments are basically similar to the method embodiments, and thus are described simply. The relevant parts can refer to the description of the method embodiments.

[0118] The system and medium provided by the embodiments of the present application are one-to-one corresponding to the method, and thus the system and medium have similar beneficial technical effects to the method. Since the beneficial technical effects of the method have been described in detail above, the beneficial technical effects of the system and medium will not be repeated here.

[0119] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can be in the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can be in the form of a computer program product implemented on one or more computer usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer usable program code.

[0120] The computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide processes for implementing the functions specified in the flowchart block or blocks or in conjunction with the flowcharts described above. Figure 1 The computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide processes for implementing the functions specified in the flowchart block or blocks or in conjunction with the flowcharts described above. Figure 1 The computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide processes for implementing the functions specified in the flowchart block or blocks or in conjunction with the flowcharts described above.

[0121] The computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide processes for implementing the functions specified in the flowchart block or blocks or in conjunction with the flowcharts described above. Figure 1 The computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide processes for implementing the functions specified in the flowchart block or blocks or in conjunction with the flowcharts described above. Figure 1 The computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide processes for implementing the functions specified in the flowchart block or blocks or in conjunction with the flowcharts described above.

[0122] In a typical configuration, a computing device includes one or more processors (CPUs), input / output interfaces, network interfaces, and memory.

[0123] The memory can include non-persistent memory and / or volatile memory, such as random access memory (RAM) and / or cache memory, for storing instructions and data. The memory can also include non-volatile memory, such as read only memory (ROM), electrically programmable read only memory (EPROM), electrically erasable programmable read only memory (EEPROM), flash memory, or other solid state memory technology. The memory, or alternately the memory and the processor, can be one or more computer readable storage mediums.

[0124] Computer readable media includes permanent and non-permanent, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read only memory (ROM), electrically programmable read only memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), digital versatile disc (DVD), or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information accessible to a computing device. According to the definition herein, computer readable media does not include transitory media, such as modulated data signals and carrier waves.

[0125] It is also to be noted that the terms "comprising", "including", and any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but can also include other elements not expressly listed or inherent to such process, method, article, or apparatus. An element proceeded by "comprises a... " does not, without more constraints, exclude the existence of additional identical elements in the process, method, article, or apparatus that comprises the element.

[0126] The above embodiments are only used to illustrate the present application, but not to limit it. Instead of the above, various modifications and changes can be made to the application by those skilled in the art. Any modification, equivalent replacement, improvement, and the like made within the spirit and principle of the application shall fall into the scope of claims of the application.

Claims

1. A power distribution switch control device energy saving optimization method based on data fusion, characterized in that, The method comprises the following steps: S1, obtaining switch operation data and current operation state data of the power distribution switch, and obtaining control record data and device parameter data of the control device; S2, importing the control record data and the device parameter data of the control device into a device control difficulty analysis model to analyze the control difficulty of the control device; S3, importing the switch operation data and the current operation state data of the power distribution switch into a running stability analysis model to analyze the running stability of the power distribution switch; S4, constructing a control device energy-saving benefit evaluation model, importing the control difficulty analysis result of the control device and the running stability analysis result of the power distribution switch into the control device energy-saving benefit evaluation model, and evaluating the energy-saving benefit of the control device; S5, adjusting the energy-saving mode according to the energy-saving benefit evaluation result of the control device; The step S2 of analyzing the control difficulty of the control device comprises the following specific steps: S21, extracting the control record data and the device parameter data of the control device under the current energy-saving mode; S22, based on the control record data and the device parameter data of the control device under the current energy-saving mode, constructing a device control difficulty analysis model, analyzing the control difficulty of the control device under the current energy-saving mode, and obtaining the control difficulty analysis result of the control device under the current energy-saving mode; Wherein, the control difficulty calculation formula is: ； In the formula, Kn is the control difficulty of the control device under the current energy-saving mode, fz is the control operation complexity analysis result of the control device under the current energy-saving mode, fb is the control frequency fluctuation level analysis result of the control device under the current energy-saving mode, ps is the manual control times of the control device under the current energy-saving mode, and pt is the total control times of the control device under the current energy-saving mode; The step S22 of constructing the device control difficulty analysis model comprises the following specific steps: S221, based on the control record data and the device parameter data of the control device under the current energy-saving mode, analyzing the control operation complexity of the control device under the current energy-saving mode, and obtaining the control operation complexity analysis result of the control device under the current energy-saving mode; S222, based on the control record data of the control device under the current energy-saving mode, analyzing the control frequency fluctuation level of the control device under the current energy-saving mode, and obtaining the control frequency fluctuation level analysis result of the control device under the current energy-saving mode; The step S4 of constructing the control device energy-saving benefit evaluation model comprises the following specific steps: S41, extracting the control difficulty analysis result of the control device under the current energy-saving mode and the running stability analysis result of the power distribution switch; S42, according to the control difficulty analysis result of the control device under the current energy-saving mode and the running stability analysis result of the power distribution switch, evaluating the energy-saving benefit of the control device under the current energy-saving mode; Wherein, the evaluation formula of the energy-saving benefit of the control device is: ； In the formula, NX is the energy saving benefit of the control device in the current energy saving mode, Kn is the control difficulty analysis result of the control device in the current energy saving mode, and Yw is the operation stability analysis result of the power distribution switch in the current energy saving mode.

2. The data fusion based energy optimization method for control of power distribution switchgear as claimed in claim 1 wherein, The operation stability of the power distribution switch is analyzed in the step S3, including the following specific steps: S31, extracting the switch operation data and the current operation state data of the power distribution switch in the current energy saving mode; S32, based on the switch operation data and the current operation state data of the power distribution switch in the current energy saving mode, constructing an operation stability analysis model, analyzing the operation stability of the power distribution switch in the current energy saving mode, and obtaining the operation stability analysis result of the power distribution switch in the current energy saving mode; In the formula, Yw is the operation stability of the power distribution switch in the current energy saving mode, gr is the control behavior interference degree analysis result of the control device generated in the operation process of the power distribution switch in the current energy saving mode, and sh is the operation loss degree analysis result of the power distribution switch in the current energy saving mode. ； The construction process of the operation stability analysis model in the step S32 includes the following specific steps:

3. The data fusion based energy optimization method for control of power distribution switchgear as claimed in claim 2 wherein, S321, based on the switch operation data and the current operation state data of the power distribution switch in the current energy saving mode, analyzing the control behavior interference degree of the control device generated in the operation process of the power distribution switch in the current energy saving mode, and obtaining the control behavior interference degree analysis result of the control device generated in the operation process of the power distribution switch in the current energy saving mode; S322, based on the switch operation data and the current operation state data of the power distribution switch in the current energy saving mode, analyzing the operation loss degree of the power distribution switch in the current energy saving mode, and obtaining the operation loss degree analysis result of the power distribution switch in the current energy saving mode. In the step S5, the energy saving mode is adjusted according to the energy saving benefit evaluation result of the control device, including the following specific steps:

4. The data fusion based energy optimization method for control of power distribution switchgear as claimed in claim 3 wherein, S51, obtaining the energy saving benefit evaluation result of the control device in all energy saving modes; S52, obtaining the energy saving mode corresponding to the maximum energy saving benefit evaluation result of the control device in the energy saving benefit evaluation result of the control device in all energy saving modes as the optimal energy saving mode, and adjusting the energy saving mode of the power distribution switch control device to the optimal energy saving mode. The system includes:

5. The energy saving optimization system of power distribution switch control device based on data fusion according to any one of claims 1-4, characterized in that, A data acquisition module is configured to acquire the switch operation data and the current operation state data of the power distribution switch, and simultaneously acquire the control record data and the device parameter data of the control device; A control difficulty analysis module is configured to import the control record data and the device parameter data of the control device into a device control difficulty analysis model, and analyze the control difficulty of the control device; An operation stability analysis module is configured to import the switch operation data and the current operation state data of the power distribution switch into an operation stability analysis model, and analyze the operation stability of the power distribution switch; ​ The energy-saving benefit evaluation module is configured to construct an energy-saving benefit evaluation model of the control device, import the control difficulty analysis result of the control device and the operation stability analysis result of the power distribution switch into the energy-saving benefit evaluation model of the control device, and evaluate the energy-saving benefit of the control device. The energy-saving mode adjustment module is configured to adjust the energy-saving mode according to the energy-saving benefit evaluation result of the control device. The control module is configured to control the operation of the data acquisition module, the control difficulty analysis module, the operation stability analysis module, the energy-saving benefit evaluation module, and the energy-saving mode adjustment module.

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