CN113723512B

CN113723512B - Resource balanced distribution method and system for electric vehicle photovoltaic charging station network

Info

Publication number: CN113723512B
Application number: CN202111011690.7A
Authority: CN
Inventors: 陈羿铭; 王宇凤
Original assignee: Nupt Institute Of Big Data Research At Yancheng
Current assignee: Nupt Institute Of Big Data Research At Yancheng
Priority date: 2021-08-31
Filing date: 2021-08-31
Publication date: 2022-08-02
Anticipated expiration: 2041-08-31
Also published as: CN113723512A

Abstract

The invention discloses a resource balanced distribution method and a resource balanced distribution system for a photovoltaic charging station network of an electric vehicle, wherein the method comprises the steps of obtaining longitude and latitude coordinates of N photovoltaic charging columns; clustering longitude and latitude coordinates of the N photovoltaic charging columns to obtain M photovoltaic charging stations; constructing an electric vehicle charging network according to the M photovoltaic charging stations; acquiring photovoltaic power generation capacity, discharge duration, original charge price and electricity purchase cost of each photovoltaic charging station in the electric vehicle charging network at different time periods; calculating the net income of each photovoltaic charging station in different time periods according to the photovoltaic power generation amount, the discharge time, the original charging price and the electricity purchasing cost; and setting new charging prices for each photovoltaic charging station in different time periods according to the discharging time period, the net income and the original charging price. Has the advantages that: the charging requirements for the users are equalized, and the photovoltaic charging station achieves the maximum benefit.

Description

Resource balanced distribution method and system for electric vehicle photovoltaic charging station network

Technical Field

The invention relates to the technical field of electric vehicle charging, in particular to a resource balanced distribution method and system for an electric vehicle photovoltaic charging station network.

Background

At present that resources are in short supply, new energy vehicles, especially pure electric vehicles, gradually become research hotspots, and electric vehicle users are distributed in different places in a city, and due to factors such as population distribution, the charging demands of the users reaching electric vehicle charging stations have the phenomenon of geographic position distribution imbalance, so that the phenomena that the user demands are blocked at certain charging stations and the charging resources of other charging stations are idle can occur.

Disclosure of Invention

The present invention is directed to solving, at least to some extent, one of the technical problems in the art described above. Therefore, a first object of the present invention is to provide a method for resource balanced allocation of an electric vehicle photovoltaic charging station network, wherein new charging prices are set for each photovoltaic charging station in the electric vehicle charging network at different time periods through the discharge time, net income and original charging price of each photovoltaic charging station in the electric vehicle charging network at different time periods, so that the charging demands on users are balanced, and the photovoltaic charging stations achieve maximum benefits.

The second purpose of the invention is to provide a resource balanced distribution system of an electric vehicle photovoltaic charging station network.

In order to achieve the above object, an embodiment of a first aspect of the present invention provides a method for balanced resource allocation of an electric vehicle photovoltaic charging station network, including:

acquiring longitude and latitude coordinates of each photovoltaic charging column; the number of the photovoltaic charging columns is N;

clustering longitude and latitude coordinates of the N photovoltaic charging columns to obtain M clustering centers, and obtaining M photovoltaic charging stations according to the M clustering centers;

constructing an electric vehicle charging network according to the M photovoltaic charging stations;

acquiring photovoltaic power generation capacity of each photovoltaic charging station in the electric vehicle charging network at different time periods;

acquiring the discharge duration of each photovoltaic charging station in the electric vehicle charging network in different time periods;

acquiring the original charging price of each photovoltaic charging station in the electric vehicle charging network in different time periods;

acquiring the electricity purchasing cost of each photovoltaic charging station in the electric vehicle charging network in different time periods;

calculating the net income of each photovoltaic charging station in different time periods according to the photovoltaic power generation amount, the discharge time, the original charging price and the electricity purchasing cost;

and setting new charging prices for each photovoltaic charging station in different time periods according to the discharging time period, the net income and the original charging price.

Further, acquiring longitude and latitude coordinates of a photovoltaic charging post comprises:

receiving a first positioning signal sent by a positioning satellite through a GPS module arranged on a photovoltaic charging column;

performing signal segmentation processing on the first positioning signal to obtain a plurality of sub first positioning signals, and respectively obtaining a plurality of intensities corresponding to each sub first positioning signal at a plurality of moments;

calculating according to a plurality of intensities corresponding to each sub-first positioning signal at a plurality of moments to obtain an intensity standard deviation of each sub-first positioning signal, respectively judging whether the intensity standard deviation is smaller than a preset intensity standard deviation, screening out the sub-first positioning signals of which the intensity standard deviation is smaller than the preset intensity standard deviation, and generating a second positioning signal;

calculating a noise power in the second positioning signal;

calculating a signal power in the second positioning signal;

calculating to obtain a signal-to-noise ratio of the second positioning signal according to the noise power and the signal power, judging whether the signal-to-noise ratio is smaller than a preset signal-to-noise ratio, and extracting parity bits of the second positioning signal when the signal-to-noise ratio is smaller than the preset signal-to-noise ratio to obtain a first odd signal and a first even signal;

converting the first odd-numbered signal from a time domain to a frequency domain to obtain a frequency domain odd-numbered signal;

converting the first even number signal from a time domain to a frequency domain to obtain a frequency domain even number signal;

performing modulus calculation on the frequency domain odd number signal to obtain a first modulus;

performing modulus calculation on the frequency domain even number signal to obtain a second modulus value;

judging whether the first modulus value is smaller than a preset modulus value or not, and carrying out zero setting processing on the frequency domain odd number signal when the first modulus value is determined to be smaller than the preset modulus value;

judging whether the second modulus value is smaller than a preset modulus value or not, and carrying out zero setting processing on the frequency domain even number signal when the second modulus value is smaller than the preset modulus value;

performing sparse processing on the frequency domain odd-numbered signals subjected to zero processing, and converting the frequency domain odd-numbered signals into time domains to obtain second odd-numbered signals;

performing sparse processing on the frequency domain even number signal subjected to zero setting processing, and converting the frequency domain even number signal into a time domain to obtain a second even number signal;

combining the second odd-numbered signal and the second even-numbered signal to obtain a third positioning signal;

and analyzing the third positioning signal to obtain the longitude and latitude coordinates of the photovoltaic power generation column.

Further, clustering the longitude and latitude coordinates of the N photovoltaic charging columns to obtain M clustering centers, including:

generating a first longitude and latitude coordinate set according to the longitude and latitude coordinates of the N photovoltaic charging columns;

sequencing each longitude and latitude coordinate in the first longitude and latitude coordinate set according to the sequence of coordinate values from small to large to obtain a sequenced first longitude and latitude coordinate set;

acquiring longitude and latitude coordinates at the head end position in the sorted first longitude and latitude coordinate set, and taking the longitude and latitude coordinates as first target longitude and latitude coordinates;

respectively calculating the Euclidean distance from each longitude and latitude coordinate in the sorted first longitude and latitude coordinate set to the first target longitude and latitude coordinate, screening out the longitude and latitude coordinate with the Euclidean distance smaller than a preset Euclidean distance, and generating a coordinate clustering set according to the first target longitude and latitude coordinate and the longitude and latitude coordinate with the Euclidean distance smaller than the preset Euclidean distance;

removing longitude and latitude coordinates included in the coordinate clustering set from the first longitude and latitude coordinate set to obtain a second longitude and latitude coordinate set;

sequencing each longitude and latitude coordinate in the second longitude and latitude coordinate set from small to large according to the coordinate values to obtain a sequenced second longitude and latitude coordinate set;

acquiring longitude and latitude coordinates at the head end position in the sorted second longitude and latitude coordinate set, and taking the longitude and latitude coordinates as second target longitude and latitude coordinates, and repeating the steps until each longitude and latitude coordinate in the longitude and latitude coordinate set is clustered to obtain M coordinate clustered sets;

respectively sequencing the longitude and latitude coordinates included in each coordinate clustering set in the M coordinate clustering sets from small to large according to the coordinate values;

respectively obtaining longitude and latitude coordinates at the middle position in each sorted coordinate clustering set to obtain M middle longitude and latitude coordinates, and obtaining M clustering centers according to the M middle longitude and latitude coordinates.

Further, before analyzing the third positioning signal, the method further comprises performing enhancement processing on the third positioning signal.

Further, performing enhancement processing on the third positioning signal includes:

performing signal segmentation processing on the third positioning signal to obtain a plurality of sub-third positioning signals, respectively obtaining the amplitude of each sub-third positioning signal to obtain a plurality of amplitudes, calculating to obtain an average amplitude according to the plurality of amplitudes, and inquiring a preset average amplitude-gain coefficient table according to the average amplitude to obtain a corresponding gain coefficient;

and adjusting the gain value of a gain amplifier according to the gain coefficient, and inputting the third positioning signal into the gain amplifier with the adjusted gain value for enhancement processing.

Further, calculating a noise power in the second positioning signal includes:

inputting the second positioning signal into a down converter for down-conversion processing to obtain a baseband positioning signal;

performing up-sampling processing on the baseband positioning signal to obtain a digital positioning signal;

performing signal segmentation processing on the digital signal to obtain a plurality of sub-digital positioning signals, and performing Hanning window processing on the plurality of sub-digital positioning signals respectively;

respectively carrying out fast Fourier transform on a plurality of sub-digital positioning signals subjected to Hanning window processing to obtain a plurality of complex sequences and carrying out smoothing processing;

respectively carrying out modulus squaring treatment on each smoothed complex sequence to obtain a first power spectrogram corresponding to each sub-digital positioning signal;

superposing the first power spectrogram corresponding to each sub-digital positioning signal and then averaging to obtain a second power spectrogram of the second positioning signal; the second power spectrogram comprises a power spectral line;

in the second power spectrogram, acquiring a power value of each spectral point on the power spectral line, classifying the spectral points with the same power value to obtain a plurality of spectral point sets, and counting the number of spectral points included in each spectral point set;

drawing a curve to be detected by taking the number of the spectrum points in each spectrum point set as a vertical coordinate and the power value of each spectrum point set as a horizontal coordinate;

acquiring a power value of each coordinate point on the curve to be detected, comparing the power value of each coordinate point with the power values of adjacent coordinate points, screening out the coordinate points of which the power values are greater than the power values of the adjacent coordinate points, and generating a first coordinate point set;

comparing the power values of the coordinate points included in the first coordinate point set with a preset power value, screening out the coordinate points of which the power values are greater than the preset power value, and generating a second coordinate point set;

and sorting the coordinate points in the second coordinate point set according to the sequence of the power values from small to large, screening out the minimum power value, and taking the minimum power value as the noise power in the second positioning signal.

Further, setting new charging prices for each photovoltaic charging station at different time periods according to the discharge time period, the net income, and the original charging price, including:

when the discharging time length of the same photovoltaic charging station in the same time period is determined to be greater than a preset discharging time length and the net income is determined to be greater than a preset net income, a first discharging time length difference value between the discharging time length and the preset discharging time length and a first net income difference value between the net income and the preset net income are determined, a first adjusting parameter is determined according to the first discharging time length difference value and the first net income difference value, the original charging price is adjusted according to the first adjusting parameter and is used as a new charging price of the photovoltaic charging station in the time period;

when the discharging time length of the same photovoltaic charging station in the same time period is determined to be larger than a preset discharging time length and the net income is determined to be smaller than a preset net income, a second discharging time length difference value of the discharging time length and the preset discharging time length and a second net income difference value of the net income and the preset net income are determined, a second adjusting parameter is determined according to the second discharging time length difference value and the second net income difference value, the original charging price is adjusted according to the second adjusting parameter and is used as a new charging price of the photovoltaic charging station in the time period;

when the discharging time length of the same photovoltaic charging station in the same time period is determined to be smaller than a preset discharging time length and the net income is determined to be larger than the preset net income, a third discharging time length difference value of the discharging time length and the preset discharging time length and a third net income difference value of the net income and the preset net income are determined, a third adjusting parameter is determined according to the third discharging time length difference value and the third net income difference value, and the original charging price is adjusted to be smaller according to the third adjusting parameter and is used as a new charging price of the photovoltaic charging station in the time period;

when the fact that the discharging time of the same photovoltaic charging station in the same time period is smaller than the preset discharging time and the net income is smaller than the preset net income is determined, a fourth discharging time difference value of the discharging time and the preset discharging time and a fourth net income difference value of the net income and the preset net income are determined, a fourth adjusting parameter is determined according to the fourth discharging time difference value and the fourth net income difference value, the original charging price is adjusted according to the fourth adjusting parameter and is used as a new charging price of the photovoltaic charging station in the time period.

In order to achieve the above object, a second aspect of the present invention provides a system for balanced resource distribution of a photovoltaic charging station network of an electric vehicle, including: the longitude and latitude coordinate acquisition module is used for acquiring longitude and latitude coordinates of each photovoltaic charging column; the number of the photovoltaic charging columns is N;

the clustering module is used for clustering longitude and latitude coordinates of the N photovoltaic charging columns to obtain M clustering centers, and obtaining M photovoltaic charging stations according to the M clustering centers;

the building module is used for building an electric vehicle charging network according to the M photovoltaic charging stations;

the total charging times acquisition module is used for acquiring the total charging times of each photovoltaic charging station in the electric vehicle charging network within a preset time period;

the sub-charging times acquisition module is used for equally dividing the preset time period to obtain a plurality of sub-time periods and acquiring the sub-charging times of each photovoltaic charging station in the electric vehicle charging network in the sub-time periods;

the charging rate acquisition module is used for acquiring the charging rate of each photovoltaic charging station in the electric vehicle charging network within a preset time period;

and the pricing module is used for performing time-period combined pricing on each photovoltaic charging station according to the total charging times, the sub-charging times and the charging rate.

Further, the latitude and longitude coordinate acquiring module includes:

the first positioning signal acquisition module is used for receiving a first positioning signal sent by a positioning satellite through a GPS module arranged on the photovoltaic charging column;

a second positioning signal generation module for

a second positioning signal processing module for:

calculating a noise power in the second positioning signal;

calculating a signal power in the second positioning signal;

performing modulus calculation on the frequency domain odd number signal to obtain a first modulus value;

a control module to:

Further, the clustering module includes:

the first longitude and latitude coordinate set generating module is used for generating a first longitude and latitude coordinate set according to the longitude and latitude coordinates of the N photovoltaic charging columns;

a first target longitude and latitude coordinate acquisition module, configured to:

the coordinate clustering set generating module is used for respectively calculating the Euclidean distance from each longitude and latitude coordinate in the sorted first longitude and latitude coordinate set to the first target longitude and latitude coordinate, screening out the longitude and latitude coordinate with the Euclidean distance smaller than a preset Euclidean distance, and generating a coordinate clustering set according to the first target longitude and latitude coordinate and the longitude and latitude coordinate with the Euclidean distance smaller than the preset Euclidean distance;

the second longitude and latitude coordinate set generation module is used for eliminating longitude and latitude coordinates included in the coordinate clustering set from the first longitude and latitude coordinate set to obtain a second longitude and latitude coordinate set;

a cluster center acquisition module configured to:

Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by the practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and drawings.

The technical solution of the present invention is further described in detail by the accompanying drawings and embodiments.

Drawings

The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention. In the drawings:

FIG. 1 is a flow chart of a resource balance allocation method of an electric vehicle photovoltaic charging station network according to the present invention;

FIG. 2 is a block diagram of a resource balancing distribution system of an electric vehicle photovoltaic charging station network according to the present invention;

fig. 3 is a block diagram of a resource balanced distribution system of an electric vehicle photovoltaic charging station network according to an embodiment of the invention.

Reference numerals:

the system comprises a longitude and latitude coordinate acquisition module 1, a clustering module 2, a construction module 3, a photovoltaic power generation capacity acquisition module 4, a discharge duration acquisition module 5, an original charging price acquisition module 6, an electricity purchase cost acquisition module 7, a net income calculation module 8, a pricing module 9, a first positioning signal acquisition module 10, a second positioning signal generation module 11, a second positioning signal processing module 12 and a control module 13.

Detailed Description

The preferred embodiments of the present invention will be described in conjunction with the accompanying drawings, and it will be understood that they are described herein for the purpose of illustration and explanation and not limitation.

The following describes a method and a system for resource balanced allocation of an electric vehicle photovoltaic charging station network according to an embodiment of the present invention with reference to fig. 1 to 3.

As shown in fig. 1, a method for resource balanced allocation of an electric vehicle photovoltaic charging station network includes:

s1, acquiring longitude and latitude coordinates of each photovoltaic charging column; the number of the photovoltaic charging columns is N;

s2, clustering longitude and latitude coordinates of the N photovoltaic charging columns to obtain M clustering centers, and obtaining M photovoltaic charging stations according to the M clustering centers;

s3, constructing an electric vehicle charging network according to the M photovoltaic charging stations;

s4, acquiring the photovoltaic power generation amount of each photovoltaic charging station in the electric vehicle charging network in different time periods;

s5, acquiring the discharge duration of each photovoltaic charging station in the electric vehicle charging network in different time periods;

s6, acquiring the original charging price of each photovoltaic charging station in the electric vehicle charging network in different time periods;

s7, acquiring the electricity purchasing cost of each photovoltaic charging station in the electric vehicle charging network in different time periods;

s8, calculating the net income of each photovoltaic charging station in different time periods according to the photovoltaic power generation amount, the discharge time, the original charging price and the electricity purchasing cost;

and S9, setting new charging prices for each photovoltaic charging station in different time periods according to the discharging time period, the net income and the original charging price.

The working principle of the scheme is as follows: acquiring longitude and latitude coordinates of each photovoltaic charging column; the number of the photovoltaic charging columns is N; clustering longitude and latitude coordinates of the N photovoltaic charging columns to obtain M clustering centers, and obtaining M photovoltaic charging stations according to the M clustering centers; constructing an electric vehicle charging network according to the M photovoltaic charging stations; acquiring photovoltaic power generation capacity of each photovoltaic charging station in the electric vehicle charging network at different time periods; acquiring the discharge duration of each photovoltaic charging station in the electric vehicle charging network in different time periods; acquiring the original charging price of each photovoltaic charging station in the electric vehicle charging network in different time periods; acquiring the electricity purchasing cost of each photovoltaic charging station in the electric vehicle charging network in different time periods; calculating the net income of each photovoltaic charging station in different time periods according to the photovoltaic power generation amount, the discharge time, the original charging price and the electricity purchasing cost; and setting new charging prices for each photovoltaic charging station in different time periods according to the discharging time period, the net income and the original charging price.

The beneficial effect of above-mentioned scheme: taking longitude and latitude coordinates of each photovoltaic charging column; the number of the photovoltaic charging columns is N; clustering longitude and latitude coordinates of the N photovoltaic charging columns, clustering the photovoltaic charging columns with similar positions into one class to obtain M clustering centers, and obtaining M photovoltaic charging stations according to the M clustering centers, wherein each photovoltaic charging station comprises a plurality of photovoltaic charging columns; constructing an electric vehicle charging network according to the M photovoltaic charging stations, and acquiring the photovoltaic power generation amount of each photovoltaic charging station in the electric vehicle charging network in different time periods; acquiring the discharge duration of each photovoltaic charging station in the electric vehicle charging network in different time periods; acquiring the original charging price of each photovoltaic charging station in the electric vehicle charging network in different time periods; acquiring the electricity purchasing cost of each photovoltaic charging station in the electric vehicle charging network in different time periods; calculating the net income of each photovoltaic charging station in different time periods according to the photovoltaic power generation amount, the discharge time, the original charging price and the electricity purchasing cost; setting new charging prices for each photovoltaic charging station in different time periods according to the discharging time length, the net income and the original charging price, facilitating a user to check information of each charging station on the internet through a constructed electric vehicle charging network, recording the use condition of each charging station, facilitating a manager to manage each charging station, and setting charging prices for each photovoltaic charging station in different time periods through the net income, the discharging time length and the original charging price of each photovoltaic charging station in different time periods, so that the charging demand for the user is equalized, the photovoltaic charging stations achieve maximum income, wherein the original charging price is the initial price of the photovoltaic charging station, namely the charging price before adjustment is not carried out; the user charges at night, and when the storage electric quantity of the photovoltaic charging station is used up, the user needs to purchase electricity to charge the electric automobile of the user, and the electricity purchasing cost is the cost for purchasing electricity.

According to some embodiments of the invention, obtaining longitude and latitude coordinates of a photovoltaic charging post comprises:

calculating a noise power in the second positioning signal;

calculating a signal power in the second positioning signal;

The working principle of the scheme is as follows: receiving a first positioning signal sent by a positioning satellite through a GPS module arranged on a photovoltaic charging column; performing signal segmentation processing on the first positioning signal to obtain a plurality of sub first positioning signals, and respectively obtaining a plurality of intensities corresponding to each sub first positioning signal at a plurality of moments; calculating the intensity standard deviation of each sub-first positioning signal according to a plurality of intensities corresponding to each sub-first positioning signal at a plurality of moments, wherein the intensity standard deviation is the standard deviation of the plurality of intensities corresponding to each sub-first positioning signal at the plurality of moments, the intensity standard deviation represents the discrete degree of each sub-first positioning signal, and the smaller the intensity standard deviation table is, the smaller the discrete degree of each sub-first positioning signal is, the stronger the stability of each sub-first positioning signal is; the larger the intensity standard deviation is, the larger the dispersion degree of the sub first positioning signals is, the worse the stability of the sub first positioning signals is; respectively judging whether the intensity standard deviation is smaller than a preset intensity standard deviation, screening out sub-first positioning signals of which the intensity standard deviation is smaller than the preset intensity standard deviation, and generating second positioning signals; calculating a noise power in the second positioning signal; calculating a signal power in the second positioning signal; calculating to obtain a signal-to-noise ratio of the second positioning signal according to the noise power and the signal power, judging whether the signal-to-noise ratio is smaller than a preset signal-to-noise ratio, and extracting parity bits of the second positioning signal when the signal-to-noise ratio is smaller than the preset signal-to-noise ratio to obtain a first odd signal and a first even signal; converting the first odd-numbered signal from a time domain to a frequency domain to obtain a frequency domain odd-numbered signal; converting the first even number signal from a time domain to a frequency domain to obtain a frequency domain even number signal; performing modulus calculation on the frequency domain odd-numbered signal to obtain a first modulus, wherein the first modulus represents the strength of an effective signal in the frequency domain odd-numbered signal; performing modulus calculation on the frequency domain even number signal to obtain a second modulus value, wherein the second modulus value represents the strength of an effective signal in the frequency domain even number signal; judging whether the first modulus is smaller than a preset modulus, wherein the preset modulus is an average value of the modulus of the frequency domain odd signal with small noise and the modulus of the frequency domain even signal with small noise; when the first modulus is determined to be smaller than a preset modulus, carrying out zero setting processing on the frequency domain odd number signal; judging whether the second modulus value is smaller than a preset modulus value or not, and carrying out zero setting processing on the frequency domain even number signal when the second modulus value is smaller than the preset modulus value; performing sparse processing on the frequency domain odd-numbered signals subjected to zero processing, and converting the frequency domain odd-numbered signals into time domains to obtain second odd-numbered signals; performing sparse processing on the frequency domain even number signal subjected to zero setting processing, and converting the frequency domain even number signal into a time domain to obtain a second even number signal; combining the second odd-numbered signal and the second even-numbered signal to obtain a third positioning signal; and analyzing the third positioning signal to obtain the longitude and latitude coordinates of the photovoltaic power generation column.

The beneficial effect of above-mentioned scheme: the method comprises the following steps that the longitude and latitude coordinates of each photovoltaic charging column are obtained, if the obtained longitude and latitude coordinates have errors, the final clustering result is inaccurate, and the user experience is reduced, so that the accurate obtaining of the longitude and latitude coordinates of each photovoltaic charging column is necessary, and the method for accurately obtaining the longitude and latitude coordinates of each photovoltaic charging column is provided; receiving a first positioning signal sent by a positioning satellite through a GPS (global positioning system) arranged on a photovoltaic charging column; the first satellite signal is limited by cost, its transmission power is often small, and before reaching the GPS, it is attenuated by interference of various factors (such as noise), and generally the first positioning signal received by the GPS is often buried in the noise,

performing signal segmentation processing on the first positioning signal to obtain a plurality of sub first positioning signals, and respectively obtaining a plurality of intensities corresponding to each sub first positioning signal at a plurality of moments; calculating to obtain an intensity standard deviation of each sub-first positioning signal according to a plurality of intensities corresponding to each sub-first positioning signal at a plurality of moments, wherein the intensity standard deviation is the standard deviation of the plurality of intensities corresponding to each sub-first positioning signal at the plurality of moments, the intensity standard deviation represents the discrete degree of each sub-first positioning signal, and the smaller the intensity standard deviation table is, the smaller the discrete degree of each sub-first positioning signal is, the stronger the stability of each sub-first positioning signal is; the larger the intensity standard deviation is, the larger the dispersion degree of the sub first positioning signals is, the worse the stability of the sub first positioning signals is; respectively judging whether the intensity standard deviation is smaller than a preset intensity standard deviation, screening out sub-first positioning signals of which the intensity standard deviation is smaller than the preset intensity standard deviation, and generating second positioning signals; and the unstable part of the first positioning signal is filtered, so that the second positioning signal is more accurate, and the accuracy of finally acquiring the longitude and latitude coordinates is improved. Calculating a noise power in the second positioning signal; calculating a signal power in the second positioning signal; calculating to obtain a signal-to-noise ratio of the second positioning signal according to the noise power and the signal power, judging whether the signal-to-noise ratio is smaller than a preset signal-to-noise ratio, when the signal-to-noise ratio is determined to be smaller than the preset signal-to-noise ratio, indicating that noise in the second positioning signal is strong, and extracting parity bits of the second positioning signal to obtain a first odd-numbered signal and a first even-numbered signal; converting the first odd-numbered signal from a time domain to a frequency domain to obtain a frequency domain odd-numbered signal; converting the first even number signal from a time domain to a frequency domain to obtain a frequency domain even number signal; performing modulus calculation on the frequency domain odd-numbered signal to obtain a first modulus value, wherein the first modulus value represents the strength of an effective signal in the frequency domain odd-numbered signal; performing modulus calculation on the frequency domain even number signal to obtain a second modulus value, wherein the second modulus value represents the strength of an effective signal in the frequency domain even number signal; judging whether the first modulus is smaller than a preset modulus, wherein the preset modulus is an average value of the modulus of the frequency domain odd signal with small noise and the modulus of the frequency domain even signal with small noise; when the first modulus is determined to be smaller than a preset modulus, carrying out zero setting processing on the frequency domain odd-numbered signal; judging whether the second modulus value is smaller than a preset modulus value or not, and carrying out zero setting processing on the frequency domain even number signal when the second modulus value is smaller than the preset modulus value; performing sparse processing on the frequency domain odd-numbered signals subjected to zero processing, and converting the frequency domain odd-numbered signals into time domains to obtain second odd-numbered signals; performing sparse processing on the frequency domain even number signal subjected to zero setting processing, and converting the frequency domain even number signal into a time domain to obtain a second even number signal; combining the second odd-numbered signal and the second even-numbered signal to obtain a third positioning signal; and analyzing the third positioning signal to obtain the longitude and latitude coordinates of the photovoltaic power generation column. The second positioning signals are extracted according to the parity bits, then the second positioning signals are processed in the frequency domain, and then the signal quality is enhanced by using a sparse processing method, so that the influence of noise in the signals is greatly eliminated, the method is simple, the operation speed is high, the accuracy is high, the finally obtained longitude and latitude coordinates of the photovoltaic power generation column are more accurate, the accuracy of a subsequent clustering result is ensured, and the experience of a user is further improved.

According to some embodiments of the present invention, clustering longitude and latitude coordinates of N photovoltaic charging columns to obtain M clustering centers includes:

generating a first longitude and latitude coordinate set according to the longitude and latitude coordinates of the N photovoltaic charging columns; sequencing each longitude and latitude coordinate in the first longitude and latitude coordinate set according to the sequence of coordinate values from small to large to obtain a sequenced first longitude and latitude coordinate set;

The working principle of the scheme is as follows: generating a first longitude and latitude coordinate set according to the longitude and latitude coordinates of the N photovoltaic charging columns; sequencing each longitude and latitude coordinate in the first longitude and latitude coordinate set according to the sequence of coordinate values from small to large to obtain a sequenced first longitude and latitude coordinate set; acquiring longitude and latitude coordinates at the head end position in the sorted first longitude and latitude coordinate set, and taking the longitude and latitude coordinates as first target longitude and latitude coordinates; respectively calculating the Euclidean distance from each longitude and latitude coordinate in the sorted first longitude and latitude coordinate set to the first target longitude and latitude coordinate, screening out the longitude and latitude coordinate with the Euclidean distance smaller than a preset Euclidean distance, and generating a coordinate clustering set according to the first target longitude and latitude coordinate and the longitude and latitude coordinate with the Euclidean distance smaller than the preset Euclidean distance; removing longitude and latitude coordinates included in the coordinate clustering set from the first longitude and latitude coordinate set to obtain a second longitude and latitude coordinate set; sequencing each longitude and latitude coordinate in the second longitude and latitude coordinate set from small to large according to the coordinate values to obtain a sequenced second longitude and latitude coordinate set; acquiring longitude and latitude coordinates at the head end position in the sorted second longitude and latitude coordinate set, and taking the longitude and latitude coordinates as second target longitude and latitude coordinates, and repeating the steps until each longitude and latitude coordinate in the longitude and latitude coordinate set is clustered to obtain M coordinate clustered sets; respectively sequencing the longitude and latitude coordinates included in each coordinate clustering set in the M coordinate clustering sets from small to large according to the coordinate values; respectively obtaining longitude and latitude coordinates at the middle position in each sorted coordinate clustering set to obtain M middle longitude and latitude coordinates, and obtaining M clustering centers according to the M middle longitude and latitude coordinates.

The beneficial effect of above-mentioned scheme: the accurate clustering of longitude and latitude coordinates of the N photovoltaic charging columns is necessary, the photovoltaic charging stations with similar positions are clustered into one type to obtain M photovoltaic charging stations, the accuracy of price making for each photovoltaic charging station in different time periods is guaranteed, the scheme uses the Euclidean distance of the longitude and latitude coordinates for clustering, and the accuracy of a final clustering result is improved.

According to some embodiments of the invention, before analyzing the third positioning signal, further comprising performing enhancement processing on the third positioning signal.

The working principle and the beneficial effects of the scheme are as follows: and enhancing the third positioning signal subjected to noise reduction so that the finally obtained longitude and latitude coordinates are more accurate.

According to some embodiments of the invention, performing enhancement processing on the third positioning signal comprises:

The working principle of the scheme is as follows: performing signal segmentation processing on the third positioning signal to obtain a plurality of sub-third positioning signals, respectively obtaining the amplitude of each sub-third positioning signal to obtain a plurality of amplitudes, calculating to obtain an average amplitude according to the plurality of amplitudes, and inquiring a preset average amplitude-gain coefficient table according to the average amplitude to obtain a corresponding gain coefficient; and adjusting the gain value of a gain amplifier according to the gain coefficient, and inputting the third positioning signal into the gain amplifier with the adjusted gain value for enhancement processing.

The beneficial effect of above-mentioned scheme: the gain value obtained according to the scheme is more accurate, the optimization of enhancing the third positioning signal is improved, the details in the enhanced third positioning signal are more obvious, the characteristics are clearer, and the accuracy of the final analysis result is improved.

According to some embodiments of the invention, calculating the noise power in the second positioning signal comprises:

The working principle of the scheme is as follows: inputting the second positioning signal into a down converter for down-conversion processing to obtain a baseband positioning signal; performing up-sampling processing on the baseband positioning signal to obtain a digital positioning signal; performing signal segmentation processing on the digital signal to obtain a plurality of sub-digital positioning signals, and performing Hanning window processing on the plurality of sub-digital positioning signals respectively; respectively carrying out fast Fourier transform on a plurality of sub-digital positioning signals subjected to Hanning window processing to obtain a plurality of complex sequences and carrying out smoothing processing;

respectively carrying out modulus squaring treatment on each smoothed complex sequence to obtain a first power spectrogram corresponding to each sub-digital positioning signal; superposing the first power spectrogram corresponding to each sub-digital positioning signal and then averaging to obtain a second power spectrogram of the second positioning signal; the second power spectrogram comprises a power spectral line; in the second power spectrogram, acquiring a power value of each spectral point on the power spectral line, classifying the spectral points with the same power value to obtain a plurality of spectral point sets, and counting the number of spectral points included in each spectral point set; drawing a curve to be detected by taking the number of the spectrum points in each spectrum point set as a vertical coordinate and the power value of each spectrum point set as a horizontal coordinate; acquiring a power value of each coordinate point on the curve to be detected, comparing the power value of each coordinate point with the power values of adjacent coordinate points, screening out the coordinate points of which the power values are greater than the power values of the adjacent coordinate points, and generating a first coordinate point set; comparing the power values of the coordinate points included in the first coordinate point set with a preset power value, screening out the coordinate points of which the power values are greater than the preset power value, and generating a second coordinate point set; and sorting the coordinate points in the second coordinate point set according to the sequence of the power values from small to large, screening out the minimum power value, and taking the minimum power value as the noise power in the second positioning signal.

The beneficial effect of above-mentioned scheme: accurately calculating the noise power in the second positioning signal is necessary, and inputting the second positioning signal into a down converter for down-conversion processing to obtain a baseband positioning signal; performing up-sampling processing on the baseband positioning signal to obtain a digital positioning signal, performing down-conversion and up-sampling processing on a second positioning signal respectively to enable the obtained digital positioning signal to be more accurate, performing signal segmentation processing on the digital signal to obtain a plurality of sub-digital positioning signals, and performing Hanning window processing on the plurality of sub-digital positioning signals respectively; respectively carrying out fast Fourier transform on a plurality of sub-digital positioning signals subjected to Hanning window processing to obtain a plurality of complex sequences and carrying out smoothing processing; respectively carrying out modulus squaring treatment on each smoothed complex sequence to obtain a first power spectrogram corresponding to each sub-digital positioning signal; the power spectrogram obtained by the method is more accurate; superposing the first power spectrogram corresponding to each sub-digital positioning signal and then averaging to obtain a second power spectrogram of the second positioning signal; the second power spectrogram comprises a power spectral line; in the second power spectrogram, acquiring a power value of each spectral point on the power spectral line, classifying the spectral points with the same power value to obtain a plurality of spectral point sets, and counting the number of spectral points included in each spectral point set; drawing a curve to be detected by taking the number of the spectrum points in each spectrum point set as a vertical coordinate and the power value of each spectrum point set as a horizontal coordinate; acquiring a power value of each coordinate point on the curve to be detected, comparing the power value of each coordinate point with the power values of adjacent coordinate points, screening out the coordinate points of which the power values are greater than the power values of the adjacent coordinate points, and generating a first coordinate point set; comparing the power values of the coordinate points included in the first coordinate point set with a preset power value, screening out the coordinate points of which the power values are greater than the preset power value, and generating a second coordinate point set; the second coordinate point set is a local maximum point on the to-be-detected curve; and sorting the coordinate points in the second coordinate point set according to the sequence of the power values from small to large, screening out the minimum power value, and taking the minimum power value as the noise power in the second positioning signal.

According to some embodiments of the invention, establishing new charging prices for each photovoltaic charging station at different time periods according to the discharge time period, the net income, and the raw charging price comprises:

The working principle of the scheme is as follows: when the discharging time length of the same photovoltaic charging station in the same time period is determined to be greater than a preset discharging time length and the net income is determined to be greater than a preset net income, a first discharging time length difference value between the discharging time length and the preset discharging time length and a first net income difference value between the net income and the preset net income are determined, a first adjusting parameter is determined according to the first discharging time length difference value and the first net income difference value, the original charging price is adjusted according to the first adjusting parameter and is used as a new charging price of the photovoltaic charging station in the time period; for example, if the time period is from 8 am to 9 am, the photovoltaic charging station includes 6 photovoltaic charging poles, the original charging price of the photovoltaic charging station from 8 am to 9 am is 75 yuan per hour, the total discharging time of the 6 photovoltaic charging poles is 300 minutes, the preset discharging time is 180 minutes, the net income is 340 yuan, and the preset net income is 200 yuan, then the first discharging time difference is 300 minutes to 180 minutes =120 minutes, the first net income difference is 340 yuan to 200 yuan =140 yuan, and the preset discharging time difference-net income difference-adjustment parameter table is queried by 120 minutes and 140 yuan to obtain a corresponding first adjustment parameter of 10%, so that the adjusted charging price of the photovoltaic charging station from 8 am to 9 am is 75+75 × 10% =82.5 yuan. When the discharging time length of the same photovoltaic charging station in the same time period is determined to be larger than a preset discharging time length and the net income is determined to be smaller than a preset net income, a second discharging time length difference value of the discharging time length and the preset discharging time length and a second net income difference value of the net income and the preset net income are determined, a second adjusting parameter is determined according to the second discharging time length difference value and the second net income difference value, the original charging price is adjusted according to the second adjusting parameter and is used as a new charging price of the photovoltaic charging station in the time period; for example, if the time period is from 8 am to 9 am, the photovoltaic charging station includes 6 photovoltaic charging poles, the original charging price of the photovoltaic charging station from 8 am to 9 am is 40 yuan per hour, the total discharging time of the 6 photovoltaic charging poles is 150 minutes, the preset discharging time is 180 minutes, the net income is 150 yuan, and the preset net income is 200 yuan, then the first discharging time difference is 300 minutes to 180 minutes =120 minutes, the first net income difference is 150 yuan to 200 yuan = -50 yuan, the preset discharging time difference-net income difference-adjustment parameter table is queried through 120 minutes and the-50 yuan, and the corresponding second adjustment parameter is 20%, and then the adjusted charging price of the photovoltaic charging station from 8 am to 9 am is 40+40 × 20% =48 yuan. When the discharging time length of the same photovoltaic charging station in the same time period is determined to be smaller than a preset discharging time length and the net income is determined to be larger than the preset net income, a third discharging time length difference value of the discharging time length and the preset discharging time length and a third net income difference value of the net income and the preset net income are determined, a third adjusting parameter is determined according to the third discharging time length difference value and the third net income difference value, and the original charging price is adjusted to be smaller according to the third adjusting parameter and is used as a new charging price of the photovoltaic charging station in the time period; for example, if the time period is from 8 am to 9 am of the current day, the photovoltaic charging station includes 6 photovoltaic charging columns, the original charging price of the photovoltaic charging station from 8 am to 9 am is 100 yuan per hour, the total discharging time of the 6 photovoltaic charging columns is 160 minutes, the preset discharging time is 180 minutes, the net income is 230 yuan, and the preset net income is 200 yuan, then the first discharging time difference is 160 minutes to 180 minutes = -20 minutes, the first net income difference is 230 yuan to 200 yuan =30 yuan, the preset discharging time difference-net income difference-adjustment parameter table is queried through-20 minutes and the 30 yuan, the corresponding first adjustment parameter is-10%, and then the charging price of the photovoltaic charging station after being adjusted from 8 am to 9 am is 100 × 10% =90 yuan. When the fact that the discharging time of the same photovoltaic charging station in the same time period is smaller than the preset discharging time and the net income is smaller than the preset net income is determined, a fourth discharging time difference value of the discharging time and the preset discharging time and a fourth net income difference value of the net income and the preset net income are determined, a fourth adjusting parameter is determined according to the fourth discharging time difference value and the fourth net income difference value, the original charging price is adjusted according to the fourth adjusting parameter and is used as a new charging price of the photovoltaic charging station in the time period. For example, if the time period is from 8 am to 9 am of the current day, the photovoltaic charging station includes 6 photovoltaic charging columns, the original charging price of the photovoltaic charging station from 8 am to 9 am is 100 yuan per hour, the total discharging time of the 6 photovoltaic charging columns is 60 minutes, the preset discharging time is 180 minutes, the net income is 90 yuan, and the preset net income is 200 yuan, then the first discharging time difference is 60 minutes to 180 minutes = -120 minutes, the first net income difference is 90 yuan to 200 yuan = -110 yuan, the preset discharging time difference-net income difference-adjustment parameter table is queried through-20 minutes and the-110 yuan, and the corresponding first adjustment parameter is-30%, and then the charging price of the photovoltaic charging station after being adjusted from 8 am to 9 am is 100-.

The beneficial effect of above-mentioned scheme: according to the discharging duration, the net income and the original charging price, new charging prices are set for each photovoltaic charging station in different time periods, so that the finally obtained prices are more accurate, the situation that some charging stations are idle is avoided, the number of users of each charging station is averagely distributed, and the maximum profit of the photovoltaic charging stations is guaranteed.

As shown in fig. 2, a resource balance distribution system for an electric vehicle photovoltaic charging station network includes:

the longitude and latitude coordinate acquisition module 1 is used for acquiring longitude and latitude coordinates of each photovoltaic charging column; the number of the photovoltaic charging columns is N;

the clustering module 2 is used for clustering longitude and latitude coordinates of the N photovoltaic charging columns to obtain M clustering centers, and obtaining M photovoltaic charging stations according to the M clustering centers;

the building module 3 is used for building an electric vehicle charging network according to the M photovoltaic charging stations;

the working principle of the scheme is as follows: the longitude and latitude coordinate acquisition module 1 is used for acquiring longitude and latitude coordinates of each photovoltaic charging column; the number of the photovoltaic charging columns is N; the clustering module 2 is used for clustering longitude and latitude coordinates of the N photovoltaic charging columns to obtain M clustering centers, and obtaining M photovoltaic charging stations according to the M clustering centers; the building module 3 is used for building an electric vehicle charging network according to the M photovoltaic charging stations; the photovoltaic power generation capacity acquisition module 4 is used for acquiring the total charging times of each photovoltaic charging station in the electric vehicle charging network within a preset time period; the discharging duration obtaining module 5 is configured to equally divide the preset time period to obtain a plurality of sub-time periods, and obtain the sub-charging times of each photovoltaic charging station in the electric vehicle charging network within the sub-time periods; the original charging price acquisition module 6 is used for acquiring the charging rate of each photovoltaic charging station in the electric vehicle charging network within a preset time period; and the electricity purchase cost acquisition module 7 is used for performing time-period combined pricing on each photovoltaic charging station according to the total charging times, the sub-charging times and the charging rate.

The beneficial effect of above-mentioned scheme: the longitude and latitude coordinate acquisition module 1 is used for acquiring longitude and latitude coordinates of each photovoltaic charging column; the number of the photovoltaic charging columns is N; the clustering module 2 is used for clustering longitude and latitude coordinates of the N photovoltaic charging columns, clustering the photovoltaic charging columns with similar positions into one class to obtain M clustering centers, and obtaining M photovoltaic charging stations according to the M clustering centers, wherein each photovoltaic charging station comprises a plurality of photovoltaic charging columns; the building module 3 is used for building an electric vehicle charging network according to the M photovoltaic charging stations, and the photovoltaic power generation capacity obtaining module 4 is used for obtaining the total charging times of each photovoltaic charging station in the electric vehicle charging network within a preset time period; the discharging duration obtaining module 5 is configured to equally divide the preset time period to obtain a plurality of sub-time periods, and obtain the sub-charging times of each photovoltaic charging station in the electric vehicle charging network within the sub-time periods; the original charging price acquisition module 6 is used for acquiring the charging rate of each photovoltaic charging station in the electric vehicle charging network within a preset time period; the electricity purchase cost acquisition module 7 is used for carrying out time-sharing combined pricing on each photovoltaic charging station according to the total charging times, the sub-charging times and the charging rate, a user can conveniently check information of each charging station on the network through the constructed electric vehicle charging network, the service condition of each charging station is recorded, a manager can conveniently manage each charging station, the charging price of each hour is set for each photovoltaic charging station through the total charging times of each photovoltaic charging station, the sub-charging times and the charging rate in different time periods, the charging demands of the user are balanced, and the photovoltaic charging stations achieve maximum benefits.

As shown in fig. 3, according to some embodiments of the present invention, the latitude and longitude coordinate acquiring module 1 includes:

the first positioning signal acquisition module 10 is used for receiving a first positioning signal sent by a positioning satellite through a GPS module arranged on the photovoltaic charging column;

a second positioning signal generation module 11 for

a second positioning signal processing module 12 for:

calculating a noise power in the second positioning signal;

calculating a signal power in the second positioning signal;

a control module 13 for:

The working principle of the scheme is as follows: the first positioning signal acquisition module 10 is configured to receive a first positioning signal sent by a positioning satellite through a GPS module disposed on the photovoltaic charging column; the second positioning signal generating module 11 is configured to perform signal segmentation processing on the first positioning signal to obtain a plurality of sub-first positioning signals, and respectively obtain a plurality of intensities corresponding to each sub-first positioning signal at a plurality of times; calculating according to a plurality of intensities corresponding to each sub-first positioning signal at a plurality of moments to obtain an intensity standard deviation of each sub-first positioning signal, respectively judging whether the intensity standard deviation is smaller than a preset intensity standard deviation, screening out the sub-first positioning signals of which the intensity standard deviation is smaller than the preset intensity standard deviation, and generating a second positioning signal; a second positioning signal processing module 12, configured to calculate a noise power in the second positioning signal; calculating a signal power in the second positioning signal; calculating to obtain a signal-to-noise ratio of the second positioning signal according to the noise power and the signal power, judging whether the signal-to-noise ratio is smaller than a preset signal-to-noise ratio, and extracting parity bits of the second positioning signal when the signal-to-noise ratio is smaller than the preset signal-to-noise ratio to obtain a first odd signal and a first even signal; converting the first odd-numbered signal from a time domain to a frequency domain to obtain a frequency domain odd-numbered signal; converting the first even number signal from a time domain to a frequency domain to obtain a frequency domain even number signal; performing modulus calculation on the frequency domain odd number signal to obtain a first modulus value; performing modulus calculation on the frequency domain even number signal to obtain a second modulus value; judging whether the first modulus value is smaller than a preset modulus value or not, and carrying out zero setting processing on the frequency domain odd number signal when the first modulus value is determined to be smaller than the preset modulus value; judging whether the second modulus value is smaller than a preset modulus value or not, and carrying out zero setting processing on the frequency domain even number signal when the second modulus value is smaller than the preset modulus value; performing sparse processing on the frequency domain odd-numbered signals subjected to zero processing, and converting the frequency domain odd-numbered signals into time domains to obtain second odd-numbered signals; performing sparse processing on the frequency domain even number signal subjected to zero setting processing, and converting the frequency domain even number signal into a time domain to obtain a second even number signal; the control module 13 is configured to perform signal combination on the second odd-numbered signal and the second even-numbered signal to obtain a third positioning signal; and analyzing the third positioning signal to obtain the longitude and latitude coordinates of the photovoltaic power generation column.

The beneficial effect of above-mentioned scheme: the method comprises the following steps that the longitude and latitude coordinates of each photovoltaic charging column are obtained, if the obtained longitude and latitude coordinates have errors, the final clustering result is inaccurate, and the user experience is reduced, so that the accurate obtaining of the longitude and latitude coordinates of each photovoltaic charging column is necessary, and the method for accurately obtaining the longitude and latitude coordinates of each photovoltaic charging column is provided; the first positioning signal acquisition module 10 is configured to receive a first positioning signal sent by a positioning satellite through a GPS module disposed on the photovoltaic charging column; because the first satellite signal is limited by factors such as cost and the like, the transmitting power of the first satellite signal is often small, and the first satellite signal is attenuated by interference of various factors (such as noise) before reaching the GPS, generally, the first positioning signal received by the GPS is often submerged in the noise, the second positioning signal generation module 11 performs signal segmentation processing on the first positioning signal to obtain a plurality of sub-first positioning signals, and a plurality of intensities corresponding to each sub-first positioning signal at a plurality of moments are respectively obtained; calculating to obtain an intensity standard deviation of each sub-first positioning signal according to a plurality of intensities corresponding to each sub-first positioning signal at a plurality of moments, wherein the intensity standard deviation is the standard deviation of the plurality of intensities corresponding to each sub-first positioning signal at the plurality of moments, the intensity standard deviation represents the discrete degree of each sub-first positioning signal, and the smaller the intensity standard deviation table is, the smaller the discrete degree of each sub-first positioning signal is, the stronger the stability of each sub-first positioning signal is; the larger the standard deviation of the intensity indicates that the larger the dispersion degree of the sub-first positioning signal is, the worse the stability of the sub-first positioning signal is; respectively judging whether the intensity standard deviation is smaller than a preset intensity standard deviation, screening out sub-first positioning signals of which the intensity standard deviation is smaller than the preset intensity standard deviation, and generating second positioning signals; and the unstable part of the first positioning signal is filtered, so that the second positioning signal is more accurate, and the accuracy of finally acquiring the longitude and latitude coordinates is improved. The second positioning signal processing module 12 calculates the noise power in the second positioning signal; calculating a signal power in the second positioning signal; calculating to obtain a signal-to-noise ratio of the second positioning signal according to the noise power and the signal power, judging whether the signal-to-noise ratio is smaller than a preset signal-to-noise ratio, when the signal-to-noise ratio is determined to be smaller than the preset signal-to-noise ratio, indicating that noise in the second positioning signal is strong, and extracting parity bits of the second positioning signal to obtain a first odd-numbered signal and a first even-numbered signal; converting the first odd-numbered signal from a time domain to a frequency domain to obtain a frequency domain odd-numbered signal; converting the first even number signal from a time domain to a frequency domain to obtain a frequency domain even number signal; performing modulus calculation on the frequency domain odd-numbered signal to obtain a first modulus value, wherein the first modulus value represents the strength of an effective signal in the frequency domain odd-numbered signal; performing modulus calculation on the frequency domain even number signal to obtain a second modulus value, wherein the second modulus value represents the strength of an effective signal in the frequency domain even number signal; judging whether the first modulus is smaller than a preset modulus, wherein the preset modulus is an average value of the modulus of the frequency domain odd signal with small noise and the modulus of the frequency domain even signal with small noise; when the first modulus is determined to be smaller than a preset modulus, carrying out zero setting processing on the frequency domain odd-numbered signal; judging whether the second modulus value is smaller than a preset modulus value or not, and carrying out zero setting processing on the frequency domain even number signal when the second modulus value is smaller than the preset modulus value; performing sparse processing on the frequency domain odd-numbered signals subjected to zero processing, and converting the frequency domain odd-numbered signals into time domains to obtain second odd-numbered signals; performing sparse processing on the frequency domain even number signal subjected to zero setting processing, and converting the frequency domain even number signal into a time domain to obtain a second even number signal; the control module 13 combines the second odd-numbered signal and the second even-numbered signal to obtain a third positioning signal; and analyzing the third positioning signal to obtain the longitude and latitude coordinates of the photovoltaic power generation column. The second positioning signals are extracted according to the parity bits, then the second positioning signals are processed in the frequency domain, and then the signal quality is enhanced by using a sparse processing method, so that the influence of noise in the signals is greatly eliminated, the method is simple, the operation speed is high, the accuracy is high, the finally obtained longitude and latitude coordinates of the photovoltaic power generation column are more accurate, the accuracy of a subsequent clustering result is ensured, and the experience of a user is further improved.

According to some embodiments of the invention, the clustering module comprises:

the first longitude and latitude coordinate set generation module is used for generating a first longitude and latitude coordinate set according to the longitude and latitude coordinates of the N photovoltaic charging columns;

a cluster center acquisition module configured to:

The working principle of the scheme is as follows: the first longitude and latitude coordinate set generating module is used for generating a first longitude and latitude coordinate set according to the longitude and latitude coordinates of the N photovoltaic charging columns; the first target longitude and latitude coordinate acquisition module is used for sequencing each longitude and latitude coordinate in the first longitude and latitude coordinate set from small to large according to coordinate values to obtain a sequenced first longitude and latitude coordinate set, acquiring the longitude and latitude coordinate at the head end position in the sequenced first longitude and latitude coordinate set and taking the longitude and latitude coordinate as a first target longitude and latitude coordinate; the coordinate clustering set generating module is used for respectively calculating the Euclidean distance from each longitude and latitude coordinate in the sorted first longitude and latitude coordinate set to the first target longitude and latitude coordinate, screening out the longitude and latitude coordinate with the Euclidean distance smaller than a preset Euclidean distance, and generating a coordinate clustering set according to the first target longitude and latitude coordinate and the longitude and latitude coordinate with the Euclidean distance smaller than the preset Euclidean distance; the second longitude and latitude coordinate set generation module is used for eliminating longitude and latitude coordinates included in the coordinate clustering set from the first longitude and latitude coordinate set to obtain a second longitude and latitude coordinate set; the clustering center acquisition module is used for sequencing each longitude and latitude coordinate in the second longitude and latitude coordinate set from small to large according to the coordinate value to obtain a sequenced second longitude and latitude coordinate set; acquiring longitude and latitude coordinates at the head end position in the sorted second longitude and latitude coordinate set, and taking the longitude and latitude coordinates as second target longitude and latitude coordinates, and repeating the steps until each longitude and latitude coordinate in the longitude and latitude coordinate set is clustered to obtain M coordinate clustered sets; respectively sequencing the longitude and latitude coordinates included in each coordinate clustering set in the M coordinate clustering sets from small to large according to the coordinate values; respectively obtaining longitude and latitude coordinates at the middle position in each sorted coordinate clustering set to obtain M middle longitude and latitude coordinates, and obtaining M clustering centers according to the M middle longitude and latitude coordinates.

It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.

Claims

1. A resource balanced distribution method for an electric vehicle photovoltaic charging station network is characterized by comprising the following steps:

setting new charging prices for each photovoltaic charging station at different time periods according to the discharging time period, the net income and the original charging price;

wherein, carry out clustering processing to the longitude and latitude coordinate of N photovoltaic charging post, obtain M clustering centers, include:

2. The method for the balanced resource allocation of the photovoltaic charging station network of the electric vehicle as claimed in claim 1, wherein the step of obtaining longitude and latitude coordinates of one photovoltaic charging post comprises:

calculating a noise power in the second positioning signal;

calculating a signal power in the second positioning signal;

judging whether the first modulus is smaller than a preset modulus, and carrying out zero setting processing on the frequency domain odd-numbered signal when the first modulus is smaller than the preset modulus;

and analyzing the third positioning signal to obtain the longitude and latitude coordinates of the photovoltaic charging column.

3. The method for resource balanced distribution of the electric vehicle photovoltaic charging station network according to claim 2, further comprising performing enhancement processing on the third positioning signal before analyzing the third positioning signal.

4. The method for balanced resource allocation of the electric vehicle photovoltaic charging station network according to claim 3, wherein the enhancing the third positioning signal comprises:

5. The method for resource balanced distribution of the electric vehicle photovoltaic charging station network according to claim 2, wherein calculating the noise power in the second positioning signal comprises:

performing signal segmentation processing on the digital positioning signal to obtain a plurality of sub-digital positioning signals, and performing Hanning window processing on the plurality of sub-digital positioning signals respectively;

6. The method for resource balanced allocation of an electric vehicle photovoltaic charging station network according to claim 1, wherein the step of formulating a new charging price for each photovoltaic charging station at different time periods according to the discharging time period, the net income and the original charging price comprises:

7. A resource balanced distribution system of an electric vehicle photovoltaic charging station network is characterized by comprising:

the longitude and latitude coordinate acquisition module is used for acquiring longitude and latitude coordinates of each photovoltaic charging column; the number of the photovoltaic charging columns is N;

the photovoltaic power generation acquisition module is used for acquiring the photovoltaic power generation of each photovoltaic charging station in the electric vehicle charging network in different time periods;

the discharging duration acquisition module is used for acquiring the discharging duration of each photovoltaic charging station in the electric vehicle charging network in different time periods;

the system comprises an original charging price acquisition module, a charging management module and a charging management module, wherein the original charging price acquisition module is used for acquiring the original charging price of each photovoltaic charging station in the electric vehicle charging network in different time periods;

the electricity purchasing cost acquisition module is used for acquiring electricity purchasing costs of each photovoltaic charging station in the electric vehicle charging network in different time periods;

the net income calculation module is used for calculating net income of each photovoltaic charging station in different time periods according to the photovoltaic power generation amount, the discharging time, the original charging price and the electricity purchasing cost;

the pricing module is used for making a new charging price for each photovoltaic charging station in different time periods according to the discharging time length, the net income and the original charging price;

wherein the clustering module comprises:

the coordinate clustering set generating module is used for respectively calculating Euclidean distances from each longitude and latitude coordinate in the sorted first longitude and latitude coordinate set to the first target longitude and latitude coordinate, screening out longitude and latitude coordinates of which the Euclidean distances are smaller than a preset Euclidean distance, and generating a coordinate clustering set according to the first target longitude and latitude coordinates and the longitude and latitude coordinates of which the Euclidean distances are smaller than the preset Euclidean distances;

the second longitude and latitude coordinate set generation module is used for eliminating longitude and latitude coordinates included in the coordinate cluster set from the first longitude and latitude coordinate set to obtain a second longitude and latitude coordinate set;

a cluster center acquisition module configured to:

acquiring longitude and latitude coordinates at the head end position in the sorted second longitude and latitude coordinate set, and taking the longitude and latitude coordinates as second target longitude and latitude coordinates, and repeating the steps until clustering processing is carried out on each longitude and latitude coordinate in the longitude and latitude coordinate set to obtain M coordinate clustered sets;

respectively obtaining longitude and latitude coordinates at the middle position in each ordered coordinate clustering set to obtain M middle longitude and latitude coordinates, and obtaining M clustering centers according to the M middle longitude and latitude coordinates.

8. The system for the balanced distribution of resources of the photovoltaic charging station network of the electric vehicles according to claim 7, wherein the latitude and longitude coordinate acquisition module comprises:

a second positioning signal generation module for

a second positioning signal processing module for:

calculating a noise power in the second positioning signal;

calculating a signal power in the second positioning signal;

a control module to: