Dynamic load change rate calculation method, system and device and readable storage medium

Abstract

The invention discloses a dynamic load change rate calculation method, system and device and a readable storage medium, and the method comprises the steps: collecting the input power and the output power of a load system, calculating the difference value between the input power and the output power, and obtaining the energy deviation caused by the transient change of a load; calculating an instantaneous load change rate based on the energy deviation caused by the transient change of the load and the dynamic time window; and performing time weighted filtering on the instantaneous load change rate to obtain a dynamic load change rate. According to the method, the problem of noise amplification caused by direct differential of the power signal is effectively avoided, and the estimation accuracy of the load change trend is improved on the premise that a complex control algorithm is not introduced.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of power load regulation, and relates to a dynamic load change rate calculation method, system, device and readable storage medium. BACKGROUND

[0002] In modern industrial control, motor drive, variable frequency compressor, power grid scheduling and many other fields, dynamic regulation of load is an important link to improve system energy efficiency and optimize operating state. The system needs to accurately calculate the load change rate so as to timely adjust the control parameters when the load increases or decreases, and improve the system response capability. The traditional load change rate calculation method mainly relies on differential operation, that is, the load change rate is estimated by deriving the power, current or torque signal. However, since the load signal often contains a large amount of high-frequency noise, this differential calculation method is very sensitive to short-time power fluctuations, is easily disturbed and amplifies noise, resulting in sharp fluctuations in the calculated change rate, thereby affecting the stability and control accuracy of the system, and causing the control system to be misregulated.

[0003] In order to suppress high-frequency noise, the prior art usually adopts low-pass filtering or fixed sliding mean filtering to reduce calculation error. However, these methods introduce additional calculation lag, which causes the system to be unable to quickly respond to the real change of the load. In addition, the filtering method with a fixed window is difficult to adapt to the dynamic demand under different load change conditions, and may cause excessive calculation when the load is smooth, and may be slow to react when the load is suddenly changed, resulting in that the calculated load change rate still has a large error in some cases. Therefore, how to accurately estimate the load change rate without relying on traditional differential calculation, while avoiding the influence of high-frequency noise, has become a technical problem to be solved. SUMMARY

[0004] To solve the problems in the prior art, the present application provides a dynamic load change rate calculation method, system, device and readable storage medium, which effectively avoids the problem of amplifying noise caused by directly differentiating the power signal through the coordinated design of power deviation, time weighted filtering smoothing and adaptive dynamic time window, improves the estimation accuracy of the load change trend without introducing complex control algorithms, and can be widely applied to intelligent control of variable frequency compressors, load prediction of power grids, variable frequency control of industrial motors and many other fields, thereby providing a more stable, accurate and efficient load estimation method for intelligent control systems, and improving the overall control accuracy and economic efficiency of system operation.

[0005] The present application adopts the following technical solutions.

[0006] The first aspect of the present application provides a dynamic load change rate calculation method, comprising:

[0007] The input power and output power of the load system are collected, and the difference between the input power and the output power is calculated to obtain an energy deviation caused by load transient change;

[0008] The instantaneous load change rate is calculated based on the energy deviation caused by load transient change and a dynamic time window;

[0009] The instantaneous load change rate is time-weighted filtered to obtain a dynamic load change rate.

[0010] Preferably, the instantaneous load change rate is calculated by dividing the energy deviation caused by load transient change by the dynamic time window and multiplying by a unit matching and system calibration coefficient.

[0011] Preferably, the dynamic time window is:

[0012]

[0013] wherein T(t) is the dynamic time window at time t; T min is the minimum window length; T init is the initial time window value; λ is the adjustment factor; L(t-1) is the load change rate at time t-1; L threshold is the load change determination threshold.

[0014] Preferably, the calculation formula of the adjustment factor λ is:

[0015]

[0016] wherein λ0 is the basic adjustment factor, σ L is the standard deviation of the load change rate within the window, and ∈ is a constant.

[0017] Preferably, the time-weighted filtering of the instantaneous load change rate to obtain the dynamic load change rate is as follows:

[0018]

[0019] wherein L avg (t) is the dynamic load change rate at time t; w i is the time decay weighting coefficient; L(t-i) is the load change rate at time t-i; and N is the number of historical time points participating in the time-weighted filtering.

[0020] Preferably, the calculation formula of the time decay weighting coefficient w i is:

[0021]

[0022] wherein τ is the time decay factor; and i represents the time step index from the current time.

[0023] Preferably, the calculation formula of the time decay factor τ is:

[0024]

[0025] wherein τ0 is a default memory constant; σ L is the standard deviation of the load change rate in the window, representing the current fluctuation intensity.

[0026] The second aspect of the present application provides a dynamic load change rate calculation system, comprising:

[0027] a power collection and calculation module, configured to collect the input power and the output power of the load system and calculate the difference between the input power and the output power to obtain the energy deviation caused by the load transient change;

[0028] a transient load change rate calculation module, configured to calculate the transient load change rate based on the energy deviation caused by the load transient change and the dynamic time window;

[0029] a time weighted filtering module, configured to perform time weighted filtering on the transient load change rate to obtain the dynamic load change rate.

[0030] The third aspect of the present application provides a computer device, comprising a processor configured to implement the method when executing a program stored in a memory.

[0031] The fourth aspect of the present application provides a readable storage medium, having a program stored thereon, the program being executed by a processor to implement the method.

[0032] Compared with the prior art, the present application has at least the following beneficial effects:

[0033] 1. The present application uses the balance relationship among the input power, the output power and the loss power to replace the traditional differential calculation method, and does not rely on the traditional differential operation, but is based on the balance relationship among the input power, the output power and the loss power for calculation, avoids the interference of noise signals on the result, makes the calculated change rate more stable and reliable, can effectively suppress the influence of high-frequency noise on the calculation result, reflects the actual load change trend, and will not be disturbed by short-time noise, thereby significantly improving the stability and anti-interference ability of the calculation.

[0034] 2、The application introduces a dynamic time window in calculation, and the calculation window can be automatically adjusted in real time according to load fluctuation, so that the calculation window is automatically increased to improve calculation stability when the load fluctuation is low, and the window is automatically reduced to improve system response speed when the load fluctuation is high, so that the system can adapt to dynamic load changes faster, and the optimal calculation accuracy, stability and real-time performance can be maintained under different load conditions, and the intelligent level and load adjustment capability of the control system are improved. The application also dynamically adjusts the adjustment factor according to the severity of the current load fluctuation, so that the dynamic time window can adaptively optimize the dynamic response sensitivity.

[0035] 3、The application integrates power change trends in a short time through time-weighted filtering, so that the finally calculated load change rate can better reflect the actual trend, rather than the instantaneous value, so that the calculation result can be ensured not to be affected by short-time fluctuation, and the real load change can be quickly adapted, the calculation accuracy and real-time performance can be better balanced, the load calculation result is more in line with the actual working condition requirement, the control system can accurately adjust the operation state, unnecessary energy consumption and adjustment error are reduced, the calculation lag problem of the traditional filtering method is avoided, and high calculation accuracy and real-time performance are maintained, the system response speed can be optimized, and the load tracking capability is improved. The application also introduces a time decay weighting coefficient based on a time decay factor, so that the memory period can be extended when the fluctuation is small, the stable response can be maintained, the memory depth can be automatically reduced when the fluctuation is severe, the response speed can be improved, and the time-weighted filtering algorithm can adaptively process time series data. BRIEF DESCRIPTION OF DRAWINGS

[0036] Figure 1 The application is a dynamic load change rate calculation method flowchart;

[0037] Figure 2 The application is a dynamic load change rate calculation method implementation flowchart;

[0038] Figure 3 The application is a dynamic load change rate calculation system composition structure diagram. DETAILED DESCRIPTION

[0039] To make the purpose, technical scheme and advantages of the application clearer, the technical scheme of the application will be described clearly and completely below in combination with the drawings in the embodiments of the application. The embodiments described in the application are only a part of the embodiments of the application, not all the embodiments. Based on the spirit of the application, other embodiments obtained by those skilled in the art without creative labor are within the protection scope of the application.

[0040] Embodiment 1 of the application provides a dynamic load change rate calculation method, as shown in Figures 1-2 The method comprises:

[0041] Step 1: Collect the input power and output power of the load system and calculate the difference between the input power and the output power to obtain the energy deviation caused by the transient change of the load;

[0042] Further preferably, to achieve stable estimation of dynamic load changes, the present application proposes a dynamic load change rate calculation method based on power balance. This method uses the principle of energy conservation to construct a power model, combines time-weighted trend analysis and adaptive time window adjustment strategy, and improves the real-time performance and accuracy of the calculation while avoiding high-frequency noise interference. The power balance modeling is as follows:

[0043] The system collects the input power P imput (t) of the frequency converter or inverter side output (t), and estimates the load change trend of the system at the current time through the difference between the two. According to the law of conservation of power:

[0044] P input (t) = P output (t) + P loss (t)

[0045] Where P input (t) is the input power of the system (power provided by the frequency converter), P output (t) is the power consumed by the actual load (for refrigeration, mechanical movement, etc.), and P loss (t) is the system loss power, including motor stator resistance loss, hysteresis loss, mechanical friction and other nonlinear loss terms.

[0046] Since the loss is relatively stable in a short time, ΔP(t) = P input (t) - P output (t) can be approximately regarded as the energy deviation caused by the transient change of the system load.

[0047] Step 2: Calculate the instantaneous load change rate based on the energy deviation caused by the transient change of the load and the dynamic time window;

[0048] Further preferably, (1) based on the above power balance modeling to achieve the initial estimation of the change rate, the preliminary load change rate is defined as:

[0049]

[0050] Where L(t) is the estimated load change rate at the current time, k is the unit matching and system calibration coefficient (which can be obtained according to device modeling), and T(t) is the current dynamic time window (see (2) below). When the unit is unified, L(t) is usually expressed in W / s.

[0051] The change rate of the load is calculated through the relationship among the input power, the output power and the loss power, thereby avoiding the high-frequency noise problem caused by traditional differential calculation, and providing an optimal adjustment scheme with real-time performance and robustness for scenarios such as variable frequency driving and motor control system.

[0052] (2) In order to keep the optimal response characteristics of the system in different operating states, the adaptive time window adjustment strategy is adopted. When the load changes sharply, the smoothing period is shortened, and the system sensitivity is improved; when the load changes smoothly, the smoothing period is lengthened, and the calculation stability is improved. The dynamic window adjustment formula is as follows:

[0053] The processing for the initial time t=1: in the system initialization stage, since L(0) does not exist, T(1) can be set as T init is calculated, wherein T init is the default initial time window value, or T(1) is set as T min .

[0054] When t≥2,

[0055] wherein T min is the minimum window length, used to limit extreme shortening. T min parameters are usually determined by system characteristics, including control period, noise level, and the bearing capacity of the controlled device to the adjustment frequency. In the present application, the recommended value can be set to 3-5 times of the system sampling period, for example, in a system with a sampling period of 1ms, the recommended setting T min =3ms-5ms, to ensure that the system still has filtering ability when responding with high sensitivity. In addition, it can also be adaptively adjusted in combination with the noise level and dynamic fluctuation state.

[0056] L threshold is the load change determination threshold, which is set to determine the sensitivity of "significant change". In the actual system, the load change determination threshold L threshold parameter can be set in combination with the maximum load fluctuation characteristics of the system, and the recommended value range is 5%-15% of the system full load change rate. The specific value can be set through historical operation data statistics or online automatic adjustment mechanism.

[0057] |L(t-1)| is the change rate amplitude at t-1 time.

[0058] λ is the adjustment factor, which controls the response slope:

[0059]

[0060] wherein λ0 is the basic adjustment factor (an empirical constant, which can be set to 1-3), σ Lis the standard deviation of the load change rate within the sliding window, and ∈ is a tiny constant to avoid zero denominator.

[0061] The adjustment factor λ is dynamically adjusted according to the severity of the current load fluctuation, achieving adaptive optimization of dynamic response sensitivity.

[0062] The above dynamic window adjustment formula makes the window adjustment smooth and continuous, avoiding control errors caused by sudden changes.

[0063] Step 3: Time-weighted filtering of the instantaneous load change rate to obtain the dynamic load change rate, achieving time-weighted trend estimation.

[0064] Further preferably, since the collected power signal may have burst noise or short-period fluctuations, in order to suppress the influence of such disturbances on the calculation of the change rate, an exponential weighted average method is introduced to time-weighted smooth L(t), obtaining the trend change rate:

[0065]

[0066] where, is the time decay weighting coefficient, the closer to the current time the weight is larger. i represents the time step index (i.e. the current is t, i=1 represents t-1, i=2 represents t-2, etc.) from the current time. This weight makes the data closer to the current time have higher weight, better reflecting real-time.

[0067] N is the number of historical time points participating in smoothing.

[0068] τ is the time decay factor, controlling the "memory length" of the system to historical data, ensuring that historical data does not excessively affect real-time response, specifically as follows:

[0069]

[0070] where, τ0 is the default memory constant (e.g. 3-5), σ L is the standard deviation of the load change rate within the sliding window, representing the current fluctuation severity.

[0071] τ controls the memory depth of historical data, when the fluctuation is small, the system prolongs the memory period, maintaining stable response; when the fluctuation is severe, the system automatically reduces the memory depth, improving the response speed, achieving adaptive processing of time series data.

[0072] Through the above smoothing strategy, the system can greatly suppress error fluctuations caused by sensor errors, PWM noise, etc. while retaining trend information.

[0073] The dynamic load change rate calculation method can be widely applied to intelligent control of a variable frequency compressor, load prediction of a power grid, variable frequency control of an industrial motor and the like.

[0074] Embodiment 2 of the present application provides a dynamic load change rate calculation system, comprising:

[0075] a power collection and calculation module configured to collect input power and output power of a load system and calculate a difference between the input power and the output power to obtain an energy deviation caused by load transient change;

[0076] a transient load change rate calculation module configured to calculate a transient load change rate based on the energy deviation caused by load transient change and a dynamic time window;

[0077] a time-weighted filtering module configured to perform time-weighted filtering on the transient load change rate to obtain a dynamic load change rate.

[0078] In a specific implementation, the dynamic load change rate calculation system has a structure as shown in Figure 3 .

[0079] Embodiment 3 of the present application provides a computer device, comprising a processor configured to implement the method of embodiment 1 when executing a program stored in a memory.

[0080] Embodiment 4 of the present application provides a readable storage medium having a program stored thereon, the program being configured to implement the method of embodiment 1 when executed by a processor.

[0081] Compared with the prior art, the present application has at least the following beneficial effects:

[0082] 1. The present application uses the balance relationship among input power, output power and loss power to replace the traditional differential calculation method, and is not dependent on traditional differential operation, but is based on the balance relationship among input power, output power and loss power to perform calculation, avoids the interference of noise signals on the result, makes the calculated change rate more stable and reliable, can effectively suppress the influence of high-frequency noise on the calculation result, reflects the actual load change trend, and will not be disturbed by short-time noise, thereby significantly improving the stability and anti-interference ability of calculation.

[0083] 2、The application introduces a dynamic time window in calculation, and the calculation window can be self-adaptively adjusted in real time according to load fluctuation, so that the calculation window is automatically increased to improve calculation stability when the load fluctuation is low, and the window is automatically reduced to improve system response speed when the load fluctuation is high, so that the system can adapt to dynamic load changes faster, and optimal calculation accuracy, stability and real-time performance can be maintained under different load conditions, and the intelligent level and load adjustment capability of the control system are improved. The application also realizes adaptive optimization of the dynamic response sensitivity of the dynamic time window by dynamically adjusting the adjustment factor according to the severity of the current load fluctuation.

[0084] 3、The application integrates power change trends in a short time through time-weighted filtering, so that the finally calculated load change rate can better reflect the actual trend, rather than the instantaneous value, so that the calculation result can be ensured not to be affected by short-time fluctuation, and the real load change can be quickly adapted, the calculation accuracy and real-time performance can be better balanced, the load calculation result is more in line with actual working condition requirements, the control system can accurately adjust the operation state, unnecessary energy consumption and adjustment error are reduced, the calculation lag problem of the traditional filtering method is avoided, high calculation accuracy and real-time performance are maintained, the system response speed can be optimized, and the load tracking capability is improved. The application also introduces a time decay weighting coefficient based on a time decay factor, so that the memory period can be extended when the fluctuation is small, the stable response can be maintained, the memory depth can be automatically reduced when the fluctuation is severe, the response speed can be improved, and adaptive processing of time series data by the time-weighted filtering algorithm is realized.

[0085] The present disclosure can be a system, a method, and / or a computer program product. The computer program product can include a computer readable storage medium (or media) having computer readable program instructions thereon for causing a processor to carry out aspects of the present disclosure.

[0086] Computer readable storage media can be tangible storage media which can retain and store instructions for use by an instruction execution device. Computer readable storage media can be, for example, but is not limited to, an electronic storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of computer readable storage media include the following: a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), a static random access memory (SRAM), a portable compact disc read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk, a mechanically encoded device such as punch-cards or raised structures in a groove having instructions recorded thereon, and any suitable combination of the foregoing. A computer readable storage medium, as used herein, is not to be construed as being transitory signals per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through a waveguide or other transmission media (e.g., light pulses passing through a fiber-optic cable), or electrical signals transmitted through a wire.

[0087] Computer readable program instructions described herein can be downloaded to respective computing / processing devices from a computer readable storage medium or to an external computer or external storage device via a network, for example, the Internet, a local area network, a wide area network and / or a wireless network. The network can comprise copper transmission cables, optical transmission fibers, wireless transmission, routers, firewalls, switches, gateway computers and / or edge servers. A network adapter card or network interface in each computing / processing device receives computer readable program instructions from the network and forwards the computer readable program instructions for storage in a computer readable storage medium within the respective computing / processing device.

[0088] Computer readable program instructions for carrying out operations of the present disclosure can be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine dependent instructions, microcode, firmware instructions, state-setting data, or either source code or object code written in any combination of one or more programming languages, including an object oriented programming language such as Smalltalk, C++ or the like, and conventional procedural programming languages such as the "C" programming language or similar programming languages. The computer readable program instructions can execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection can be made to an external computer (for example, through the Internet using an Internet Service Provider). In some embodiments, electronic circuitry including, for example, programmable logic circuitry, field-programmable gate arrays (FPGA), or programmable logic arrays (PLA) can execute the computer readable program instructions by utilizing state information of the computer readable program instructions to personalize the electronic circuitry, in order to perform aspects of the present disclosure.

[0089] Finally, it should be noted that the above-mentioned embodiments are merely used to illustrate the technical solutions of the present application, but not to limit it. Although the present application has been described in detail with reference to the above-mentioned embodiments, those skilled in the art should understand that the specific embodiments of the present application can be modified or replaced, and any modification or replacement without departing from the spirit and scope of the present application should be covered in the protection scope of the claims of the present application.

Claims

1. A method for calculating a dynamic load change rate, characterized in that: The method comprises: Collect the input power and output power of the load system and calculate the difference between the input power and the output power to obtain the energy deviation caused by the transient change of the load; Calculate the instantaneous load change rate based on the energy deviation caused by the load transient change and the dynamic time window; Perform time-weighted filtering on the instantaneous load change rate to obtain the dynamic load change rate.

2. The method for calculating a dynamic load change rate according to claim 1, wherein: The instantaneous load change rate is calculated by dividing the energy deviation caused by the transient load change by the dynamic time window and then multiplying the result by the unit matching and system calibration coefficients.

3. The method for calculating a dynamic load change rate according to claim 1, wherein: The dynamic time window is: Among them, T(t) is the dynamic time window at time t; T min is the minimum window length; T init is the initial time window value; λ is the adjustment factor; L(t-1) is the load change rate at time t-1; L threshold The load change determination threshold.

4. The method for calculating a dynamic load change rate according to claim 3, wherein: The calculation formula of the adjustment factor λ is: Among them, λ0 is the basic adjustment factor, σ L is the standard deviation of the load change rate within the window, and ∈ is a constant.

5. The method for calculating a dynamic load change rate according to claim 1, wherein: The instantaneous load change rate is subjected to time-weighted filtering to obtain the dynamic load change rate, which is specifically as follows: Among them, L avg (t) is the dynamic load change rate at time t; w i is the time attenuation weighting coefficient; L(ti) is the load change rate at time ti; N is the number of historical moments participating in time weighted filtering; i represents the time step index from the current moment.

6. The method for calculating the dynamic load change rate according to claim 5, wherein: Time decay weighting coefficient w i The calculation formula is: Where τ is the time decay factor.

7. The method for calculating a dynamic load change rate according to claim 6, wherein: The calculation formula of the time decay factor τ is: Among them, τ0 is the default memory constant; σ L is the standard deviation of the load change rate within the window, which represents the severity of the current fluctuation.

8. A dynamic load change rate calculation system, used to execute the method according to any one of claims 1 to 7, characterized in that: include: The power acquisition and calculation module is used to collect the input power and output power of the load system and calculate the difference between the input power and the output power to obtain the energy deviation caused by the transient change of the load; An instantaneous load change rate calculation module is used to calculate the instantaneous load change rate based on the energy deviation caused by the transient load change and the dynamic time window; The time-weighted filtering module is used to perform time-weighted filtering on the instantaneous load change rate to obtain the dynamic load change rate.

9. A computer device, characterized in that: The computer device includes a processor, and the processor is configured to implement the method according to any one of claims 1 to 7 when executing a program stored in a memory.

10. A readable storage medium having a program stored thereon, characterized in that: When the program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

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