Micro-grid electric energy quality closed-loop evaluation and treatment method and system based on variance convergence

Abstract

The invention relates to the technical field of micro-grid electric energy quality evaluation and treatment, and discloses a micro-grid electric energy quality closed-loop evaluation and treatment method and system based on variance convergence, and the method comprises the steps: collecting the data of each node in a micro-grid, and carrying out the calculation of the data, and obtaining an electric energy quality index; after the electric energy quality index is quantified, calculating an electric energy quality evaluation result of the whole micro-grid; setting a time period, and calculating the convergence degree of the power quality indexes in the time period; when the calculated convergence degree is greater than a set convergence degree threshold value, adjusting the weight of each electric energy quality index, obtaining each electric energy quality again, quantifying the electric energy quality into a score, and recalculating the overall electric energy quality evaluation result of the microgrid; and treating the microgrid power quality problem based on the overall power quality evaluation result of the microgrid. According to the method, the problem of evaluation and treatment of the electric energy quality in the micro-grid is solved, and the micro-grid can obtain accurate electric energy quality evaluation and effective treatment under multiple working conditions through closed-loop evaluation and treatment.

Description

Technical Field

[0001] The present invention relates to the technical field of microgrid power quality assessment and management, and in particular to a microgrid power quality closed-loop assessment and management method and system based on variance convergence. Background Art

[0002] A power supply and consumption network that can operate both independently and in parallel with the grid is called a microgrid, which combines distributed photovoltaic, wind power and other new energy sources, loads, power quality management devices, and relay protection devices. Microgrids mostly consume the power generated by new energy sources locally, and their grid-connected ports are a power-controllable load for the grid side. Therefore, vigorously developing microgrids in distribution networks can effectively improve the absorption rate of new energy sources. The capacity of microgrids is generally small, and the operation modes of microgrids are generally more diverse, which leads to various power quality problems in microgrids. Effective evaluation of the power quality of microgrids is a necessary part of power quality management. In traditional power quality evaluation, each power quality indicator in the microgrid, including typical indicators such as harmonics, three-phase imbalance, voltage deviation, and frequency deviation, is first quantitatively evaluated, and then weighted; multiple indicators are summed according to the weights to obtain the overall power quality evaluation result. In conventional power quality assessment, once the weights are determined, they are not adjusted later. If the operating state of the microgrid changes, the adaptability of the weights will decrease, thus affecting the accuracy of the overall power quality assessment results. Therefore, how to dynamically adjust the power quality index weights according to the operating conditions of the microgrid requires further research. Summary of the invention

[0003] The purpose of the present invention is to solve the problem of power quality assessment and management in a microgrid. Through closed-loop assessment and management, the microgrid can obtain accurate power quality assessment and effective management under multiple working conditions, and provide a microgrid power quality closed-loop assessment and management method and system based on variance convergence.

[0004] In order to achieve the above-mentioned object of the invention, the embodiment of the present invention provides the following technical solutions:

[0005] The closed-loop evaluation and control method of microgrid power quality based on variance convergence includes the following steps:

[0006] Step 1: collect data from each node in the microgrid, calculate the data to obtain power quality indicators; and quantify the power quality indicators to calculate the overall power quality evaluation result of the microgrid;

[0007] Step 2, setting a time period and calculating the convergence of the power quality index within the time period;

[0008] Step 3: When the calculated convergence degree is greater than the set convergence degree threshold, the weights of the power quality indicators are adjusted, the power quality of each indicator is re-acquired and quantified into scores, and the overall power quality evaluation result of the microgrid is recalculated;

[0009] Step 4: Manage the power quality issues of the microgrid based on the overall power quality assessment results of the microgrid.

[0010] The microgrid power quality closed-loop assessment and management system based on variance convergence includes:

[0011] The microgrid power quality index convergence evaluation module is used to calculate the data of each node in the microgrid, obtain the power quality index, and calculate the score and convergence of each power quality index. When the convergence is greater than the set threshold, the microgrid power quality index weight adjustment module is enabled;

[0012] A microgrid power quality index weight adjustment module adjusts the weight of each power quality index;

[0013] A microgrid power quality overall assessment update module is used to recalculate the overall power quality assessment result of the microgrid according to the adjusted power quality index weights;

[0014] The microgrid power quality management module is used to manage power quality issues based on the overall power quality assessment results of the microgrid; after the management is completed, the microgrid power quality indicator convergence assessment module is enabled to calculate the convergence degree.

[0015] Compared with the prior art, the present invention has the following beneficial effects:

[0016] (1) The microgrid power quality index convergence evaluation module in the present invention can monitor the power quality of the microgrid under the operating conditions, and reflect the changes of various power quality indicators of the microgrid as the microgrid operating conditions change;

[0017] (2) The method proposed in the present invention can timely adjust the weight of the power quality index according to the changes in the power quality index of the microgrid, thereby ensuring the accuracy of the power quality assessment of the microgrid;

[0018] (3) The present invention manages the microgrid power quality problems in a closed loop according to the weight changes of the microgrid power quality indicators and the microgrid power quality assessment results, and then conducts further assessment after the management, so as to ensure the power quality of the microgrid during operation. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments are briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without creative work.

[0020] Figure 1 It is a schematic diagram of the process of the present invention;

[0021] Figure 2 It is a block diagram of the system module of the present invention;

[0022] Figure 3 It is a unit block diagram of a microgrid power quality index convergence evaluation module of the present invention;

[0023] Figure 4 It is a unit block diagram of the microgrid power quality overall assessment and update module of the present invention. DETAILED DESCRIPTION

[0024] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. The components of the embodiments of the present invention generally described and shown in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the drawings is not intended to limit the scope of the claimed invention, but merely represents the selected embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without making creative work belong to the scope of protection of the present invention.

[0025] It should be noted that similar numbers and letters represent similar items in the following figures, so once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. At the same time, in the description of the present invention, the terms "first", "second", etc. are only used to distinguish the description, and cannot be understood as indicating or implying relative importance, or implying any such actual relationship or order between these entities or operations. In addition, the terms "connected", "connected", etc. can be directly connected between elements, or indirectly connected via other elements.

[0026] Embodiment 1:

[0027] The present invention is achieved through the following technical solutions: Figure 1 As shown in FIG. 1 , the closed-loop evaluation and control method for microgrid power quality based on variance convergence includes the following steps:

[0028] Step 1: collect data from each node in the microgrid, calculate the data to obtain power quality indicators; and quantify the power quality indicators to calculate the overall power quality evaluation result of the microgrid.

[0029] First, voltage and current data of each node in the microgrid are collected using voltage sensors and current sensors. The collected data are calculated to obtain the power quality indicators to be evaluated, including harmonic distortion rate THD, three-phase imbalance ε, and voltage deviation δ. U , frequency deviation δ f , the specific indicator formula is as follows:

[0030]

[0031]

[0032] δ f =f m -f N

[0033] Among them, U m1 Indicates fundamental voltage, U mh Indicates harmonic voltage; U m Indicates the actual operating voltage of the microgrid, U N Indicates rated voltage; f m Indicates the actual operating frequency of the microgrid, f N represents the rated frequency; ν is the intermediate parameter, and Uma, Umb and Umc are the three-phase voltages of the microgrid respectively.

[0034] Then, according to the quantification standard of power quality indicators, as shown in Table 1, the power quality indicators are quantified, that is, the scores of each indicator are given. The scores of harmonic distortion rate, three-phase unbalance, voltage deviation, and frequency deviation can be expressed as S h , S u , S v , S f express.

[0035] Table 1 Power quality indicators and corresponding scores of various power quality indicators

[0036]

[0037] Table 1 shows the scores of various power quality indicators of the node. For example, when the harmonic distortion rate of the node is 1.5%, the score corresponding to the indicator is S. h =90.

[0038] After the quantitative scores of these power quality indicators are weighted, the overall power quality evaluation result S of the microgrid can be obtained. m , the weighted formula is as follows:

[0039] S m =W h S h +W u S u +W v S v +W f S f

[0040] Among them, W h , W u , W v , W f They respectively represent the weights of harmonic distortion rate, three-phase unbalance, voltage deviation, and frequency deviation.

[0041] These weights are obtained by using an objective weighting method for the above four power quality indicators. The objective weighting method uses certain mathematical algorithms, such as entropy weight method and variance method, to perform certain statistical analysis on the power quality indicators to reflect the discreteness of the data, that is, the convergence. The greater the discreteness, the weaker the convergence, indicating that the more drastic the change of this indicator, the greater the weight is given to this drastic indicator. In this way, the evaluation results of the power quality indicators can better reflect the drastic changes in the indicators. In general, the weights of each indicator obtained by the objective weighting method are W j for:

[0042]

[0043] Among them, W j represents the weight of the jth power quality indicator; D j Indicates the discrete degree of the jth power quality indicator, j = 1, 2, 3, 4. As an implementation method, when j = 1, W1 = W h ; When j = 1, W2 = W u ; When j = 3, W3 = W v ; When j = 4, W4 = W f .

[0044] Step 2: Set a time period and calculate the convergence of the power quality indicators within the time period.

[0045] When the operating state of the microgrid does not change significantly, the power quality of the microgrid does not change significantly either. At this time, the convergence of the power quality index does not change. In this case, the index weights are still applicable, and the overall evaluation results of the microgrid power quality are also accurate.

[0046] When the operating state of the microgrid changes, which causes a significant change in the power quality of the microgrid, the power quality index data of the microgrid will change significantly, and its convergence will change. In this case, the weights obtained by the above-mentioned objective weighting method are no longer applicable to the data convergence of the power quality index at this time, and the overall evaluation result of the microgrid power quality calculated thereby will be inaccurate.

[0047] Therefore, in the operation of the microgrid, voltage sensors and current sensors are used to collect data from each node of the microgrid in real time, and then the power quality indicators are calculated, including harmonic distortion rate, three-phase imbalance, voltage deviation, and frequency deviation; these power quality indicator data are sampled and calculated according to the time period T1, and the score of the time period T1 can be obtained, which is expressed as:

[0048] S x =[S h S u S v S f ]

[0049] Among them, S x Indicates the power quality index score within the time period T1.

[0050] Then define a larger time period T2. For example, if time period T1 is one hour, then time period T2 can be 24 hours. If time period T1 is one day, then time period T2 can be one month. If time period T1 is one month, then time period T2 can be one year. The convergence of all power quality indicators within time period T2 is judged. This solution uses the variance algorithm to judge the convergence:

[0051]

[0052] D var Indicates the convergence of the power quality index within the time period T2; S xi represents the power quality index score of the i-th time period T1 within the time period T2, i = 1, 2, ..., n, n represents that the time period T2 contains n time periods T1; Represents the average value of n Sx within the time period T2.

[0053] The convergence degree D var The convergence threshold is compared with the set one, which is set by the evaluator according to the actual operation status of the microgrid and the power quality management requirements.

[0054] Step 3: When the calculated convergence degree is greater than the set convergence degree threshold, the weights of the power quality indicators are adjusted, the power quality of each indicator is re-acquired and quantified into scores, and then the overall power quality evaluation result of the microgrid is recalculated.

[0055] When the convergence degree is less than the threshold, it is considered that the power quality of the microgrid has not changed significantly, and the evaluation algorithm remains unchanged. When the convergence degree is greater than the threshold, it is considered that the power quality of the microgrid has changed significantly, and the indicator greater than the threshold has the largest change. At this time, the original weight system is no longer applicable to the current power quality status of the microgrid, and the weights of each indicator need to be adjusted. That is, the objective weighting formula is used to readjust the weights:

[0056]

[0057] Among them, W j ` represents the readjusted weight of the jth power quality index; D j ` represents the discrete degree of readjustment of the j-th power quality indicator, j = 1, 2, 3, 4.

[0058] Then, the overall power quality assessment result of the microgrid is recalculated using the following weighted formula:

[0059] S m `=W h `S h '+W u `S u '+W v `S v `+W f `S f `

[0060] Among them, S m ` represents the recalculated power quality assessment result of the microgrid as a whole; S h `、S u `、S v `、S f ` respectively represent the re-collected electric energy index data; W h `、W u `、W v `、W f `respectively represent the weights of the readjusted harmonic distortion rate, three-phase unbalance, voltage deviation, and frequency deviation.

[0061] Step 4: Manage the power quality issues of the microgrid based on the overall power quality assessment results of the microgrid.

[0062] Furthermore, the latest results of the power quality assessment reflect the latest power quality status of the microgrid, which reflects the need for microgrid power quality problem management, and then the power quality problems are managed, including active power filtering management, static reactive power generation management, energy storage management, etc. These management methods adopt existing methods in the current power system, which is not the innovation point emphasized in this plan and will not be discussed in detail here.

[0063] After the above-mentioned microgrid power quality management, the convergence of various indicators of the microgrid power quality is evaluated again. When the convergence of the indicator is less than the set threshold, it is considered that the power quality of the microgrid is stable, and the status quo of the evaluation algorithm is kept unchanged.

[0064] In summary, the present invention solves the problem of microgrid power quality assessment and management. When the operating conditions of the microgrid change, resulting in changes in the power quality problems of the microgrid, the weights of the microgrid power quality assessment can be adjusted in time, the power quality assessment results can be updated, and the power quality management of the microgrid can be started to keep the power quality of the microgrid within a certain standard.

[0065] like Figure 2 As shown, this scheme also proposes a microgrid power quality closed-loop assessment and management system based on variance convergence, which is used to implement the above-mentioned method. The system includes:

[0066] The microgrid power quality index convergence evaluation module is used to calculate the data of each node in the microgrid, obtain the power quality index, and calculate the score and convergence of each power quality index. When the convergence is greater than the set threshold, the microgrid power quality index weight adjustment module is enabled;

[0067] A microgrid power quality index weight adjustment module adjusts the weight of each power quality index;

[0068] A microgrid power quality overall assessment update module is used to recalculate the overall power quality assessment result of the microgrid according to the adjusted power quality index weights;

[0069] The microgrid power quality management module is used to manage power quality issues based on the overall power quality assessment results of the microgrid; after the management is completed, the microgrid power quality indicator convergence assessment module is enabled to calculate the convergence degree.

[0070] Furthermore, if Figure 3 As shown, the microgrid power quality index convergence evaluation module includes:

[0071] The power quality index acquisition unit is used to collect voltage data and current data of each node in the microgrid using a voltage sensor and a current sensor, and obtain the power quality index to be evaluated after calculating the collected data; the power quality index includes harmonic distortion rate, three-phase unbalance, voltage deviation, and frequency deviation;

[0072] A power quality index score calculation unit is used to quantify each power quality index into a score, obtain the weight of each power quality index based on an objective weighting method, and calculate the overall power quality evaluation result of the microgrid according to the score and weight of each power quality index;

[0073] A convergence calculation unit, used to calculate the convergence of all power quality indicators within the time period T2 by using a variance algorithm after setting the time period T1 and the time period T2;

[0074] The convergence comparison unit is used to compare the convergence calculated by the convergence calculation unit with a set convergence threshold, and when the convergence is greater than the set convergence threshold, the microgrid power quality index weight adjustment module is enabled.

[0075] like Figure 4 As shown, the microgrid power quality overall assessment and update module includes:

[0076] A power quality index retrieving unit, used for retrieving each power quality index and quantifying each power quality index into a score;

[0077] The overall evaluation updating unit is used to recalculate the overall power quality evaluation result of the microgrid based on the readjusted weights of each power quality unit and the re-obtained scores of each power quality indicator.

[0078] The microgrid power quality management module includes but is not limited to an active power filter, a static VAR generator, and an energy storage device, and is used to manage the power quality problems of the microgrid.

[0079] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A closed-loop evaluation and management method for microgrid power quality based on variance convergence, characterized by: The following steps are involved: Step 1: collect data from each node in the microgrid and calculate the data to obtain power quality indicators; And after quantifying the power quality indicators, the overall power quality assessment results of the microgrid are calculated; Step 2, setting a time period and calculating the convergence of the power quality index within the time period; Step 3: When the calculated convergence degree is greater than the set convergence degree threshold, the weights of the power quality indicators are adjusted, the power quality of each indicator is re-acquired and quantified into scores, and the overall power quality evaluation result of the microgrid is recalculated; Step 4: Manage the power quality issues of the microgrid based on the overall power quality assessment results of the microgrid.

2. The microgrid power quality closed-loop assessment and management method based on variance convergence according to claim 1 is characterized in that: In step 1, the step of collecting data from each node in the microgrid and calculating the data to obtain the power quality index includes: Use voltage sensors and current sensors to collect voltage and current data of each node in the microgrid, calculate the collected data, and obtain the power quality indicators to be evaluated, including harmonic distortion rate THD, three-phase imbalance ε, voltage deviation δ U , frequency deviation δ f , the specific indicator formula is as follows: d f =f m -f N Among them, U m1 Indicates fundamental voltage, U mh Indicates harmonic voltage; U m Indicates the actual operating voltage of the microgrid, U N Indicates rated voltage; f m Indicates the actual operating frequency of the microgrid, f N represents the rated frequency; ν is the intermediate parameter, and Uma, Umb and Umc are the three-phase voltages of the microgrid respectively.

3. The microgrid power quality closed-loop assessment and management method based on variance convergence according to claim 2 is characterized in that: In step 1, the step of quantifying the power quality index includes: According to the quantitative standard of power quality indicators, the power quality indicators are quantified, that is, the scores of each power quality indicator are given. The scores of harmonic distortion rate, three-phase unbalance, voltage deviation and frequency deviation are expressed as S h , S u , S v , S f express.

4. The microgrid power quality closed-loop assessment and management method based on variance convergence according to claim 3 is characterized in that: In step 1, the step of calculating the overall power quality assessment result of the microgrid includes: The quantitative scores of the power quality indicators are weighted to obtain the overall power quality evaluation result S of the microgrid. m , the weighted formula is as follows: S m =W h S h +W u S u +W v S v +W f S f Among them, W h , W u , W v , W f They respectively represent the weights of harmonic distortion rate, three-phase unbalance, voltage deviation, and frequency deviation.

5. The microgrid power quality closed-loop assessment and management method based on variance convergence according to claim 4 is characterized in that: In step 1, when calculating the overall power quality evaluation result of the microgrid, the weight of each power quality indicator is: Among them, W j represents the weight of the jth power quality indicator; D j Indicates the discrete degree of the j-th power quality indicator, j=1,2,3,4.

6. The microgrid power quality closed-loop assessment and management method based on variance convergence according to claim 5 is characterized in that: The step 2 specifically includes the following steps: By sampling and calculating these power quality index data according to the time period T1, the score of the time period T1 can be obtained, which is expressed as: S x =[S h S u S v S f ] Among them, S x Indicates the power quality index score within the time period T1; Define a time period T2 that is n times the time period T1, and judge the convergence of all power quality indicators within the time period T2. Use the variance algorithm to judge the convergence: D var Indicates the convergence of the power quality index within the time period T2; S xi represents the power quality index score of the i-th time period T1 within the time period T2, i = 1, 2, ..., n, n represents that the time period T2 includes n time periods T1; Indicates n S in time period T2 x The mean of .

7. The microgrid power quality closed-loop assessment and management method based on variance convergence according to claim 5 is characterized in that: The step 3 specifically comprises the following steps: When the convergence degree is greater than the threshold, the weights of each indicator are adjusted: Among them, W j ` represents the readjusted weight of the jth power quality index; D j ` represents the discrete degree of readjustment of the jth power quality index, j = 1, 2, 3, 4; The following weighted formula is used to recalculate the overall power quality assessment result of the microgrid: S m `=W h `S h `+W u `S u +W v `S v `+W f `S f Among them, S m ` represents the recalculated power quality assessment result of the microgrid as a whole; S h `、S u `、S v `、S f ` respectively represent the re-collected electric energy index data; W h `、W u `、W v `、W f `respectively represent the weights of the readjusted harmonic distortion rate, three-phase unbalance, voltage deviation, and frequency deviation.

8. A microgrid power quality closed-loop assessment and management system based on variance convergence, used to implement the method described in any one of claims 1 to 7, characterized in that: include: The microgrid power quality index convergence evaluation module is used to calculate the data of each node in the microgrid, obtain the power quality index, and calculate the score and convergence of each power quality index. When the convergence is greater than the set threshold, the microgrid power quality index weight adjustment module is enabled; A microgrid power quality index weight adjustment module adjusts the weight of each power quality index; A microgrid power quality overall assessment update module is used to recalculate the overall power quality assessment result of the microgrid according to the adjusted power quality index weights; The microgrid power quality management module is used to manage power quality issues based on the overall power quality assessment results of the microgrid; After the governance is completed, the microgrid power quality index convergence evaluation module is enabled to calculate the convergence degree.

9. The microgrid power quality closed-loop assessment and management system based on variance convergence according to claim 8, characterized in that: The microgrid power quality index convergence evaluation module includes: The power quality index acquisition unit is used to collect voltage data and current data of each node in the microgrid using a voltage sensor and a current sensor, and obtain the power quality index to be evaluated after calculating the collected data; the power quality index includes harmonic distortion rate, three-phase unbalance, voltage deviation, and frequency deviation; A power quality index score calculation unit is used to quantify each power quality index into a score, obtain the weight of each power quality index based on an objective weighting method, and calculate the overall power quality evaluation result of the microgrid according to the score and weight of each power quality index; A convergence calculation unit, used to calculate the convergence of all power quality indicators within the time period T2 by using a variance algorithm after setting the time period T1 and the time period T2; The convergence comparison unit is used to compare the convergence calculated by the convergence calculation unit with a set convergence threshold, and when the convergence is greater than the set convergence threshold, the microgrid power quality index weight adjustment module is enabled.

10. The microgrid power quality closed-loop assessment and management system based on variance convergence according to claim 8, characterized in that: The microgrid power quality overall assessment and update module comprises: A power quality index retrieving unit, used for retrieving each power quality index and quantifying each power quality index into a score; The overall evaluation updating unit is used to recalculate the overall power quality evaluation result of the microgrid based on the readjusted weights of each power quality unit and the re-obtained scores of each power quality indicator.

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