CN107302230A - A kind of photovoltaic power generation equipment is incorporated into the power networks optimization method - Google Patents
A kind of photovoltaic power generation equipment is incorporated into the power networks optimization method Download PDFInfo
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- Y04S10/00—Systems supporting electrical power generation, transmission or distribution
- Y04S10/12—Monitoring or controlling equipment for energy generation units, e.g. distributed energy generation [DER] or load-side generation
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- Y04S40/00—Systems for electrical power generation, transmission, distribution or end-user application management characterised by the use of communication or information technologies, or communication or information technology specific aspects supporting them
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- Y04S40/126—Systems for electrical power generation, transmission, distribution or end-user application management characterised by the use of communication or information technologies, or communication or information technology specific aspects supporting them characterised by data transport means between the monitoring, controlling or managing units and monitored, controlled or operated electrical equipment using wireless data transmission
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Abstract
It is incorporated into the power networks optimization method the invention discloses a kind of photovoltaic power generation equipment, party's net of justice employs active power reference value quick calculation method, it is quick to calculate the reference power for meeting grid-connected requirement, the fluctuation of primary signal can effectively be improved, the purpose for stabilizing power swing is reached, realizes that photovoltaic is smoothly grid-connected；This method judges and determined the mode of operation of photovoltaic apparatus according to the power output information and voltage on line side value information of photovoltaic apparatus, to realize the optimization being incorporated into the power networks；In addition, the monitoring method of the present invention, is communicated using wireless encryption and realizes the communication of monitoring data so that supervising device monitors more simple and reliable for photovoltaic power generation equipment.
Description
Technical Field
The invention relates to the field of photoelectric power generation, in particular to a grid-connected operation optimization method for photovoltaic power generation equipment.
Background
With the development of economic globalization, the traditional energy brings high-quality life to people, and also harms the living environment more and more seriously, and more countries begin to pay attention to the utilization of clean energy. The traditional energy source will gradually be replaced by renewable clean energy. The demand of human energy is increasing continuously, and solar power generation is concerned and favored by various countries due to the characteristics of environmental protection and economy.
The grid-connected photovoltaic power generation system is a photovoltaic power generation system connected with an alternating current power grid, and in the traditional photovoltaic power generation field, the grid-connected method is to convert direct current energy of a photovoltaic square matrix into alternating current through a power regulator to realize grid connection.
At present, a common method for calculating grid-connected reference power of a photovoltaic power station, such as low-pass filtering, has certain time delay, is low in tracking precision, and cannot well reflect the characteristics of original signals. The spectral compensation method is too idealized. The conventional empirical mode decomposition method is difficult to apply and perform real-time online quick calculation due to the problem of calculation speed.
The load of the operation of the photovoltaic power station is mostly inductive load. The large amount of inductive loads not only cause the power factor of the system to be too low, the production efficiency to be reduced and the electric energy expense of enterprises to be increased, but also cause the voltage fluctuation of a power grid, seriously affect the safe operation of loaded equipment and bring unnecessary economic loss to the enterprises. According to the technical regulation of the photovoltaic power station access power grid of the national grid company, the power factor of large and medium-sized photovoltaic power stations can be continuously adjusted within the range of 0.98 (leading) to 0.98 (lagging). Therefore, large centralized and distributed photovoltaic power stations need to improve power factors in a reactive compensation mode, and electric energy quality and power grid safety are guaranteed.
In the photovoltaic module monitoring system, a monitoring device is responsible for monitoring the working state of a photovoltaic module (namely a data acquisition device) in the system; the communication subsystem is responsible for data transmission between the monitoring device and the data acquisition device. Currently, in the photovoltaic power generation industry, a communication subsystem in a photovoltaic module monitoring system is composed of a traditional wired mode and a traditional wireless mode.
Disclosure of Invention
The invention provides a grid-connected operation optimization method of photovoltaic power generation equipment, which adopts a method for quickly calculating an active power reference value, quickly calculates reference power meeting the requirement of photovoltaic grid connection under the condition of keeping the characteristic of the output power of original photovoltaic, and can effectively improve the fluctuation of original signals through a recombined photovoltaic power signal obtained by an improved empirical mode decomposition method and a novel wavelet denoising method, thereby achieving the purpose of stabilizing the power fluctuation and realizing smooth grid connection of photovoltaic; judging and determining the working mode of the photovoltaic equipment according to the power output information and the network side voltage value information of the photovoltaic equipment, judging whether the output state information of the photovoltaic battery meets a first switching condition when the photovoltaic equipment is in an active power output mode, and switching the photovoltaic grid-connected inverter from the active power output mode to a reactive power compensation mode when the output state information of the photovoltaic battery meets the first switching condition; when the photovoltaic equipment is in a reactive power compensation mode, judging whether the output state information of the photovoltaic battery meets a second switching condition, and when the output state information of the photovoltaic battery meets the second switching condition, switching the photovoltaic equipment from the reactive power compensation mode to an active power output mode so as to realize optimization of grid-connected operation; in addition, the monitoring method of the invention adopts wireless encryption communication to realize the communication of the monitoring data, so that the monitoring device is simpler and more reliable for monitoring the photovoltaic power generation equipment.
In order to achieve the purpose, the invention provides a grid-connected operation optimization method for photovoltaic power generation equipment, which comprises the following steps:
s1, rapidly calculating an active power reference value of photovoltaic power generation equipment, and detecting a grid side voltage value of a photovoltaic power station in real time;
s2, sending the active power reference value and the voltage value of the photovoltaic power station network side to a monitoring device in a wireless communication mode;
s3, determining a grid-connected working mode of the photovoltaic power generation equipment according to the active power reference value and the grid-side direct-current voltage information;
and S4, controlling the photovoltaic equipment to operate optimally by the monitoring device according to the grid-connected working mode.
Preferably, in step S1, the active power reference value of the photovoltaic power generation device is calculated quickly by specifically adopting the following method:
s11, segmenting the output power signal of the photovoltaic power station according to time, then decomposing the output power signal of each segment by using an improved empirical mode decomposition method,obtaining IMF component cjFor the boundary value of each section of output power signal, adopting the IMF mean value of the previous section of output power signal to obtain a plurality of IMF components;
s12, performing wavelet denoising on the IMF component obtained in the step S11 by adopting a novel wavelet denoising method to obtain a denoised new IMF component, wherein a threshold function of the novel wavelet denoising method is as follows:
wherein,d is the wavelet coefficient length, σ is the noise variance, WjkIs a wavelet coefficient, f is an input signal frequency
And S13, sequencing the new IMF components obtained in the step S12 by using a principal component analysis method, and combining the sequenced new IMF components to obtain a photovoltaic power station grid-connected reference power value.
Preferably, in step S11, the improved empirical mode decomposition method includes the following steps:
s111, adding the white noise signal into the output power signal to obtain two sets of white noise signal sets M1,M2]Wherein M is1＝S+N；M2S-N, S being the output power signal and N being the white noise signal;
s112, for M1And M2Respectively carrying out empirical mode decomposition to obtain two groups of IMF sets c1jAnd c2j；
S113, two groups of IMF sets c obtained in the step two are subjected to1jAnd c2jCombining to obtain IMF component cjWherein
Preferably, in step S13, the method includes the following steps:
s131, setting IMF component set X ═ X1,x2,...xi...,xM]TLet yi＝xi-E(xi) Wherein, E (x)i) Is xiY-Y matrix1,y2,...,yM]TThe covariance of X is C;
s132, the covariance C of step S131 is decomposed by the following formula, where C is equal to UM×NΛM×NUT M×NΛ is a characteristic value diagonal matrix of C, and U is an orthogonal matrix formed by characteristic vectors;
s133, obtaining P ═ U from Y obtained in step S131 and U obtained in step S132T M×NAnd Y, sorting the IMF components according to the contribution rate in the P from large to small.
Preferably, in step S2, the following steps are specifically adopted to implement wireless encrypted communication:
s21, the monitoring device sends a downlink data packet to the base station, wherein the data packet comprises the photovoltaic equipment terminal identity and the query data type;
s22, the base station analyzes data of the data packet according to a communication protocol of the base station and the monitoring device, and identifies the terminal identity of the photovoltaic equipment and inquires the data type; assembling the identity and the query data type of the photovoltaic equipment terminal according to a communication protocol of the base station and the photovoltaic equipment terminal to obtain an assembled data message; encrypting the assembled data message to obtain an encrypted data message; sending the encrypted data message to a photovoltaic equipment terminal through a radio frequency channel;
s23, the photovoltaic equipment terminal decrypts the encrypted data message to obtain photovoltaic equipment data; assembling photovoltaic equipment data into a format message according to a serial port protocol; sending the format message to a data acquisition device through a serial port;
s24, the data acquisition device checks the format message; after the format message passes the verification, obtaining a data part of the photovoltaic equipment from the format message; analyzing the data part of the photovoltaic equipment according to a serial port protocol to obtain photovoltaic equipment data;
s25, acquiring target data after the data acquisition device acquires the data of the photovoltaic equipment; packing the target data according to a serial port protocol to obtain serial port data; sending the serial port data to a photovoltaic equipment terminal through a serial port;
s26, the photovoltaic equipment terminal checks serial port data; after the serial port data passes the verification, acquiring a photovoltaic equipment data part from the serial port data, and assembling the photovoltaic equipment data part according to a communication protocol of a photovoltaic equipment terminal and a base station to obtain an assembled data message, wherein the data message carries the identity of the photovoltaic equipment terminal; encrypting the assembled data message to obtain encrypted data; transmitting the encrypted data to the base station through a radio frequency channel;
s27, the base station decrypts the encrypted data to obtain a decrypted data message; analyzing the decrypted data message, and identifying the identity of the carried photovoltaic equipment terminal; extracting photovoltaic equipment data from the analyzed data message, and packaging the photovoltaic equipment data according to a communication protocol of the base station and the monitoring device to obtain packaged data, wherein the packaged data comprises a photovoltaic equipment terminal identity and a response data type; the packed data is sent to the monitoring device.
Preferably, in step S3, the operation mode of the photovoltaic device is determined as follows:
when the active power reference value is larger than the first output power threshold value P1 and the voltage value fluctuation of the grid side is smaller than the first voltage fluctuation threshold value V1, the photovoltaic device enters an active output mode;
when the active reference value is smaller than the second output power threshold value P2 and the grid side voltage value fluctuation value is larger than the second voltage fluctuation threshold value V2, the optical tiger device enters a reactive compensation mode.
Preferably, in step S4, when the photovoltaic device enters the active output mode, the photovoltaic device is controlled to operate as follows:
continuously acquiring an active reference value of the photovoltaic equipment;
judging whether the active reference value meets a first switching condition or not;
and when the active reference value meets the first switching condition, switching the photovoltaic grid-connected inverter from the active power output mode to a reactive power compensation mode.
Preferably, in step S4, when the photovoltaic device enters the reactive compensation mode, the photovoltaic device is controlled to operate as follows:
continuously acquiring a fluctuation value of the grid side voltage of the photovoltaic equipment;
judging whether the network side voltage fluctuation value meets a second switching condition or not;
and when the grid side voltage fluctuation value meets the second switching condition, switching the photovoltaic equipment from the reactive power compensation mode to the active power output mode.
Preferably, the step of judging whether the active reference value satisfies a first switching condition includes:
when the active reference value of the photovoltaic device is smaller than a first power threshold value P1, determining whether a first duration for which the output power of the photovoltaic device is smaller than the first power threshold value P1 reaches a first time threshold value T1, and if the first duration reaches the first time threshold value T1, the first output state information satisfies the first switching condition.
Preferably, the step of determining whether the network-side voltage fluctuation value satisfies a second switching condition includes:
when the grid-side voltage fluctuation value is greater than or equal to a voltage fluctuation second threshold value V2, judging whether a second time duration for which the grid-side voltage fluctuation value is greater than or equal to a second voltage fluctuation threshold value V2 reaches a second time threshold value T2, and if the second time duration reaches the second time threshold value T2, the grid-side voltage fluctuation value meets the second switching condition.
The technical scheme of the invention has the following advantages:
(1) the method adopts a rapid calculation method of the active power reference value, under the condition of keeping the characteristic of the original photovoltaic output power, the reference power meeting the requirement of photovoltaic grid connection is rapidly calculated, and the photovoltaic power signal recombined after the improved empirical mode decomposition method and the novel wavelet denoising method can effectively improve the volatility of the original signal, achieve the purpose of stabilizing the power fluctuation and realize the smooth photovoltaic grid connection.
(2) Judging and determining the working mode of the photovoltaic equipment according to the power output information and the network side voltage value information of the photovoltaic equipment, judging whether the output state information of the photovoltaic battery meets a first switching condition when the photovoltaic equipment is in an active power output mode, and switching the photovoltaic grid-connected inverter from the active power output mode to a reactive power compensation mode when the output state information of the photovoltaic battery meets the first switching condition; and when the photovoltaic equipment is in the reactive power compensation mode, judging whether the output state information of the photovoltaic battery meets a second switching condition, and when the output state information of the photovoltaic battery meets the second switching condition, switching the photovoltaic equipment from the reactive power compensation mode to the active power output mode so as to realize optimization of grid-connected operation.
(3) According to the monitoring method, the communication of the monitoring data is realized by adopting wireless encryption communication, so that the monitoring device is simpler and more reliable for monitoring the photovoltaic power generation equipment.
Drawings
Fig. 1 shows a flow chart of a grid-connected operation optimization method for a photovoltaic power generation device.
Detailed Description
Fig. 1 shows a flow chart of a grid-connected operation optimization method for photovoltaic power generation equipment, which includes the following steps: s1, rapidly calculating an active power reference value of photovoltaic power generation equipment, and detecting a grid side voltage value of a photovoltaic power station in real time; s2, sending the active power reference value and the voltage value of the photovoltaic power station network side to a monitoring device in a wireless communication mode; s3, determining a grid-connected working mode of the photovoltaic power generation equipment according to the active power reference value and the grid-side direct-current voltage information; and S4, controlling the photovoltaic equipment to operate optimally by the monitoring device according to the grid-connected working mode.
In step S1, the active power reference value of the photovoltaic power generation device is calculated quickly by specifically adopting the following method:
s11, segmenting the output power signal of the photovoltaic power station according to time, and then decomposing the output power signal of each segment by using an improved empirical mode decomposition method to obtain an IMF component cjFor the boundary value of each section of output power signal, adopting the IMF mean value of the previous section of output power signal to obtain a plurality of IMF components;
s12, performing wavelet denoising on the IMF component obtained in the step S11 by adopting a novel wavelet denoising method to obtain a denoised new IMF component, wherein a threshold function of the novel wavelet denoising method is as follows:
wherein,d is the wavelet coefficient length, σ is the noise variance, WjkIs the wavelet coefficient, and f is the input signal frequency;
and S13, sequencing the new IMF components obtained in the step S12 by using a principal component analysis method, and combining the sequenced new IMF components to obtain a photovoltaic power station grid-connected reference power value.
In step S11, the improved empirical mode decomposition method includes the following steps:
s111, adding the white noise signal into the output power signal to obtain two sets of white noise signal sets M1,M2]Wherein M is1＝S+N；M2S-N, S being the output power signal and N being the white noise signal;
s112, for M1And M2Respectively carrying out empirical mode decomposition to obtain two groups of IMF sets c1jAnd c2j；
S113, two groups of IMF sets c obtained in the step two are subjected to1jAnd c2jCombining to obtain IMF component cjWherein。
In step S13, the method includes the steps of:
s131, setting IMF component set X ═ X1,x2,...xi...,xM]TLet yi＝xi-E(xi) Wherein, E (x)i) Is xiY-Y matrix1,y2,...,yM]TThe covariance of X is C;
s132, the covariance C of step S131 is decomposed by the following formula, where C is equal to UM×NΛM×NUT M×NΛ is a characteristic value diagonal matrix of C, and U is an orthogonal matrix formed by characteristic vectors;
s133, obtaining P ═ U from Y obtained in step S131 and U obtained in step S132T M×NAnd Y, sorting the IMF components according to the contribution rate in the P from large to small.
In step S2, the following steps are specifically adopted to implement wireless encrypted communication:
s21, the monitoring device sends a downlink data packet to the base station, wherein the data packet comprises the photovoltaic equipment terminal identity and the query data type;
s22, the base station analyzes data of the data packet according to a communication protocol of the base station and the monitoring device, and identifies the terminal identity of the photovoltaic equipment and inquires the data type; assembling the identity and the query data type of the photovoltaic equipment terminal according to a communication protocol of the base station and the photovoltaic equipment terminal to obtain an assembled data message; encrypting the assembled data message to obtain an encrypted data message; sending the encrypted data message to a photovoltaic equipment terminal through a radio frequency channel;
s23, the photovoltaic equipment terminal decrypts the encrypted data message to obtain photovoltaic equipment data; assembling photovoltaic equipment data into a format message according to a serial port protocol; sending the format message to a data acquisition device through a serial port;
s24, the data acquisition device checks the format message; after the format message passes the verification, obtaining a data part of the photovoltaic equipment from the format message; analyzing the data part of the photovoltaic equipment according to a serial port protocol to obtain photovoltaic equipment data;
s25, acquiring target data after the data acquisition device acquires the data of the photovoltaic equipment; packing the target data according to a serial port protocol to obtain serial port data; sending the serial port data to a photovoltaic equipment terminal through a serial port;
s26, the photovoltaic equipment terminal checks serial port data; after the serial port data passes the verification, acquiring a photovoltaic equipment data part from the serial port data, and assembling the photovoltaic equipment data part according to a communication protocol of a photovoltaic equipment terminal and a base station to obtain an assembled data message, wherein the data message carries the identity of the photovoltaic equipment terminal; encrypting the assembled data message to obtain encrypted data; transmitting the encrypted data to the base station through a radio frequency channel;
s27, the base station decrypts the encrypted data to obtain a decrypted data message; analyzing the decrypted data message, and identifying the identity of the carried photovoltaic equipment terminal; extracting photovoltaic equipment data from the analyzed data message, and packaging the photovoltaic equipment data according to a communication protocol of the base station and the monitoring device to obtain packaged data, wherein the packaged data comprises a photovoltaic equipment terminal identity and a response data type; the packed data is sent to the monitoring device.
Preferably, in step S3, the operation mode of the photovoltaic device is determined as follows:
when the active power reference value is larger than the first output power threshold value P1 and the voltage value fluctuation of the grid side is smaller than the first voltage fluctuation threshold value V1, the photovoltaic device enters an active output mode;
when the active reference value is smaller than the second output power threshold value P2 and the grid side voltage value fluctuation value is larger than the second voltage fluctuation threshold value V2, the optical tiger device enters a reactive compensation mode.
Preferably, in step S4, when the photovoltaic device enters the active output mode, the photovoltaic device is controlled to operate as follows:
continuously acquiring an active reference value of the photovoltaic equipment;
judging whether the active reference value meets a first switching condition or not;
and when the active reference value meets the first switching condition, switching the photovoltaic grid-connected inverter from the active power output mode to a reactive power compensation mode.
Preferably, in step S4, when the photovoltaic device enters the reactive compensation mode, the photovoltaic device is controlled to operate as follows:
continuously acquiring a fluctuation value of the grid side voltage of the photovoltaic equipment;
judging whether the network side voltage fluctuation value meets a second switching condition or not;
and when the grid side voltage fluctuation value meets the second switching condition, switching the photovoltaic equipment from the reactive power compensation mode to the active power output mode.
Preferably, the step of judging whether the active reference value satisfies a first switching condition includes:
when the active reference value of the photovoltaic device is smaller than a first power threshold value P1, determining whether a first duration for which the output power of the photovoltaic device is smaller than the first power threshold value P1 reaches a first time threshold value T1, and if the first duration reaches the first time threshold value T1, the first output state information satisfies the first switching condition.
Preferably, the step of determining whether the network-side voltage fluctuation value satisfies a second switching condition includes:
when the grid-side voltage fluctuation value is greater than or equal to a voltage fluctuation second threshold value V2, judging whether a second time duration for which the grid-side voltage fluctuation value is greater than or equal to a second voltage fluctuation threshold value V2 reaches a second time threshold value T2, and if the second time duration reaches the second time threshold value T2, the grid-side voltage fluctuation value meets the second switching condition.
The foregoing is a more detailed description of the invention in connection with specific preferred embodiments and it is not intended that the invention be limited to these specific details. For those skilled in the art to which the invention pertains, several equivalent substitutions or obvious modifications, which are equivalent in performance or use, should be considered to fall within the scope of the present invention without departing from the spirit of the invention.
Claims (10)
1. A grid-connected operation optimization method for photovoltaic power generation equipment comprises the following steps:
s1, rapidly calculating an active power reference value of photovoltaic power generation equipment, and detecting a grid side voltage value of a photovoltaic power station in real time;
s2, sending the active power reference value and the voltage value of the photovoltaic power station network side to a monitoring device in a wireless communication mode;
s3, determining a grid-connected working mode of the photovoltaic power generation equipment according to the active power reference value and the grid-side direct-current voltage information;
and S4, controlling the photovoltaic equipment to operate optimally by the monitoring device according to the grid-connected working mode.
2. The method according to claim 1, wherein in step S1, the active power reference value of the photovoltaic power generation device is calculated rapidly by using the following method:
s11, segmenting the output power signal of the photovoltaic power station according to time, and then decomposing the output power signal of each segment by using an improved empirical mode decomposition method to obtain an IMF component cjFor the boundary value of each section of output power signal, adopting the IMF mean value of the previous section of output power signal to obtain a plurality of IMF components;
s12, performing wavelet denoising on the IMF component obtained in the step S11 by adopting a novel wavelet denoising method to obtain a denoised new IMF component, wherein a threshold function of the novel wavelet denoising method is as follows:
wherein,d is the wavelet coefficient length, σ is the noise variance, WjkIs a wavelet coefficient, f is an input signal frequency
And S13, sequencing the new IMF components obtained in the step S12 by using a principal component analysis method, and combining the sequenced new IMF components to obtain a photovoltaic power station grid-connected reference power value.
3. The method of claim 2, wherein in step S11, the improved empirical mode decomposition method comprises the steps of:
s111, adding the white noise signal into the output power signal to obtain two sets of white noise signal sets M1,M2]Wherein M is1＝S+N；M2S-N, S being the output power signal and N being the white noise signal;
s112, for M1And M2Respectively carrying out empirical mode decomposition to obtain two groups of IMF sets c1jAnd c2j；
S113, two groups of IMF sets c obtained in the step two are subjected to1jAnd c2jCombining to obtain IMF component cjWherein。
4. The method of claim 2, wherein in step S13, the method comprises the steps of:
s131, setting IMF component set X ═ X1,x2,...xi...,xM]TLet yi＝xi-E(xi) Wherein, E (x)i) Is xiY-Y matrix1,y2,...,yM]TThe covariance of X is C;
the covariance C of step S131 is decomposed by the following equation, where C is UM×NΛM×NUT M×NΛ is a characteristic value diagonal matrix of C, and U is an orthogonal matrix formed by characteristic vectors;
from Y obtained in step S131 and U obtained in step S132, P ═ U is obtainedT M×NAnd Y, sorting the IMF components according to the contribution rate in the P from large to small.
5. The method according to any of claims 1 to 4, wherein in step S2, the wireless encrypted communication is implemented by specifically adopting the following steps:
s21, the monitoring device sends a downlink data packet to the base station, wherein the data packet comprises the photovoltaic equipment terminal identity and the query data type;
s22, the base station analyzes data of the data packet according to a communication protocol of the base station and the monitoring device, and identifies the terminal identity of the photovoltaic equipment and inquires the data type; assembling the identity and the query data type of the photovoltaic equipment terminal according to a communication protocol of the base station and the photovoltaic equipment terminal to obtain an assembled data message; encrypting the assembled data message to obtain an encrypted data message; sending the encrypted data message to a photovoltaic equipment terminal through a radio frequency channel;
s23, the photovoltaic equipment terminal decrypts the encrypted data message to obtain photovoltaic equipment data; assembling photovoltaic equipment data into a format message according to a serial port protocol; sending the format message to a data acquisition device through a serial port;
s24, the data acquisition device checks the format message; after the format message passes the verification, obtaining a data part of the photovoltaic equipment from the format message; analyzing the data part of the photovoltaic equipment according to a serial port protocol to obtain photovoltaic equipment data;
s25, acquiring target data after the data acquisition device acquires the data of the photovoltaic equipment; packing the target data according to a serial port protocol to obtain serial port data; sending the serial port data to a photovoltaic equipment terminal through a serial port;
s26, the photovoltaic equipment terminal checks serial port data; after the serial port data passes the verification, acquiring a photovoltaic equipment data part from the serial port data, and assembling the photovoltaic equipment data part according to a communication protocol of a photovoltaic equipment terminal and a base station to obtain an assembled data message, wherein the data message carries the identity of the photovoltaic equipment terminal; encrypting the assembled data message to obtain encrypted data; transmitting the encrypted data to the base station through a radio frequency channel;
s27, the base station decrypts the encrypted data to obtain a decrypted data message; analyzing the decrypted data message, and identifying the identity of the carried photovoltaic equipment terminal; extracting photovoltaic equipment data from the analyzed data message, and packaging the photovoltaic equipment data according to a communication protocol of the base station and the monitoring device to obtain packaged data, wherein the packaged data comprises a photovoltaic equipment terminal identity and a response data type; the packed data is sent to the monitoring device.
6. The method according to any one of claims 1 to 5, wherein in step S3, the photovoltaic device operation mode is determined by:
when the active power reference value is larger than the first output power threshold value P1 and the voltage value fluctuation of the grid side is smaller than the first voltage fluctuation threshold value V1, the photovoltaic device enters an active output mode;
when the active reference value is smaller than the second output power threshold value P2 and the grid side voltage value fluctuation value is larger than the second voltage fluctuation threshold value V2, the optical tiger device enters a reactive compensation mode.
7. The method according to claim 6, wherein in step S4, when the photovoltaic device enters into active output mode operation, the photovoltaic device is controlled to operate as follows:
continuously acquiring an active reference value of the photovoltaic equipment;
judging whether the active reference value meets a first switching condition or not;
and when the active reference value meets the first switching condition, switching the photovoltaic grid-connected inverter from the active power output mode to a reactive power compensation mode.
8. The method according to claim 6, wherein in step S4, when the photovoltaic device enters the reactive compensation mode, the photovoltaic device is controlled to operate as follows:
continuously acquiring a fluctuation value of the grid side voltage of the photovoltaic equipment;
judging whether the network side voltage fluctuation value meets a second switching condition or not;
and when the grid side voltage fluctuation value meets the second switching condition, switching the photovoltaic equipment from the reactive power compensation mode to the active power output mode.
9. The method of claim 7, wherein the step of determining whether the active reference value satisfies a first switching condition comprises:
when the active reference value of the photovoltaic device is smaller than a first power threshold value P1, determining whether a first duration for which the output power of the photovoltaic device is smaller than the first power threshold value P1 reaches a first time threshold value T1, and if the first duration reaches the first time threshold value T1, the first output state information satisfies the first switching condition.
10. The method of claim 8, wherein the step of determining whether the grid-side voltage ripple value satisfies a second switching condition comprises:
when the grid-side voltage fluctuation value is greater than or equal to a voltage fluctuation second threshold value V2, judging whether a second time duration for which the grid-side voltage fluctuation value is greater than or equal to a second voltage fluctuation threshold value V2 reaches a second time threshold value T2, and if the second time duration reaches the second time threshold value T2, the grid-side voltage fluctuation value meets the second switching condition.
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