Method and system for processing multi-dimensional data of electricity market

Abstract

The invention discloses a method and a system for processing multi-dimensional data of a power market, and belongs to the technical field of processing of the multi-dimensional data, and the method comprises the steps: obtaining reference points of the multi-dimensional data of the power market at all time points according to peak and valley points of the multi-dimensional data of the power market; according to the overall derivative condition around the power market multi-dimensional data, the change amplitude of each power market multi-dimensional data and the corresponding reference point is reflected; small-range fluctuation of the multi-dimensional data of the power market due to external elements is reflected according to the difference between the multi-dimensional data of the power market and the peak-valley points; obtaining the abnormal amplitude of each starting point according to the abnormal fluctuation range of the two sides of each starting point, the distance between the starting points and the fluctuation foldability of the abnormal fluctuation range; according to the abnormal amplitude values of all the starting points, all the reasonable points are selected and obtained, configuration is executed on the power market multi-dimensional data around the reasonable points according to the power market multi-dimensional data of all the reasonable points, an improved queue is obtained, the accuracy of the abnormal values is maintained, and the reduction performance after reduction is better.

Description

Technical Field

[0001] The present invention belongs to the technical field of multidimensional data processing, and in particular relates to a method and system for processing multidimensional data in an electricity market. Background Art

[0002] The term "electricity market" encompasses both broad and narrow definitions. The broad definition of the electricity market encompasses all aspects of the power industry, including generation, transmission, distribution, and supply, including the electricity spot market, medium- and long-term electricity trading markets, ancillary services markets, capacity markets, and financial markets. The narrow definition of the electricity market refers to the electricity spot market and medium- and long-term electricity trading markets. It is a mechanism through which electricity producers and users trade electricity and related products through negotiation and bidding, with prices and quantities determined through market competition.

[0003] In terms of multidimensional data in the power market, an existing technical solution with a patent publication number of "CN219801975U" is often used to process the multidimensional data in the power market. The solution includes a terminal device (the terminal device can be a computer), and the terminal device is used to store and process the transmitted multidimensional data in the power market. The multidimensional data in the power market is wind speed data, wind direction data, power forecast data, meteorological data or market transaction data used in the power market.

[0004] Storing and processing the transmitted multi-dimensional data of the power market for a long time will result in a huge storage volume, so it is necessary to reduce the multi-dimensional data of the power market to reduce the storage area.

[0005] When analyzing the multidimensional data of the power market and determining the storage method of the multidimensional data of the power market, because the multidimensional data of the power market is a variable quantity, which continues to increase and decrease with the change of time point, the redundancy of the multidimensional data of the power market itself is not large. Using the LZ77 method to reduce the multidimensional data of the power market makes the reduction efficiency insufficient. Summary of the Invention

[0006] In order to solve the defects in the existing technology, the present invention proposes a system and method for processing multidimensional data of the power market, which obtains the benchmark points of the power market multidimensional data at each time point based on the peak and valley points of the power market multidimensional data, and reflects the change amplitude of each power market multidimensional data and the corresponding benchmark point based on the overall derivative status around the power market multidimensional data; reflects the small-scale fluctuations of the power market multidimensional data caused by external factors based on the difference between each power market multidimensional data and the peak and valley points; obtains the distortion point based on the distortion amplitude, and obtains the abnormal fluctuation range through expansion of the distortion point; obtains the abnormal amplitude of each starting point based on the distance between the abnormal fluctuation range on both sides of each starting point and the starting point and the traceability of the fluctuation of the abnormal fluctuation range; obtains all reasonable points based on the abnormal amplitudes of all starting points, and thus configures the power market multidimensional data around the reasonable point based on the power market multidimensional data of each reasonable point to obtain an improved queue, thereby maintaining the accuracy of the abnormal value and making the reduction performance after reduction better.

[0007] The present invention utilizes the following technical solutions.

[0008] A method for processing multidimensional data of an electricity market, comprising:

[0009] The terminal device stores and processes the transmitted multi-dimensional data of the power market, where the multi-dimensional data of the power market is wind speed data, wind direction data, power forecast data, meteorological data or market transaction data used by the power market;

[0010] The method for storing and processing the transmitted multi-dimensional data of the power market by the terminal device includes:

[0011] Step 1: Obtain multi-dimensional data of the electricity market at each time point;

[0012] Step 2: Obtain the distortion points and abnormal fluctuation ranges of the distortion points in the power market multidimensional data based on the distortion amplitude attribute of the power market multidimensional data. Obtain the abnormal amplitude of the starting point based on the traceability attribute of the abnormal fluctuation range. Use the abnormal amplitude of the starting point to perform selection and obtain a reasonable point. Use the power market multidimensional data of the reasonable point to perform supplementation on the surrounding power market multidimensional data to obtain an improved queue.

[0013] Step 3: Improve the queue reduction to achieve improved storage of multi-dimensional data in the power market.

[0014] Furthermore, in Step 1, the terminal device collects the multidimensional data of the electricity market once every 60 seconds, and collects the multidimensional data of the electricity market at all time points in 3 hours in total; in the Cartesian system, the time points are used as the values ​​on the X-axis and the multidimensional data of the electricity market are used as the values ​​on the Y-axis to construct the regression line of the multidimensional data.

[0015] Furthermore, in Step 1, the method for constructing the regression line of multidimensional data is the least squares method.

[0016] Furthermore, Step 2 includes:

[0017] Step 2-1: Obtain the reference points of the multi-dimensional data of the power market at each time point based on the peak and valley points of the multi-dimensional data of the power market; obtain the distortion coefficient of each multi-dimensional data of the power market based on the variation amplitude of each multi-dimensional data of the power market and the corresponding reference point; obtain the distortion amplitude of each multi-dimensional data of the power market based on the distortion coefficient of each multi-dimensional data of the power market and the difference between the same peak and valley points; obtain all distortion points based on the distortion amplitude of all multi-dimensional data of the power market; and obtain the abnormal fluctuation range of each distortion point;

[0018] Step 2-2: Select starting points in the entire multi-dimensional data of the power market according to a pre-defined number of equal numbers; obtain the abnormal amplitude of each starting point based on the multiple abnormal fluctuation ranges around each starting point and the distance between the starting points, combined with the traceability of the multiple abnormal fluctuation ranges around each starting point; select all reasonable points based on the abnormal amplitudes of all starting points;

[0019] Step 2-3: Based on the multi-dimensional data of the power market at each reasonable point, the surrounding multi-dimensional data of the power market is supplemented to obtain the configured multi-dimensional data of the power market; all the configured multi-dimensional data of the power market and all the unconfigured multi-dimensional data of the power market constitute an improvement queue.

[0020] Furthermore, Step 2-1 includes:

[0021] Obtain all valley points and peak points within the regression line of the multidimensional data; for the qth received electricity market multidimensional data within the regression line of the multidimensional data, obtain the distance from the qth received electricity market multidimensional data to the previous valley point and the distance from the qth received electricity market multidimensional data to the next valley point; take the lowest of the pair of valley point distances and define it as the reference range span of the qth received electricity market multidimensional data; use the qth received electricity market multidimensional data as the midpoint and take the reference range span of electricity market multidimensional data on both sides to define them as the reference points of the qth received electricity market multidimensional data; for the jth reference point of the qth received electricity market multidimensional data, define the derivative of the line connecting the jth reference point and the j-1th reference point of the qth received electricity market multidimensional data as the reference derivative of the jth reference point of the qth received electricity market multidimensional data, and the reference derivative of the first reference point is zero.

[0022] Furthermore, Step 2-1 also includes: the distortion coefficient U of the qth transmitted power market multidimensional data q The operational equation is:

[0023]

[0024] In the equation: p represents the base range span of the qth incoming multi-dimensional power market data, l q，j represents the benchmark derivative of the jth benchmark point on the qth transmitted power market multidimensional data side, l q，-j Represents the benchmark derivative of the jth benchmark point on the other side of the qth transmitted electricity market multidimensional data.

[0025] Furthermore, Step 2-1 also includes: the distortion amplitude N of the qth transmitted power market multi-dimensional data q The operational equation is:

[0026]

[0027] In the equation: U q represents the distortion coefficient of the qth incoming multidimensional data of the power market, z q The quantity represents the quantity obtained by subtracting the multidimensional data of the power market with the lowest value from the pair of adjacent valley points on both sides of the qth received multidimensional data of the power market. It represents the mean of the multidimensional data of the electricity market obtained by subtracting the lowest valley point in a pair of valley points on both sides of each peak point. Logistic() represents the Logistic function.

[0028] Furthermore, Step 2-1 also includes: obtaining the distortion amplitude of all the multidimensional data of the power market; pre-defining the distortion threshold, performing selection on all the multidimensional data of the power market according to the distortion amplitude, defining the multidimensional data of the power market with a distortion amplitude higher than the distortion threshold as a distortion point, and obtaining all the distortion points; defining the range between the valley points adjacent to each distortion point on both sides as the abnormal fluctuation range of each distortion point, and obtaining the abnormal fluctuation range of all the distortion points.

[0029] Furthermore, in Step 2-1, the predefined distortion threshold is one-half.

[0030] Furthermore, Step 2-2 includes: pre-defining a number, taking a piece of transmitted multi-dimensional data of the power market as a starting point at each distance from the number on the regression line, and obtaining multiple starting points; pre-defining an abnormal number, using each starting point as the midpoint and selecting an abnormal number of abnormal fluctuation ranges on both sides to define the abnormal reference domain of each starting point.

[0031] Furthermore, Step 2-2 also includes: the abnormal amplitude V of the rth starting point r The operational equation is:

[0032]

[0033] In the equation: M represents the number of abnormal fluctuation categories in the abnormal reference domain, t r,k Represents the distance between the kth abnormal fluctuation range distortion point and the rth starting point in the abnormal reference domain of the rth starting point, μ r,1 The standard deviation of the number of transmitted multidimensional data of the power market within all abnormal fluctuation ranges within the abnormal reference domain of the r-th starting point; the standard deviation of the time intervals between all adjacent pairs of distortion points within the abnormal fluctuation range within the abnormal reference domain of the r-th starting point; e is the Euler number.

[0034] Furthermore, Step 2-2 also includes: obtaining the abnormal amplitudes of all starting points; defining the abnormal critical value in advance, selecting all starting points according to the abnormal amplitude, defining the multidimensional data of the power market with abnormal amplitudes lower than the abnormal critical value as reasonable points, and obtaining all reasonable points.

[0035] Furthermore, Step 2-3 includes: pre-defining the filling number, using each reasonable point as the midpoint to select the filling number of power market multidimensional data on both sides, defining it as the representation range of each reasonable point, and terminating the selection of the power market multidimensional data on one side when the power market multidimensional data selected on one side is the power market multidimensional data in the abnormal fluctuation area; performing configuration on the power market multidimensional data of all power market multidimensional data within the representation range of each reasonable point, treating the power market multidimensional data of each reasonable point as the new power market multidimensional data of each power market multidimensional data in the representation range of the reasonable point, and defining it as each configured power market multidimensional data; arranging all configured power market multidimensional data and all unconfigured power market multidimensional data in the order of their time points to form an improved queue.

[0036] Furthermore, Step 3 includes: applying the LZ77 method to reduce the improved queue, obtaining the reduced queue, and storing the reduced queue to achieve improved storage of multi-dimensional data in the power market.

[0037] A system for processing multidimensional data of an electricity market, comprising:

[0038] Terminal equipment, the terminal equipment is used to store and process the transmitted multi-dimensional data of the power market, where the multi-dimensional data of the power market is wind speed data, wind direction data, power forecast data, meteorological data or market transaction data used by the power market;

[0039] Modules running on terminal devices include:

[0040] Acquisition module, obtains multi-dimensional data of the power market at each time point;

[0041] a selection module for obtaining distortion points and abnormal fluctuation ranges of the distortion points within the power market multidimensional data based on the distortion amplitude attribute of the power market multidimensional data, obtaining the abnormal amplitude of the starting point based on the traceability attribute of the abnormal fluctuation range, performing selection to obtain a reasonable point using the abnormal amplitude of the starting point, and using the power market multidimensional data at the reasonable point to perform supplementation on surrounding power market multidimensional data to obtain an improved queue;

[0042] The storage module is used to improve queue reduction and achieve improved storage of multi-dimensional data in the power market.

[0043] The beneficial effects of the present invention are that, compared with the prior art, the technical effects of the present invention include:

[0044] The reference points of the multidimensional data of the power market at each time point are obtained according to the peak and valley points of the multidimensional data of the power market. The change amplitude of each multidimensional data of the power market and the corresponding reference point is reflected according to the overall derivative situation around the multidimensional data of the power market, so as to obtain a more reliable distortion amplitude. The small-scale fluctuations of the multidimensional data of the power market due to external factors are reflected according to the difference between each multidimensional data of the power market and the peak and valley points. The distortion amplitude is obtained by combining the distortion coefficient of each multidimensional data of the power market, which avoids the interference of external factors on the distortion amplitude calculation and more accurately reflects the distortion amplitude. The value is selected to obtain the distortion point, and the abnormal fluctuation range is obtained by expanding the distortion point; the abnormal amplitude of each starting point is obtained according to the distance between the abnormal fluctuation range on both sides of each starting point and the starting point and the traceability of the abnormal fluctuation range, so as to determine whether the value around the starting point needs to maintain accuracy; all reasonable points are obtained according to the abnormal amplitude of all starting points, and the multi-dimensional data of the power market around the reasonable point is configured according to the multi-dimensional data of the power market at each reasonable point to obtain an improved queue, which increases the redundancy of the value and maintains the accuracy of the abnormal value, so that the reduction performance after reduction is better. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 It is a partial flow chart of the method for processing multi-dimensional data of the power market described in the present invention;

[0046] Figure 2 It is a partial structural diagram of the processing system of multi-dimensional data of the power market described in the present invention. DETAILED DESCRIPTION

[0047] To make the objectives, technical solutions, and advantages of the present invention more clear, the following will be combined with the accompanying drawings in the embodiments of the present invention to clearly and completely express the technical solutions of the present invention. The embodiments expressed in this application are only some embodiments of the present invention, not all embodiments. Based on the spirit of the present invention, other embodiments obtained by ordinary technicians in this field without making creative work are all within the scope of protection of the present invention.

[0048] like Figure 1 As shown, the method for processing multidimensional data of the power market according to the present invention includes:

[0049] The terminal device stores and processes the transmitted multi-dimensional data of the power market, where the multi-dimensional data of the power market is wind speed data, wind direction data, power forecast data, meteorological data or market transaction data used by the power market;

[0050] The method for storing and processing the transmitted multi-dimensional data of the power market by the terminal device includes:

[0051] Step 1: Obtain multi-dimensional data of the electricity market at each time point;

[0052] In a preferred but non-limiting embodiment of the present invention, in Step 1, the present application improves the redundancy of the transmitted electricity market multidimensional data while maintaining the accuracy of the anomaly value, thereby using the LZ77 method to perform reduction, so that the transmitted electricity market multidimensional data is initially obtained; the terminal device collects the electricity market multidimensional data once at a time point of 60 seconds, and collects the electricity market multidimensional data at all time points in 3 hours in total; in the Cartesian system, the time point is used as the value on the X-axis, and the electricity market multidimensional data is used as the value on the Y-axis to construct a regression line of the multidimensional data.

[0053] In a preferred but non-limiting embodiment of the present invention, in Step 1, the method for constructing the regression line of multidimensional data is the least squares method.

[0054] Step 2: Obtain the distortion points and abnormal fluctuation ranges of the distortion points in the power market multidimensional data based on the distortion amplitude attribute of the power market multidimensional data. Obtain the abnormal amplitude of the starting point based on the traceability attribute of the abnormal fluctuation range. Use the abnormal amplitude of the starting point to perform selection and obtain a reasonable point. Use the power market multidimensional data of the reasonable point to perform supplementation on the surrounding power market multidimensional data to obtain an improved queue.

[0055] In a preferred but non-limiting embodiment of the present invention, Step 2 includes:

[0056] Step 2-1: Obtain the reference points of the multi-dimensional data of the power market at each time point based on the peak and valley points of the multi-dimensional data of the power market; obtain the distortion coefficient of each multi-dimensional data of the power market based on the variation amplitude of each multi-dimensional data of the power market and the corresponding reference point; obtain the distortion amplitude of each multi-dimensional data of the power market based on the distortion coefficient of each multi-dimensional data of the power market and the difference between the same peak and valley points; obtain all distortion points based on the distortion amplitude of all multi-dimensional data of the power market; and obtain the abnormal fluctuation range of each distortion point;

[0057] Under normal circumstances, the multidimensional data of the power market shows an alternating increase and decrease. Under abnormal conditions such as abnormal changes in wind or weather, the regression line of the multidimensional data will show disordered distortion fluctuations. When reducing the multidimensional data of the power market, the accuracy of the abnormal value of the distortion fluctuation range must be maintained; therefore, the distortion amplitude of each multidimensional data of the power market is obtained by the derivative change of the line connecting the adjacent points in the regression line of the multidimensional data to reflect the disordered distortion fluctuation of the regression line of the multidimensional data, so that the distortion point is selected according to the distortion amplitude, and the abnormal fluctuation range of the regression line is obtained according to the distortion point.

[0058] In a preferred but non-limiting embodiment of the present invention, Step 2-1 includes:

[0059] Obtain all valley points (the multidimensional data of the power market at this point on the regression line is lower than the multidimensional data of the power market at the points adjacent to it on both sides) and peak points (the multidimensional data of the power market at this point on the regression line is higher than the multidimensional data of the power market at the points adjacent to it on both sides) within the regression line of the multidimensional data. For the qth multidimensional data transmitted within the regression line of the multidimensional data, obtain the distance from the qth multidimensional data transmitted to the previous valley point (the distance is the number of multidimensional data transmitted between the qth multidimensional data transmitted and its previous valley point) and the distance from the qth multidimensional data transmitted to its next valley point (the distance is the number of multidimensional data transmitted between the qth multidimensional data transmitted and its previous valley point). The number of multidimensional data of the electricity market transmitted between the first valley point and the next valley point is obtained, and the lowest one within the distance between a pair of valley points is taken as the benchmark range span of the qth multidimensional data of the electricity market transmitted; with the qth multidimensional data of the electricity market transmitted as the midpoint, the benchmark range span of the multidimensional data of the electricity market is taken on both sides respectively, and they are defined as the benchmark points of the qth multidimensional data of the electricity market transmitted; facing the jth benchmark point of the qth multidimensional data of the electricity market transmitted, the derivative of the line connecting the jth benchmark point and the j-1th benchmark point of the qth multidimensional data of the electricity market transmitted is defined as the benchmark derivative of the jth benchmark point of the qth multidimensional data of the electricity market transmitted, and the benchmark derivative of the first benchmark point is zero.

[0060] In a preferred but non-limiting embodiment of the present invention, Step 2-1 further includes: the distortion coefficient U of the qth transmitted power market multi-dimensional data q The operational equation is:

[0061]

[0062] In the equation: p represents the base range span of the qth incoming multi-dimensional power market data, l q，j represents the benchmark derivative of the jth benchmark point on the qth transmitted power market multidimensional data side, l q，-jRepresents the benchmark derivative of the jth benchmark point on the other side of the qth transmitted electricity market multidimensional data.

[0063] Here|l q，j -l q，-j | represents the modulus of the quantity obtained by subtracting the benchmark derivatives, reflecting the difference between the benchmark derivatives on both sides of the qth transmitted power market multidimensional data, |l q，j -l q，-j The higher | is, the higher the difference between the reference derivatives of the reference points on both sides of the qth transmitted power market multidimensional data is, and the higher the distortion coefficient of the qth transmitted power market multidimensional data is.

[0064] Furthermore, because external factors such as electromagnetic interference often cause small fluctuations in the multi-dimensional power market data, in addition to considering the value obtained by subtracting the base derivative, the distortion coefficient must be corrected based on these small fluctuations to obtain the distortion amplitude. The lowest value represents the lowest multi-dimensional power market data.

[0065] In a preferred but non-limiting embodiment of the present invention, Step 2-1 further includes: the distortion amplitude N of the qth transmitted power market multi-dimensional data q The operational equation is:

[0066]

[0067] In the equation: U q represents the distortion coefficient of the qth incoming multidimensional data of the power market, z q The quantity represents the quantity obtained by subtracting the multidimensional data of the power market with the lowest value from the pair of adjacent valley points on both sides of the qth received multidimensional data of the power market. It represents the mean of the multidimensional data of the electricity market obtained by subtracting the lowest valley point in a pair of valley points on both sides of each peak point. Logistic() represents the Logistic function.

[0068] Here The lower the value, the lower the change in the qth transmitted multidimensional data of the power market. The more likely it is that the fluctuation is low-amplitude caused by external factors rather than fluctuation caused by distortion. This value is used as the correction coefficient to calibrate the distortion coefficient.

[0069] In a preferred but non-limiting embodiment of the present invention, Step 2-1 further includes: obtaining the distortion amplitude of all the multidimensional data of the electricity market; pre-defining a distortion threshold, performing selection on all the multidimensional data of the electricity market according to the distortion amplitude, defining the multidimensional data of the electricity market with a distortion amplitude higher than the distortion threshold as a distortion point, and obtaining all the distortion points; defining the range between the valley points adjacent to each distortion point on both sides as the abnormal fluctuation range of each distortion point, and obtaining the abnormal fluctuation range of all the distortion points.

[0070] In a preferred but non-limiting embodiment of the present invention, in Step 2-1, the pre-defined distortion threshold is one-half.

[0071] Step 2-2: Select starting points in the entire multi-dimensional data of the power market according to a pre-defined number of equal numbers; obtain the abnormal amplitude of each starting point based on the multiple abnormal fluctuation ranges around each starting point and the distance between the starting points, combined with the traceability of the multiple abnormal fluctuation ranges around each starting point; select all reasonable points based on the abnormal amplitudes of all starting points;

[0072] In order to improve the reduction performance of the LZ77 method, the redundancy of other non-abnormal values ​​should be increased while maintaining the accuracy of the abnormal values; multiple starting points are evenly obtained on the regression line, and the abnormal amplitude of each starting point is obtained according to the distribution of the abnormal fluctuation range on both sides of each starting point, so as to determine whether the data around the starting point needs to be maintained accurately; the shorter the abnormal fluctuation range is between the starting points, the higher the effect on the starting point, then the higher the abnormal amplitude of the starting point, and the more accurate the multi-dimensional data of the power market around the starting point needs to be maintained; the lower the traceability of the fluctuation of the abnormal fluctuation range around the starting point, the less likely it is a reasonable fluctuation caused by the effect of the power equipment facing the power market, then the higher the abnormal amplitude of the starting point, and the more accurate the multi-dimensional data of the power market around the starting point needs to be maintained; for all starting points, reasonable points that do not need to be maintained accurately are selected according to the abnormal amplitude.

[0073] In a preferred but non-limiting embodiment of the present invention, Step 2-2 includes: pre-defining a number, taking a piece of transmitted multi-dimensional data of the power market as a starting point at each distance from the number on the regression line, and obtaining multiple starting points; pre-defining an abnormal number, using each starting point as the midpoint, and defining an abnormal reference domain for each starting point by selecting an abnormal number of abnormal fluctuation ranges on both sides; and when the abnormal number of abnormal fluctuation ranges on one side is less than the abnormal number of abnormal fluctuation ranges, taking the highest possible abnormal fluctuation range.

[0074] In a preferred but non-limiting embodiment of the present invention, Step 2-2 further includes: the abnormal amplitude V of the rth starting point r The operational equation is:

[0075]

[0076] In the equation: M represents the number of abnormal fluctuation categories in the abnormal reference domain, t r,k represents the distance between the distortion point of the kth abnormal fluctuation range and the rth starting point within the abnormal reference domain of the rth starting point (the distance is the number of multi-dimensional data of the power market transmitted between the distortion point of the kth abnormal fluctuation range and the rth starting point), μ r,1The standard deviation of the number of transmitted multidimensional data of the power market within all abnormal fluctuation ranges within the abnormal reference domain of the r-th starting point; the standard deviation of the time intervals between all adjacent pairs of distortion points within the abnormal fluctuation range within the abnormal reference domain of the r-th starting point; e is the Euler number.

[0077] Here Represents the cumulative distance between the midpoint of all abnormal fluctuations in the rth abnormal reference domain and the rth starting point, The lower it is, the smaller the distance between the midpoint of all abnormal fluctuations in the rth abnormal reference domain and the rth starting point is, and the higher the abnormal amplitude of the rth starting point is; μ r,1 +μ r,2 It reflects the traceability of the overall fluctuation amplitude of all abnormal fluctuations in the rth abnormal reference domain, μ r,1 +μ r,2 The higher the value is, the more disordered the fluctuations of all abnormal fluctuations in the r-th abnormal reference domain are, and the less likely they are reasonable fluctuations, so the higher the abnormal amplitude of the r-th starting point is.

[0078] In a preferred but non-limiting embodiment of the present invention, Step 2-2 also includes: obtaining the abnormal amplitudes of all starting points; defining the abnormal critical value in advance, selecting all starting points based on the abnormal amplitude, defining the multidimensional data of the electricity market with abnormal amplitudes lower than the abnormal critical value as reasonable points, and obtaining all reasonable points; the value of the defined abnormal critical value can be three tenths.

[0079] Step 2-3: Based on the multi-dimensional data of the power market at each reasonable point, the surrounding multi-dimensional data of the power market is supplemented to obtain the configured multi-dimensional data of the power market; all the configured multi-dimensional data of the power market and all the unconfigured multi-dimensional data of the power market constitute an improvement queue.

[0080] For the multidimensional data of the electricity market within the range of all reasonable points, the multidimensional data of the electricity market at the reasonable point is used to represent the multidimensional data of the electricity market of all the multidimensional data within the range of the reasonable point, so as to increase the numerical redundancy and improve the reduction performance; for all the multidimensional data of the electricity market outside the range of the reasonable point, no processing is performed to maintain its numerical accuracy.

[0081] In a preferred but non-limiting embodiment of the present invention, Step 2-3 includes: pre-defining the filling number, using each reasonable point as the midpoint to exceed the filling number of power market multidimensional data selected on both sides, defining it as the representation range of each reasonable point, and terminating the selection of the power market multidimensional data on this side when the power market multidimensional data selected on one side is the power market multidimensional data in the abnormal fluctuation area; performing configuration on the power market multidimensional data of all power market multidimensional data within the representation range of each reasonable point, treating the power market multidimensional data of each reasonable point as the new power market multidimensional data of each power market multidimensional data in the representation range of the reasonable point, and defining it as each configured power market multidimensional data; arranging all configured power market multidimensional data and all unconfigured power market multidimensional data in the order of their time points to form an improved queue.

[0082] Step 3: Improve the queue reduction to achieve improved storage of multi-dimensional data in the power market.

[0083] In a preferred but non-limiting embodiment of the present invention, Step 3 includes: applying the LZ77 method to reduce the improved queue, obtaining the reduced queue, and storing the reduced queue to achieve improved storage of multi-dimensional data of the electricity market.

[0084] like Figure 2 As shown, the present invention provides a system for processing multi-dimensional data of a power market, comprising:

[0085] a terminal device (which may be a computer), the terminal device being used to store and process the transmitted multi-dimensional data of the power market, the multi-dimensional data of the power market being wind speed data, wind direction data, power forecast data, meteorological data, or market transaction data used in the power market;

[0086] Modules running on terminal devices include:

[0087] Acquisition module, obtains multi-dimensional data of the power market at each time point;

[0088] a selection module for obtaining distortion points and abnormal fluctuation ranges of the distortion points within the power market multidimensional data based on the distortion amplitude attribute of the power market multidimensional data, obtaining the abnormal amplitude of the starting point based on the traceability attribute of the abnormal fluctuation range, performing selection to obtain a reasonable point using the abnormal amplitude of the starting point, and using the power market multidimensional data at the reasonable point to perform supplementation on surrounding power market multidimensional data to obtain an improved queue;

[0089] The storage module is used to improve queue reduction and achieve improved storage of multi-dimensional data in the power market.

[0090] The beneficial effects of the present invention are that, compared with the prior art, the technical effects of the present invention include:

[0091] The reference points of the multidimensional data of the power market at each time point are obtained according to the peak and valley points of the multidimensional data of the power market. The change amplitude of each multidimensional data of the power market and the corresponding reference point is reflected according to the overall derivative situation around the multidimensional data of the power market, so as to obtain a more reliable distortion amplitude. The small-scale fluctuations of the multidimensional data of the power market due to external factors are reflected according to the difference between each multidimensional data of the power market and the peak and valley points. The distortion amplitude is obtained by combining the distortion coefficient of each multidimensional data of the power market, which avoids the interference of external factors on the distortion amplitude calculation and more accurately reflects the distortion amplitude. The value is selected to obtain the distortion point, and the abnormal fluctuation range is obtained by expanding the distortion point; the abnormal amplitude of each starting point is obtained according to the distance between the abnormal fluctuation range on both sides of each starting point and the starting point and the traceability of the abnormal fluctuation range, so as to determine whether the value around the starting point needs to maintain accuracy; all reasonable points are obtained according to the abnormal amplitude of all starting points, and the multi-dimensional data of the power market around the reasonable point is configured according to the multi-dimensional data of the power market at each reasonable point to obtain an improved queue, which increases the redundancy of the value and maintains the accuracy of the abnormal value, so that the reduction performance after reduction is better.

[0092] The present disclosure can be a system, method, and / or computer program product. The computer program product can include a computer-readable storage medium having computer-readable program instructions thereon for causing a processor to implement various aspects of the disclosure.

[0093] The computer-readable backup medium can be a tangible network capable of retaining and backing up instructions executed by the instruction execution network. The computer-readable backup medium can be, but is not limited to, an electrical backup network, a magnetic backup network, an optical backup network, an electromagnetic backup network, a semiconductor backup network, or any suitable combination thereof. Further examples of computer-readable backup media (a non-exhaustive list) include: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a static random access memory (SRAM), a portable compact disc read-only memory (HDROM), a digital versatile disc (DXD), a memory stick, a floppy disk, a mechanically encoded network, such as a punch card or a raised structure in a groove on which instructions are backed up, or any suitable combination thereof. Computer readable backup media as used herein is not to be construed as transient signals themselves, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through waveguides or other transmission media (e.g., light pulses through power line cables), or electrical signals transmitted through wires.

[0094] The computer-readable program instructions expressed herein can be downloaded from a computer-readable backup medium to each computing / processing power grid circuit, or downloaded to an external computer or external backup power grid circuit via a wireless network, such as the Internet, a local area network, a wide area network, and / or a wireless network. A wireless network can include copper transmission cables, power transmission lines, wireless transmission, routers, firewalls, switches, gateway computers, and / or edge servers. A wireless network adapter card or wireless network interface in each computing / processing power grid circuit receives the computer-readable program instructions from the wireless network and forwards them to the computer-readable backup medium in each computing / processing power grid circuit for storage.

[0095] The computer program instructions for performing the operations of the present disclosure can be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-specific instructions, microcode, firmware instructions, conditional values, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Standard A, H++, and conventional procedural programming languages ​​such as "H" language or similar programming languages. The computer-readable program instructions can be executed entirely on the client computer, partially on the client computer, as a stand-alone software package, partially on the client computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer can be connected to the client computer via any wireless network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computer (such as through the Internet using an Internet service provider). In some embodiments, the electronic circuit is customized by using the status values ​​of computer-readable program instructions, such as a programmable logic circuit, a field programmable gate array (FPGA) or a programmable logic array (PLA), which can execute computer-readable program instructions to achieve various aspects of the overhead disclosure.

[0096] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents, and any modifications or equivalent replacements that do not deviate from the spirit and scope of the present invention should be covered within the protection scope of the claims of the present invention.

Claims

1. A method for processing multidimensional data in an electricity market, characterized in that: include: The terminal device performs storage processing on the transmitted multi-dimensional data of the power market, where the multi-dimensional data of the power market is wind speed data, wind direction data, power forecast data, meteorological data or market transaction data used in the power market; The method for storing and processing the transmitted multi-dimensional data of the power market by the terminal device includes: Step 1: Obtain multi-dimensional data of the power market at each time point; Step 2: Obtain the distortion points and abnormal fluctuation ranges of the distortion points in the power market multidimensional data according to the distortion amplitude attribute of the power market multidimensional data, obtain the abnormal amplitude of the starting point according to the traceability attribute of the abnormal fluctuation range, use the abnormal amplitude of the starting point to perform selection and obtain a reasonable point, and use the power market multidimensional data of the reasonable point to perform supplementation on the surrounding power market multidimensional data to obtain an improved queue; Step 3: Improve the queue reduction to achieve improved storage of multi-dimensional data in the power market.

2. The method for processing multidimensional data of the power market according to claim 1, characterized in that: In Step 1, the terminal equipment collects the multidimensional data of the power market once every 60 seconds, and collects the multidimensional data of the power market at all time points in 3 hours in total; in the Cartesian system, the time point is the value on the X-axis, and the multidimensional data of the power market is the value on the Y-axis to construct the regression line of the multidimensional data; In Step 1, the method for constructing the regression line of multidimensional data is the least squares method.

3. The method for processing multidimensional data of the power market according to claim 2, characterized in that: Step 2 includes: Step 2-1: Obtain the reference points of the multidimensional data of the power market at each time point according to the peak and valley points of the multidimensional data of the power market; obtain the distortion coefficient of each multidimensional data of the power market according to the variation amplitude of each multidimensional data of the power market and the corresponding reference point; obtain the distortion amplitude of each multidimensional data of the power market according to the distortion coefficient of each multidimensional data of the power market and the difference between the same peak and valley points; obtain all distortion points according to the distortion amplitude of all multidimensional data of the power market; obtain the abnormal fluctuation range of each distortion point; Step 2-2: Select starting points in equal numbers in all the multi-dimensional data of the power market according to the pre-defined number; obtain the abnormal amplitude of each starting point according to the multiple abnormal fluctuation ranges around each starting point and the distance between the starting points, combined with the traceability of the multiple abnormal fluctuation ranges around each starting point; select and obtain all reasonable points according to the abnormal amplitudes of all starting points; Step 2-3: According to the multi-dimensional data of the power market at each reasonable point, the multi-dimensional data of the surrounding power market is supplemented to obtain the configured multi-dimensional data of the power market; all the configured multi-dimensional data of the power market and all the unconfigured multi-dimensional data of the power market constitute an improvement queue.

4. The method for processing multidimensional data of the power market according to claim 3, characterized in that: Step 2-1 includes: Obtain all valley points and peak points in the regression line of the multidimensional data; facing the qth transmitted power market multidimensional data in the regression line of the multidimensional data, obtain the distance from the qth transmitted power market multidimensional data to the previous valley point and the distance from the qth transmitted power market multidimensional data to its next valley point, take the lowest one of the distances between a pair of valley points, and define it as the reference range span of the qth transmitted power market multidimensional data; take the qth transmitted power market multidimensional data as the midpoint and take the reference range span of power market multidimensional data on both sides, and define it as the reference point of the qth transmitted power market multidimensional data; facing the jth reference point of the qth transmitted power market multidimensional data, define the derivative of the line connecting the jth reference point and the j-1th reference point of the qth transmitted power market multidimensional data as the reference derivative of the jth reference point of the qth transmitted power market multidimensional data, and the reference derivative of the first reference point is zero; Step 2-1 also includes: the distortion coefficient U of the qth transmitted multidimensional data of the power market q The operational equation is: In the equation: p represents the base range span of the qth multi-dimensional data of the power market, l q，j represents the benchmark derivative of the jth benchmark point on the qth transmitted power market multidimensional data side, l q，-j Represents the benchmark derivative of the jth benchmark point on the other side of the qth transmitted power market multidimensional data.

5. The method for processing multidimensional data of the power market according to claim 4, characterized in that: Step 2-1 also includes: the distortion amplitude N of the qth transmitted multidimensional data of the power market q The operational equation is: In the equation: U q represents the distortion coefficient of the qth transmitted multidimensional data of the power market, z q The quantity represents the quantity obtained by subtracting the multidimensional data of the power market with the lowest value in a pair of adjacent valley points on both sides from the multidimensional data of the power market of the qth transmitted power market. It represents the mean of the multidimensional data of the electricity market obtained by subtracting the lowest valley point in a pair of valley points on both sides from each peak point. Logistic() represents the Logistic function. Step 2-1 also includes: obtaining the distortion amplitude of all the multidimensional data of the power market; defining the distortion critical value in advance, selecting all the multidimensional data of the power market according to the distortion amplitude, defining the multidimensional data of the power market with a distortion amplitude higher than the distortion critical value as a distortion point, and obtaining all the distortion points; defining the range between the valley points adjacent to each distortion point on both sides as the abnormal fluctuation range of each distortion point, and obtaining the abnormal fluctuation range of all the distortion points.

6. The method for processing multidimensional data of the power market according to claim 5, characterized in that: In Step 2-1, the pre-defined distortion threshold is one-half.

7. The method for processing multidimensional data of the power market according to claim 6, characterized in that: Step 2-2 includes: defining a number in advance, taking a transmitted multi-dimensional data of the power market as a starting point at each distance from the number on the regression line, and obtaining multiple starting points; defining an abnormal number in advance, using each starting point as the midpoint, and selecting an abnormal number of abnormal fluctuation ranges on both sides to define the abnormal reference domain of each starting point; Step 2-2 also includes: the abnormal amplitude V of the rth starting point r The operational equation is: In the equation: M represents the number of abnormal fluctuation categories in the abnormal reference domain, t r,k Represents the distance between the distortion point of the kth abnormal fluctuation range in the abnormal reference domain of the rth starting point and the rth starting point, μ r,1 The standard deviation of the number of multi-dimensional data of the power market transmitted in the abnormal fluctuation range in the abnormal reference domain representing the rth starting point, the standard deviation of the time interval between all adjacent pairs of distortion points in the abnormal fluctuation range in the abnormal reference domain representing the rth starting point; e is the Euler number; Step 2-2 also includes: obtaining the abnormal amplitude of all starting points; defining the abnormal critical value in advance, selecting all starting points according to the abnormal amplitude, defining the multidimensional data of the power market with abnormal amplitude lower than the abnormal critical value as reasonable points, and obtaining all reasonable points.

8. The method for processing multidimensional data of the power market according to claim 7, characterized in that: Step 2-3 includes: defining the filling number in advance, using each reasonable point as the midpoint to select the filling number of power market multidimensional data on both sides, defining it as the representation range of each reasonable point, and terminating the selection of the power market multidimensional data on one side when the power market multidimensional data selected on the side is the power market multidimensional data in the abnormal fluctuation area; configuring the power market multidimensional data of all power market multidimensional data within the representation range of each reasonable point, treating the power market multidimensional data of each reasonable point as the new power market multidimensional data of each power market multidimensional data in the representation range of the reasonable point, defining it as each configured power market multidimensional data; arranging all configured power market multidimensional data and all unconfigured power market multidimensional data in the order of their time points to form an improvement queue.

9. The method for processing multidimensional data of the power market according to claim 8, characterized in that: Step 3 includes: using the LZ77 method to reduce the improved queue, obtaining the reduced queue, storing the reduced queue, and achieving improved storage of multi-dimensional data in the power market.

10. A system for processing multidimensional data of power market, characterized in that: include: Terminal equipment, the terminal equipment is used to store and process the transmitted multi-dimensional data of the power market, where the multi-dimensional data of the power market is wind speed data, wind direction data, power forecast data, meteorological data or market transaction data used in the power market; Modules running on terminal devices include: Acquisition module, to obtain multi-dimensional data of the power market transmitted at each time point; A selection module is used to obtain the distortion point and the abnormal fluctuation range of the distortion point in the power market multidimensional data according to the distortion amplitude attribute of the power market multidimensional data, obtain the abnormal amplitude of the starting point according to the traceability attribute of the abnormal fluctuation range, use the abnormal amplitude of the starting point to perform selection to obtain a reasonable point, and use the power market multidimensional data of the reasonable point to perform supplementation on the surrounding power market multidimensional data to obtain an improved queue; The storage module is used to improve queue reduction and achieve improved storage of multi-dimensional data in the electricity market.

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