Three-phase imbalance compensation method and system for power distribution area

Abstract

The invention discloses a three-phase imbalance compensation method and system for a power distribution station area, and relates to the technical field of three-phase imbalance compensation, and the method comprises the steps: obtaining dynamic data in the power distribution station area, and carrying out the preprocessing of the dynamic data; constructing a digital twinborn model according to the dynamic data, and simulating operation scenes of a peak load scene and a valley load scene by changing a load condition and a power grid state; automatically adjusting a compensation strategy by using an intelligent optimization algorithm based on a result of the operation scene; and issuing the optimized compensation strategy to a compensation device in real time, and automatically adjusting the operation state by the compensation device according to the compensation strategy to realize real-time compensation of the three-phase imbalance. According to the method, the digital twinborn model is constructed, so that problems possibly occurring under different working conditions can be predicted in advance, and a more effective coping strategy is formulated; and the compensation strategy is automatically adjusted by applying an intelligent optimization algorithm, so that complex and changeable power grid conditions can be quickly adapted, and the compensation accuracy and timeliness are improved.

Description

Technical Field

[0001] The invention relates to the technical field of three-phase unbalanced compensation, and in particular to a three-phase unbalanced compensation method and system for a distribution station area. Background Art

[0002] With the continuous growth of electricity demand and the diversification of power equipment, distribution substations are facing increasingly complex load conditions and grid status changes. Traditional distribution substation management methods often have limitations when dealing with three-phase imbalance problems. In the past, the monitoring and control of distribution substations mainly relied on fixed parameter settings and regular manual inspections, which made it difficult to adapt to the dynamic changes of loads in real time and accurately. This method is not only inefficient, but also unable to compensate for three-phase imbalance in a timely and effective manner, which may lead to a decline in power quality, increased equipment losses, and instability in the power system. In the process of technological development, digital technology and intelligent algorithms have been gradually applied to the power field. When processing complex grid data and changing load conditions, optimization algorithms also have problems of insufficient accuracy and slow response speed. In recent years, with the advancement of sensor technology and the improvement of data processing capabilities, dynamic data of distribution substations can be obtained more accurately, but how to make full use of these data to build an effective digital twin model and implement an efficient and intelligent three-phase imbalance compensation strategy based on this is still a challenge facing current technology.

[0003] At present, there are many deficiencies in the technology for dealing with the three-phase imbalance problem in distribution stations, including: in terms of data collection, the data obtained by the existing technology is often not comprehensive and accurate enough, the ability to capture dynamic data is limited, the pre-processing means are relatively simple, and it is difficult to extract key and effective information; in terms of model construction, the existing model is difficult to accurately reflect the real and complex conditions of the distribution station area, and cannot effectively simulate important scenarios such as peak load and valley load by changing the load conditions and the power grid status; for the formulation of compensation strategies, the algorithm used has a low degree of intelligence, and cannot automatically adjust the compensation strategy quickly and accurately according to the results of the operating scenarios, resulting in poor compensation effects and inability to effectively cope with complex and changeable power grid conditions; in the implementation of the compensation strategy, there is a problem of delay in sending, the compensation device cannot respond in time, and it is difficult to achieve real-time compensation of three-phase imbalance; the existing technology lacks continuous and effective monitoring of the actual system operation status, and cannot timely feedback new data for updating model parameters and optimizing compensation strategies, making it difficult to maintain the adaptability and accuracy of the system for a long time. Summary of the invention

[0004] The present invention is proposed in view of the fact that when the compensation strategy is formulated, the compensation strategy cannot be adjusted automatically and quickly according to the results of the operation scenario, resulting in poor compensation effect and inability to effectively cope with complex and changeable power grid conditions.

[0005] Therefore, the problem to be solved by the present invention is how to provide a compensation strategy that is dynamically adjusted according to dynamic data, so as to improve the three-phase unbalanced compensation effect of the distribution station and effectively cope with the complex and changeable power grid conditions.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0007] In the first aspect, an embodiment of the present invention provides a method for compensating three-phase imbalance in a distribution station area, which includes obtaining dynamic data in the distribution station area and preprocessing the dynamic data; constructing a digital twin model based on the dynamic data and simulating peak load scenarios and valley load scenarios by changing the load conditions and the grid status; based on the results of the operating scenarios, automatically adjusting the compensation strategy using an intelligent optimization algorithm; sending the optimized compensation strategy to the compensation device in real time, and the compensation device automatically adjusts the operating status according to the compensation strategy to achieve real-time compensation for three-phase imbalance; continuously monitoring the operating status of the actual system, feeding back the re-acquired data to the digital twin model, and continuously updating the model parameters and optimizing the compensation strategy.

[0008] As a preferred solution of the three-phase unbalanced compensation method for the distribution station area described in the present invention, the dynamic data includes current, voltage, temperature and humidity data; the compensation device includes reactive power compensation equipment and an intelligent phase-changing switch.

[0009] As a preferred solution of the three-phase unbalanced compensation method for the distribution station area of ​​the present invention, the digital twin model is based on the LSTM network to make a preliminary prediction of the real-time load in the distribution station area, and obtains the first revised prediction value according to the influence of historical data, specifically: based on the output of the LSTM network, the real-time load in the distribution station area is preliminarily predicted to obtain a preliminary load prediction value Based on preliminary load forecasts According to the influence of the historical data, the first revised forecast value is obtained Based on the first revised prediction value Perform intelligent optimization algorithm to obtain the second revised prediction value

[0010] As a preferred solution of the three-phase unbalanced compensation method for the distribution station area of ​​the present invention, the preliminary load prediction value It is expressed by the following formula:

[0011]

[0012] in, is the initial load forecast value; α is its corresponding weight coefficient; L(t-Δt) is the historical load value at the past time t-Δt; T(t) is the temperature at time t; β is the influence coefficient of temperature; t is the current time; γ is the influence coefficient of time; δ is a constant offset;

[0013] The first corrected predicted value It is expressed by the following formula:

[0014]

[0015] in, is the first revised predicted value; is the preliminary load forecast value; L(ti) is the historical load value at the i-th time point in the past; N is the number of historical data considered; ε is a positive integer, usually 2 or 3.

[0016] As a preferred solution of the three-phase unbalanced compensation method for the distribution station area described in the present invention, wherein: the second corrected prediction value is obtained by performing an intelligent optimization algorithm on the first corrected prediction value, and the compensation strategy is adjusted by the second corrected prediction value, specifically: based on the second corrected prediction value Adjust the compensation strategy and get the first prediction result L t .

[0017] As a preferred solution of the three-phase unbalanced compensation method for the distribution station area of ​​the present invention, the specific formula of the intelligent optimization algorithm is as follows:

[0018]

[0019] in, is the second revised predicted value; is the first revised predicted value; Q is the number of items involved in the calculation; is a radical function of time; ln(2+tk) is a natural number logarithmic function.

[0020] As a preferred solution of the three-phase unbalanced compensation method for the distribution station area of ​​the present invention, the specific formula for adjusting the compensation strategy is as follows:

[0021]

[0022] Among them, L t is the first prediction result; is the second corrected prediction value; H is the number of sampling points in the time interval; sin(ωt i ) is a sine function, ω is the angular frequency; is an exponential function, σ is the attenuation coefficient; It is a complex function related to the upper limit T of the time interval.

[0023] In the second aspect, in order to further solve the above-mentioned technical problems, the embodiments of the present invention provide a three-phase unbalanced compensation system for a distribution station area, which includes: a data acquisition module for collecting dynamic data of the distribution area; a model construction module for building a digital twin model based on the collected dynamic data; a strategy adjustment module for automatically adjusting the compensation strategy according to the results of the operating scenario and the use of an intelligent optimization algorithm; a compensation adjustment module for automatically adjusting the operating state of the compensation device according to the compensation strategy; and a closed-loop control module for feeding back new data to the digital twin model, continuously updating the model parameters and optimizing the compensation strategy.

[0024] In a third aspect, an embodiment of the present invention provides a computer device, comprising a memory and a processor, wherein the memory stores a computer program, wherein: when the computer program is executed by the processor, any step of a three-phase unbalanced compensation method for a distribution station area as described in the first aspect of the present invention is implemented.

[0025] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein: when the computer program is executed by a processor, any step of a three-phase unbalanced compensation method for a distribution station area as described in the first aspect of the present invention is implemented.

[0026] The beneficial effects of the present invention are as follows: the present invention constructs a digital twin model by utilizing a recurrent neural network LSTM and dynamic data. The digital twin model can predict in advance possible problems under different working conditions, thereby formulating more effective response strategies; the intelligent optimization algorithm is used to automatically adjust the compensation strategy, which can quickly adapt to complex and changeable power grid conditions, improve the accuracy and timeliness of compensation, continuously monitor the actual system operation status and feedback data, continuously update model parameters and optimize compensation strategies, forming a benign closed-loop system, so that the entire compensation system can be continuously improved and optimized with time and power grid changes, and always maintain a good compensation effect. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work. Among them:

[0028] Figure 1 This is a flow chart for implementing the present invention in Example 1. DETAILED DESCRIPTION

[0029] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the accompanying drawings.

[0030] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0031] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0032] Example 1

[0033] Reference Figure 1 , which is the first embodiment of the present invention, and provides a method for compensating three-phase unbalance in a distribution station area, comprising the following steps:

[0034] S1: Obtain dynamic data within the distribution station area and pre-process the dynamic data.

[0035] Preferably, Figure 1 The implementation process of the present invention is shown as follows. First, dynamic data in the distribution area is collected and a digital twin model is constructed. By changing the load conditions and the grid status, the peak load scenario and the valley load scenario operation scenario are simulated. The compensation strategy is automatically adjusted according to the results of the operation scenario, and then the optimized compensation strategy is sent to the compensation device in real time. The compensation device automatically adjusts the operation status according to the compensation strategy, continuously monitors the operation status of the actual system, and feeds back the data acquired again to the digital twin model, continuously updating the model parameters and optimizing the compensation strategy.

[0036] Furthermore, the dynamic data includes current, voltage, temperature and humidity data.

[0037] Preferably, preprocessing ensures data quality and consistency by performing real-time preprocessing of dynamic data on data nodes, including data cleaning, noise reduction, and standardization.

[0038] S2: Build a digital twin model based on dynamic data and simulate peak load and valley load operation scenarios by changing load conditions and grid status.

[0039] Specifically, the digital twin model is based on the LSTM network to make a preliminary prediction of the real-time load in the distribution station area, obtain a preliminary load forecast value, and then use the load forecast value according to the historical data to obtain the first revised forecast value, which is as follows:

[0040] Based on the output of the LSTM network, a preliminary forecast of the real-time load in the distribution station area is made to obtain a preliminary load forecast value.

[0041] Based on preliminary load forecasts According to the influence of historical data, the first revised forecast value is obtained

[0042] Based on the first revised prediction value Perform intelligent optimization algorithm to obtain the second revised prediction value

[0043] Specifically, historical data includes electrical parameters, time, environment, and operating status;

[0044] Specifically, the intelligent optimization algorithm is an existing technology. The intelligent optimization algorithm can automatically adjust the compensation strategy according to the simulation results of the digital twin model and the operating status of the actual system, thereby improving the accuracy and efficiency of compensation.

[0045] Further, the preliminary load forecast value It is expressed by the following formula:

[0046]

[0047] in, is the initial load forecast value; α is its corresponding weight coefficient; L(t-Δt) is the historical load value at the past time t-Δt; T(t) is the temperature at time t; β is the influence coefficient of temperature; t is the current time; γ is the influence coefficient of time; δ is a constant offset, usually 2 or 3;

[0048] Furthermore, the first revised prediction value It is expressed by the following formula:

[0049]

[0050] in, is the first revised predicted value; is the preliminary load forecast value; L(ti) is the historical load value at the i-th time point in the past; N is the number of historical data considered; ε is a positive integer.

[0051] S3: Based on the results of the operating scenario, the compensation strategy is automatically adjusted using an intelligent optimization algorithm.

[0052] Preferably, the second corrected prediction value is obtained by performing an intelligent optimization algorithm on the first corrected prediction value, and the compensation strategy is adjusted by the second corrected prediction value, specifically:

[0053] Based on the second revised prediction value Adjust the compensation strategy and get the first prediction result L t .

[0054] Specifically, the specific formula of the intelligent optimization algorithm is as follows:

[0055]

[0056] in, is the second revised predicted value; is the first revised predicted value; N is the number of items involved in the calculation; is a root function of time, reflecting that with the passage of time, its influence on the revised forecast value gradually tends to be flat; ln(2+tk) is a natural number logarithmic function, which means that the influence weight of the recent past time point on the current revised forecast value is relatively large, while the influence weight of the distant past time point on the current revised forecast value is relatively small.

[0057] Furthermore, the specific formula for adjusting the compensation strategy is as follows:

[0058]

[0059] Among them, L t is the first prediction result; is the second corrected prediction value; H is the number of sampling points in the time interval; sin(ωt i ) is a sine function; ω is the angular frequency; is an exponential function, and σ is the attenuation coefficient, which is used to attenuate or adjust the weight of other parts in the summation term, thereby reflecting the different importance of time distance to the revised prediction value; It is a complex function related to the upper limit T of the time interval.

[0060] Furthermore, complex functions It is expressed by the following formula:

[0061]

[0062] in, is a complex function; T is the upper limit of the time interval, and the upper limit of the time interval is the time value used to define the end point of a specific time period in the definition of the time period.

[0063] S4: The optimized compensation strategy is sent to the compensation device in real time. The compensation device automatically adjusts the operating state according to the compensation strategy to achieve real-time compensation for three-phase imbalance.

[0064] Furthermore, the compensation device includes a reactive power compensation device and an intelligent phase-changing switch.

[0065] Preferably, by using static VAR generator and static VAR compensator equipment, the reactive power is quickly adjusted to improve the imbalance of three-phase current, and by intelligently controlling the phase-changing switch, the unbalanced load is redistributed among the three phases to make the three-phase load tend to be balanced.

[0066] Preferably, the compensation device automatically adjusts the operating state according to the optimized compensation strategy, and can achieve rapid response and accurate compensation for three-phase imbalance.

[0067] S5: Continuously monitor the operating status of the actual system, feed back the acquired data into the digital twin model, and continuously update the model parameters and optimize the compensation strategy.

[0068] Specifically, the optimization compensation strategy includes the following steps: continuously monitoring the grid operation status and compensation effect, feeding new data into the optimization model to further improve and perfect the compensation strategy, and regularly re-evaluating and updating the compensation strategy to adapt to new situations as the grid structure, load changes, and technology develop.

[0069] Preferably, the operating status of the actual system is continuously monitored, and the data is fed back to the digital twin model, so that the model parameters are continuously updated and the compensation strategy is optimized, forming a dynamic closed-loop management system that can promptly detect problems and changes in the system and improve the adaptability and reliability of the system.

[0070] The present embodiment also provides a three-phase unbalanced compensation system for a distribution station area, including: a data acquisition module for collecting dynamic data of the distribution area; a model construction module for building a digital twin model based on the collected dynamic data; a strategy adjustment module for automatically adjusting the compensation strategy based on the results of the operating scenario and using an intelligent optimization algorithm; a compensation adjustment module for automatically adjusting the operating state of the compensation device according to the compensation strategy; and a closed-loop control module for feeding new data back to the digital twin model, continuously updating the model parameters and optimizing the compensation strategy.

[0071] This embodiment also provides a computer device, which is applicable to a three-phase unbalanced compensation method for a distribution station area, and includes: a memory and a processor; the memory is used to store computer executable instructions, and the processor is used to execute computer executable instructions to implement a three-phase unbalanced compensation method for a distribution station area as proposed in the above embodiment.

[0072] The computer device may be a terminal, and the computer device includes a processor, a memory, a communication interface, a display screen and an input device connected via a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be achieved through WIFI, an operator network, NFC (near field communication) or other technologies. The display screen of the computer device may be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device may be a touch layer covering the display screen, or a key, trackball or touchpad provided on the housing of the computer device, or an external keyboard, touchpad or mouse, etc.

[0073] This embodiment also provides a storage medium on which a computer program is stored. When the program is executed by a processor, a three-phase unbalance compensation method for a distribution station area as proposed in the above embodiment is implemented; the storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (Static Random Access Memory, referred to as SRAM), electrically erasable programmable read-only memory (Electrically Erasable Programmable Read-Only Memory, referred to as EEPROM), erasable programmable read-only memory (Erasable Programmable Read-Only Memory, referred to as EPROM), programmable read-only memory (Programmable Red-Only Memory, referred to as PROM), read-only memory (Read-Only Memory, referred to as ROM), magnetic memory, flash memory, disk or optical disk.

[0074] In summary, the present invention uses the recurrent neural network LSTM and dynamic data to build a digital twin model, which can better adjust the compensation strategy quickly and accurately according to the results of the operating site, effectively cope with complex and changeable power grid conditions, and improve the three-phase unbalanced compensation effect; through the closed-loop control module, new data feedback can be used in time to update model parameters and optimize compensation strategies, so that the adaptability and accuracy of the system can be maintained for a long time.

[0075] Example 2

[0076] Referring to Tables 1 to 3, the second embodiment of the present invention is shown. This embodiment is different from the first embodiment in that, in order to verify its beneficial effects, operating data and related instructions of the present invention in an actual environment are provided.

[0077] Table 1 shows the line loss rate, equipment failure rate and comprehensive power quality index data collected in the peak load scenario and the valley load scenario in this embodiment.

[0078] Table 1 Comparison table of performance differences in distribution station areas

[0079]

[0080] Table 2 shows the power supply reliability, voltage fluctuation amplitude and harmonic content data collected in the peak load scenario and the valley load scenario in this embodiment.

[0081] Table 2 Comparison of key elements of distribution station areas

[0082]

[0083] Table 3 shows the transformer overload rate, power outage duration, and user complaint rate data collected in the peak load scenario and the valley load scenario in this embodiment.

[0084] Table 3 Analysis of the operation status of distribution station area

[0085]

[0086] It can be seen from the above table that the present invention can deal with the three-phase imbalance problem in the distribution station area with a more accurate compensation strategy, a more efficient execution capability and a more significant beneficial effect compared with the prior art. It can effectively meet the high requirements of power grid operation and improve the stability and reliability of the power system.

[0087] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A three-phase unbalance compensation method for a distribution station area, characterized by: include: Obtain dynamic data within the distribution station area and pre-process the dynamic data; Building a digital twin model based on the dynamic data and simulating peak load scenario and valley load scenario operation scenarios by changing load conditions and grid status; Based on the results of the operating scenarios, the compensation strategy is automatically adjusted using intelligent optimization algorithms; The optimized compensation strategy is sent to the compensation device in real time, and the compensation device automatically adjusts the operating state according to the compensation strategy to achieve real-time compensation for three-phase imbalance; The operating status of the actual system is continuously monitored, and the acquired data is fed back to the digital twin model to continuously update the model parameters and optimize the compensation strategy.

2. The three-phase unbalance compensation method for a distribution station area according to claim 1, characterized in that: The dynamic data includes current, voltage, temperature and humidity data; The compensation device comprises a reactive power compensation device and an intelligent phase-changing switch.

3. The three-phase unbalance compensation method for a distribution station area as claimed in claim 2, characterized in that: The digital twin model is based on the LSTM network to make a preliminary prediction of the real-time load in the distribution station area, and obtains the load prediction value. The first revised prediction value is obtained by the load prediction value and the historical data, which is specifically: Based on the output of the LSTM network, a preliminary forecast of the real-time load in the distribution station area is made to obtain a preliminary load forecast value. Based on preliminary load forecasts According to the influence of the historical data, the first revised forecast value is obtained Based on the first revised prediction value Perform intelligent optimization algorithm to obtain the second corrected prediction value 4. The three-phase unbalance compensation method for a distribution station area as claimed in claim 3, characterized in that: The initial load forecast value It is expressed by the following formula: in, is the initial load forecast value; α is its corresponding weight coefficient; L(t-Δt) is the historical load value at the past time t-Δt; T(t) is the temperature at time t; β is the influence coefficient of temperature; t is the current time; γ is the influence coefficient of time; δ is a constant offset; The first corrected predicted value It is expressed by the following formula: in, is the first revised predicted value; is the preliminary load forecast value; L(ti) is the historical load value at the i-th time point in the past; N is the number of historical data considered; ε is a positive integer.

5. The three-phase unbalance compensation method for a distribution station area as claimed in claim 4, characterized in that: The second revised prediction value is obtained by performing an intelligent optimization algorithm on the first revised prediction value, and the first prediction result is obtained by adjusting the compensation strategy through the second revised prediction value, specifically: Based on the second revised prediction value Adjust the compensation strategy and get the first prediction result L t .

6. The three-phase unbalance compensation method for a distribution station area as claimed in claim 5, characterized in that: The specific formula of the intelligent optimization algorithm is as follows: in, is the second revised predicted value; is the first revised predicted value; Q is the number of items involved in the calculation; is a radical function of time; ln(2+tk) is a natural number logarithmic function.

7. The three-phase unbalance compensation method for a distribution station area as claimed in claim 6, characterized in that: The specific formula for adjusting the compensation strategy is as follows: Among them, L t is the first prediction result; is the second corrected prediction value; H is the number of sampling points in the time interval; sin(ωt i ) is a sine function, ω is the angular frequency; is an exponential function, σ is the attenuation coefficient; It is a complex function related to the upper limit T of the time interval.

8. A three-phase unbalanced compensation system for a power distribution area, based on a three-phase unbalanced compensation method for a power distribution area according to any one of claims 1 to 7, characterized in that: include: Data acquisition module, used to collect dynamic data of the power distribution area; Model building module, used to build a digital twin model based on the collected dynamic data; The strategy adjustment module is used to automatically adjust the compensation strategy according to the results of the operation scenario and the application of intelligent optimization algorithms; A compensation adjustment module, used for the compensation device to automatically adjust the operating state according to the compensation strategy; The closed-loop control module is used to feed new data back to the digital twin model, continuously update model parameters and optimize compensation strategies.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method for compensating three-phase unbalance in a distribution station area according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of a three-phase unbalance compensation method for a distribution station area according to any one of claims 1 to 7 are implemented.

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