A dynamic management and control system and method for electrical energy data

Abstract

This invention relates to the field of power management and control, specifically to a dynamic management and control system and method for electrical energy data, comprising: an EMS monitoring module, a load power module, a state prediction module, a power supply balancing module, and a dynamic response module. The EMS monitoring module is used to acquire real-time power, the load power module is used to output the active power curve, the state prediction module is used to determine the charging and discharging state of the global variables of the EMS, the power supply balancing module performs power supply balancing settings for PCS equipment, and the dynamic response module is used to adjust the charging and discharging power output of each PCS. This invention can prevent reverse current impact on power equipment, avoid backfeeding problems in the power system, optimize energy storage revenue, reduce the impact of abnormal current on PCS and batteries, improve energy utilization efficiency, maximize the release of energy storage value, suppress grid voltage fluctuations through proactive defense strategies, and improve the accuracy of grid billing.

Description

Technical Field

[0001] This invention relates to the field of power management and control, specifically to a dynamic management and control system and method for electrical energy data. Background Technology

[0002] An Electric Energy Management System (EMS) is a comprehensive automated control system for the power transmission process. It is used to control the production, transmission, and distribution of electricity. It includes components such as Supervisory Control and Data Acquisition (SCADA), power generation control, and network analysis. It can monitor the grid status in real time, adjust the output of generator sets, and meet the power generation demand.

[0003] When the energy storage converter (PCS) in the EMS supplies power to the grid, if the EMS fails to coordinate the output of the PCS and the new energy inverter in real time, there may be a situation where the power flows back to an unexpected area due to abnormal system configuration or control. This can cause the power to flow back to the upstream grid or back to other loads, which can not only cause problems with grid billing and reduce equipment revenue, but may also trigger circuit overvoltage protection and damage grid equipment.

[0004] Existing technologies protect the normal operation of the PCS by adding directional protection relays or setting reverse power protection voltages, but this requires sophisticated grid monitoring methods. In the context of microgrids such as photovoltaic and wind power, the power output is complex, the PCS discharge fluctuation margin is small, the protection action is not timely enough, and the dynamic anti-reverse current effect of the EMS system is poor. Summary of the Invention

[0005] The purpose of this invention is to provide a dynamic management and control system and method for electrical energy data to solve the problems mentioned in the background art.

[0006] To solve the above-mentioned technical problems, the present invention provides the following technical solution: a dynamic management and control system for electrical energy data, comprising: an EMS monitoring module, a load power module, a status prediction module, a power supply balance module, and a dynamic response module;

[0007] The EMS monitoring module is used to obtain the real-time power of the current load side through the energy meter and transmit the meter data to the EMS system using the Modbus TCP protocol. The EMS system uses an industrial real-time database to store the data, eliminates data noise through moving average filtering, collects the instantaneous power of the circuit at regular intervals, and dynamically adjusts the EMS sampling frequency according to the load fluctuation rate. It also cyclically obtains the load power data from the global variables of the power grid for the instantaneous power.

[0008] The load power module is used to transform the load power data, decompose the harmonic components and fundamental components in the power curve, determine the active power of the circuit, calibrate the power offset, correct the power factor angle, and output the corrected active power curve.

[0009] The state prediction module is used to determine the stability of active power based on historical power curves. Based on the autocorrelation coefficient, standard deviation and confidence interval of historical data, it dynamically updates the maximum error threshold and calculates the power reference value on a rolling basis based on historical data. When the deviation of active power from the power reference value exceeds the predetermined maximum error threshold for charging or discharging for a certain period of time, it determines that the global variables of the EMS are in a charging or discharging state. At the same time, it predicts the power trend according to the integrated LSTM / ARIMA model and predicts the charging and discharging state of the global variables of the EMS system in the next cycle.

[0010] The power supply balancing module is used to define a global variable structure, which includes power values ​​and timestamps. When the global variable is in a charging or discharging state, the instantaneous reverse current power of the circuit is calculated according to the active power curve. The power supply balancing is set in the PCS device of the power system according to the instantaneous reverse current power. At the same time, the register address of the PCS and the CAN frame data are parsed, and the status flag bit of the PCS device is updated.

[0011] The dynamic response module is used to determine the numerical relationship between the instantaneous reverse current power in the global variable and the sum of the maximum discharge power currently set in all PCS when the global variable is in a charging or discharging state. It calculates the charging and discharging power output of each PCS register according to the numerical relationship, sets the power output status of all PCS in the current cycle and the next cycle, monitors the PCS battery, disconnects when the charging and discharging capacity is higher than the risk value, and completes the power synchronization of the load-side PCS in the current cycle.

[0012] Furthermore, the EMS monitoring module includes: an energy metering unit, a data cleaning unit, and an interface communication unit;

[0013] The power metering unit is used to obtain instantaneous load power through the power meter and uses anti-aliasing filter + synchronous sampling technology to process instantaneous load power;

[0014] The data cleaning unit consists of a database located within the EMS, used to store sampled data and remove abnormal data using a Kalman filter.

[0015] The interface communication unit is used to connect the energy meter, EMS and PCS via network cable and network port, and push data in real time using ModbusTcp protocol.

[0016] Furthermore, the load power module includes: a power conversion unit and a turns ratio calibration unit;

[0017] The power conversion unit is used to generate a power curve, and windowed wavelet transform or FFT is used to extract the fundamental and harmonic components in the power.

[0018] The transformer ratio calibration unit is used to calibrate the power offset through the CT / PT transformer ratio, perform a moving average on the instantaneous power, and correct the active power.

[0019] Furthermore, the state prediction module includes: a power stabilization unit and a deviation prediction unit;

[0020] The power stabilization unit is used to calculate the autocorrelation coefficient of the historical active power curve using a sliding window to determine the stability of historical power generation data.

[0021] The deviation prediction unit is used to determine the dynamic charge and discharge threshold, predict the power trend in the next cycle, and adjust the PCS power in advance.

[0022] Furthermore, the power supply balancing module includes: a global variable unit, a reverse current judgment unit, and a status flag unit;

[0023] The global variable unit is used to define global variables in EMS and store them using Redis, displaying circuit power curves, charging and discharging status and alarm status.

[0024] The reverse current judgment unit is used to calculate the instantaneous reverse current power of the circuit based on the amount of overflow of the active power curve within the window.

[0025] The status flag unit is used to determine the charging and discharging status of the PCS register and update the PCS status flag bits.

[0026] Furthermore, the dynamic response module includes: a variable adjustment unit and a PCS setting unit;

[0027] The variable adjustment unit is used to determine the relationship between the transformer's maximum power data and the instantaneous reverse power in the global variables;

[0028] The PCS setting unit is used to set the battery power output of all PCS according to numerical relationships.

[0029] A method for dynamic management and control of electrical energy data includes the following steps:

[0030] Step S1. The instantaneous load power is sampled by the power meter sampling circuit, and the sampling frequency is dynamically adjusted according to the load fluctuation rate. The sampling results are transmitted to the EMS system. The EMS system defines global variables of the power grid, cyclically obtains the instantaneous load power in the global variables of the power grid, and outputs discrete power curves. The EMS is an electric energy management system.

[0031] Step S2. The discrete power curve is processed by windowed wavelet transform or FFT transform to extract the fundamental component and harmonic components. After correcting the power factor angle, the active power curve is obtained.

[0032] Step S3. Calculate the power reference value and the maximum error threshold for charging and discharging based on historical power data. By determining whether the active power exceeds the error range, the charging and discharging status of the global variables is obtained.

[0033] Step S4. When the global variable is in a charging or discharging state, calculate the instantaneous reverse current power of the circuit based on the overflow amount of the active power curve within the error range, perform battery balancing settings for each PCS device according to the instantaneous reverse current power, and update the PCS status flag bit. The PCS is an energy storage converter.

[0034] Step S5. Determine the numerical relationship between the instantaneous reverse current power in the global variables and the sum of the maximum discharge power of all PCS, determine the charge and discharge power output of each PCS battery, set the power output status of all PCS, and complete the power synchronization of the load-side PCS in the current cycle.

[0035] Furthermore, step S1 includes:

[0036] Step S11. Obtain the instantaneous load power on the grid load side using an anti-aliasing filter or synchronous sampling technology through an energy meter. The hardware interface of the energy meter is compatible with the communication interface of the EMS and supports Modbus RTU / TCP, DL / T645, IEC 61850 and Modbus Tcp protocols.

[0037] Step S12. The energy meter dynamically adjusts the sampling frequency according to the load fluctuation rate, so that the sampling frequency v = v0 + k·(P1-P2) / t0, where P1 and P2 are the power of the previous sampling and the load power obtained in the current sampling, respectively, t0 is the previous sampling interval, v0 is the basic sampling frequency, and k is the preset fluctuation adjustment coefficient.

[0038] Step S13. For each sampling, the sampling result is uploaded to the EMS system through the communication port. The EMS system uses an industrial real-time database to store data and eliminates data noise through moving average filtering. A global variable structure is defined in the EMS system. The global variable contains power value and timestamp, representing the charging and discharging power of all PCS batteries to the grid.

[0039] The instantaneous load power in the global variables of the power grid is obtained in a loop and stored in a global variable structure. The relationship between instantaneous load power and time is fitted in time order to obtain discrete power curves.

[0040] Furthermore, step S2 includes:

[0041] Step S21. Lock the fundamental frequency using a phase-locked loop, synchronously acquire voltage and current data using an energy meter, and perform windowed wavelet transform or FFT transform on the discrete power curve to calculate the initial active power:

[0042]

[0043] Where Pw is the initial active power, h is the harmonic order designation, H is the total harmonic order, and V... h and I h The voltage and current of the h-th harmonic are respectively, θ h Let be the phase difference between voltage and current in the h-th harmonic;

[0044] Step S22. The power offset is calibrated by CT / PT ratio, and the fundamental component is averaged to obtain the calibrated active power Pu. The active power of each sampling point in the time domain is fitted to obtain the active power curve Pu(t).

[0045] Furthermore, step S3 includes:

[0046] Step S31. Input historical power data into the digital modeling tool, determine the mean, autocorrelation coefficient and standard deviation of the historical data, determine the rolling window period using the autocorrelation coefficient of the historical data, and take the rolling window length when the autocorrelation coefficient reaches its maximum value as the rolling window period.

[0047] Step S32. Take the average value of the active power curve within the rolling window period as the power reference value. With a confidence level of 90%-95%, determine the maximum error threshold for charging and discharging, so that the probability of the power within the rolling window period being within the error interval [P0-w1, P0+w2] is higher than the confidence level, where P0 is the power reference value, w1 is the global variable maximum error threshold for charging, and w2 is the maximum error threshold for discharging.

[0048] Step S33. Continuously monitor the active power curve. When the active power curve is higher than the upper limit of the error interval, determine that the global variable is in a discharging state. When the active power curve is lower than the lower limit of the error interval, determine that the global variable is in a charging state.

[0049] Furthermore, step S4 includes:

[0050] Step S41. When the global variable is in the charging state, the instantaneous reverse current power of the circuit is the lower bound of the error interval minus the instantaneous load power. When the global variable is in the discharging state, the instantaneous reverse current power of the circuit is the instantaneous load power minus the upper bound of the error interval.

[0051] Step S42. Set the power supply balance in the PCS device of the power system according to the instantaneous reverse current power, and at the same time parse the register address of the PCS and the CAN frame data to update the status flag bit of the PCS device.

[0052] Furthermore, step S5 includes:

[0053] Step S51. Determine the charging and discharging power output of the PCS battery:

[0054] When the global variable is in the discharge state, determine whether the instantaneous reverse current power in the global variable is greater than the sum of the maximum discharge power of all PCS. If it is greater, set the discharge power of all PCS to the maximum discharge power. If it is not greater, set the discharge power of all PCS to the instantaneous reverse current power / number of PCS.

[0055] When the global variable is in the charging state, determine whether the difference between the maximum power of the circuit transformer and the instantaneous load power is greater than the sum of the maximum discharge power set by all PCS. If it is greater, set the discharge power of all PCS to the maximum discharge power. If it is not greater, set the charging power of all PCS to the difference between the maximum power of the transformer and the instantaneous load power / the number of PCS.

[0056] Step S52. Set the power output status of all PCS to complete the power synchronization of the load-side PCS in the current cycle.

[0057] Compared with the prior art, the beneficial effects achieved by the present invention are:

[0058] 1. This invention obtains the real-time power of the current load side through an energy meter and transmits it to the EMS system. It cyclically obtains the load power data from the global variables based on the real-time power, transforms the load power data, determines the active power of the circuit, thereby judging the power direction of the PCS, and pre-adjusting the control mode of the PCS to prevent the current from back impacting the power equipment and avoid the problem of backfeeding in the power system.

[0059] 2. This invention introduces the stability of active power based on historical records, calculates the autocorrelation coefficient and maximum error range, judges and predicts the charging and discharging state of global variables based on the deviation of active power from the maximum error range, sets up PCS equipment in the power system to balance power transmission, accurately controls the timing of discharge, optimizes energy storage benefits, reduces the impact of abnormal current on PCS and batteries, improves energy utilization efficiency, maximizes the release of energy storage value, and avoids technical risks.

[0060] 3. Based on the circuit charging and discharging status, this invention determines whether the load power data in the global variables is greater than the sum of the maximum charging and discharging power currently set for all PCS, thereby setting the discharge power of all PCS. This avoids energy storage from participating in peak-valley arbitrage due to reverse current interruption. Through the active defense strategy of EMS, it achieves precise matching of energy storage, photovoltaics, and load, suppresses grid voltage fluctuations, and improves the accuracy of grid billing. Attached Figure Description

[0061] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings:

[0062] Figure 1 This is a schematic diagram of the structure of a dynamic management and control system for electrical energy data according to the present invention;

[0063] Figure 2 This is a schematic diagram illustrating the steps of a dynamic management and control method for electrical energy data according to the present invention. Detailed Implementation

[0064] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0065] Please see Figure 1 The present invention provides a technical solution: a dynamic management and control system for electrical energy data, comprising: an EMS monitoring module, a load power module, a status prediction module, a power supply balance module, and a dynamic response module;

[0066] The EMS monitoring module is used to obtain the real-time power of the current load side through the energy meter and transmit the meter data to the EMS system using the Modbus TCP protocol. The EMS system uses an industrial real-time database to store the data, eliminates data noise through moving average filtering, collects the instantaneous power of the circuit at regular intervals, and dynamically adjusts the EMS sampling frequency according to the load fluctuation rate. It also cyclically obtains the load power data from the global variables of the power grid for the instantaneous power.

[0067] The EMS monitoring module includes: an energy metering unit, a data cleaning unit, and an interface communication unit;

[0068] The power metering unit is used to obtain instantaneous load power through the power meter and uses anti-aliasing filter + synchronous sampling technology to process instantaneous load power;

[0069] The data cleaning unit consists of a database located within the EMS, used to store sampled data and remove abnormal data using a Kalman filter.

[0070] The interface communication unit is used to connect the energy meter, EMS and PCS via network cable and network port, and push data in real time using ModbusTcp protocol.

[0071] The load power module is used to transform the load power data, decompose the harmonic components and fundamental components in the power curve, determine the active power of the circuit, calibrate the power offset, correct the power factor angle, and output the corrected active power curve.

[0072] The load power module includes: a power conversion unit and a transformer ratio calibration unit;

[0073] The power conversion unit is used to generate a power curve, and windowed wavelet transform or FFT is used to extract the fundamental and harmonic components in the power.

[0074] The transformer ratio calibration unit is used to calibrate the power offset through the CT / PT transformer ratio, perform a moving average on the instantaneous power, and correct the active power.

[0075] The state prediction module is used to determine the stability of active power based on historical power curves. Based on the autocorrelation coefficient, standard deviation and confidence interval of historical data, it dynamically updates the maximum error threshold and calculates the power reference value on a rolling basis based on historical data. When the deviation of active power from the power reference value exceeds the predetermined maximum error threshold for charging or discharging for a certain period of time, it determines that the global variables of the EMS are in a charging or discharging state. At the same time, it predicts the power trend according to the integrated LSTM / ARIMA model and predicts the charging and discharging state of the global variables of the EMS system in the next cycle.

[0076] The state prediction module includes: a power stabilization unit and a deviation prediction unit;

[0077] The power stabilization unit is used to calculate the autocorrelation coefficient of the historical active power curve using a sliding window to determine the stability of historical power generation data.

[0078] The deviation prediction unit is used to determine the dynamic charge and discharge threshold, predict the power trend in the next cycle, and adjust the PCS power in advance.

[0079] The power supply balancing module is used to define a global variable structure, which includes power values ​​and timestamps. When the global variable is in a charging or discharging state, the instantaneous reverse current power of the circuit is calculated according to the active power curve. The power supply balancing is set in the PCS device of the power system according to the instantaneous reverse current power. At the same time, the register address of the PCS and the CAN frame data are parsed, and the status flag bit of the PCS device is updated.

[0080] The power supply balancing module includes: a global variable unit, a reverse current judgment unit, and a status flag unit;

[0081] The global variable unit is used to define global variables in EMS and store them using Redis, displaying circuit power curves, charging and discharging status and alarm status.

[0082] The reverse current judgment unit is used to calculate the instantaneous reverse current power of the circuit based on the amount of overflow of the active power curve within the window.

[0083] The status flag unit is used to determine the charging and discharging status of the PCS register and update the PCS status flag bits.

[0084] The dynamic response module is used to determine the numerical relationship between the instantaneous reverse current power in the global variable and the sum of the maximum discharge power currently set in all PCS when the global variable is in a charging or discharging state. It calculates the charging and discharging power output of each PCS register according to the numerical relationship, sets the power output status of all PCS in the current cycle and the next cycle, monitors the PCS battery, disconnects when the charging and discharging capacity is higher than the risk value, and completes the power synchronization of the load-side PCS in the current cycle.

[0085] The dynamic response module includes: a variable adjustment unit and a PCS setting unit;

[0086] The variable adjustment unit is used to determine the relationship between the transformer's maximum power data and the instantaneous reverse power in the global variables;

[0087] The PCS setting unit is used to set the battery power output of all PCS according to numerical relationships.

[0088] like Figure 2 As shown, a method for dynamic management and control of electrical energy data includes the following steps:

[0089] Step S1. The instantaneous load power is sampled by the power meter sampling circuit, and the sampling frequency is dynamically adjusted according to the load fluctuation rate. The sampling results are transmitted to the EMS system. The EMS system defines global variables of the power grid, cyclically obtains the instantaneous load power in the global variables of the power grid, and outputs discrete power curves. The EMS is an electric energy management system.

[0090] Step S1 includes:

[0091] Step S11. Obtain the instantaneous load power on the grid load side using an anti-aliasing filter or synchronous sampling technology through an energy meter. The hardware interface of the energy meter is compatible with the communication interface of the EMS and supports Modbus RTU / TCP, DL / T645, IEC 61850 and Modbus Tcp protocols.

[0092] Step S12. The energy meter dynamically adjusts the sampling frequency according to the load fluctuation rate, so that the sampling frequency v = v0 + k·(P1-P2) / t0, where P1 and P2 are the power of the previous sampling and the load power obtained in the current sampling, respectively, t0 is the previous sampling interval, v0 is the basic sampling frequency, and k is the preset fluctuation adjustment coefficient.

[0093] Step S13. For each sampling, the sampling result is uploaded to the EMS system through the communication port. The EMS system uses an industrial real-time database to store data and eliminates data noise through moving average filtering. A global variable structure is defined in the EMS system. The global variable contains power value and timestamp, representing the charging and discharging power of all PCS batteries to the grid.

[0094] The instantaneous load power in the global variables of the power grid is obtained in a loop and stored in a global variable structure. The relationship between instantaneous load power and time is fitted in time order to obtain discrete power curves.

[0095] Step S2. The discrete power curve is processed by windowed wavelet transform or FFT transform to extract the fundamental component and harmonic components. After correcting the power factor angle, the active power curve is obtained.

[0096] Step S2 includes:

[0097] Step S21. Lock the fundamental frequency using a phase-locked loop, synchronously acquire voltage and current data using an energy meter, and perform windowed wavelet transform or FFT transform on the discrete power curve to calculate the initial active power:

[0098]

[0099] Where Pw is the initial active power, h is the harmonic order designation, H is the total harmonic order, and V... h and I h The voltage and current of the h-th harmonic are respectively, θ h Let be the phase difference between voltage and current in the h-th harmonic;

[0100] Step S22. The power offset is calibrated by CT / PT ratio, and the fundamental component is averaged to obtain the calibrated active power Pu. The active power of each sampling point in the time domain is fitted to obtain the active power curve Pu(t).

[0101] Step S3. Calculate the power reference value and the maximum error threshold for charging and discharging based on historical power data. By determining whether the active power exceeds the error range, the charging and discharging status of the global variables is obtained.

[0102] Step S3 includes:

[0103] Step S31. Input historical power data into the digital modeling tool, determine the mean, autocorrelation coefficient and standard deviation of the historical data, determine the rolling window period using the autocorrelation coefficient of the historical data, and take the rolling window length when the autocorrelation coefficient reaches its maximum value as the rolling window period.

[0104] Step S32. Take the average value of the active power curve within the rolling window period as the power reference value. With a confidence level of 90%-95%, determine the maximum error threshold for charging and discharging, so that the probability of the power within the rolling window period being within the error interval [P0-w1, P0+w2] is higher than the confidence level, where P0 is the power reference value, w1 is the global variable maximum error threshold for charging, and w2 is the maximum error threshold for discharging.

[0105] Step S33. Continuously monitor the active power curve. When the active power curve is higher than the upper limit of the error interval, determine that the global variable is in a discharging state. When the active power curve is lower than the lower limit of the error interval, determine that the global variable is in a charging state.

[0106] Step S4. When the global variable is in a charging or discharging state, calculate the instantaneous reverse current power of the circuit based on the overflow amount of the active power curve within the error range, perform battery balancing settings for each PCS device according to the instantaneous reverse current power, and update the PCS status flag bit. The PCS is an energy storage converter.

[0107] Step S4 includes:

[0108] Step S41. When the global variable is in the charging state, the instantaneous reverse current power of the circuit is the lower bound of the error interval minus the instantaneous load power. When the global variable is in the discharging state, the instantaneous reverse current power of the circuit is the instantaneous load power minus the upper bound of the error interval.

[0109] Step S42. Set the power supply balance in the PCS device of the power system according to the instantaneous reverse current power, and at the same time parse the register address of the PCS and the CAN frame data to update the status flag bit of the PCS device.

[0110] Step S5. Determine the numerical relationship between the instantaneous reverse current power in the global variables and the sum of the maximum discharge power of all PCS, determine the charge and discharge power output of each PCS battery, set the power output status of all PCS, and complete the power synchronization of the load-side PCS in the current cycle.

[0111] Step S5 includes:

[0112] Step S51. Determine the charging and discharging power output of the PCS battery:

[0113] When the global variable is in the discharge state, determine whether the instantaneous reverse current power in the global variable is greater than the sum of the maximum discharge power of all PCS. If it is greater, set the discharge power of all PCS to the maximum discharge power. If it is not greater, set the discharge power of all PCS to the instantaneous reverse current power / number of PCS.

[0114] When the global variable is in the charging state, determine whether the difference between the maximum power of the circuit transformer and the instantaneous load power is greater than the sum of the maximum discharge power set by all PCS. If it is greater, set the discharge power of all PCS to the maximum discharge power. If it is not greater, set the charging power of all PCS to the difference between the maximum power of the transformer and the instantaneous load power / the number of PCS.

[0115] Step S52. Set the power output status of all PCS to complete the power synchronization of the load-side PCS in the current cycle.

[0116] Example: There are 3 PCS in the power grid. Every 15ms, the power in the global variables of the circuit is monitored. The instantaneous reverse current power is 3kW and the instantaneous load power is 40kW. The circuit is in a discharging state. The sum of the maximum discharge power of the three PCS is 6kW. The Modbus TCP protocol is used to send the 06 function code to the three PCS to set the discharge power of the three PCS to 1kW.

[0117] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0118] Finally, it should be noted that the above descriptions are merely preferred embodiments of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A dynamic management method of electric energy data, characterized in that, The method comprises the following steps: Step S1. Instantaneous load power is sampled by an electric energy meter sampling circuit, and the sampling frequency is dynamically adjusted according to the load fluctuation rate, and the sampling result is transmitted to an EMS system, the EMS system defines a global variable of the power grid, the instantaneous load power in the global variable of the power grid is cyclically obtained, and a discrete power curve is output, wherein the EMS is an electric energy management system; Step S2. The discrete power curve is processed by using a windowed wavelet transform or an FFT transform, the fundamental component and the harmonic component are extracted, and after the power factor angle is corrected, an active power curve is obtained; Step S3. The maximum error threshold of power reference value and charging and discharging is calculated based on historical power data, and the charging and discharging state of the global variable is obtained by judging whether the active power exceeds the error interval; Step S4. When the global variable is in the charging or discharging state, the instantaneous reverse flow power of the circuit is calculated according to the overflow amount of the active power curve in the error interval, the battery balancing of each PCS device is set according to the instantaneous reverse flow power, and the PCS state flag bit is updated, wherein the PCS is a power storage converter; Step S5. The numerical relationship between the instantaneous reverse flow power in the global variable and the sum of the maximum discharging power of all PCSs is judged, the charging and discharging power output of each PCS battery is determined, the power output state of all PCSs is set, and the power synchronization of the load side PCS in the current period is completed.

2. The method of claim 1, wherein: Step S1 comprises: Step S11. The instantaneous load power of the load side of the power grid is obtained by using an anti-aliasing filter or a synchronous sampling technology through an electric energy meter, the hardware interface of the electric energy meter is compatible with the communication interface of the EMS, and supports Modbus RTU / TCP, DL / T645, IEC61850 and Modbus Tcp protocols; Step S12. The electric energy meter dynamically adjusts the sampling frequency according to the load fluctuation rate, so that the sampling frequency v=v0+k·(P1-P2) / t0, P1 and P2 are the load powers obtained by sampling the previous time and the current time respectively, t0 is the last sampling interval, v0 is the basic sampling frequency, and k is a preset fluctuation adjustment coefficient; Step S13. The sampling result is uploaded to the EMS system through the communication port every time the sampling is performed, the EMS system stores data by using an industrial real-time database, eliminates data noise by using a sliding average filter, defines a global variable structure in the EMS system, the global variable includes a power value and a time stamp, and represents the charging and discharging power of all PCS batteries to the power grid; The instantaneous load power in the global variable of the power grid is cyclically obtained, is stored in the global variable structure, the relationship between the instantaneous load power and time is fitted in chronological order, and a discrete power curve is obtained.

3. The method of claim 2, wherein: Step S2 comprises: Step S21. The fundamental frequency is locked by using a phase-locked loop, the voltage and current data are synchronously obtained by using the electric energy meter, the discrete power curve is subjected to a windowed wavelet transform or an FFT transform, and the initial active power is calculated: where Pw is the initial active power, h is the harmonic number index, H is the total number of harmonics, V h and I h are the voltage and current of the hth harmonic, respectively, and θ h is the phase difference between voltage and current in the hth harmonic. Step S22. The power offset is calibrated by using a CT / PT variable ratio, the moving average of the fundamental component is obtained, the calibrated active power Pu is obtained, and the active power of each sampling point in the time domain range is fitted to obtain the active power curve Pu(t).

4. The method of claim 3, wherein: Step S3 comprises: Step S31. Input historical power data into a digital modeling tool, determine the mean, autocorrelation coefficient and standard deviation of the historical data, determine the rolling window period with the autocorrelation coefficient of the historical data, and take the length of the rolling window when the autocorrelation coefficient is maximum as the rolling window period; Step S32. Take the mean of the active power curve in the rolling window period as the power reference value, and determine the maximum error threshold of charging and discharging within the confidence interval of 90%-95%, so that the probability of the power in the rolling window period being within the error interval [P0-w1, P0+w2] is higher than the confidence interval, wherein P0 is the power reference value, w1 is the global variable maximum error threshold for charging, and w2 is the maximum error threshold for discharging; Step S33. Continuously monitor the active power curve, and when the active power curve is higher than the upper limit of the error interval, it is determined that the global variable is in the discharging state, and when the active power curve is lower than the lower limit of the error interval, it is determined that the global variable is in the charging state.

5. The method of claim 4, wherein: Step S4 includes: Step S41. When the global variable is in the charging state, the instantaneous reverse flow power of the circuit is the lower limit of the error interval minus the instantaneous load power, and when the global variable is in the discharging state, the instantaneous reverse flow power of the circuit is the instantaneous load power minus the upper limit of the error interval; Step S42. According to the instantaneous reverse flow power, set the power sending balance of the PCS device in the power system, and at the same time, analyze the register address and CAN frame data of the PCS to update the PCS device state flag bit; Step S5 includes: Step S51. Determine the charging and discharging power output of the PCS battery: When the global variable is in the discharging state, determine whether the instantaneous reverse flow power in the global variable is greater than the sum of the maximum discharging power of all PCSs, if it is greater, set the discharging power of all PCSs to the maximum discharging power, and if it is not greater, set the discharging power of all PCSs to the instantaneous reverse flow power / PCS number; When the global variable is in the charging state, determine whether the difference between the maximum power of the circuit transformer and the instantaneous load power is greater than the sum of the maximum discharging power set by all PCSs, if it is greater, set the discharging power of all PCSs to the maximum discharging power, and if it is not greater, set the charging power of all PCSs to the difference between the maximum power of the transformer and the instantaneous load power / PCS number; Step S52. Set the power output state of all PCSs to complete the power synchronization of the load side PCS in the current period.

6. An electric energy data dynamic management system, characterized in that, The system includes the following modules: an EMS monitoring module, a load power module, a state prediction module, a power sending balance module, and a dynamic response module; The EMS monitoring module is used to obtain the real-time power of the current load side through an electric energy meter and transmit the meter data to an EMS system using a Modbus Tcp protocol, the EMS system stores data using an industrial real-time database, eliminates data noise through a moving average filter, collects circuit instantaneous power at a fixed time, dynamically adjusts the EMS sampling frequency according to the load fluctuation rate, and obtains the load power data in the global variable of the power grid for the instantaneous power cycle. The load power module is used for transforming load power data, decomposing harmonic components and fundamental components in a power curve, determining circuit active power, calibrating power offset, correcting power factor angle, and outputting corrected active power curve; The state prediction module is used for judging stability of active power according to historical power curve, dynamically updating maximum error threshold based on autocorrelation coefficient, standard deviation and confidence interval of historical data, calculating power reference value based on historical data, judging that the EMS global variable is in charging or discharging state when deviation of active power from the power reference value exceeds the maximum error threshold of predetermined charging or discharging for more than a certain time length, and predicting power trend and charging or discharging state of the EMS system global variable in the next period according to the integrated LSTM / ARIMA model; The power transmission balance module is used for defining a global variable structure containing power value and time stamp, calculating instantaneous reverse current power of the circuit according to the active power curve when the global variable is in the charging or discharging state, setting power transmission balance of the PCS device in the power system according to the instantaneous reverse current power, and analyzing register address and CAN frame data of the PCS to update the PCS device state flag bit; The dynamic response module is used for judging the numerical relationship between the instantaneous reverse current power in the global variable and the sum of maximum discharging power of all existing PCS settings when the global variable is in the charging or discharging state, calculating charging or discharging power output of each PCS register according to the numerical relationship, setting power output states of all PCSs in the current period and the next period, and monitoring the PCS battery to be disconnected when the charging or discharging capacity is higher than the risk value, thereby completing power synchronization of the load side PCS in the current period.

7. The dynamic management system for electric energy data according to claim 6, characterized in that: The EMS monitoring module comprises an electric energy metering unit, a data cleaning unit and an interface communication unit. The electric energy metering unit is used for acquiring instantaneous load power through an electric energy meter and processing the instantaneous load power by using an anti-aliasing filter + synchronous sampling technology. The data cleaning unit is composed of a database arranged in the EMS and is used for storing sampling data and removing abnormal data by using a Kalman filter. The interface communication unit is used for connecting the electric energy meter, the EMS and the PCS through a network cable and a network port and pushing data in real time by using a Modbus Tcp protocol.

8. The dynamic management system for electric energy data according to claim 7, characterized in that: The load power module comprises a power transformation unit and a transformation ratio calibration unit. The power transformation unit is used for generating a power curve and extracting fundamental components and harmonic components in power by using windowed wavelet transform or FFT. The transformation ratio calibration unit is used for calibrating power offset by CT / PT transformation ratio, performing moving average on instantaneous power, and correcting active power. The state prediction module comprises an electric power stability unit and a deviation prediction unit. The electric power stability unit is used for calculating autocorrelation coefficient of historical active power curve by using a sliding window and judging stability of historical power generation data. The deviation prediction unit is used for determining a dynamic charging and discharging threshold, predicting power trend in the next period, and adjusting PCS power in advance.

9. The dynamic management system for electric energy data according to claim 8, characterized in that: The power transmission balance module comprises a global variable unit, a reverse current judgment unit and a state flag unit. The global variable unit is used for defining global variables in the EMS and adopts Redis storage to show circuit power curve, charging and discharging state and alarm state. The reverse flow judging unit is used for calculating the instantaneous reverse flow power of the circuit according to the overflow amount of the active power curve in the window. The state flag unit is used for judging the charging and discharging state of the PCS register and updating the PCS state flag bit.

10. The dynamic management system for electric energy data according to claim 9, characterized in that: The dynamic reaction module comprises a variable adjusting unit and a PCS setting unit. The variable adjusting unit is used for judging the relationship between the maximum power data of the transformer and the instantaneous reverse flow power in the global variable. The PCS setting unit is used for setting the battery power output of all PCSs according to the numerical relationship.

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