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

Abstract

The present invention relates to a load parameter identification device and method at the station end of a power system, comprising the following steps: 1) collecting the voltage and current signals of the secondary loop of the power grid in real time, and converting and filtering the obtained voltage and current signals to perform discrete Sampling to obtain the original sampling values of voltage and current signals; 2) Real-time acquisition of the switching state information of the secondary circuit of the power grid, and performing anti-shake and discrimination on the obtained switching state information and converting it into a digital signal to obtain the breakdown of the line switch. 3) Perform phasor calculation and load parameter identification according to the original sampling values of voltage and current signals, and obtain the phasor calculation results and load parameter identification results; 4) The Switch status information, phasor data obtained in step 3) and load model parameter identification results are displayed through the man-machine interface and uploaded to the dispatching master station.

Description

A load parameter identification device and method for power system station end

technical field

The invention belongs to the technical field of dynamic monitoring of power systems, and in particular relates to a load parameter identification device and method at a station end of a power system.

Background technique

The power system model is very important to the simulation analysis and calculation of power system operation, and the modeling of its load parameters plays a key role in the application of the power system model. Different load models and parameters are selected, and there are differences in the dynamic response results in the simulation analysis of the power system, and even affect the judgment of the stability of the power system. To analyze different power system stability problems, the requirements for load models are also different. Different load models that meet the actual load position, composition, structure and other conditions must be established according to the application purpose of the load model and the specific requirements of the corresponding problems for the load model. , to ensure the accuracy of the simulation analysis.

In recent years, researchers from various countries have carried out a series of fruitful work in load modeling, and applied it in engineering practice. However, there are still a series of problems to be solved in the existing load model identification work. First, there is the problem of tracking the time-varying nature of the load model. Similar to load forecasting, the time-varying nature of the load model is also reflected in the short-term different periods and changes over time. Among the existing load modeling methods, the statistical synthesis method uses the interval cycle method to track the time-varying characteristics of the load model with a low frequency, and its workload is relatively large; the overall detection and identification method is based on the post-fault response, which can Whether to carry out the overall detection and identification of the load model depends on whether the fault exists, and the overall detection and identification method is not ideal for tracking the time-varying load model. Whether the load identification can be carried out cannot be selected artificially but depends on the existence of the fault. Secondly, it is the problem of model description for the diversity of load models. The model structure adopted in the load model identification mainly uses the induction motor to describe the characteristics of the dynamic load, and uses the polynomial model or the power exponential model to describe the characteristics of the static load. However, with the rapid development of smart grid technology in recent years, new energy, energy storage, electric vehicles and other new electrical equipment are connected to the grid on a large scale, and the large-scale popularization of distributed power generation and various energy storage devices makes it difficult to Like in the traditional power system, it can be clearly distinguished which node is a complete load node, and certain distributed power generation or energy storage devices will also be connected under the load-dominated busbar. In addition, with the large-scale popularization of power electronic equipment, the proportion of power electronic loads represented by inverter air conditioners in the power load is also increasing. The characteristics of dynamic loads are difficult to be fully described by induction motors. It is necessary to introduce New model structure to handle. Finally, even if only considering the load model structure composed entirely of induction motors and static loads, the existing research has not considered the diversity problem caused by different parameters under the same model structure and the diversity of loads after passing through the transfer reactance. aggregation problem.

Contents of the invention

In view of the above problems, the object of the present invention is to provide a load parameter identification device and method at the station end of the power system, through which the actual measured synchrophasor data at the station end can be realized and the online identification of the dominant load parameters can be performed through the measured signal.

In order to achieve the above object, the present invention adopts the following technical solutions: a load parameter identification device at the station end of a power system, characterized in that it 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 to discretely sample the real-time collected voltage and current signals of the power system station end power grid to obtain the original sampled values of the voltage and current signals and send them to the logic calculation module; the second The data acquisition module is used to convert the input signal of the real-time collected power system station end grid into a digital signal and send it to the logic calculation module; Perform phasor calculation and load parameter identification on the signal, and send the phasor calculation results and load parameter identification results to the function management module; the function management module displays the received phasor calculation results and load parameter identification results in real time and storage, and upload to the dispatching master station.

The first data acquisition module includes an AC input module, a voltage/current conversion module, a first ADC module, and a second ADC module; the AC input module is used to collect current and voltage signals at the station end of the power system in real time and send them to the The voltage/current conversion module; the voltage/current conversion module filters and converts the received voltage and current signals, and sends the converted voltage signal to the first ADC module, and sends the converted current signal to the 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 the initial value sampling result to the logic calculation module.

The second data acquisition module includes a switch-in signal detection module and a micro-control unit module, the switch-in signal detection module measures the switch-in status information of the power grid in real time, and sends it to the micro-control unit module; the micro-control unit The module performs anti-shake and discrimination on the received input state information, converts it into a digital signal, and sends it to the logic calculation module.

The logic computing module includes an FPGA module, a first DSP module and a second DSP module; the FPGA performs grouping and data synchronization according to the input voltage and current signals, and sends them 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 signal, and the calculated phasor data is forwarded to the second DSP module; the second DSP module loads the received phasor data Parameter identification, and send the load parameter identification result to the function management module.

The function management module includes a CPU, a man-machine interface module, a communication module and a data storage module; after the CPU receives the data sent by the first DSP module and the second DSP module, the calculated phasor calculation result and The load parameter identification result is sent to the man-machine interface module, the data storage module and the communication module; the man-machine interface module displays the phasor calculation result and the load parameter identification result in real time; the data storage module is used to store the phasor calculation result and load parameter identification results; the communication module is used to upload the phasor calculation results and load parameter identification results sent by the CPU to the master dispatching station.

A method for identifying load parameters at the station end of a power system is characterized in that it includes the following steps: 1) Collecting voltage and current signals of a secondary circuit of a power grid in real time, and performing discrete sampling after converting and filtering the obtained voltage and current signals to obtain The original sampling values of voltage and current signals; 2) Real-time acquisition of the opening and closing state information of the secondary circuit of the power grid, and the obtained opening and closing state information is stabilized and judged and then converted into digital signals to obtain the opening and closing state information of the line switch It is used for the display of man-machine interface; 3) Perform phasor calculation and load parameter identification according to the original sampling values of voltage and current signals, and obtain the phasor calculation results and load parameter identification results; 4) Convert the switch status information in step 2) to , The phasor data and load parameter identification results obtained in step 3) are displayed through the man-machine interface and uploaded to the dispatching master station.

In said step 3), the method for performing phasor calculation and load parameter identification includes the following steps: 3.1) Perform real-time phasor calculation according to the original sampling values of voltage and current signals to obtain phasor data of voltage and current, including three steps: The phasor data of phase fundamental voltage and current and the phasor data of positive sequence, negative sequence and zero sequence voltage and current; 3.2) According to the phasor data of voltage and current obtained in step 3.1), the system disturbance is judged, and the disturbance is obtained The voltage and current phasor data of the discrimination condition; 3.3) Carry out the load parameter identification calculation according to the obtained voltage and current signal phasor data meeting the disturbance discrimination condition, and obtain the load parameter identification result.

In said step 3.2), the disturbance discrimination method comprises the following steps:

3.2.1) Judging whether the current input current of each phase has a sudden change according to the preset current sudden change value, the judgment formula is:

||I _Φ (t)|-|I _Φ (t-60ms)||＞I _D ，

In the formula, I _D is the fixed value of the current sudden change, |I _Φ (t)| is the effective value of the current at time t, and |I _Φ (t-60ms)| is the effective value at the moment before the current 60ms;

3.2.2) Judging whether the current zero-sequence current has a sudden change according to the preset zero-sequence current mutation value, the judgment formula is:

||I ₀ (t)|-|I ₀ (t-60ms)||＞I _0D ,

In the formula, I _0D is the constant value of zero-sequence current mutation, |I ₀ (t)| is the effective value of zero-sequence current at time t, and |I ₀ (t-60ms) is the effective value of zero-sequence current at time 60ms before;

3.2.3) According to the preset voltage mutation value, judge whether the current input voltage signal of each phase has a mutation, and the judgment formula is:

||U _Φ (t)|-|U _Φ (t-60ms)||＞U _D ，

In the formula, U _D is the fixed value of the voltage mutation, |U _Φ (t)| is the effective value of the phase voltage at time t, and |U _Φ (t-60ms)| is the effective value of the phase voltage at the time before 60ms;

3.2.4) Judging whether the current zero-sequence voltage has a sudden change according to the preset zero-sequence voltage mutation value, the judgment formula is:

||U ₀ (t)|-|U ₀ (t-60ms)||＞U _0D ,

In the formula, U _0D is the fixed value of zero-sequence voltage mutation, |U ₀ (t)| is the effective value of zero-sequence voltage at time t, and |U ₀ (t-60ms) is the effective value of zero-sequence voltage at time 60ms before.

In said step 3.3), the method for load parameter identification includes the following steps:

3.3.1) Extract the phasor data of voltage and current that meet the disturbance discrimination conditions in the same time period, and calculate the active power and reactive power according to the amplitude of the voltage and current;

3.3.2) Set the value range of load parameters according to the phasor data in step 3.3.1), and then determine the search space, randomly generate the initial position and velocity of each particle, create an objective function, and calculate the 0th generation of each particle The optimal extremum and global optimal value of the position;

The calculation formulas of the initial position and velocity of each particle are:

The calculation formulas of the optimal position of each particle in the 0th generation and the global optimal particle position are:

Among them, 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 i-th particle, For the initial velocity of the jth parameter of the i-th particle, rand(0,1) generates a random number between 0-1, is the maximum value of the jth parameter, is the minimum value of the jth parameter, is the maximum moving speed of the jth parameter, is the minimum moving speed of the jth parameter, is the optimal position of the i-th particle in the 0th generation, Bestx ⁰ is the optimal position of all particles in the 0th generation, para(.) is the function to obtain the position vector according to the objective function, f(.) is the objective function That is, the sum of the squares of deviations between the predicted values of active power and reactive power (P_p, Q_p) and the actual measured values (P, Q). For n power measurement points, the objective function is expressed as:

3.3.3) Based on the optimal particle position of each particle in the previous generation and the position of the global optimal particle, the velocity of each particle in the current generation is obtained:

In the formula, is the velocity of the i-th particle at generation g+1, ω is the inertia factor, c ₁ and c ₂ are the acceleration constants respectively, is the position of the i-th particle when it obtains the optimal value in g iterations, and Bestx ^g is the position of all particles when they obtain the optimal value in g iterations;

3.3.4) Update the position of each particle in the current generation according to the speed of each particle in the current generation, and obtain the position of each particle in the current generation, that is

In the formula, is the position of the i-th 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 updated, namely

In the formula, is the position of the i-th particle when it obtains the optimal value in the g+1 iteration, and Bestx ^g+1 is the position of all particles when they obtain the optimal value in the g+1 iteration;

3.3.6) Repeat 3.3.3) to 3.3.5) until the set number of iterations is satisfied, and according to the optimal position of all particles in each iteration, select a set of parameters with the smallest objective function value as the final load parameter Identification results.

Due to the adoption of the above technical scheme, the present invention has the following advantages: 1. The present invention uses two data acquisition modules to measure the secondary circuit of the power grid in real time, and performs phasor calculation and load parameter identification according to the real-time measurement data, which can quickly target real-time The measurement data is used for response calculation, which solves the problem of tracking the time-varying load model. 2. The present invention proposes the identification of load parameters by calculating the phasor method, and implements the application method through the hardware device, which effectively improves the calculation efficiency. 3. The present invention proposes a disturbance discrimination method for identification and calculation of load parameters, which can set disturbance parameters according to load measurement requirements, and has a wider application range.

Description of drawings

Fig. 1 is a schematic diagram of the hardware topology of the load identification device of the present invention;

Fig. 2 is a logical schematic diagram of the load identification device of the present invention.

Detailed ways

The present invention will be described in detail below in conjunction with the accompanying drawings and embodiments.

As shown in Fig. 1, a load parameter identification device at the station end of a power system proposed by 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 to discretely sample the real-time collected voltage and current signals of the power system power station end grid to obtain the original sampled values of the voltage and current signals and send them to the logic calculation module; the second data acquisition module is used to The input signal of the power system power station end grid collected in real time is converted into a digital signal and sent to the logic calculation module; the logic calculation module performs phasor calculation and load parameter identification based on the received original sampling values of voltage and current and the input signal. And send the phasor calculation results and load parameter identification results to the function management module; the function management module displays and stores the received phasor calculation results and load parameter identification results in real time, and uploads them to the dispatching master station.

The first data acquisition module includes an AC input module, a voltage/current conversion module, a first ADC module and a second ADC module. The AC input module is used to collect the current and voltage signals of the power grid at the station end of the power system in real time, and send them to the voltage/current conversion module; the voltage/current conversion module filters and converts the received voltage and current signals, and converts the converted voltage The signal is sent to the first ADC module, and the converted current signal is sent to the second ADC module; the first ADC module and the second ADC module perform analog-to-digital conversion and sampling on the received voltage signal and current signal respectively, and the initial The value sampling result is sent to the logic calculation module.

The second data acquisition module includes a switch-in signal detection module and an MCU (micro control unit) module, and the drive-in signal detection module collects the drive-in status information of the power system station end power grid in real time, and sends it to the MCU module; After anti-shake and discrimination, the binary input status information is converted into a digital signal and sent to the function module.

The logic computing module includes an FPGA module, a first DSP module and a second DSP module. The FPGA performs grouping and data synchronization according to the input voltage and current signals, and sends them 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; the calculated phasor data is forwarded to the second DSP module, and the second DSP module identifies the load parameters through the received phasor data.

The function management module includes CPU, man-machine interface module, communication module and data storage module. After receiving the data sent by the first DSP module and the second DSP module, the CPU sends the calculated phasor data and load parameter identification results to the man-machine interface module, data storage module and communication module respectively; the man-machine interface module displays the phase data in real time. phasor data and load parameter identification results; the data storage module is used to store phasor data and load parameter identification results; the communication module is used to upload the phasor data and load parameter identification results sent by the CPU to the dispatching master station.

In the above embodiments, there are one or two AC input modules. Each AC input module can collect 12 channels of voltage and 12 channels of current signals, and two AC input modules support signal collection at most 8 intervals.

As shown in Figure 2, based on the load parameter identification device at the station end of the power system, the present invention also provides a load parameter identification method at the station end of the power system, including the following steps:

1) Collect the voltage and current signals of the secondary loop of the power grid in real time, convert and filter the obtained voltage and current signals, and perform discrete sampling to obtain the original sampling values of the voltage and current signals.

2) Collect the switching state information of the secondary circuit of the power grid in real time, and convert the obtained switching state information into digital signals after anti-shake and discrimination, and obtain the opening and closing state information of the line switch.

3) Perform phasor calculation and load parameter identification based on the original sampling values of the voltage and current signals, and obtain the phasor calculation results and load parameter identification results.

The calculation method for phasor calculation and load model parameter identification includes the following steps:

3.1) Perform real-time phasor calculations based on the original sampling values of voltage and current signals to obtain phasor data of voltage and current.

Perform phasor calculations based on the original sampling values of the voltage and current signals to obtain the calculated amplitude and phase angle, including the phasors of the three-phase fundamental voltage and fundamental current, and the voltage phasors of positive sequence, negative sequence, and zero sequence and current phasor data. Suppose the measured analog signal is: Then its corresponding phasor form is where V is the amplitude, is the phase angle. When the maximum value of the measured analog signal v(t) appears in the second pulse, the phase angle of the phasor is 0 degrees; when the measured analog signal v(t) positive zero-crossing point is synchronized with the second pulse, the phase angle of the phasor for -90 degrees. When the magnitude V of the phasor is constant, the phase angle of the phasor The relationship with the frequency of the measured analog signal is: dφ/dt=2π(ff ₀ )f ₀ =50Hz; when the frequency of the measured analog signal is equal to 50Hz, the calculated phase angle remains unchanged; when the frequency of the measured analog signal is greater than When the frequency is 50Hz, the phase angle will gradually increase; when the frequency of the measured analog signal is less than 50Hz, the phase angle will gradually decrease. The external second pulse clock signal is introduced to unify the consistency of the data time scale to correspond to the section nodes of the measured data.

3.2) Perform system disturbance discrimination based on the obtained voltage and current phasor data, and obtain voltage and current phasor data that meet the disturbance discrimination conditions.

When judging the state of system disturbance based on the obtained voltage, current amplitude and phase angle phasor data, the judging conditions include phase current mutation, zero-sequence current mutation, phase voltage mutation and zero-sequence voltage mutation, and the specific judgment method includes the following steps :

3.2.1) Judging whether the current input current of each phase has a sudden change according to the preset current sudden change value, the judgment formula is:

||I _Φ (t)|-|I _Φ (t-60ms)||＞I _D (1)

In the formula, ID is the fixed value of the sudden change of current, |I _Φ (t)| is the effective value of current t time, |I _Φ ( _t -60ms)| is the effective value of current 60ms before.

3.2.2) Judging whether the current zero-sequence current has a sudden change according to the preset zero-sequence current mutation value, the judgment formula is:

||I ₀ (t)|-|I ₀ (t-60ms)||＞I _0D (2)

In the formula, I _0D is the fixed value of zero-sequence current sudden change, |I ₀ (t)| is the effective value of zero-sequence current at time t, |I ₀ (t-60ms)| is the effective value of zero-sequence current at the time before 60ms .

3.2.3) According to the preset voltage mutation value, judge whether the current input voltage signal of each phase has a mutation, and the judgment formula is:

||U _Φ (t)|-|U _Φ (t-60ms)||＞U _D (3)

In the formula, U _D is the constant value of the voltage mutation, |U _Φ (t)| is the effective value of the phase voltage at time t, and |U _Φ (t-60ms)| is the effective value of the phase voltage 60ms before.

3.2.4) Judging whether the current zero-sequence voltage has a sudden change according to the preset zero-sequence voltage mutation value, the judgment formula is:

||U ₀ (t)|-|U ₀ (t-60ms)||＞U _0D (4)

In the formula, U _0D is the fixed value of zero-sequence voltage mutation, |U ₀ (t)| is the effective value of zero-sequence voltage at time t, |U ₀ (t-60ms)| is the effective value of zero-sequence voltage 60ms before .

3.3) Carry out load parameter identification calculation according to the obtained voltage and current phasor data that meet the disturbance discrimination conditions, and obtain the load parameter identification result.

The present invention optimizes the deviation between the predicted value and the measured value of active power and reactive power through a differential evolution optimization algorithm, and the objective function is calculated from four quantities of voltage amplitude, voltage phase angle, active power and reactive power Solve the value of the state variable of the induction motor at the current moment from the measured value, and use the load model parameters to be optimized to solve the predicted value of the state variable of the load model at the next moment, and then calculate the two outputs of the load model active power and reactive power at the next moment The predicted value of the variable is then compared with the actual measured value to calculate the deviation. Differential evolution optimization uses the objective function calculated above to optimize the value of the objective function by changing the value of the load model parameters, and obtains a set of load model parameters that make the objective function reach the minimum value as the result of load model parameter identification. Specifically, the following steps are included:

3.3.1) Extract the voltage and current phasor data that meet the disturbance discrimination conditions in the same time period, and calculate the active power P and reactive power Q according to the amplitude of the voltage and current.

3.3.2) Set the value range of load parameters according to the phasor data in step 3.3.1), and then determine the search space, randomly generate the initial position and velocity of each particle, create an objective function, and calculate the 0th generation of each particle The optimal extremum and global optimal value of the position.

The calculation formulas of the initial position and velocity of each particle are:

The calculation formulas of the optimal position of each particle in the 0th generation and the global optimal particle position are:

Among them, 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 i-th particle, For the initial velocity of the jth parameter of the i-th particle, rand(0,1) generates a random number between 0-1, is the maximum value of the jth parameter, is the minimum value of the jth parameter, is the maximum moving speed of the jth parameter, is the minimum moving speed of the jth parameter, is the optimal position of the i-th particle in the 0th generation, Bestx ⁰ is the optimal position of all particles in the 0th generation, para(.) is the function to obtain the position vector according to the objective function, f(.) is the objective function That is, the sum of the squares of deviations between the predicted values of active power and reactive power (P_p, Q_p) and the actual measured values (P, Q). For n power measurement points, the objective function is expressed as:

3.3.3) Based on the optimal particle position of each particle in the previous generation and the position of the global optimal particle, the velocity of each particle in the current generation is obtained, namely

In the formula, is the velocity of the i-th particle at generation g+1, ω is the inertia factor, c ₁ and c ₂ are the acceleration constants respectively, is the position of the i-th particle when it obtains the optimal value in g iterations, and Bestx ^g is the position of all particles when they obtain the optimal value in g iterations.

3.3.4) Update the position of each particle in the current generation according to the speed of each particle in the current generation, and obtain the position of each particle in the current generation, that is

In the formula, is the position of the i-th 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 updated, namely

In the formula, is the position of the i-th particle when it obtains the optimal value in the g+1 iteration, and Bestx ^g+1 is the position of all particles when they obtain the optimal value in the g+1 iteration.

3.3.6) Repeat 3.3.3) to 3.3.5) until the set number of iterations is satisfied, and according to the optimal position of all particles in each iteration, select a set of parameters with the smallest objective function value as the final load parameter Identification results.

4) Display the switch status information in step 2), the phasor data and load parameter identification results obtained in step 3) through the man-machine interface, and upload them to the dispatching master station.

The above-mentioned embodiments are only used to illustrate the present invention, wherein the structure, connection mode and manufacturing process of each component can be changed to some extent, and any equivalent transformation and improvement carried out on the basis of the technical solution of the present invention should not 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.