A power intelligent distribution method and system for a micro-grid system

Abstract

The application relates to the technical field of power intelligent distribution, in particular to a power intelligent distribution method and system of a micro-grid system, which comprises the following steps: collecting bus voltages in the micro-grid system and load currents of each distributed power supply in real time; determining current current synchronism asynchronism degrees of each distributed power supply in a current time period; obtaining current trend difference degrees of each distributed power supply in the current time period; determining current current adjustment coefficients of each distributed power supply; correcting the load currents of each distributed power supply at a current time through the current current adjustment coefficients of each distributed power supply, obtaining voltage compensation amounts of each distributed power supply at the current time by combining line impedances of the distributed power supply and the bus voltages, and distributing powers of each distributed power supply. Therefore, the matching degree of power distribution in the micro-grid system is improved.

Description

Technical Field

[0001] This application relates to the field of intelligent power allocation technology, specifically to an intelligent power allocation method and system for a microgrid system. Background Technology

[0002] A microgrid is a small-scale power generation and distribution system composed of distributed power sources, energy storage devices, energy conversion devices, loads, monitoring and protection devices, etc. It can generate, distribute and manage electricity self-sufficiently, ensuring the reliability of power supply. With the popularization of renewable energy and the development of smart grid technology, the application prospects of microgrids are very broad.

[0003] Power allocation in microgrid systems is crucial for ensuring efficient and reliable system operation and achieving sustainable development. Effective power allocation not only improves energy utilization efficiency but also optimizes power resources, reduces waste, and ensures grid stability and meets user needs. However, distributed generation in microgrids is often affected by load variations. Load fluctuations can lead to unstable current output, and electrical parameters in the microgrid system may change with time and environmental conditions, affecting the accuracy of current output from distributed generation sources and reducing the precision of power allocation. Summary of the Invention

[0004] To address the aforementioned technical problems, the purpose of this application is to provide a method and system for intelligent power allocation in a microgrid system, the specific technical solution of which is as follows:

[0005] In a first aspect, embodiments of this application provide a method for intelligent power allocation in a microgrid system, the method comprising the following steps:

[0006] Real-time acquisition of bus voltage and load current of each distributed power source in the microgrid system;

[0007] Analyze the differences in load current between each distributed power source in the current time period and the same time period in its history over many days to determine the synchronization and asynchrony of current in each distributed power source in the current time period.

[0008] Based on the changing trend of the current synchronization and asynchrony of all currents of each distributed power source in the current time period, the difference in current trend of each distributed power source in the current time period is determined.

[0009] Based on the current trend difference, the load current of each distributed power source at the current moment and at the same moment over multiple historical days is weighted and summed to determine the current adjustment coefficient of each distributed power source.

[0010] By using the current adjustment coefficient of each distributed power source, the load current of each distributed power source at the current moment is corrected. Combined with the line impedance and bus voltage of the distributed power source, the voltage compensation amount of each distributed power source at the current moment is obtained, and the power of each distributed power source is allocated.

[0011] In one embodiment, determining the current synchronization and asynchrony includes:

[0012] The load current of each distributed power source at all times during the current time period is compiled into a real-time current sequence, and the load current of each distributed power source at all times during the same time period of each day during the current time period is compiled into a historical current sequence.

[0013] Calculate the absolute value of the difference between the elements at the same position in the real-time current sequence and each historical current sequence to obtain the current difference sequence.

[0014] Based on the numerical distribution of each current difference sequence, the synchronous and asynchronous degree of each current is determined.

[0015] In one embodiment, further determination of the current synchronization and asynchrony includes:

[0016] Calculate the mean and average absolute deviation of each current difference sequence, and use the product of the mean and the average absolute deviation as the synchronization and asynchrony of each current in the current time period of each distributed power source.

[0017] In one embodiment, determining the degree of difference in current trend includes:

[0018] For all current synchronicity and asynchrony of each distributed power source in the current time period, perform linear fitting and calculate the mean of the difference between all fitted values ​​and the true values ​​on the fitted line, which is denoted as the fitting error.

[0019] Calculate the mean of the current synchronization and asynchrony of all currents for each distributed power source in the current time period, and denot it as the first mean. Combine the fitting error with the first mean to determine the current trend difference, wherein the current trend difference is positively correlated with the fitting error and negatively correlated with the first mean.

[0020] In one embodiment, the current trend difference is the ratio of the fitting error to the first mean.

[0021] In one embodiment, determining the current adjustment coefficient includes:

[0022] Calculate the average load current of each distributed power source at the current moment over the same historical days, and record it as the second average. Calculate the product of the load current of each distributed power source at the current moment and the current trend difference, and record it as the first product. Calculate the difference between the value 1 and the current trend difference of each distributed power source in the current time period, and record it as the first difference. Determine the product of the first difference and the second average of each distributed power source at the current moment, and record it as the second product.

[0023] By combining the first product and the second product, and the maximum value in the real-time current sequence corresponding to each distributed power source at the current moment, the current adjustment coefficient of each distributed power source is determined.

[0024] In one embodiment, the sum of the first product and the second product is calculated, and the current adjustment factor of each distributed power source is the ratio of the sum of the distributed power sources to the maximum value.

[0025] In one embodiment, determining the voltage compensation amount of each distributed power source at the current moment includes:

[0026] Calculate the product of the load current of each distributed power source at the current moment and the current adjustment coefficient, which is used as the corrected current value of each distributed power source at the current moment. Calculate the product of the corrected current value and the line impedance of each distributed power source, which is recorded as the third product. The voltage compensation amount of each distributed power source is the difference between the bus voltage and the third product.

[0027] In one embodiment, the allocation of power to each distributed power source includes:

[0028] Based on the voltage compensation amount and actual voltage of each distributed power source at the current moment, the compensated voltage value of each distributed power source at the current moment is determined. Combined with the corrected current value of each distributed power source at the current moment, the power that each distributed power source should allocate is obtained.

[0029] Secondly, embodiments of this application also provide a power intelligent distribution system for a microgrid system, including a memory, a processor, and a computer program stored in the memory and running on the processor, wherein the processor executes the computer program to implement the steps of any of the methods described above.

[0030] This application has at least the following beneficial effects:

[0031] This application acquires the bus voltage and load current of each distributed power source in real time within a microgrid system; analyzes the difference between the load current of each distributed power source in the current time period and the load current of the same time period over several historical days, and determines the synchronization and asynchrony of the currents of each distributed power source in the current time period; it improves the sensitivity to load fluctuations and the reliability of correcting the current load current based on historical load current data, and captures the transient characteristics of distributed power sources; based on the changing trend of the synchronization and asynchrony of all currents of each distributed power source in the current time period, it determines the current trend difference of each distributed power source in the current time period; the determination of the current trend difference enhances the predictive ability of load periodicity, reflects the reference value of historical load currents, and makes the power allocation strategy more in line with actual needs; based on the current trend difference, it performs a weighted summation of the load current of each distributed power source at the current moment and the load current of the same time period over several historical days to determine the synchronization and asynchrony of the currents of each distributed power source in the current time period. The distributed power supply's current adjustment coefficient achieves a dynamic balance between short-term load current fluctuations and long-term trends. By assigning weights to real-time and historical load currents, it can quickly respond to sudden load changes and suppress erroneous adjustments caused by accidental events during power allocation, thus improving the robustness of subsequent power allocation. The current adjustment coefficient of each distributed power supply corrects its current load current. Combined with the line impedance and bus voltage of the distributed power supply, the voltage compensation amount of each distributed power supply is obtained, and the power of each distributed power supply is allocated. This real-time correction mechanism of the current adjustment coefficient ensures dynamic matching between power allocation and the capacity and status of the distributed power supply, avoiding output current instability caused by load fluctuations, improving the accuracy of load current, significantly suppressing voltage fluctuations and frequency deviations, and achieving synergistic optimization of power allocation in terms of efficiency, economy, and accuracy. Attached Figure Description

[0032] To more clearly illustrate the technical solutions and advantages in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0033] Figure 1 A flowchart illustrating the steps of a power intelligent allocation method for a microgrid system, provided in one embodiment of this application;

[0034] Figure 2 A flowchart for determining the voltage compensation amount for distributed power sources. Detailed Implementation

[0035] To further illustrate the technical means and effects adopted by this application to achieve the intended purpose of the invention, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effects of a power intelligent allocation method and system for a microgrid system proposed in this application. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0036] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains.

[0037] The following description, in conjunction with the accompanying drawings, details a specific scheme for a power intelligent allocation method and system for a microgrid system provided in this application.

[0038] Please see Figure 1 The diagram illustrates a flowchart of a power intelligent allocation method for a microgrid system according to an embodiment of this application. The method includes the following steps:

[0039] S1 collects the bus voltage and load current of each distributed power source in the microgrid system in real time.

[0040] In this embodiment, smart meters are installed on the main line of each distributed power source in the microgrid system to collect the voltage of the bus in real time, as well as the load current of each distributed power source during operation. The data collection is kept synchronously, and the collection frequency is set to 1Hz. The implementer can set it according to the actual situation. This embodiment does not impose any restrictions.

[0041] To improve the reliability of load current data analysis, this implementation uses the current moment plus the duration of 5 minutes before it as the current time period. The implementation user can set the length of the time period according to the actual situation.

[0042] S2, analyze the difference in load current between each distributed power source in the current time period and the same time period in its history, and determine the synchronization and asynchrony of each current in the current time period of each distributed power source.

[0043] To analyze the differences in load current between different distributed power sources during the same time period on different days, this embodiment obtains the load current for the same time period N days prior to the current time period. For example, if the current time is 18:00, then the current time period is 17:55~18:00. The embodiment obtains the load current from 17:55~18:00 on the day before the current, the load current from 17:55~18:00 on the two days before the current, and so on, up to the load current from 17:55~18:00 on the N days before the current, using this as historical data. In this embodiment, N=30 is set; implementers can set this value according to their actual situation, and this embodiment does not impose any restrictions.

[0044] During the operation of distributed power sources, the power generation of wind, hydro, and solar power varies across different seasons. For example, in summer, influenced by the subtropical high, the pressure gradient is smaller, wind speed is relatively weaker, and precipitation is relatively higher than in other seasons. Additionally, summer daylight hours can reach 14-15 hours, resulting in lower wind power generation and higher hydro and solar power generation. Therefore, the load current of distributed power sources varies with the seasons. Furthermore, since seasonal environmental changes are not instantaneous but rather have a time-dependent effect, the load current of different distributed power sources exhibits similar variation characteristics.

[0045] Based on the above analysis, for each distributed power source, this embodiment first arranges the load current at all times within the current time period into a real-time current sequence according to the time order. For the load current at all times within the same time period each day in the previous N days, the historical current sequence for each day is also arranged in time order.

[0046] For each distributed power source, the difference between the real-time current sequence and each historical current sequence is analyzed to determine the synchronous and asynchronous degree of each current in the current time period of each distributed power source. Here, the difference represents the degree of difference between two variables, which can be calculated by means of difference, absolute value of difference, ratio, etc. This embodiment does not limit it.

[0047] This embodiment calculates the absolute value of the difference between the real-time current sequence of each distributed power source and the elements at the same position in each historical current sequence, forming a current difference sequence. Based on the numerical distribution of elements in each current difference sequence, the synchronization and asynchrony of each current in the current time period of each distributed power source is calculated. The specific calculation formula is as follows:

[0048] In the formula, Let j be the current synchronization asynchronous degree of the i-th distributed power source in the current time period. Let be the mean of the j-th current difference sequence for the i-th distributed power source in the current time period. Let be the average absolute deviation of the current difference sequence of the i-th distributed power source in the current time period. The calculation of the average absolute deviation is a well-known technique, and the specific process will not be elaborated here.

[0049] It should be understood that during the operation of a distributed power source, the more similar the external environment is between two days, the closer the load current of the distributed power source will be. In this case, the difference in load current between the two days will be small, and the fluctuation range of the current difference will also be small. Because similar environmental conditions lead to a high degree of consistency in the load current of the distributed power source, the smaller the deviation, the higher the stability and consistency of the distributed power source's operating state. Increased similarity reduces the current synchronization and asynchrony between the historical current sequence and the real-time current sequence of the distributed power source. Under this operating state, the load of the distributed power source is relatively balanced.

[0050] S3. Based on the changing trend of the synchronization and asynchrony of all currents of each distributed power source in the current time period, determine the current trend difference of each distributed power source in the current time period.

[0051] Regarding seasonal cycle variations, due to the long cycle time, in the absence of sudden weather changes, the weather differences between different days within a local time period are often small. This results in a relatively concentrated distribution of load current in distributed power sources. Therefore, the current synchronization and asynchrony of all distributed power sources currently exhibit similar trends with minimal differences in trend changes. This indicates that the higher the reliability of historical current data, the greater its reference value, suggesting that the power grid is operating in a balanced and stable state.

[0052] Therefore, this embodiment employs the least squares method to perform linear fitting on the current synchronicity and asynchronicity of all distributed power sources in chronological order. The mean of the absolute values ​​of the differences between all fitted values ​​and the true values ​​on the fitted curve is calculated and denoted as the fitting error. In addition, the mean of the current synchronicity and asynchronicity of all distributed power sources in the current time period is calculated and denoted as the first mean. Combining the fitting error and the first mean, the current trend difference of each distributed power source in the current time period is determined. The current trend difference is positively correlated with the fitting error and negatively correlated with the first mean.

[0053] In this embodiment, as an example, the calculation method for the current trend difference is as follows:

[0054] In the formula, Let represent the current trend difference of the i-th distributed power source in the current time period. Let be the fitting error for the current time period of the i-th distributed power source. Let be the first mean value of the i-th distributed power source in the current time period.

[0055] It should be understood that during the seasonal operation of distributed power sources, the current synchronization and asynchrony changes are relatively similar within the same season. The fluctuations in current synchronization and asynchrony among all distributed power sources are small. Therefore, the fitting error of the fitted straight line is often small. The smaller the current trend difference, the higher the probability that the current trend of the distributed power source in the current time period is consistent with the historical trend of the same time period. This indicates that the load current of the distributed power source is relatively stable, and the historical load current data has high reliability. The current trend difference is intended to represent the proportion of the fitting error in the first mean. A higher proportion reflects larger fluctuations in the load current during the same historical time period, indicating a poorer load balance in the distributed power source.

[0056] S4. Based on the current trend difference, the load current of each distributed power source at the current moment and at the same moment in its history for multiple days is weighted and summed to determine the current adjustment coefficient of each distributed power source.

[0057] When the current trend difference value of distributed generation is small, it indicates that the operating status of distributed generation is relatively stable during the seasonal cycle. Historical data can be relied upon more heavily to correct the real-time current data of distributed generation, thereby ensuring the accuracy of the load current and enabling better power allocation in the microgrid. Based on the current trend difference value, a weighted sum of the load current of each distributed generation at the current moment and at the same moment N historical days is performed to determine the current adjustment coefficient of each distributed generation. The specific expression is as follows:

[0058] In the formula, Let be the current adjustment factor for the i-th distributed power source. Let be the load current of the i-th distributed power source at the current moment. Let represent the current trend difference of the i-th distributed power source in the current time period. Let be the average load current at the same time N days prior to the current time of the i-th distributed power source, denoted as the second average. Let be the maximum value in the real-time current sequence corresponding to the i-th distributed power source at the current moment. This is denoted as the first difference. This is denoted as the first product. This is denoted as the second product.

[0059] It should be understood that when a distributed power source is running, the more similar the current state at the current moment is to the current state at the same historical moment, the smaller the difference in the current trend of the distributed power source. The effect of correcting the current data at the current moment by using the current data at the same historical moment is better, the value of the current adjustment coefficient is more accurate, and it is more in line with the current operating state of the distributed power source, and the power allocation of the current distributed power source is more accurate.

[0060] This embodiment compares the weighted sum of the current values ​​of each distributed power source with its maximum load current. In contrast, normalization can unify the load current of distributed power sources with different capacities into a relatively proportional range, making distributed power sources with different capacities comparable during the control process, achieving fair and accurate power allocation among distributed power sources, while taking into account the actual capacity limitations of each distributed power source, and enhancing the robustness of the intelligent power allocation system.

[0061] S5 corrects the load current of each distributed power source at the current moment by using the current adjustment coefficient of each distributed power source, and obtains the voltage compensation amount of each distributed power source at the current moment by combining the line impedance and bus voltage of the distributed power source, and allocates the power of each distributed power source.

[0062] During the correction of distributed generation (DG) systems, the different line specifications used by different DGs result in varying line impedances, leading to different load powers for the DGs at the same voltage and causing instability in the microgrid operation. Therefore, by using the aforementioned indicators to correct the current load current of each DG, and combining this with the line impedance and bus voltage, the voltage compensation amount for each DG at the current moment is obtained. The specific calculation method is as follows:

[0063]

[0064]

[0065] In the formula, Let i be the corrected load current of the i-th distributed power source at the current moment. Let be the current adjustment factor for the i-th distributed power source. Let be the load current of the i-th distributed power source at the current moment. Let be the voltage compensation amount for the i-th distributed power source at the current moment. Let be the line impedance of the i-th distributed power source at the current moment. The measurement of line impedance is a well-known technique. This represents the current bus voltage of the microgrid system. This is denoted as the third product. The flowchart for determining the voltage compensation amount of a distributed power source is as follows: Figure 2 As shown.

[0066] The larger the current adjustment coefficient of the distributed power source, the more accurate the measured load current value of the distributed power source is, the closer the corrected load current is to the original load current, and the higher the accuracy of the corrected load current.

[0067] Furthermore, the sum of the voltage compensation amount and the actual voltage of each distributed power source at the current moment is calculated as the voltage value after compensation for each distributed power source at the current moment. Using the voltage value after compensation for each distributed power source at the current moment and the corrected load current, the power that each distributed power source should allocate at the current moment is obtained.

[0068] Based on the same inventive concept as the above method, this application embodiment also provides a power intelligent allocation system for a microgrid system, including a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, it implements the steps of any one of the above-described power intelligent allocation methods for a microgrid system.

[0069] It should be noted that the order of the embodiments described above is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. Furthermore, specific embodiments of this specification have been described above. Additionally, the processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired results. In some implementations, multitasking and parallel processing are possible or may be advantageous.

[0070] The various embodiments in this specification are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.

[0071] The above description is only a preferred embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, improvements, etc., made within the principles of this application should be included within the protection scope of this application.

Claims

1. A method for intelligent power allocation in a microgrid system, characterized in that, The method includes the following steps: Real-time acquisition of bus voltage and load current of each distributed power source in the microgrid system; Analyze the differences in load current between each distributed power source in the current time period and the same time period in its history over many days to determine the synchronization and asynchrony of current in each distributed power source in the current time period. Based on the changing trend of the current synchronization and asynchrony of all currents of each distributed power source in the current time period, the difference in current trend of each distributed power source in the current time period is determined. Based on the current trend difference, the load current of each distributed power source at the current moment and at the same moment over multiple historical days is weighted and summed to determine the current adjustment coefficient of each distributed power source. By using the current adjustment coefficient of each distributed power source, the load current of each distributed power source at the current moment is corrected. Combined with the line impedance and bus voltage of the distributed power source, the voltage compensation amount of each distributed power source at the current moment is obtained, and the power of each distributed power source is allocated. The determination of the synchronous and asynchronous nature of the current includes: The load current of each distributed power source at all times during the current time period is compiled into a real-time current sequence, and the load current of each distributed power source at all times during the same time period of each day during the current time period is compiled into a historical current sequence. Calculate the absolute value of the difference between the elements at the same position in the real-time current sequence and each historical current sequence to obtain the current difference sequence. Based on the numerical distribution of each current difference sequence, the degree of synchronicity and asynchrony of each current is determined; The determination of the current trend difference includes: For all current synchronicity and asynchrony of each distributed power source in the current time period, perform linear fitting and calculate the mean of the difference between all fitted values ​​and the true values ​​on the fitted line, which is denoted as the fitting error. Calculate the mean of the current synchronization and asynchrony of all currents of each distributed power source in the current time period, and denot it as the first mean. Combine the fitting error with the first mean to determine the current trend difference, wherein the current trend difference is positively correlated with the fitting error and negatively correlated with the first mean. The determination of the current adjustment coefficient includes: Calculate the average load current of each distributed power source at the current moment over the same historical days, and record it as the second average. Calculate the product of the load current of each distributed power source at the current moment and the current trend difference, and record it as the first product. Calculate the difference between the value 1 and the current trend difference of each distributed power source in the current time period, and record it as the first difference. Determine the product of the first difference and the second average of each distributed power source at the current moment, and record it as the second product. By combining the first product and the second product, and the maximum value in the real-time current sequence corresponding to each distributed power source at the current moment, the current adjustment coefficient of each distributed power source is determined.

2. The intelligent power allocation method for a microgrid system as described in claim 1, characterized in that, Further determination of the synchronous and asynchronous nature of the current includes: Calculate the mean and average absolute deviation of each current difference sequence, and use the product of the mean and the average absolute deviation as the synchronization and asynchrony of each current in the current time period of each distributed power source.

3. The intelligent power allocation method for a microgrid system as described in claim 1, characterized in that, The current trend difference is the ratio of the fitting error to the first mean.

4. The intelligent power allocation method for a microgrid system as described in claim 1, characterized in that, The sum of the first product and the second product is calculated, and the current adjustment coefficient of each distributed power source is the ratio of the sum of the products to the maximum value of each distributed power source.

5. The intelligent power allocation method for a microgrid system as described in claim 1, characterized in that, The determination of the voltage compensation amount for each distributed power source at the current moment includes: Calculate the product of the load current of each distributed power source at the current moment and the current adjustment coefficient, which is used as the corrected current value of each distributed power source at the current moment. Calculate the product of the corrected current value and the line impedance of each distributed power source, which is recorded as the third product. The voltage compensation amount of each distributed power source is the difference between the bus voltage and the third product.

6. The intelligent power allocation method for a microgrid system as described in claim 5, characterized in that, The allocation of power to each distributed power source includes: Based on the voltage compensation amount and actual voltage of each distributed power source at the current moment, the compensated voltage value of each distributed power source at the current moment is determined. Combined with the corrected current value of each distributed power source at the current moment, the power that each distributed power source should allocate is obtained.

7. A power intelligent distribution system for a microgrid system, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method as described in any one of claims 1-6.

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