CN107831383A - The load parameter device for identifying and its method at a kind of power system plant stand end - Google Patents

The load parameter device for identifying and its method at a kind of power system plant stand end Download PDF

Info

Publication number
CN107831383A
CN107831383A CN201711015719.2A CN201711015719A CN107831383A CN 107831383 A CN107831383 A CN 107831383A CN 201711015719 A CN201711015719 A CN 201711015719A CN 107831383 A CN107831383 A CN 107831383A
Authority
CN
China
Prior art keywords
module
current
voltage
phasor
load parameter
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Granted
Application number
CN201711015719.2A
Other languages
Chinese (zh)
Other versions
CN107831383B (en
Inventor
熊春晖
李明宇
王颖
尚慧玉
陆超
刘春晓
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Tsinghua University
China Southern Power Grid Co Ltd
Original Assignee
Tsinghua University
China Southern Power Grid Co Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Tsinghua University, China Southern Power Grid Co Ltd filed Critical Tsinghua University
Priority to CN201711015719.2A priority Critical patent/CN107831383B/en
Publication of CN107831383A publication Critical patent/CN107831383A/en
Application granted granted Critical
Publication of CN107831383B publication Critical patent/CN107831383B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Classifications

    • GPHYSICS
    • G01MEASURING; TESTING
    • G01RMEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere

Landscapes

  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Supply And Distribution Of Alternating Current (AREA)

Abstract

The present invention relates to a kind of load parameter device for identifying at power system plant stand end and its method, comprise the following steps:1) the voltage and current signal in collection electric grid secondary loop, and carry out discrete sampling after the voltage to obtaining, current signal progress translation filtering in real time, obtains the original sample value of voltage, current signal;2) opening into status information for electric grid secondary loop is gathered in real time, and data signal is converted to opening after status information carries out stabilization and differentiation for obtaining, and the division status information for obtaining line switching is used for the display of man-machine interface;3) phasor calculation is carried out according to the original sample value of voltage, current signal and load parameter recognizes, obtain phasor calculation result and load parameter identification result;4) by the phasor data obtained in the switching-state information in step 2), step 3) and load model parameters identification result, shown by man-machine interface, and upload to scheduling station.

Description

Load parameter identification device and method for power system station end
Technical Field
The invention belongs to the technical field of dynamic monitoring of an electric power system, and particularly relates to a load parameter identification device and method for a power system station.
Background
The power system model is crucial to the operation simulation analysis and calculation of the power system, and the modeling of the load parameters plays a key role in the application of the power system model. Different load models and parameters are selected, so that differences exist in dynamic response results in simulation analysis of the power system, and even the judgment of the stability of the power system is influenced. Different power system stability problems are analyzed, requirements for load models are different, and different load models meeting conditions of actual load positions, components, structures and the like are established according to application purposes of the load models and specific requirements of corresponding problems on the load models, so that accuracy of simulation analysis is guaranteed.
In recent years, researchers in various countries have performed a series of highly effective works in load modeling, and have been applied to engineering practice. However, the following series of problems still remain to be solved in the existing load model identification work. First, it is a tracking problem for the time-varying nature of the load model. Similarly to load prediction, the time-varying behavior of the load model is similarly reflected in short-term, varying periods of time and changes over time, etc. In the existing load modeling method, the statistical synthesis method adopts an interval period method to track the time-varying characteristic of a load model with lower frequency, and the workload is higher; the general measurement and identification method is developed based on response after a fault, whether the general measurement and identification of the load model can be carried out or not depends on whether the fault exists or not, the tracking of the general measurement and identification method on the time-varying property of the load model is not ideal enough, and whether the load identification can be carried out or not cannot be artificially selected but depends on the existence of the fault. Secondly, the problem of model description of the diversity of the load model. The model structure adopted in the load model identification mainly uses an induction motor to describe the characteristics of dynamic load, and uses a polynomial model or a power exponent model to describe the characteristics of static load. However, with the rapid development of smart grid technology in recent years, new electric devices such as new energy sources, energy storage devices, and electric vehicles are connected to the power grid on a large scale, and the large-scale popularization of distributed power generation and various energy storage devices makes it difficult to clearly distinguish which node is a complete load node in a traditional power system, and a certain distributed power generation or energy storage device is also connected to the lower side of a bus with a dominant load. In addition, with the widespread of power electronic devices on a large scale, the proportion of power electronic loads represented by inverter air conditioners in power loads is increasing, the characteristics of dynamic loads are difficult to be completely described by induction motors, and new model structures need to be introduced for processing. Finally, even if only the load model structure consisting entirely of the induction motor and the dead load is considered, the existing research does not consider the diversity problem caused by different parameters under the same model structure and the aggregation problem of the diversity load after passing through the transmission reactance.
Disclosure of Invention
In view of the above problems, an object of the present invention is to provide a load parameter identification device and method for a power system plant station, which can implement the station end to measure synchronous phasor data and perform online identification of leading load parameters through measured signals.
In order to realize the purpose, the invention adopts the following technical scheme: a load parameter identification device of a power system station end is characterized in that: the system comprises a first data acquisition module, a second data acquisition module, a logic calculation module and a function management module; the first data acquisition module is used for discretely sampling voltage and current signals of a power grid at a station end of the power system, which are acquired in real time, obtaining original sampling values of the voltage and current signals and sending the original sampling values to the logic calculation module; the second data acquisition module is used for converting the real-time acquired input signal of the power grid at the station end of the power system into a digital signal and sending the digital signal to the logic calculation module; the logic calculation module performs phasor calculation and load parameter identification according to the received original sampling values of the voltage and the current and the input signal, and sends a phasor calculation result and a load parameter identification result to the function management module; and the function management module displays and stores the received phasor calculation result and the load parameter identification result in real time and uploads the phasor calculation result and the load parameter identification result to the scheduling master station.
The first data acquisition module comprises an alternating current input module, a voltage/current conversion module, a first ADC module and a second ADC module; the alternating current input module is used for acquiring current and voltage signals of a power system station end in real time and sending the current and voltage signals to the voltage/current conversion module; the voltage/current conversion module performs filtering conversion on the received voltage and current signals, sends the converted voltage signals to the first ADC module, and sends the converted current signals to the second ADC module; the first ADC module and the second ADC module respectively perform analog-to-digital conversion and sampling on the received voltage signal and current signal, and send initial value sampling results to the logic calculation module.
The second data acquisition module comprises an access signal detection module and a micro control unit module, and the access signal detection module measures access state information of the power grid in real time and sends the access state information to the micro control unit module; the micro control unit module is used for converting the received input/output state information into a digital signal after anti-shaking and distinguishing and sending the digital signal to the logic calculation module.
The logic calculation module comprises an FPGA module, a first DSP module and a second DSP module; the FPGA performs packaging and data synchronization according to input voltage and current signals and sends the packaged data to the first DSP module and the second DSP module; the first DSP module carries out phasor calculation according to the input synchronous voltage and current signals, and phasor data obtained by calculation are forwarded to the second DSP module; and the second DSP module carries out load parameter identification through the received phasor data and sends a load parameter identification result to the function management module.
The function management module comprises a CPU, a man-machine interface module, a communication module and a data storage module; after receiving the data sent by the first DSP module and the second DSP module, the CPU respectively sends the calculated phasor calculation result and the load parameter identification result to the human-computer interface module, the data storage module and the communication module; the man-machine interface module displays phasor calculation results and load parameter identification results in real time; the data storage module is used for storing phasor calculation results and load parameter identification results; and the communication module is used for uploading the phasor calculation result and the load parameter identification result sent by the CPU to the scheduling master station.
A load parameter identification method for a power system station end is characterized by comprising the following steps: 1) Acquiring voltage and current signals of a secondary circuit of a power grid in real time, performing conversion filtering on the acquired voltage and current signals, and performing discrete sampling to acquire original sampling values of the voltage and current signals; 2) Acquiring the opening state information of a secondary circuit of the power grid in real time, converting the acquired opening state information into a digital signal after anti-shaking and distinguishing, and acquiring the opening and closing state information of a circuit switch for displaying a human-computer interface; 3) Carrying out phasor calculation and load parameter identification according to original sampling values of the voltage and current signals to obtain a phasor calculation result and a load parameter identification result; 4) And (3) displaying the switching state information in the step 2), the phasor data obtained in the step 3) and the load parameter identification result through a human-computer interface, and uploading the information to a scheduling master station.
In the step 3), the method for performing phasor calculation and load parameter identification comprises the following steps: 3.1 Carrying out real-time phasor calculation according to original sampling values of the voltage and current signals to obtain phasor data of the voltage and the current, wherein the phasor data comprises phasor data of three-phase fundamental voltage and current and phasor data of positive sequence, negative sequence and zero sequence voltage and current; 3.2 Carrying out system disturbance judgment according to the phasor data of the voltage and the current obtained in the step 3.1) to obtain phasor data of the voltage and the current meeting disturbance judgment conditions; 3.3 According to the obtained phasor data of the voltage and current signals meeting the disturbance judgment condition, carrying out load parameter identification calculation to obtain a load parameter identification result.
In the step 3.2), the disturbance judging method includes the following steps:
3.2.1 According to a preset current mutation constant value, judging whether each currently input current has mutation, wherein the judgment formula is as follows:
||I Φ (t)|-|I Φ (t-60ms)||>I D
in the formula I D For current mutation quantitative, | I Φ (t) | is the effective value at the moment of current t, | I Φ (t-60 ms) | is an effective value of the current at the moment before 60 ms;
3.2.2 According to the preset fixed value of the zero-sequence current break variable), judging whether the current zero-sequence current breaks, wherein the judgment formula is as follows:
||I 0 (t)|-|I 0 (t-60ms)||>I 0D
in the formula I 0D For zero sequence current mutation quantitative determination, | I 0 (t) | is the effective value of zero sequence current at time t, | I 0 (t-60 ms) is an effective value of zero sequence current at the moment before 60 ms;
3.2.3 According to a preset voltage mutation constant value, judging whether the current input voltage signal of each phase has mutation, wherein the judgment formula is as follows:
||U Φ (t)|-|U Φ (t-60ms)||>U D
in the formula of U D For voltage step quantitative determination, | U Φ (t) | is the effective value of the phase voltage at time t, | U Φ (t-60 ms) | is an effective value of the phase voltage at the moment 60ms ago;
3.2.4 According to a preset zero-sequence voltage mutation fixed value, judging whether the current zero-sequence voltage has mutation or not, wherein the judgment formula is as follows:
||U 0 (t)|-|U 0 (t-60ms)||>U 0D
in the formula,U 0D For zero sequence voltage step-change quantitative determination, | U 0 (t) | is the effective value at time t of zero sequence voltage, | U 0 And (t-60 ms) is an effective value of zero sequence voltage at the moment before 60 ms.
In the step 3.3), the method for identifying the load parameters comprises the following steps:
3.3.1 Extracting phasor data of voltage and current which accord with disturbance judgment conditions in the same time period, and calculating according to the amplitudes of the voltage and the current to obtain active power and reactive power;
3.3.2 Setting a value range of a load parameter according to the phasor data in the step 3.3.1), further determining a search space, randomly generating an initial position and a speed of each particle, creating an objective function, and calculating to obtain an optimal extreme value and a global optimal value of the 0 th generation position of each particle;
the calculation formulas of the initial position and the velocity of each particle are respectively as follows:
the calculation formulas of the optimal position of each particle in the 0 th generation and the global optimal particle position are respectively as follows:
wherein i =1, 2.. N is the number of particles, j =1, 2.. D is the dimension of the parameter,for the jth parameter of the ith particleIn the initial position of the device, the position of the device,for the initial velocity of the jth parameter of the ith particle, rand (0, 1) generates a random number between 0 and 1,is the maximum value of the jth parameter,is the minimum value of the jth parameter,the maximum moving speed of the jth parameter,the minimum moving speed for the jth parameter,bestx, the optimal position of the ith particle in generation 0 0 For the optimal position of all particles in generation 0, para (·) is a function that finds the position vector according to an objective function, f (·) is the objective function, i.e., the sum of squared deviations between the predicted values (P _ P, Q _ P) and the actual measured values (P, Q) of the active and reactive power, which is expressed for n power measurement points as:
3.3.3 Based on the optimal particle position of each particle of the previous generation and the position of the global optimal particle, the velocity of each particle of the current generation is obtained:
in the formula (I), the compound is shown in the specification,is the g +1 th generation velocity of the ith particle, omega is the inertia factor, c 1 And c 2 Respectively, the acceleration constants are the constant values of the acceleration,bestx for the position of the ith particle at which the optimum value was obtained in g iterations g Positions where the optimal values are obtained in g iterations for all particles;
3.3.4 Update the position of each particle of the current generation according to the speed of each particle of the current generation to obtain the position of each particle of the current generation, namely
In the formula (I), the compound is shown in the specification,is the position of the ith particle in the g +1 generation;
3.3.5 According to the position and speed of each particle in the current generation, the optimal particle position and the global optimal particle position of each particle in the current generation are obtained by updating, namely
In the formula (I), the compound is shown in the specification,bestx for the position of the ith particle at which the optimum value was obtained in g +1 iterations g+1 Positions where optimal values are obtained for all particles in g +1 iterations;
3.3.6 3.3.3) to 3.3.5) are repeated until the set iteration times are met, and a group of parameters with the minimum objective function value are selected as the final load parameter identification result according to the optimal positions of all the particles in each iteration.
Due to the adoption of the technical scheme, the invention has the following advantages: 1. the invention adopts two data acquisition modules to carry out real-time measurement on the secondary circuit of the power grid, carries out phasor calculation according to real-time measurement data and completes load parameter identification, can quickly carry out response calculation aiming at the real-time measurement data, and solves the problem of tracking the time-varying property of a load model. 2. The invention provides an application mode which is realized by carrying out load parameter identification through a phasor calculation mode and through a hardware device, thereby effectively improving the calculation efficiency. 3. The disturbance judgment method aiming at the load parameter identification calculation can set the disturbance parameters according to the load measurement requirement, and is wider in application range.
Drawings
FIG. 1 is a schematic diagram of a hardware topology of a load identification device according to the present invention;
FIG. 2 is a logic diagram of the load identification apparatus of the present invention.
Detailed Description
The invention is described in detail below with reference to the figures and examples.
As shown in fig. 1, the load parameter identification apparatus for a power system station according to the present invention includes a first data acquisition module, a second data acquisition module, a logic calculation module, and a function management module. The first data acquisition module is used for discretely sampling voltage and current signals of a power grid at a station end of a power system, which are acquired in real time, obtaining original sampling values of the voltage and current signals and sending the original sampling values to the logic calculation module; the second data acquisition module is used for converting the real-time acquired input signal of the power grid at the station end of the power system into a digital signal and transmitting the digital signal to the logic calculation module; the logic calculation module performs phasor calculation and load parameter identification according to the received voltage and current original sampling values and the input signal, and sends a phasor calculation result and a load parameter identification result to the function management module; and the function management module displays and stores the received phasor calculation result and the load parameter identification result in real time and uploads the phasor calculation result and the load parameter identification result to the scheduling master station.
The first data acquisition module comprises an alternating current input module, a voltage/current conversion module, a first ADC module and a second ADC module. The alternating current input module is used for acquiring current and voltage signals of a power grid at a station end of a power system plant in real time and sending the current and voltage signals to the voltage/current conversion module; the voltage/current conversion module carries out filtering conversion on the received voltage and current signals, sends the converted voltage signals to the first ADC module and sends the converted current signals to the second ADC module; the first ADC module and the second ADC module respectively perform analog-to-digital conversion and sampling on the received voltage signal and current signal, and send initial value sampling results to the logic calculation module.
The second data acquisition module comprises an access signal detection module and an MCU (micro control unit) module, wherein the access signal detection module acquires access state information of a power grid at a station end of the power system in real time and sends the access state information to the MCU module; the MCU module is used for converting the received open-close state information into a digital signal after carrying out anti-shake and discrimination on the received open-close state information, and sending the digital signal to the function module.
The logic calculation module comprises an FPGA module, a first DSP module and a second DSP module. And the FPGA carries out packaging and data synchronization according to the input voltage and current signals and sends the packaged data to the first DSP module and the second DSP module. The first DSP module carries out phasor calculation according to the input synchronous voltage and current signals; and the phasor data obtained by calculation is forwarded to a second DSP module, and the second DSP module carries out load parameter identification through the received phasor data.
The function management module comprises a CPU, a man-machine interface module, a communication module and a data storage module. After receiving the data sent by the first DSP module and the second DSP module, the CPU respectively sends the calculated phasor data and the load parameter identification result to the human-computer interface module, the data storage module and the communication module; the man-machine interface module displays phasor data and a load parameter identification result in real time; the data storage module is used for storing phasor data and a load parameter identification result; and the communication module is used for uploading the phasor data and the load parameter identification result sent by the CPU to the scheduling master station.
In the above embodiments, one or two ac input modules are provided. Each AC input module can collect 12 paths of voltage signals and 12 paths of current signals, and the two AC input modules support at most 8 intervals of signal collection.
As shown in fig. 2, based on the load parameter identification device of the power system plant end, the present invention further provides a load parameter identification method of the power system plant end, including the following steps:
1) The method comprises the steps of collecting voltage and current signals of a secondary circuit of a power grid in real time, carrying out conversion filtering on the obtained voltage and current signals, and then carrying out discrete sampling to obtain original sampling values of the voltage and current signals.
2) And acquiring the opening state information of the secondary circuit of the power grid in real time, converting the acquired opening state information into a digital signal after anti-shaking and distinguishing, and acquiring the opening and closing state information of the circuit switch.
3) And carrying out phasor calculation and load parameter identification according to the original sampling values of the voltage and current signals to obtain a phasor calculation result and a load parameter identification result.
The calculation method for carrying out phasor calculation and load model parameter identification comprises the following steps:
3.1 According to the original sampling values of the voltage and current signals, real-time phasor calculation is carried out to obtain phasor data of the voltage and the current.
And carrying out phasor calculation according to the original sampling values of the voltage and current signals to obtain the calculated amplitude and phase angle degrees of the original sampling values, including the phasors of the three-phase fundamental voltage and fundamental current, and the voltage phasor and current phasor data of positive sequence, negative sequence and zero sequence. The measured analog signal is assumed to be:then its corresponding phasor form isWherein V is the amplitude value of the signal,is the phase angle. When the maximum value of the measured analog signal v (t) occurs at the pulse per second, the phase angle of the phasorIs 0 degree; when the positive zero crossing point of the actually measured analog signal v (t) is synchronous with the second pulse, the phase angle of the phasorIs-90 degrees. Phase angle of phasor when amplitude V of phasor is not changedThe relationship with the frequency of the measured analog signal is: d φ/dt =2 π (f-f) 0 )f 0 =50Hz; when the frequency of the actually measured analog signal is equal to 50Hz, the calculated phase angle is unchanged; when the frequency of the actually measured analog signal is greater than 50Hz, the phase angle is gradually increased; when the frequency of the measured analog signal is less than 50Hz, the phase angle gradually decreases. And introducing an external pulse-per-second clock signal for unifying the consistency of data time scales so as to correspond to the section nodes of the measured data.
3.2 Carry on the systematic disturbance to distinguish according to the voltage obtained, current phasor data, get the voltage, current phasor data which accords with the disturbance and distinguishes the condition.
When the system disturbance state is judged according to the obtained amplitude and phase angle phasor data of the voltage and the current, the judging conditions comprise phase current sudden change, zero sequence current sudden change, phase voltage sudden change and zero sequence voltage sudden change, and the specific judging method comprises the following steps:
3.2.1 According to a preset current mutation constant value, judging whether each currently input current has mutation, wherein the judgment formula is as follows:
||I Φ (t)|-|I Φ (t-60ms)||>I D (1)
in the formula I D For current step quantitative determination, | I Φ (t) | is the effective value of the current at time t, | I Φ (t-60 ms) | is the effective value of the current at the moment before 60 ms.
3.2.2 According to the preset fixed value of the zero-sequence current break variable), judging whether the current zero-sequence current breaks, wherein the judgment formula is as follows:
||I 0 (t)|-|I 0 (t-60ms)||>I 0D (2)
in the formula I 0D For zero sequence current mutation quantitative value, | I 0 (t) | is the effective value at time t of zero sequence current, | I 0 And (t-60 ms) | is an effective value of zero sequence current at the moment before 60 ms.
3.2.3 According to a preset voltage mutation constant value, judging whether the current input voltage signal of each phase has mutation, wherein the judgment formula is as follows:
||U Φ (t)|-|U Φ (t-60ms)||>U D (3)
in the formula of U D For voltage step quantitative determination, | U Φ (t) | is the effective value at time t of the phase voltage, | U Φ (t-60 ms) | is the effective value of the phase voltage at the time before 60 ms.
3.2.4 According to a preset zero-sequence voltage mutation fixed value, judging whether the current zero-sequence voltage has mutation or not, wherein the judgment formula is as follows:
||U 0 (t)|-|U 0 (t-60ms)||>U 0D (4)
in the formula of U 0D For zero sequence voltage step-change quantitative determination, | U 0 (t) | is the effective value at time t of zero sequence voltage, | U 0 (t-60 ms) | is the effective value of zero sequence voltage at the moment before 60 ms.
3.3 According to the obtained phasor data of voltage and current meeting the disturbance judgment condition, carrying out load parameter identification calculation to obtain a load parameter identification result.
According to the method, the deviation between the predicted values and the measured values of the active power and the reactive power is optimized through a differential evolution optimization algorithm, the state variable numerical value of the induction motor at the current moment is solved from the four measured values of the voltage amplitude, the voltage phase angle, the active power and the reactive power through objective function calculation, the predicted value of the state variable of the load model at the next moment is solved by using the load model parameter to be optimized, and the predicted values of two output variables of the active power and the reactive power of the load model at the next moment are calculated to be compared with the actual measured value to calculate the deviation. And the differential evolution optimization utilizes the objective function obtained by the previous calculation, and optimizes the numerical value of the objective function by changing the numerical value of the load model parameter to obtain a group of load model parameters which enable the objective function to reach the minimum value as the result of load model parameter identification. Specifically, the method comprises the following steps:
3.3.1 Phasor data of the voltage and the current which meet the disturbance judgment condition in the same time period are extracted, and the active power P and the reactive power Q are obtained through calculation according to the amplitude values of the voltage and the current.
3.3.2 Setting a value range of the load parameter according to the phasor data in the step 3.3.1), further determining a search space, randomly generating an initial position and a speed of each particle, creating an objective function, and calculating to obtain an optimal extreme value and a global optimal value of the 0 th generation position of each particle.
The calculation formulas of the initial position and the velocity of each particle are respectively as follows:
the calculation formulas of the optimal position of each particle in the 0 th generation and the global optimal particle position are respectively as follows:
wherein i =1, 2.. N is the number of particles, j =1, 2.. D isThe dimensions of the parameters are such that,is the initial position of the jth parameter of the ith particle,for the initial velocity of the jth parameter of the ith particle, rand (0, 1) generates a random number between 0 and 1,is the maximum value of the jth parameter,is the minimum value of the jth parameter,the maximum moving speed of the jth parameter,the minimum moving speed for the jth parameter,bestx, the optimum position of the ith particle in generation 0 0 For the optimal positions of all particles in the 0 th generation, para () is a function for solving a position vector according to an objective function, f () is an objective function, namely the deviation square sum between the predicted values (P _ P, Q _ P) and the actual measured values (P, Q) of the active power and the reactive power, and the objective function is expressed as follows for n power measurement points:
3.3.3 Based on the optimal particle position of each particle of the previous generation and the position of the globally optimal particle, the velocity of each particle of the current generation, i.e.
In the formula (I), the compound is shown in the specification,is the g +1 th generation velocity of the ith particle, omega is the inertia factor, c 1 And c 2 Respectively, the acceleration constants are the acceleration constants,bestx is the position of the ith particle at which the optimal value was obtained in g iterations g The positions where the optimal values were obtained in g iterations for all particles.
3.3.4 Update the position of each particle of the current generation according to the speed of each particle of the current generation to obtain the position of each particle of the current generation, namely
In the formula (I), the compound is shown in the specification,the position of the ith particle in the g +1 generation.
3.3.5 According to the position and speed of each particle of the current generation, the optimal particle position and the global optimal particle position of each particle of the current generation are obtained by updating, namely
In the formula (I), the compound is shown in the specification,bestx for the position of the ith particle at which the optimum value was obtained in g +1 iterations g+1 The maximum is obtained in g +1 iterations for all particlesPosition of merit.
3.3.6 3.3.3) to 3.3.5) are repeated until the set iteration times are met, and a group of parameters with the minimum objective function value are selected as the final load parameter identification result according to the optimal positions of all the particles in each iteration.
4) And (3) displaying the switching state information in the step 2), the phasor data obtained in the step 3) and the load parameter identification result through a human-computer interface, and uploading the information to a scheduling master station.
The above embodiments are only used for illustrating the present invention, and the structure, connection manner, manufacturing process and the like of each component can be changed, and equivalent changes and improvements made on the basis of the technical scheme of the present invention should not be excluded from the protection scope of the present invention.

Claims (9)

1. The utility model provides a load parameter identification device of electric power system station end which characterized in that: the system comprises a first data acquisition module, a second data acquisition module, a logic calculation module and a function management module;
the first data acquisition module is used for discretely sampling voltage and current signals of a power grid at a station end of a power system, which are acquired in real time, obtaining original sampling values of the voltage and current signals and sending the original sampling values to the logic calculation module;
the second data acquisition module is used for converting the real-time acquired input signal of the power grid at the station end of the power system into a digital signal and sending the digital signal to the logic calculation module;
the logic calculation module carries out phasor calculation and load parameter identification according to the received voltage and current original sampling values and the input signal, and sends a phasor calculation result and a load parameter identification result to the function management module;
and the function management module displays and stores the received phasor calculation result and the load parameter identification result in real time and uploads the phasor calculation result and the load parameter identification result to the scheduling master station.
2. The apparatus according to claim 1, wherein the load parameter identification device comprises: the first data acquisition module comprises an alternating current input module, a voltage/current conversion module, a first ADC module and a second ADC module;
the alternating current input module is used for acquiring current and voltage signals of a power system station end in real time and sending the current and voltage signals to the voltage/current conversion module;
the voltage/current conversion module performs filtering conversion on the received voltage and current signals, sends the converted voltage signals to the first ADC module, and sends the converted current signals to the second ADC module;
the first ADC module and the second ADC module respectively perform analog-to-digital conversion and sampling on the received voltage signal and current signal, and send initial value sampling results to the logic calculation module.
3. The apparatus according to claim 1, wherein the load parameter identification device comprises: the second data acquisition module comprises an access signal detection module and a micro control unit module, and the access signal detection module measures access state information of the power grid in real time and sends the access state information to the micro control unit module; the micro control unit module is used for converting the received input/output state information into a digital signal after anti-shaking and distinguishing and sending the digital signal to the logic calculation module.
4. The apparatus according to claim 1, wherein the load parameter identification device comprises: the logic calculation module comprises an FPGA module, a first DSP module and a second DSP module;
the FPGA carries out packaging and data synchronization according to the input voltage and current signals and sends the packaged data to the first DSP module and the second DSP module;
the first DSP module performs phasor calculation according to the input synchronous voltage and current signals, and phasor data obtained through calculation are forwarded to the second DSP module;
and the second DSP module carries out load parameter identification through the received phasor data and sends a load parameter identification result to the function management module.
5. The apparatus according to claim 1, wherein the load parameter identification device comprises: the function management module comprises a CPU, a man-machine interface module, a communication module and a data storage module;
after receiving the data sent by the first DSP module and the second DSP module, the CPU respectively sends the calculated phasor calculation result and the load parameter identification result to the human-computer interface module, the data storage module and the communication module;
the man-machine interface module displays phasor calculation results and load parameter identification results in real time;
the data storage module is used for storing phasor calculation results and load parameter identification results;
and the communication module is used for uploading phasor calculation results and load parameter identification results sent by the CPU to the scheduling master station.
6. A load parameter identification method for a power system station end is characterized by comprising the following steps:
1) Acquiring voltage and current signals of a secondary circuit of a power grid in real time, performing conversion filtering on the acquired voltage and current signals, and performing discrete sampling to acquire original sampling values of the voltage and current signals;
2) Acquiring the opening state information of a secondary circuit of the power grid in real time, converting the acquired opening state information into a digital signal after anti-shaking and distinguishing, and acquiring the opening and closing state information of a circuit switch for displaying a human-computer interface;
3) Carrying out phasor calculation and load parameter identification according to original sampling values of the voltage and current signals to obtain a phasor calculation result and a load parameter identification result;
4) And (3) displaying the switching state information in the step 2), the phasor calculation result and the load parameter identification result obtained in the step 3) through a human-computer interface, and uploading the information to a scheduling master station.
7. The method according to claim 6, wherein the method comprises: in the step 3), the method for performing phasor calculation and load parameter identification comprises the following steps:
3.1 Carrying out real-time phasor calculation according to original sampling values of the voltage and current signals to obtain phasor data of the voltage and the current, wherein the phasor data comprises phasor data of three-phase fundamental voltage and current and phasor data of positive sequence, negative sequence and zero sequence voltage and current;
3.2 Carrying out system disturbance judgment according to the phasor data of the voltage and the current obtained in the step 3.1) to obtain phasor data of the voltage and the current meeting disturbance judgment conditions;
3.3 Carrying out load parameter identification calculation according to the obtained phasor data of the voltage and current signals meeting the disturbance judgment condition to obtain a load parameter identification result.
8. The method according to claim 7, wherein the method comprises: in the step 3.2), the disturbance judging method includes the following steps:
3.2.1 According to a preset current mutation constant value, judging whether each current input at present mutates, wherein the judgment formula is as follows:
||I Φ (t)|-|I Φ (t-60ms)||>I D
in the formula I D For current mutation quantitative, | I Φ (t) | is the effective value of the current at time t, | I Φ (t-60 ms) | is the effective value of the current at the moment before 60 ms;
3.2.2 According to the preset fixed value of the zero-sequence current break variable), judging whether the current zero-sequence current breaks, wherein the judgment formula is as follows:
||I 0 (t)|-|I 0 (t-60ms)||>I 0D
in the formula I 0D For zero sequence current mutation quantitative determination, | I 0 (t) | is the effective value at time t of zero sequence current, | I 0 (t-60 ms) is an effective value of zero-sequence current at the moment before 60 ms;
3.2.3 According to a preset voltage mutation constant value, judging whether the current input voltage signal of each phase has mutation, wherein the judgment formula is as follows:
||U Φ (t)|-|U Φ (t-60ms)||>U D
in the formula of U D For voltage step quantitative determination, | U Φ (t) | is the effective value at time t of the phase voltage, | U Φ (t-60 ms) | is the effective value of the phase voltage at the moment before 60 ms;
3.2.4 According to a preset zero-sequence voltage mutation fixed value, judging whether the current zero-sequence voltage has mutation or not, wherein the judgment formula is as follows:
||U 0 (t)|-|U 0 (t-60ms)||>U 0D ,
in the formula of U 0D For zero sequence voltage step-change quantitative determination, | U 0 (t) | is the effective value at time t of zero sequence voltage, | U 0 (t-60 ms) | is the effective value of zero sequence voltage at the moment before 60 ms.
9. The method as claimed in claim 7, wherein the method comprises the steps of: in the step 3.3), the method for identifying the load parameters comprises the following steps:
3.3.1 Extracting phasor data of voltage and current which accord with disturbance judgment conditions in the same time period, and calculating according to the amplitudes of the voltage and the current to obtain active power and reactive power;
3.3.2 Setting a value range of a load parameter according to the phasor data in the step 3.3.1), further determining a search space, randomly generating an initial position and a speed of each particle, creating an objective function, and calculating to obtain an optimal extreme value and a global optimal value of the 0 th generation position of each particle;
the calculation formulas of the initial position and the velocity of each particle are respectively as follows:
the calculation formulas of the optimal position of each particle in the 0 th generation and the global optimal particle position are respectively as follows:
wherein i =1,2, N is the number of particles, j =1,2, D is the dimension of the parameter,is the initial position of the jth parameter of the ith particle,for the initial velocity of the jth parameter of the ith particle, rand (0, 1) generates a random number between 0 and 1,is the maximum value of the jth parameter,is the minimum value of the jth parameter,the maximum moving speed of the jth parameter,the minimum moving speed for the jth parameter,bestx, the optimal position of the ith particle in generation 0 0 For the optimal positions of all particles in the 0 th generation, para () is a function for solving a position vector according to an objective function, f () is an objective function, namely the deviation square sum between the predicted values (P _ P, Q _ P) and the actual measured values (P, Q) of the active power and the reactive power, and the objective function is expressed as follows for n power measurement points:
3.3.3 Based on the optimal particle position of each particle of the previous generation and the position of the global optimal particle, the velocity of each particle of the current generation is obtained:
in the formula (I), the compound is shown in the specification,is the g +1 th generation velocity of the ith particle, omega is the inertia factor, c 1 And c 2 Respectively, the acceleration constants are the acceleration constants,bestx for the position of the ith particle at which the optimum value was obtained in g iterations g Positions where the optimal values are obtained in g iterations for all particles;
3.3.4 Update the position of each particle of the current generation according to the speed of each particle of the current generation to obtain the position of each particle of the current generation, namely
In the formula (I), the compound is shown in the specification,is the position of the ith particle in the g +1 generation;
3.3.5 According to the position and speed of each particle of the current generation, the optimal particle position and the global optimal particle position of each particle of the current generation are obtained by updating, namely
In the formula (I), the compound is shown in the specification,bestx for the position of the ith particle at which the optimum value was obtained in g +1 iterations g+1 Positions where optimal values are obtained for all particles in g +1 iterations;
3.3.6 3.3.3) to 3.3.5) until the set iteration times are met, and selecting a group of parameters with the minimum objective function value as a final load parameter identification result according to the optimal positions of all the particles in each iteration.
CN201711015719.2A 2017-10-25 2017-10-25 The load parameter device for identifying and its method at a kind of electric system plant stand end Active CN107831383B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201711015719.2A CN107831383B (en) 2017-10-25 2017-10-25 The load parameter device for identifying and its method at a kind of electric system plant stand end

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201711015719.2A CN107831383B (en) 2017-10-25 2017-10-25 The load parameter device for identifying and its method at a kind of electric system plant stand end

Publications (2)

Publication Number Publication Date
CN107831383A true CN107831383A (en) 2018-03-23
CN107831383B CN107831383B (en) 2019-10-25

Family

ID=61649375

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201711015719.2A Active CN107831383B (en) 2017-10-25 2017-10-25 The load parameter device for identifying and its method at a kind of electric system plant stand end

Country Status (1)

Country Link
CN (1) CN107831383B (en)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111948446A (en) * 2020-07-20 2020-11-17 江阴长仪集团有限公司 Self-adaptive load identification method and intelligent electric energy meter

Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20050283346A1 (en) * 2004-05-24 2005-12-22 Elkins Harold E Ii Distributed generation modeling system and method
CN103472736A (en) * 2013-09-24 2013-12-25 广西电网公司 Load modeling device based on real-time disturbance data
CN103884931A (en) * 2014-03-06 2014-06-25 电子科技大学 Testing and recording device for load characteristics of transformer substation bus
CN104134999A (en) * 2014-08-06 2014-11-05 国家电网公司 Power-distribution-network measurement effectiveness analysis practical calculation method based on multiple data sources
CN106340874A (en) * 2016-10-17 2017-01-18 南方电网科学研究院有限责任公司 Identification decision-making method and system for power load decomposition
CN106485339A (en) * 2015-08-31 2017-03-08 中车大连电力牵引研发中心有限公司 A kind of part throttle characteristics of power system determines method and system
CN106815677A (en) * 2016-12-09 2017-06-09 国网北京市电力公司 The recognition methods of non-intrusion type load and device

Patent Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20050283346A1 (en) * 2004-05-24 2005-12-22 Elkins Harold E Ii Distributed generation modeling system and method
CN103472736A (en) * 2013-09-24 2013-12-25 广西电网公司 Load modeling device based on real-time disturbance data
CN103884931A (en) * 2014-03-06 2014-06-25 电子科技大学 Testing and recording device for load characteristics of transformer substation bus
CN104134999A (en) * 2014-08-06 2014-11-05 国家电网公司 Power-distribution-network measurement effectiveness analysis practical calculation method based on multiple data sources
CN106485339A (en) * 2015-08-31 2017-03-08 中车大连电力牵引研发中心有限公司 A kind of part throttle characteristics of power system determines method and system
CN106340874A (en) * 2016-10-17 2017-01-18 南方电网科学研究院有限责任公司 Identification decision-making method and system for power load decomposition
CN106815677A (en) * 2016-12-09 2017-06-09 国网北京市电力公司 The recognition methods of non-intrusion type load and device

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111948446A (en) * 2020-07-20 2020-11-17 江阴长仪集团有限公司 Self-adaptive load identification method and intelligent electric energy meter

Also Published As

Publication number Publication date
CN107831383B (en) 2019-10-25

Similar Documents

Publication Publication Date Title
CN102279327B (en) On-line monitoring and state evaluation system for photovoltaic grid-connected power generation
CN103887815B (en) Based on wind energy turbine set parameter identification and the Dynamic Equivalence of service data
CN110133393B (en) Power consumption monitoring system and method based on non-invasive monitoring technology
CN112531694A (en) AC/DC hybrid power grid universe real-time simulation method based on digital twinning technology
Fang et al. Application of gray relational analysis to k-means clustering for dynamic equivalent modeling of wind farm
CN102170127B (en) Method for locating prime motor disturbance source triggering forced power oscillation
CN105938578A (en) Large-scale photovoltaic power station equivalent modeling method based on clustering analysis
CN104392135A (en) Probabilistic optimal power flow calculation method for alternating-current and direct-current systems of offshore wind power plants subjected to VSC-HVDC (voltage source converter-high voltage direct current) grid connection
CN202041593U (en) Running state evaluating device for new energy grid-connected power station
CN111628494A (en) Low-voltage distribution network topology identification method and system based on logistic regression method
Wang et al. Data-driven probabilistic small signal stability analysis for grid-connected PV systems
CN114123344A (en) Power system inertia evaluation method and device based on adaptive recursive least squares
CN105989206B (en) Wind power plant and photovoltaic plant model verification method based on fast reaction generator
CN105956760B (en) Intelligent power distribution network situation perception method based on multivariate time-space information modeling
CN105245188A (en) Photovoltaic inverter energy consumption characteristic on-line prediction method and device
Ni et al. A review of line loss analysis of the low-voltage distribution system
CN112564090B (en) MBLDA-based AC/DC system transient voltage stability monitoring method
CN107831383A (en) The load parameter device for identifying and its method at a kind of power system plant stand end
Perez et al. Suitability of voltage stability study methods for real-time assessment
CN103956827B (en) A kind of Detecting Power Harmonics control system based on the micro-electrical network of many power supplys
Zhang et al. A data-driven method for power system transient instability mode identification based on knowledge discovery and XGBoost algorithm
CN103178519B (en) The method of power oscillation of power system disturbing source is located in real time based on SCADA data
CN110635474A (en) Power grid dynamic trajectory trend prediction method based on long-term and short-term memory network
Shen et al. Data-driven equivalent inertia partition estimation of power systems
Wan et al. Weighted islanding detection for DC microgrid based on random forest classification

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant