CN114583721B - Comprehensive real-time intelligent management and control system for power supply command - Google Patents
Comprehensive real-time intelligent management and control system for power supply command Download PDFInfo
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- CN114583721B CN114583721B CN202210489123.0A CN202210489123A CN114583721B CN 114583721 B CN114583721 B CN 114583721B CN 202210489123 A CN202210489123 A CN 202210489123A CN 114583721 B CN114583721 B CN 114583721B
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/24—Arrangements for preventing or reducing oscillations of power in networks
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
- H02J2203/10—Power transmission or distribution systems management focussing at grid-level, e.g. load flow analysis, node profile computation, meshed network optimisation, active network management or spinning reserve management
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
- Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
- Y04S20/00—Management or operation of end-user stationary applications or the last stages of power distribution; Controlling, monitoring or operating thereof
- Y04S20/20—End-user application control systems
- Y04S20/222—Demand response systems, e.g. load shedding, peak shaving
Abstract
The invention relates to the technical field of power supply and distribution, in particular to a comprehensive real-time intelligent management and control system for power supply command, which comprises: the power supply data acquisition module is used for acquiring power supply data of a power grid, power grid unbalance degrees and distance vectors of each power supply area; the power supply data processing module is used for acquiring an overload area and a non-overload area and acquiring independent time periods corresponding to the overload areas; calculating an influence value according to the distance vector of the power supply area, and obtaining an area capable of mutual influence; and the power supply data management and control module is used for calculating the influence quantity of the overload area in an independent time period corresponding to the overload area, calculating the real power grid unbalance degree of each area according to the influence, and further determining the power supply priority of each area. The invention can realize rapid power supply management and ensure the stability of the power grid.
Description
Technical Field
The invention relates to the technical field of power supply and distribution, in particular to a comprehensive real-time intelligent management and control system for power supply command.
Background
A significant steady-state imbalance of the grid occurs when the grid of the power supply area is subjected to loads that exceed the load capacity or load limit of the grid. There are many reasons for causing grid steady state imbalance, for example: when the power grid structure in the power supply area is unreasonable or low in reliability; when high-power equipment is cut in a factory or a construction process; when the power grid equipment cannot normally work due to damage, burning and the like; as the amount of consumer power usage within the power supply area increases. For current power system management, when the steady state of power in a certain area is severe, power is transmitted to the area, and then the stability of a power grid is maintained.
Disclosure of Invention
In order to solve the technical problems, the invention aims to provide a comprehensive real-time intelligent management and control system for power supply command, and the adopted technical scheme is as follows:
the power supply data acquisition module is used for acquiring power supply data of a power grid of each power supply area, inputting the power supply data of the power grid of each power supply area into the neural network to obtain the power grid unbalance degree of each power supply area, and acquiring a distance vector corresponding to each power supply area;
the power supply data processing module is used for recording areas with the power grid unbalance degree larger than the degree threshold value and the number of the time periods larger than the duration threshold value as overload areas and recording other areas as non-overload areas in all time periods of each power supply area; obtaining an influence value according to the similarity of the distance vectors corresponding to any two power supply areas, wherein the two areas with the influence values larger than the influence threshold are areas capable of being influenced mutually; acquiring an independent time period corresponding to each overload area, wherein the independent time period is that only a single overload area and other non-overload areas exist in the time period, and the other non-overload areas and the single overload area are areas capable of being influenced mutually;
the power supply data management and control module is used for calculating the average value of the power grid unbalance degrees of other non-overloaded areas which are mutually influenced areas with the overloaded area in an independent time period corresponding to the overloaded area to obtain the influence quantity of the overloaded area; and calculating the difference between the power grid unbalance degrees of the overload area and the other non-overload areas and the influence quantity to obtain the real power grid unbalance degrees of the overload area and the other non-overload areas, and determining the power supply priority of each area according to the real power grid unbalance degrees.
Preferably, the method for obtaining the distance vector specifically includes: and acquiring the number of feeder line sections which are passed by each transformer substation when each transformer substation provides power for each power supply area, and forming a distance vector corresponding to each power supply area.
Preferably, the training process of the neural network specifically includes:
acquiring power consumption vectors and reference power consumption vectors of a power grid at different moments, wherein the power consumption vectors are one-dimensional vectors formed by voltage, voltage phase, power and frequency of the power grid at different moments; the reference power consumption vector is a one-dimensional vector formed by rated voltage, rated voltage phase, maximum power allowed to be borne by a power grid wire and frequency of a power grid;
the method comprises the following steps of artificially allocating labels for power consumption vectors and reference power consumption vectors at different moments, wherein the specific allocation method comprises the following steps: acquiring the difference between data such as voltage, voltage phase, power, frequency and the like in the power consumption vector and data such as rated voltage, rated voltage phase, maximum power allowed to bear by a power grid wire and the like in a reference vector;
when the difference exceeds 2%, the labels of the electricity consumption vector and the reference vector are labeled as a first grade, when the difference exceeds 4%, the labels of the electricity consumption vector and the reference vector are labeled as a second grade, …, and when the difference exceeds 20%, the labels of the electricity consumption vector and the reference vector are labeled as a tenth grade.
Preferably, the grid power supply data of each power supply area includes: current data, voltage data, and power data for each power supply region.
Preferably, the method for acquiring the independent time period specifically comprises:
acquiring any overload area as an overload area m, acquiring an intersection time period in which the overload area m and other overload areas have loads, and recording the intersection time period as a first intersection time period; recording the difference between all time periods with loads in the overload area m and the first intersection time period as a difference time period; and acquiring the intersection of the difference time periods and the time periods with loads in other non-overload areas, recording as a second intersection time period, and acquiring the longest time period in the second intersection time period as an independent time period corresponding to the overload area m.
Preferably, the determining the power supply priority of each area according to the actual power grid unbalance degree specifically includes: and arranging the regions according to the value of the real unbalance degree and the sequence of the real unbalance degree from large to small, and supplying power to the regions according to the sequence.
The embodiment of the invention at least has the following beneficial effects:
according to the method, the actual power grid unbalance degree with large errors is corrected according to the power grid steady state unbalance relation among different power supply areas, so that the real power grid steady state unbalance conditions of different areas are obtained, more power consumption is distributed to each power supply area or a limited power value is increased as quickly as possible in real time, the power grid is comprehensively controlled in a large range, the stability of the power grid is ensured, enough time is provided for the follow-up repair and adjustment of the power grid, and the condition that the power grid is subjected to large-range steady state unbalance is avoided.
Under normal conditions, the current, the voltage and the power of each power supply area during steady state unbalance of the power grid are calculated according to a load flow equation, however, the calculation amount required in the solving process is too large, and in consideration of the fact that accurate power supply amount does not need to be calculated in the method, the method only aims to determine the power supply priority, the method evaluates the power grid unbalance degree of each power supply area, supplies priority according to the power grid unbalance degree and the distance vector of the power supply area, reduces the calculation amount, achieves rapid power supply management, and ensures the stability of the power grid.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions and advantages of the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.
Fig. 1 is a system block diagram of a comprehensive real-time intelligent management and control system for power supply command according to the present invention.
Detailed Description
In order to further explain the technical means and effects of the present invention adopted to achieve the predetermined purpose, the following detailed description, with reference to the accompanying drawings and preferred embodiments, describes a comprehensive real-time intelligent management and control system for power supply command according to the present invention, and its specific implementation, structure, features and effects thereof. In the following description, different "one embodiment" or "another embodiment" refers to not necessarily the same embodiment. Furthermore, the particular features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.
Unless defined otherwise, 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 invention belongs.
The following describes a specific scheme of the comprehensive real-time intelligent power supply command management and control system provided by the invention in detail with reference to the accompanying drawings.
Referring to fig. 1, a system block diagram of a comprehensive real-time intelligent management and control system for power supply command according to an embodiment of the present invention is shown, where the system includes:
and the power supply data acquisition module is used for acquiring power supply data of the power grids of the power supply areas, inputting the power supply data of the power grids of the power supply areas into the neural network to obtain the power grid unbalance degree of the power supply areas, and acquiring the distance vectors corresponding to the power supply areas.
First, it should be noted that when the load borne by the grid of the power supply area exceeds the load capacity or load limit of the grid, a significant steady-state imbalance of the grid occurs, for example: when the power grid structure in the power supply area is unreasonable or low in reliability; when high-power equipment is cut in a factory or a construction process; when the power grid equipment cannot normally work due to damage, burning and the like; both of these causes can lead to grid instability as customer power usage increases. The steady state unbalance of the power grid mainly shows that the fluctuation of data such as current, voltage, power and the like is large.
And then, inputting the power grid power supply data of each power supply area into the neural network, and outputting the power grid unbalance degree of each power supply area. Wherein, the power grid power supply data of each power supply area comprises: the value of the power grid unbalance degree is 0, 0.1, 0.2, …, 0.9, the smaller the numerical value is, the smaller the power grid unbalance degree of the power supply area is, the more stable the power grid is relatively, the larger the numerical value is, the more unstable the power grid is, and the more easily large power grid accidents are caused.
Specifically, when the power grid of each power supply area is in steady-state unbalance, the fluctuation of power grid power supply data such as current, voltage and power on the power grid is shown, and the power grid unbalance degree can be obtained by using the power grid power supply data. In this embodiment, the power supply data of the power grid of each power supply area is obtained, and includes current data, voltage data, power data, and rated current and voltage, where the rated current and voltage are input current and voltage that can guarantee normal power consumption of the power supply area and are known quantities.
The training process of the neural network comprises the following steps: and (4) carrying out grade evaluation by professionals in the field according to the power grid power supply data of each power supply area, and dividing the power grid unbalance degree into ten grades. In this embodiment, the grades are denoted as 0, 0.1, 0.2, …, and 0.9, and the smaller the grade is, the smaller the degree of unbalance of the power grid in the power supply area is, the more stable the power grid is, and the larger the grade is, the more unstable the power grid is, the more likely a large grid accident is caused. The method comprises the steps of marking power grid power supply data of each power supply area to obtain a grade corresponding to the power grid unbalance degree as training data, manually collecting and marking a large amount of training data to form a training data set, training a neural network by using the training data set, and supervising the training of the network by using a mean square error loss function and a stochastic gradient descent method.
The present invention refers to a one-dimensional vector composed of data such as voltage, voltage phase, power, and frequency obtained at the same time as a power consumption vector at that time, and refers to a one-dimensional vector composed of data such as rated voltage, rated voltage phase, and maximum power and frequency allowed to be received by a power grid line as a reference power consumption vector. The neural network is a 5-layer fully-connected neural network, the input data are power consumption vectors and reference power consumption vectors, and the output data are as follows: the electric vector belongs to grades, and the neural network outputs 10 grades, wherein the grades comprise a first grade, a second grade, … and a tenth grade. The first level indicates a degree of instability of 0.0, the second level indicates a degree of instability of 0.1, …, and the tenth level indicates a degree of instability of 0.9. The method for acquiring the training set of the network comprises the following steps: the method comprises the following steps of collecting power consumption vectors and reference power consumption vectors of a power grid at different moments, and artificially distributing labels for the power consumption vectors and the reference power consumption vectors at different moments, wherein the specific distribution method comprises the following steps: and manually judging the difference between the data of voltage, voltage phase, power, frequency and the like in the power consumption vector and the data of rated voltage, rated voltage phase, maximum power allowed to bear by a power grid wire, frequency and the like in the reference vector, wherein the larger the difference is, the larger the instability degree is. The invention is exemplified by the following: when the difference exceeds 2%, labels of the electricity consumption vector and the reference vector are marked as a first grade, when the difference exceeds 4%, labels of the electricity consumption vector and the reference vector are marked as a second grade, …, when the difference exceeds 20%, labels of the electricity consumption vector and the reference vector are marked as a tenth grade, and the neural network is trained by using the data sets. And after the network training is finished, obtaining the power consumption vector a and the reference power consumption vector b at the current moment, inputting the (a) and the (b) into the neural network, outputting the grades to which the (a) and the (b) belong by the network, obtaining the instability degree corresponding to the grade s, and taking the instability degree as an evaluation index of the steady state unbalance of the power grid at the current moment.
Finally, since the power grid structure is relatively complex, in order to implement the present invention, the following simplified description of the power grid structure is required (an implementer may also describe the power grid structure in each power supply area, or simplify the power grid structure by using other methods):
the transformer substations transmit the electric power to different distribution substations firstly, and then distribute the electric power distributed by the distribution substations to each power utilization area. In this embodiment, the area supplied with power by the same power distribution station is referred to as a power supply area, and the whole city may be divided into a plurality of power supply areas. Assuming that M power supply areas are shared, that is, it can be represented that N substations supply power to the M power supply areas, a power supply line of each substation to each power supply area is called a feeder line, and the feeder line has a plurality of feeder line switches, and the switches divide the whole feeder line into different feeder line segments. The feeder switch is used for controlling the circuit to be switched on and switched off, and power dispatching can be achieved.
In this embodiment, the position characteristics of each power supply area in the power grid structure need to be described, so as to obtain a distance vector corresponding to each power supply area. The number of feeder sections through which each substation provides power to each power supply area is obtained, and distance vectors corresponding to each power supply area are formed.
Specifically, taking the power supply area a as an example, the number of feeder sections through which the nth substation provides power to the power supply area a is obtained and recorded as
And further acquiring the number of feeder line sections passed by each substation when supplying power to the power supply area A, and forming a distance vector corresponding to the power supply area A and recording the distance vector as
Wherein N is the number of the transformer substationAnd (4) counting.
It should be noted that, in this embodiment, the distance vector is only used to describe the position characteristics of each power supply area in the power grid, and may be used to distinguish the position relationship between different power supply areas, and the individual distance vector itself has no special meaning. And, if the nth substation cannot supply power to the power supply area a, it is determined that the nth substation is not capable of supplying power to the power supply area a
=0。
The power supply data processing module is used for recording areas with the power grid unbalance degree larger than the degree threshold value and the number of the time periods larger than the duration threshold value as overload areas and recording other areas as non-overload areas in all time periods of each power supply area; obtaining an influence value according to the similarity of the distance vectors corresponding to any two power supply areas, wherein the two areas with the influence values larger than the influence threshold are areas capable of being influenced mutually; and acquiring an independent time period corresponding to each overload area, wherein the independent time period is that only a single overload area and other non-overload areas exist in the time period.
Firstly, in all time periods of each power supply area, areas with the number of the time periods with the power grid unbalance degrees larger than the degree threshold value larger than the duration threshold value are marked as overload areas, and other areas are non-overload areas. The duration threshold is the product of 0.8 and the number of all time periods of each power supply area, and the value implementers of the degree threshold and the duration threshold can set the duration threshold according to actual conditions.
It should be noted that the load time of each power supply area in the same time period may aggravate the problem of grid steady-state imbalance, and further affect the degree of grid imbalance of different power supply areas in the time period. Namely, the magnitude of the grid imbalance degree of each power supply area represents the steady state of the grid in each power supply area, and meanwhile, each power supply area can affect the grid imbalance degree of other power supply areas, and each power supply area can also be affected by other areas.
When a certain power supply area has a problem of grid steady state unbalance, other power supply areas are often affected, but a certain power supply area may not have the problem of grid steady state unbalance, and the grid steady state unbalance of the power supply area is caused due to the influence of the relevant power supply area. When the steady-state unbalance degree of the power grid of a certain power supply area is not serious, the power grids of other power supply areas may fluctuate slightly, and the normal use of other power supply areas is not affected. However, when the steady-state unbalance degree of the power grid in a certain power supply area is severe, a large-area power failure may be caused, and even the power grid may be broken down. Wherein high power equipment is used; the power consumption of users or power supply areas is increased sharply; the steady state unbalance of the power grid can be caused by the damage of the electric equipment or the power distribution equipment and the like.
Meanwhile, the non-overloaded area does not have a load or a power grid unbalance degree, the unbalance degree exists due to the influence of the power grid unbalance degree of the overloaded area, but the power grid unbalance degree of the non-overloaded area is smaller, in this embodiment, it can be considered that the power grid unbalance degree of the non-overloaded area does not influence the overloaded area, and actually, a mutual influence relationship exists between the overloaded areas.
It is assumed that power supply areas a, b, c, 1, 2, 3 are present, wherein power supply areas a, b, c are overloaded areas and power supply areas 1, 2, 3 are not overloaded areas. The non-overload areas 1, 2 and 3 belong to the same power grid structure as the overload areas a, b and c, and are influenced by the steady state of the power grid caused by overload behaviors, so that the power grid unbalance degree exists. The impact between overloaded areas can be considered bi-directional, and the impact of overloaded areas on un-overloaded areas is uni-directional.
And then, obtaining an influence value according to the similarity of the distance vectors corresponding to any two power supply areas, wherein the two areas with the influence values larger than the influence threshold are areas capable of being influenced mutually. In this embodiment, the similarity of each element in the distance vectors corresponding to the two power supply regions is calculated, and the product of the similarities of the elements is used as the similarity of the distance vectors to obtain an influence value; and when all elements in the two distance vectors are equal, the similarity is 1, and then the influence value is 1. The value of the influence threshold is 0.8, an implementer can set the value of the influence threshold according to actual conditions, and other more appropriate methods can be selected to calculate the similarity between the distance vectors.
And finally, acquiring an independent time period corresponding to each overload area, wherein the independent time period is that only a single overload area and other non-overload areas exist in the time period, and the other non-overload areas and the single overload area are areas capable of being influenced mutually. Specifically, for any overload area and marked as m, acquiring an intersection time period in which the load exists only in the overload area m and other overload areas, and marking as a first intersection time period; recording the difference between all time periods with loads in the overload area m and the first intersection time period as a difference time period; and acquiring the intersection of the difference time periods and the time periods with loads in other non-overload areas, recording as a second intersection time period, and acquiring the longest time period in the second intersection time period as an independent time period corresponding to the overload area m.
And the power supply data management and control module is used for calculating the mean value of the power grid unbalance degrees of other non-overloaded areas which are mutually influenced areas with the overloaded area in an independent time period corresponding to the overloaded area, obtaining the influence quantity of the overloaded area, calculating the difference value between the power grid unbalance degrees of the overloaded area and the other non-overloaded areas and the influence quantity, obtaining the real power grid unbalance degrees of the overloaded area and the other non-overloaded areas, and determining the power supply priority level of each area according to the real power grid unbalance degrees.
Specifically, in an independent time period corresponding to an overload area, obtaining a mean value of the power grid unbalance degrees of other non-overload areas which are mutually influenceable areas with the overload area, obtaining an influence quantity of the overload area, taking the influence quantity as a correction quantity of mutual influence of a plurality of areas in the same time period, calculating a difference value between the power grid unbalance degrees of the overload area and the other non-overload areas and the correction quantity, obtaining real power grid unbalance degrees of the overload area and the other non-overload areas, and further obtaining real power grid unbalance degrees of different overload areas and non-overload areas.
And then determining power supply priority according to the value of the real power grid unbalance degree of each area, arranging the areas according to the value of the real unbalance degree in the order from the real unbalance degree to the real unbalance degree, and supplying power to the areas according to the order.
The power supply area with the power grid steady state unbalance problem can be preferentially supplied with power in the area with the large power grid unbalance degree, so that rapid power supply management is realized, and the phenomenon that the operation of a large power grid is influenced due to the power grid steady state unbalance in the area is avoided.
It should be noted that load time of each power supply area in the same time period may cause aggravation of grid steady-state unbalance, and further affect the grid unbalance degree of different power supply areas in the time period, so that the obtained grid unbalance degree is not a real value, but the grid unbalance degree under the influence of other load events, and therefore the grid unbalance degree of each area needs to be corrected to obtain the real grid unbalance degree. For example: when the influence quantity of the overload area a on the non-overload areas 1, 2 and 3 is calculated, the average value of the power grid unbalance degrees of the non-overload areas 1, 2 and 3 is used as the influence of the load event of the overload area a on the power grid steady state, and is also used as the influence of the area a on other overload areas.
Meanwhile, the power grid unbalance degree corresponds to an allowable range, if the value of the power grid unbalance degree is within the allowable range, the normal fluctuation is considered, and the automatic adjustment and recovery can be realized; if the value of the unbalance degree of the power grid exceeds the range, the power grid is considered to be unbalanced in a steady state, and the allowable range can be obtained through big data statistics.
The above-mentioned embodiments are only used for illustrating the technical solutions of the present application, and not for limiting the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; such modifications and substitutions do not substantially depart from the spirit and scope of the embodiments of the present application and are intended to be included within the scope of the present application.
Claims (5)
1. The utility model provides a comprehensive real-time intelligent management and control system of power supply commander which characterized in that, this system includes:
the power supply data acquisition module is used for acquiring power supply data of a power grid of each power supply area, inputting the power supply data of the power grid of each power supply area into the neural network to obtain the power grid unbalance degree of each power supply area, and acquiring a distance vector corresponding to each power supply area;
the method for acquiring the distance vector specifically comprises the following steps: acquiring the number of feeder line sections which are passed by each transformer substation when each transformer substation provides power for each power supply area, and forming distance vectors corresponding to each power supply area;
the power supply data processing module is used for recording areas with the power grid unbalance degree larger than the degree threshold value and the number of the time periods larger than the duration threshold value as overload areas and recording other areas as non-overload areas in all time periods of each power supply area; obtaining an influence value according to the similarity of the distance vectors corresponding to any two power supply areas, wherein the two areas with the influence values larger than the influence threshold are areas capable of being influenced mutually; acquiring an independent time period corresponding to each overload area, wherein the independent time period is that only a single overload area and other non-overload areas exist in the time period, and the other non-overload areas and the single overload area are areas capable of being influenced mutually;
the power supply data management and control module is used for calculating the average value of the power grid unbalance degrees of other non-overloaded areas which are mutually influenced areas with the overloaded area in an independent time period corresponding to the overloaded area to obtain the influence quantity of the overloaded area; and calculating the difference between the power grid unbalance degrees of the overload area and the other non-overload areas and the influence quantity to obtain the real power grid unbalance degrees of the overload area and the other non-overload areas, and determining the power supply priority of each area according to the real power grid unbalance degrees.
2. The system according to claim 1, wherein the training process of the neural network specifically comprises:
acquiring power consumption vectors and reference power consumption vectors of a power grid at different moments, wherein the power consumption vectors are one-dimensional vectors formed by voltage, voltage phase, power and frequency of the power grid at different moments; the reference power consumption vector is a one-dimensional vector formed by the rated voltage and the rated voltage phase of the power grid and the maximum power and frequency allowed to be borne by the power grid wire;
the method comprises the following steps of artificially allocating labels for power consumption vectors and reference power consumption vectors at different moments, wherein the specific allocation method comprises the following steps: obtaining the difference between the voltage, voltage phase, power and frequency data in the power consumption vector and the rated voltage, rated voltage phase and maximum power and frequency data allowed to be borne by the power grid wire in the reference vector;
when the difference exceeds 2%, the labels of the electricity consumption vector and the reference vector are labeled as a first grade, when the difference exceeds 4%, the labels of the electricity consumption vector and the reference vector are labeled as a second grade, …, and when the difference exceeds 20%, the labels of the electricity consumption vector and the reference vector are labeled as a tenth grade.
3. The system according to claim 1, wherein the grid power supply data of each power supply area includes: current data, voltage data, and power data for each power supply region.
4. The system according to claim 1, wherein the method for acquiring the independent time period specifically comprises:
acquiring any overload area as an overload area m, acquiring an intersection time period in which the overload area m and other overload areas have loads, and recording the intersection time period as a first intersection time period; recording the difference between all time periods with loads in the overload area m and the first intersection time period as a difference time period; and acquiring the intersection of the difference time periods and the time periods with loads in other non-overload areas, recording as a second intersection time period, and acquiring the longest time period in the second intersection time period as an independent time period corresponding to the overload area m.
5. The system according to claim 1, wherein the determining of the power supply priority for each area according to the actual grid imbalance degree specifically includes: and arranging the regions according to the value of the real power grid unbalance degree and the sequence of the real power grid unbalance degree from large to small, and supplying power to the regions according to the sequence.
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