CN117872027A - Power distribution network state sensing method for photovoltaic connection - Google Patents
Power distribution network state sensing method for photovoltaic connection Download PDFInfo
- Publication number
- CN117872027A CN117872027A CN202410286101.3A CN202410286101A CN117872027A CN 117872027 A CN117872027 A CN 117872027A CN 202410286101 A CN202410286101 A CN 202410286101A CN 117872027 A CN117872027 A CN 117872027A
- Authority
- CN
- China
- Prior art keywords
- distribution network
- power distribution
- verification
- period
- terminal equipment
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 238000000034 method Methods 0.000 title claims abstract description 41
- 238000012795 verification Methods 0.000 claims abstract description 157
- 230000002159 abnormal effect Effects 0.000 claims abstract description 113
- 230000008447 perception Effects 0.000 claims abstract description 21
- 230000005856 abnormality Effects 0.000 claims description 32
- 238000012544 monitoring process Methods 0.000 claims description 19
- 230000005540 biological transmission Effects 0.000 claims description 8
- 230000000737 periodic effect Effects 0.000 claims description 5
- 230000002045 lasting effect Effects 0.000 claims description 3
- 206010011906 Death Diseases 0.000 claims 3
- 238000012545 processing Methods 0.000 description 7
- 230000000007 visual effect Effects 0.000 description 6
- 238000013528 artificial neural network Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000010248 power generation Methods 0.000 description 1
- 238000012360 testing method Methods 0.000 description 1
- 238000012800 visualization Methods 0.000 description 1
Landscapes
- Remote Monitoring And Control Of Power-Distribution Networks (AREA)
Abstract
The invention relates to the technical field of power systems, and particularly discloses a power distribution network state sensing method for photovoltaic connection, which comprises the steps of obtaining a real-time voltage value of a power distribution network end, and recording a power distribution network end verification period when the time length of the real-time voltage value of the power distribution network end being larger than a nominal voltage value of the power distribution network end exceeds a preset time length; acquiring state identification data of the power distribution network terminal based on the verification period of the power distribution network terminal, and acquiring an operation state identification value of the power distribution network terminal in a period based on the state identification data; obtaining a verification signal of the power distribution network end in the period according to the running state identification value of the power distribution network end in the period; based on a verification normal signal of a power distribution network terminal in a period, identifying state perception of power distribution network terminal equipment in an operation area; based on the verification abnormal signal of the power distribution network terminal in the period, the abnormal sensing state of the power distribution network terminal equipment is identified, and the sensing of the running state of the power distribution network terminal under the normal verification and the abnormal verification is completed.
Description
Technical Field
The invention relates to the technical field of power systems, in particular to a power distribution network state sensing method for photovoltaic connection.
Background
The photovoltaic connection power distribution network refers to directly connecting electric energy generated by a photovoltaic power station into the power distribution network, and the electric energy is transmitted to a user power terminal through the power network as common coal-fired power, hydropower power and other power sources. The mode needs to be matched with facilities such as an inverter, an alternating-current transformer substation and the like to perform electric energy conversion and boosting treatment, so that the quality and stability of electric energy are ensured.
The patent application number 202011551723.2 discloses a photovoltaic power distribution network control method and a terminal, wherein the photovoltaic power distribution network control method comprises the following steps: acquiring weather data of a prediction day; based on a neural network prediction model which is trained in advance, determining the predicted output power of the photovoltaic inverter corresponding to each node in the photovoltaic power distribution network according to meteorological data of a prediction day; determining a predicted voltage value of each node according to the predicted output power of the photovoltaic inverter corresponding to each node; if the predicted voltage value of any node is larger than a first preset voltage threshold value, determining an output power reference value of each photovoltaic inverter according to a preset power distribution model; determining the working mode of the photovoltaic inverter corresponding to each node according to the predicted voltage value of each node; based on the output power reference value and the working mode, the output power of each photovoltaic inverter is controlled, and the problem that the active power is directly reduced to reduce the photovoltaic power generation efficiency can be effectively avoided.
The above patent lacks the perception to the running state of distribution network end, and the degree of visualization is low, can not timely effectual obtain the running situation of distribution network end, promptly in the running process of distribution network end, when distribution network end running state takes place unusual, can not effective discernment, lacks the visual management to distribution network end.
Disclosure of Invention
The invention aims to provide a power distribution network state sensing method for photovoltaic connection, which is characterized in that a power distribution network end verification period is obtained according to a real-time voltage value of a power distribution network end by obtaining the real-time voltage value of the power distribution network end, and the running state identification value of power distribution network terminal equipment is obtained by processing the cycle frequency of the power distribution network end verification period, the duration duty ratio of the power distribution network end verification period and the electric energy abnormal total ratio of the power distribution network end verification period, and the running state of the power distribution network end is identified based on the running state identification value of the power distribution network end, so that the sensing of the running state of the power distribution network terminal is completed.
The aim of the invention can be achieved by the following technical scheme:
a power distribution network state sensing method for photovoltaic connection, comprising the steps of:
step one: acquiring a real-time voltage value of a power distribution network end, and when the time length of the real-time voltage value of the power distribution network end being larger than the nominal voltage value of the power distribution network end exceeds a preset time length;
the real-time voltage value of the power distribution network terminal is recorded as an out-of-limit voltage;
the time period lasting for the out-of-limit voltage is recorded as an end-of-line verification period of the power distribution network;
step two: acquiring state identification data of the power distribution network terminal based on the verification period of the power distribution network terminal, and acquiring an operation state identification value of the power distribution network terminal in a period based on the state identification data;
step three: obtaining a verification signal of the power distribution network end in the period according to the running state identification value of the power distribution network end in the period;
wherein the verification signal includes a verification normal signal and a verification abnormal signal;
step four: based on a verification normal signal of a power distribution network terminal in a period, identifying state perception of power distribution network terminal equipment in an operation area;
step five: and identifying the abnormal sensing state of the power distribution network terminal equipment based on the verification abnormal signal of the power distribution network terminal in the period.
As a further scheme of the invention: in the second step, the state identification data comprises the cycle frequency of the power distribution network end verification period, the duration ratio of the power distribution network end verification period and the electric energy abnormal total ratio of the power distribution network end verification period;
marking the periodic frequency of the power distribution network end-verification period as Xz;
marking the duration duty ratio of the power distribution network end verification period as Xc;
marking the total electric energy abnormality ratio of the power distribution network end verification period as Xn;
i.e. by the formulaCalculating to obtain an operating state identification value XSB of the power distribution network end; wherein a1, a2, a3 are preset proportionality coefficients, and a1, a2, a3 are all larger than zero.
As a further scheme of the invention: the period frequency of the power distribution network end verification period is the ratio of the occurrence times of the power distribution network end verification period to the period duration of the power distribution network end.
As a further scheme of the invention: the acquisition process of the duration ratio of the power distribution network end-verification period is as follows:
acquiring the time length corresponding to each section of the power distribution network end verification period, and summing the time lengths of all the power distribution network end verification periods in the period to obtain the total time length of the power distribution network end verification period;
and calculating the ratio of the total duration of the power distribution network end verification period to the period duration of the power distribution network end, and obtaining the duration duty ratio of the power distribution network end verification period.
As a further scheme of the invention: the acquisition process of the electric energy abnormal total ratio of the power distribution network end-effect period is as follows:
acquiring an electric energy value and a transmission electric energy loss value of a load end in each section of power distribution network end verification period, and adding the electric energy value of the load end and the transmission electric energy loss value to obtain output electric energy of the power distribution network end in the power distribution network end verification period;
calculating the ratio of the output electric energy of the power distribution network end in the power distribution network end verification period to the rated electric energy of the power distribution network end, and obtaining the abnormal electric energy ratio of each power distribution network end verification period;
and summing the electric energy abnormality ratios of the power distribution network end verification time periods of all the sections, and obtaining an average value to obtain the electric energy abnormality total ratio of the power distribution network end verification time periods.
As a further scheme of the invention: the method comprises the steps of presetting a power distribution network end operating state identification value threshold value as XSB, and comparing a power distribution network end operating state identification value XSB with a power distribution network end operating state identification value threshold value XSB;
if the power distribution network end operating state identification value XSB is more than or equal to the power distribution network end operating state identification value threshold XSB, the power distribution network end is verified to be normal in the operating state period, and a verification normal signal is generated;
if the power distribution network end operation state identification value XSB is smaller than the power distribution network end operation state identification value threshold XSB, the verification abnormality is indicated in the power distribution network end operation state period, and a verification abnormality signal is generated.
As a further scheme of the invention: the method comprises the steps of marking power distribution network terminal equipment corresponding to a power distribution network terminal as target equipment, and obtaining side power distribution network terminal equipment in the same operation area of the target equipment;
acquiring a capacity similarity value of equipment capacity of the side power distribution network terminal equipment and equipment capacity of target equipment, and marking the capacity similarity value as D1;
obtaining a time similarity value of the running total time of the terminal equipment of the side distribution network and the running total time of the target equipment, and marking the time similarity value as D2;
acquiring a quality similarity value of the power supply quality of the terminal equipment of the side power distribution network and the power supply quality of the target equipment, and marking as D3;
acquiring a reliability similarity value of the power supply reliability of the terminal equipment of the side distribution network and the power supply reliability of the target equipment, and marking the reliability similarity value as D4;
calculating to obtain a resonance base Di of the side distribution network terminal equipment and the target equipment through a formula Di=D1+D2+d2+D3+d3+D4, wherein D1, D2, D3 and D4 are preset proportionality coefficients;
comparing the resonance base Di with a resonance base threshold Di;
if the resonance base Di is more than or equal to the resonance base threshold Di, the terminal equipment of the side distribution network is estimated to be the same-frequency equipment of the target equipment;
and if the resonance base Di is smaller than the resonance base threshold Di, the terminal equipment of the side distribution network is estimated to be non-same-frequency equipment of the target equipment.
As a further scheme of the invention: acquiring all same-frequency equipment of the target equipment to obtain a same-frequency equipment group of the target equipment, acquiring operation state identification values of the same-frequency equipment in the same-frequency equipment group to obtain an operation state identification value group, and arranging the operation state identification values in the operation state identification value group in order from big to small;
acquiring the position rank of an operation state identification value of the target equipment in an operation state identification value group corresponding to the same-frequency equipment group, and marking the position rank as Tp;
if Tp is more than 0 and less than or equal to 20%, the target equipment is indicated to be excellent in operation perception state;
if the TP is more than 20 percent and less than or equal to 50 percent, the target equipment is indicated to have good operation perception state;
if Tp > 50%, it means that the target device is in a normal operation perception state.
As a further scheme of the invention: acquiring operation equipment data of power distribution network terminal equipment corresponding to a power distribution network terminal, wherein the operation equipment data comprises sound data and temperature data of the power distribution network terminal equipment;
dividing the power distribution network terminal equipment into a plurality of verification areas, and setting a sound sensor and a temperature sensor in each verification area to obtain verification values of the verification areas;
marking a verification region with a verification value not falling within the verification value range, and marking the verification region as an abnormal region;
acquiring the number of components to be monitored in each abnormal area;
acquiring real-time data of the monitoring items corresponding to each element device, calling a preset numerical requirement of the corresponding monitoring item, marking the monitoring items of which the real-time data does not meet the preset numerical requirement as abnormal items, and calculating the ratio of the abnormal items to the monitoring items to obtain the abnormal ratio of the elements;
adding the component anomaly ratios of all components in each anomaly region to obtain an anomaly region anomaly ratio;
summing the abnormal region abnormal ratios of all the abnormal regions to obtain the abnormal ratio of the device in the region of the power distribution network terminal equipment;
calculating the ratio of the number of the abnormal areas of the power distribution network terminal equipment to the verification areas of the power distribution network terminal equipment to obtain the abnormal area ratio of the power distribution network terminal equipment;
and carrying out product operation on the abnormal device ratio of the power distribution network terminal equipment area and the abnormal device ratio of the power distribution network terminal equipment area to obtain the abnormal perception coefficient of the power distribution network terminal equipment.
As a further scheme of the invention: recording an abnormality sensing coefficient of the power distribution network terminal equipment as Pg, and presetting a first limit value of the abnormality sensing coefficient of the power distribution network terminal equipment as Pg1 and a second limit value as Pg2, wherein Pg1 is smaller than Pg2;
when Pg is less than Pg1, the first-level abnormality of the sensing state of the power distribution network terminal equipment is indicated; when Pg1 is less than or equal to Pg < Pg2, the second-level abnormality of the sensing state of the power distribution network terminal equipment is indicated;
when Pg is more than or equal to Pg2, the three-level abnormality of the sensing state of the power distribution network terminal equipment is indicated.
The invention has the beneficial effects that:
according to the method, the real-time voltage value of the power distribution network terminal is obtained, the verification period of the power distribution network terminal is obtained according to the real-time voltage value of the power distribution network terminal, the operation state identification value of the power distribution network terminal is obtained by processing the cycle frequency of the verification period of the power distribution network terminal, the time duty ratio of the verification period of the power distribution network terminal and the total electric energy abnormality ratio of the verification period of the power distribution network terminal, the operation state of the power distribution network terminal is identified based on the operation state identification value of the power distribution network terminal, and therefore primary perception of the operation state of the power distribution network terminal is completed;
the method comprises the steps of marking power distribution network terminal equipment as target equipment based on a verification normal signal, obtaining side power distribution network terminal equipment in the same operation area of the target equipment, processing all the side power distribution network terminal equipment and the target equipment to obtain the same-frequency equipment matched with the target equipment in the side power distribution network terminal equipment, obtaining a same-frequency equipment group of the target equipment, obtaining operation state identification value groups by obtaining operation state identification values of the same-frequency equipment in the same-frequency equipment group, arranging the operation state identification values in the operation state identification value groups according to the order of large number, obtaining the position ranking of the operation state identification values of the target equipment in the operation state identification value groups corresponding to the same-frequency equipment group, namely, comparing the operation state of the power distribution network terminal equipment in the operation area with the operation state of other power distribution network terminal equipment to obtain one operation state of the power distribution network terminal equipment in the operation area, namely, enabling the perception state of the power distribution network terminal equipment to be more accurate by comparison and realizing visual management of the normal state of the power distribution network terminal equipment;
the method comprises the steps of obtaining operation equipment data of power distribution network terminal equipment based on an effective abnormal signal, obtaining an effective value of an effective area based on the operation equipment data, identifying abnormal areas in the effective area through the effective value, processing element devices to be monitored in each abnormal area to obtain element device abnormal ratios, obtaining the abnormal area abnormal ratios based on the element device abnormal ratios, and summing the abnormal area abnormal ratios of all the abnormal areas to obtain the element device abnormal ratio of the power distribution network terminal equipment; calculating the ratio of the number of the abnormal areas of the power distribution network terminal equipment to the verification areas of the power distribution network terminal equipment to obtain the abnormal area ratio of the power distribution network terminal equipment; and carrying out product operation on the abnormal device ratio of the area of the power distribution network terminal equipment and the abnormal area ratio of the power distribution network terminal equipment to obtain abnormal sensing coefficients of the power distribution network terminal equipment, and identifying abnormal sensing state grades of the power distribution network terminal equipment based on the abnormal sensing coefficients of the power distribution network terminal equipment to realize visual management of abnormal states of the power distribution network terminal equipment.
Drawings
The invention is further described below with reference to the accompanying drawings:
FIG. 1 is a flow chart of a method of power distribution network state sensing for photovoltaic connection of the present invention;
fig. 2 is a flowchart of a judgment process for using a terminal device of a side distribution network as a same-frequency device of a target device in a distribution network state sensing method for photovoltaic connection;
fig. 3 is a flowchart for identifying the operation sensing state of a target device in a power distribution network state sensing method for photovoltaic connection according to the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Example 1
Referring to fig. 1, the invention is a power distribution network state sensing method for photovoltaic connection, comprising the following steps:
step one: acquiring a real-time voltage value of a power distribution network end, and when the time length of the real-time voltage value of the power distribution network end being larger than the nominal voltage value of the power distribution network end exceeds a preset time length;
the real-time voltage value of the power distribution network terminal is recorded as an out-of-limit voltage;
the time period lasting for the out-of-limit voltage is recorded as an end-of-line verification period of the power distribution network; step two: acquiring state identification data of the power distribution network terminal based on the verification period of the power distribution network terminal, and acquiring an operation state identification value of the power distribution network terminal in a period based on the state identification data;
step three: obtaining a verification signal of the power distribution network end in the period according to the running state identification value of the power distribution network end in the period;
wherein the verification signal includes a verification normal signal and a verification abnormal signal;
step four: based on a verification normal signal of a power distribution network terminal in a period, identifying state perception of power distribution network terminal equipment in an operation area;
step five: and identifying the abnormal sensing state of the power distribution network terminal equipment based on the verification abnormal signal of the power distribution network terminal in the period.
The period in this embodiment includes, but is not limited to, 10 days, 1 month, or 3 months.
In the second step: the operation state identification value is obtained by the following steps:
the method comprises the steps of obtaining the cycle frequency of a power distribution network end verification period, the duration ratio of the power distribution network end verification period and the electric energy abnormal total ratio of the power distribution network end verification period in the operation period of the power distribution network end;
the periodic frequency of the power distribution network end-effect period is obtained by the following steps:
and calculating the ratio of the occurrence times of the power distribution network end verification period to the period duration of the power distribution network end, and obtaining the period frequency of the power distribution network end verification period.
The acquisition process of the duration ratio of the power distribution network end-verification period is as follows:
acquiring the time length corresponding to each section of the power distribution network end verification period, and summing the time lengths of all the power distribution network end verification periods in the period to obtain the total time length of the power distribution network end verification period;
and calculating the ratio of the total duration of the power distribution network end verification period to the period duration of the power distribution network end, and obtaining the duration duty ratio of the power distribution network end verification period.
The acquisition process of the electric energy abnormal total ratio of the power distribution network end-effect period is as follows:
acquiring an electric energy value and a transmission electric energy loss value of a load end in each section of power distribution network end verification period in an operation period of the power distribution network end, and adding the electric energy value of the load end and the transmission electric energy loss value to obtain output electric energy of the power distribution network end in the power distribution network end verification period;
calculating the ratio of the output electric energy of the power distribution network end in the power distribution network end verification period to the rated electric energy of the power distribution network end, and obtaining the abnormal electric energy ratio of each power distribution network end verification period;
the rated power of the power distribution network end is obtained by multiplying the rated voltage and the rated current of the power distribution network end and integrating the duration of the verification period of the power distribution network end;
the electric energy value of the load end is obtained through the following steps:
obtaining input current and input voltage of a load terminal, multiplying the input current and the input voltage of the load terminal during operation, integrating the duration of a power distribution network terminal verification period, and obtaining the electric energy value of the load terminal at the load terminal of the power distribution network terminal verification period;
the acquisition process of the transmission power loss value comprises the following steps: by the formulaObtaining a transmission electric energy loss value of a power distribution network end, wherein I is the current, R is the wire resistance, and t is the duration of an efficiency period of the power distribution network end;
and summing the electric energy abnormality ratios of the power distribution network end verification time periods of all the sections, and obtaining an average value to obtain the electric energy abnormality total ratio of the power distribution network end verification time periods.
Marking the periodic frequency of the power distribution network end-verification period as Xz;
marking the duration duty ratio of the power distribution network end verification period as Xc;
marking the total abnormal ratio of the electric energy in the end-effect period of the distribution network as Xn, namely passing through the formulaCalculating to obtain an operating state identification value XSB of the power distribution network end; wherein a1, a2, a3 are preset proportionality coefficients, and a1, a2, a3 are all larger than zero.
The formula for obtaining the operation state identification value of the power distribution network end can be known as follows: the larger the period frequency of the verification period of the power distribution network end is, the more times of the verification period of the power distribution network end are in the operation period of the power distribution network end, the less stable the power distribution network end is in the operation period, and the smaller the obtained operation state identification value of the power distribution network end is;
the larger the duration of the verification period of the power distribution network end is, the longer the operation time occupied by the verification period of the power distribution network end is in the operation period of the power distribution network end is, the more the overvoltage time of the power distribution network end in the operation period is, and the smaller the obtained operation state identification value of the power distribution network end is;
the larger the electric energy abnormal total ratio of the verification period of the power distribution network end is, the larger the electric energy abnormal loss caused by the occupation of the verification period of the power distribution network end is in the operation period of the power distribution network end, and the smaller the obtained operation state identification value of the power distribution network end is;
the method comprises the steps of presetting a power distribution network end operating state identification value threshold value as XSB, and comparing a power distribution network end operating state identification value XSB with a power distribution network end operating state identification value threshold value XSB;
if the power distribution network end operating state identification value XSB is more than or equal to the power distribution network end operating state identification value threshold XSB, the power distribution network end is verified to be normal in the operating state period, and a verification normal signal is generated;
if the power distribution network end operation state identification value XSB is smaller than the power distribution network end operation state identification value threshold XSB, the verification abnormality is indicated in the power distribution network end operation state period, and a verification abnormality signal is generated.
Example 2
Based on verification of normal signals
Referring to fig. 2 and 3, marking power distribution network terminal equipment corresponding to a power distribution network terminal as target equipment, and acquiring other power distribution network terminal equipment in the same operation area of the target equipment;
wherein the distribution network terminal equipment includes, but is not limited to, transformer terminal equipment;
in a specific embodiment, a preset area with the radius of 20 km can be drawn by taking the target equipment as the center, and other power distribution network terminal equipment except the target equipment in the preset area is obtained and recorded as side power distribution network terminal equipment;
acquiring a capacity similarity value of equipment capacity of the side power distribution network terminal equipment and equipment capacity of target equipment, and marking the capacity similarity value as D1;
the capacity similarity value is a ratio of the equipment capacity of the side power distribution network terminal equipment to the equipment capacity of the target equipment, and the closer the ratio is to 1, the higher the equipment capacity of the side power distribution network terminal equipment and the equipment capacity similarity of the target equipment are;
obtaining a time similarity value of the running total time of the terminal equipment of the side distribution network and the running total time of the target equipment, and marking the time similarity value as D2;
the time similarity value is the time coincidence degree of the running total time of the terminal equipment of the side distribution network and the running total time of the target equipment, and the larger the time coincidence degree is, the larger the time similarity value is;
acquiring a quality similarity value of the power supply quality of the terminal equipment of the side power distribution network and the power supply quality of the target equipment, and marking as D3;
the quality similarity value is the waveform coincidence degree of the voltage waveform of the side power distribution network terminal equipment and the voltage waveform of the target equipment, and the larger the waveform coincidence degree is, the larger the quality similarity value is;
acquiring a reliability similarity value of the power supply reliability of the terminal equipment of the side distribution network and the power supply reliability of the target equipment, and marking the reliability similarity value as D4;
the reliability similarity value is a ratio of the power supply reliability of the terminal equipment of the side distribution network to the power supply reliability of the target equipment, and the closer the ratio is 1, the higher the reliability similarity of the power supply reliability of the terminal equipment of the side distribution network and the power supply reliability of the target equipment is;
the power supply reliability obtaining process comprises the following steps:
obtaining the power failure time and the power failure frequency of the power distribution network terminal equipment in the whole operation time, and carrying out product operation on the power failure time and the power failure frequency of the power distribution network terminal equipment to obtain the power supply reliability of the power distribution network terminal equipment;
calculating to obtain a resonance base Di of the side distribution network terminal equipment and the target equipment through a formula Di=D1+D2+d2+D3+d3+D4, wherein D1, D2, D3 and D4 are preset proportionality coefficients;
comparing the resonance base Di with a resonance base threshold Di;
if the resonance base Di is more than or equal to the resonance base threshold Di, the terminal equipment of the side distribution network is estimated to be the same-frequency equipment of the target equipment;
if the resonance base Di is smaller than the resonance base threshold Di, the terminal equipment of the side distribution network terminal is estimated to be non-same-frequency equipment of the target equipment;
acquiring all same-frequency equipment of the target equipment to obtain a same-frequency equipment group of the target equipment, acquiring operation state identification values of the same-frequency equipment in the same-frequency equipment group to obtain an operation state identification value group, and arranging the operation state identification values in the operation state identification value group in order from big to small;
acquiring the position ranking of the operation state identification value of the target equipment in the operation state identification value group corresponding to the same-frequency equipment group, and marking the position ranking of the operation state identification value of the target equipment in the operation state identification value group as Tp;
if Tp is more than 0 and less than or equal to 20%, the target equipment is indicated to be excellent in operation perception state;
if the TP is more than 20 percent and less than or equal to 50 percent, the target equipment is indicated to have good operation perception state;
if Tp is more than 50%, the target equipment is indicated to be in a normal operation perception state;
the operation sensing state of the target equipment is identified, namely, the operation state of the power distribution network terminal equipment in the operation area is compared with the operation states of other power distribution network terminal equipment, so that one operation state of the power distribution network terminal equipment in the operation area is obtained, namely, the sensing state of the power distribution network terminal equipment is more accurate through comparison and reference, and visual management of the normal state of the power distribution network terminal is realized.
Example 3
Based on verification of anomaly signals
Acquiring operation equipment data of power distribution network terminal equipment corresponding to a power distribution network terminal, wherein the operation equipment data comprises sound data and temperature data of the power distribution network terminal equipment;
the sound data are obtained by monitoring a sound sensor arranged at the terminal equipment of the power distribution network, and the sound sensor is used for acquiring sound decibel values of the terminal equipment of the power distribution network;
the temperature data are obtained by monitoring a temperature sensor arranged at the terminal equipment of the power distribution network, and the temperature sensor is used for acquiring the temperature value of the terminal equipment of the power distribution network;
dividing a power distribution network terminal device into a plurality of verification areas, and setting a sound sensor and a temperature sensor in each verification area;
collecting sound decibel values and temperature values of a test area through a sound sensor and a temperature sensor, marking the sound decibel values as Xs, marking the temperature values as Xw, and distributing the weight ratio of the obtained sound decibel values Xs as n1; the weight ratio of the obtained temperature value Xw is distributed as n2; wherein, n1+n2=1, the temperature value is greater than the influence of sound decibel value in the running process of the power distribution network terminal equipment by the verification factor, and n2 is greater than n1 and greater than 0;
obtaining a verification value Xi of the obtained verification region according to a formula xi=xs+n1+xw+n2;
marking a verification region with a verification value not falling within the verification value range, and marking the verification region as an abnormal region;
acquiring the number of components to be monitored in each abnormal area;
acquiring real-time data of the monitoring items corresponding to each element device, calling a preset numerical requirement of the corresponding monitoring item, marking the monitoring items of which the real-time data does not meet the preset numerical requirement as abnormal items, and calculating the ratio of the abnormal items to the monitoring items to obtain the abnormal ratio of the elements;
adding the component anomaly ratios of all components in each anomaly region to obtain an anomaly region anomaly ratio;
the monitoring items comprise, but are not limited to, a current value, a voltage value, a temperature value, a humidity value, a vibration frequency and the like, the monitoring content of the monitoring items is determined according to the corresponding use scene of the component device, the content of the monitoring items is generated by a body when the corresponding component device works, and if the current value and the voltage value included in the monitoring items are the actual current value and the actual voltage value when the component device works;
summing the abnormal region abnormal ratios of all the abnormal regions to obtain the abnormal ratio of the device in the region of the power distribution network terminal equipment;
calculating the ratio of the number of the abnormal areas of the power distribution network terminal equipment to the verification areas of the power distribution network terminal equipment to obtain the abnormal area ratio of the power distribution network terminal equipment;
carrying out product operation on the abnormal device ratio of the power distribution network terminal equipment area and the abnormal device ratio of the power distribution network terminal equipment area to obtain an abnormal sensing coefficient of the power distribution network terminal equipment;
recording an abnormality sensing coefficient of the power distribution network terminal equipment as Pg, and presetting a limit value of the abnormality sensing coefficient of the power distribution network terminal equipment as a first limit value Pg1 and a second limit value Pg2, wherein Pg1 is smaller than Pg2;
the limiting values Pg1 and Pg2 of the abnormal perception coefficient of the power distribution network terminal equipment are empirical values, and are obtained empirically;
in the actual obtaining process, a plurality of groups of abnormal device ratios of the power distribution network terminal equipment area and abnormal power distribution network terminal equipment areas are processed to obtain a plurality of groups of abnormal power distribution network terminal equipment sensing coefficients, a worker identifies sensing state grades corresponding to power distribution network terminal equipment according to the plurality of groups of abnormal power distribution network terminal equipment sensing coefficients, so that a corresponding relation between the abnormal power distribution network terminal equipment sensing coefficients and the sensing state grades corresponding to the power distribution network terminal equipment is obtained, limit values of the abnormal power distribution network terminal equipment sensing coefficients are deduced and divided according to the sensing state grades of the power distribution network terminal equipment, limit values of the power distribution network terminal equipment are Pg1 and Pg2, and identification of the sensing state grades corresponding to the power distribution network terminal equipment is completed through comparison of the limit values of the power distribution network terminal equipment;
when Pg is less than Pg1, the first-level abnormality of the sensing state of the power distribution network terminal equipment is indicated;
when Pg1 is less than or equal to Pg < Pg2, the second-level abnormality of the sensing state of the power distribution network terminal equipment is indicated;
when Pg is more than or equal to Pg2, the three-level abnormality of the sensing state of the power distribution network terminal equipment is indicated.
The larger the perceived state abnormality level of the power distribution network terminal equipment is, the worse the running state of the power distribution network terminal equipment is, and the visualized management of the abnormal state of the power distribution network terminal equipment is realized.
One of the core points of the present invention is: acquiring a real-time voltage value of a power distribution network end, acquiring a power distribution network end verification period according to the real-time voltage value of the power distribution network end, and processing the cycle frequency of the power distribution network end verification period, the time length duty ratio of the power distribution network end verification period and the electric energy abnormal total ratio of the power distribution network end verification period to acquire an operation state identification value of power distribution network terminal equipment, and identifying the operation state of the power distribution network end based on the operation state identification value of the power distribution network end so as to finish primary perception of the operation state of the power distribution network terminal;
one of the core points of the present invention is: based on the verification normal signals, marking the power distribution network terminal equipment as target equipment, acquiring side power distribution network terminal equipment in the same operation area of the target equipment, processing all the side power distribution network terminal equipment and the target equipment to obtain the same-frequency equipment matched with the target equipment in the side power distribution network terminal equipment, obtaining a same-frequency equipment group of the target equipment, acquiring operation state identification values of the same-frequency equipment in the same-frequency equipment group to obtain an operation state identification value group, arranging the operation state identification values in the operation state identification value group according to the order of large to small, acquiring the position ranking of the operation state identification value of the target equipment in the operation state identification value group corresponding to the same-frequency equipment group, namely, comparing the operation states of the power distribution network terminal equipment in the operation area with the operation states of other power distribution network terminal equipment to obtain one operation state of the power distribution network terminal equipment in the operation area, namely, by comparing and referencing, enabling the perception state of the power distribution network terminal equipment to be more accurate, and realizing the visual management of the normal state of the power distribution network terminal equipment;
one of the core points of the present invention is: acquiring operation equipment data of the power distribution network terminal equipment based on the verification abnormal signals, acquiring verification values of verification areas based on the operation equipment data, identifying abnormal areas in the verification areas through the verification values, processing element devices to be monitored in each abnormal area to obtain element and device abnormal ratios, obtaining the abnormal area abnormal ratios based on the element and device abnormal ratios, and summing the abnormal area abnormal ratios of all the abnormal areas to obtain the element and device abnormal ratio of the power distribution network terminal equipment; calculating the ratio of the number of the abnormal areas of the power distribution network terminal equipment to the verification areas of the power distribution network terminal equipment to obtain the abnormal area ratio of the power distribution network terminal equipment; and carrying out product operation on the abnormal device ratio of the area of the power distribution network terminal equipment and the abnormal area ratio of the power distribution network terminal equipment to obtain abnormal sensing coefficients of the power distribution network terminal equipment, and identifying abnormal sensing state grades of the power distribution network terminal equipment based on the abnormal sensing coefficients of the power distribution network terminal equipment to realize visual management of abnormal states of the power distribution network terminal equipment.
The foregoing describes one embodiment of the present invention in detail, but the description is only a preferred embodiment of the present invention and should not be construed as limiting the scope of the invention. All equivalent changes and modifications within the scope of the present invention are intended to be covered by the present invention.
Claims (10)
1. A power distribution network state sensing method for photovoltaic connection, comprising the steps of:
step one: acquiring a real-time voltage value of a power distribution network end, and when the time length of the real-time voltage value of the power distribution network end being larger than the nominal voltage value of the power distribution network end exceeds a preset time length;
the real-time voltage value of the power distribution network terminal is recorded as an out-of-limit voltage;
the time period lasting for the out-of-limit voltage is recorded as an end-of-line verification period of the power distribution network;
step two: acquiring state identification data of the power distribution network terminal based on the verification period of the power distribution network terminal, and acquiring an operation state identification value of the power distribution network terminal in a period based on the state identification data;
step three: obtaining a verification signal of the power distribution network end in the period according to the running state identification value of the power distribution network end in the period;
wherein the verification signal includes a verification normal signal and a verification abnormal signal;
step four: based on a verification normal signal of a power distribution network terminal in a period, identifying state perception of power distribution network terminal equipment in an operation area;
step five: and identifying the abnormal sensing state of the power distribution network terminal equipment based on the verification abnormal signal of the power distribution network terminal in the period.
2. A method for sensing the status of a power distribution network for photovoltaic connection according to claim 1, wherein in the second step, the status identification data includes the cycle frequency of the power distribution network end-of-life period, the duration duty cycle of the power distribution network end-of-life period, and the total abnormal electric energy ratio of the power distribution network end-of-life period;
marking the periodic frequency of the power distribution network end-verification period as Xz;
marking the duration duty ratio of the power distribution network end verification period as Xc;
marking the total electric energy abnormality ratio of the power distribution network end verification period as Xn;
i.e. by the formulaCalculating to obtain an operating state identification value XSB of the power distribution network end; wherein a1, a2, a3 are preset proportionality coefficients, and a1, a2, a3 are all larger than zero.
3. A method of sensing the condition of a power distribution network for photovoltaic connection according to claim 2, wherein the periodic frequency of the power distribution network end-of-verification period is the ratio of the number of occurrences of the power distribution network end-of-verification period to the period duration of the power distribution network end.
4. The method for sensing the state of a power distribution network for photovoltaic connection according to claim 2, wherein the obtaining process of the duration ratio of the end-of-power distribution network verification period is as follows:
acquiring the time length corresponding to each section of the power distribution network end verification period, and summing the time lengths of all the power distribution network end verification periods in the period to obtain the total time length of the power distribution network end verification period;
and calculating the ratio of the total duration of the power distribution network end verification period to the period duration of the power distribution network end, and obtaining the duration duty ratio of the power distribution network end verification period.
5. The power distribution network state sensing method for photovoltaic connection according to claim 2, wherein the obtaining process of the power distribution network end-verification period power abnormality total ratio is as follows:
acquiring an electric energy value and a transmission electric energy loss value of a load end in each section of power distribution network end verification period, and adding the electric energy value of the load end and the transmission electric energy loss value to obtain output electric energy of the power distribution network end in the power distribution network end verification period;
calculating the ratio of the output electric energy of the power distribution network end in the power distribution network end verification period to the rated electric energy of the power distribution network end, and obtaining the abnormal electric energy ratio of each power distribution network end verification period;
and summing the electric energy abnormality ratios of the power distribution network end verification time periods of all the sections, and obtaining an average value to obtain the electric energy abnormality total ratio of the power distribution network end verification time periods.
6. The power distribution network state sensing method for photovoltaic connection according to claim 2, wherein a power distribution network end operation state identification value threshold is preset to XSB, and the power distribution network end operation state identification value XSB is compared with the power distribution network end operation state identification value threshold XSB;
if the power distribution network end operating state identification value XSB is more than or equal to the power distribution network end operating state identification value threshold XSB, the power distribution network end is verified to be normal in the operating state period, and a verification normal signal is generated;
if the power distribution network end operation state identification value XSB is smaller than the power distribution network end operation state identification value threshold XSB, the verification abnormality is indicated in the power distribution network end operation state period, and a verification abnormality signal is generated.
7. The power distribution network state sensing method for photovoltaic connection according to claim 6, wherein power distribution network terminal equipment corresponding to a power distribution network terminal is marked as target equipment, and side power distribution network terminal equipment in the same operation area of the target equipment is obtained;
acquiring a capacity similarity value of equipment capacity of the side power distribution network terminal equipment and equipment capacity of target equipment, and marking the capacity similarity value as D1;
obtaining a time similarity value of the running total time of the terminal equipment of the side distribution network and the running total time of the target equipment, and marking the time similarity value as D2;
acquiring a quality similarity value of the power supply quality of the terminal equipment of the side power distribution network and the power supply quality of the target equipment, and marking as D3;
acquiring a reliability similarity value of the power supply reliability of the terminal equipment of the side distribution network and the power supply reliability of the target equipment, and marking the reliability similarity value as D4;
calculating to obtain a resonance base Di of the side distribution network terminal equipment and the target equipment through a formula Di=D1+D2+d2+D3+d3+D4, wherein D1, D2, D3 and D4 are preset proportionality coefficients;
comparing the resonance base Di with a resonance base threshold Di;
if the resonance base Di is more than or equal to the resonance base threshold Di, the terminal equipment of the side distribution network is estimated to be the same-frequency equipment of the target equipment;
and if the resonance base Di is smaller than the resonance base threshold Di, the terminal equipment of the side distribution network is estimated to be non-same-frequency equipment of the target equipment.
8. The method for sensing the state of a power distribution network for photovoltaic connection according to claim 7, wherein all the same-frequency devices of the target device are acquired to obtain a same-frequency device group of the target device, the operation state identification values of the same-frequency devices in the same-frequency device group are acquired to obtain an operation state identification value group, and the operation state identification values in the operation state identification value group are arranged in the order from large to small;
acquiring the position rank of an operation state identification value of the target equipment in an operation state identification value group corresponding to the same-frequency equipment group, and marking the position rank as Tp;
if Tp is more than 0 and less than or equal to 20%, the target equipment is indicated to be excellent in operation perception state;
if the TP is more than 20 percent and less than or equal to 50 percent, the target equipment is indicated to have good operation perception state;
if Tp > 50%, it means that the target device is in a normal operation perception state.
9. The power distribution network state sensing method for photovoltaic connection according to claim 6, wherein operation equipment data of power distribution network terminal equipment corresponding to a power distribution network terminal are obtained, and the operation equipment data comprise sound data and temperature data of the power distribution network terminal equipment;
dividing the power distribution network terminal equipment into a plurality of verification areas, and setting a sound sensor and a temperature sensor in each verification area to obtain verification values of the verification areas;
marking a verification region with a verification value not falling within the verification value range, and marking the verification region as an abnormal region;
acquiring the number of components to be monitored in each abnormal area;
acquiring real-time data of the monitoring items corresponding to each element device, calling a preset numerical requirement of the corresponding monitoring item, marking the monitoring items of which the real-time data does not meet the preset numerical requirement as abnormal items, and calculating the ratio of the abnormal items to the monitoring items to obtain the abnormal ratio of the elements;
adding the component anomaly ratios of all components in each anomaly region to obtain an anomaly region anomaly ratio;
summing the abnormal region abnormal ratios of all the abnormal regions to obtain the abnormal ratio of the device in the region of the power distribution network terminal equipment;
calculating the ratio of the number of the abnormal areas of the power distribution network terminal equipment to the verification areas of the power distribution network terminal equipment to obtain the abnormal area ratio of the power distribution network terminal equipment;
and carrying out product operation on the abnormal device ratio of the power distribution network terminal equipment area and the abnormal device ratio of the power distribution network terminal equipment area to obtain the abnormal perception coefficient of the power distribution network terminal equipment.
10. The power distribution network state sensing method for photovoltaic connection according to claim 9, wherein the power distribution network terminal equipment abnormality sensing coefficient is recorded as Pg, and a first limit value and a second limit value of the power distribution network terminal equipment abnormality sensing coefficient are preset as Pg1 and Pg2, respectively, wherein Pg1< Pg2;
when Pg is less than Pg1, the first-level abnormality of the sensing state of the power distribution network terminal equipment is indicated;
when Pg1 is less than or equal to Pg < Pg2, the second-level abnormality of the sensing state of the power distribution network terminal equipment is indicated;
when Pg is more than or equal to Pg2, the three-level abnormality of the sensing state of the power distribution network terminal equipment is indicated.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202410286101.3A CN117872027B (en) | 2024-03-13 | Power distribution network state sensing method for photovoltaic connection |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202410286101.3A CN117872027B (en) | 2024-03-13 | Power distribution network state sensing method for photovoltaic connection |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN117872027A true CN117872027A (en) | 2024-04-12 |
| CN117872027B CN117872027B (en) | 2024-07-02 |
Family
ID=
Citations (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20100102824A1 (en) * | 2007-04-18 | 2010-04-29 | Mario Tremblay | Electrical network fault location by distributed voltage measurements |
| JP2014045636A (en) * | 2012-08-29 | 2014-03-13 | Daiwa House Industry Co Ltd | Power supply system |
| CN104269844A (en) * | 2014-09-10 | 2015-01-07 | 国家电网公司 | Power distribution network state estimation abnormality recognition method and device |
| WO2018014706A1 (en) * | 2016-07-21 | 2018-01-25 | 蔚来汽车有限公司 | Integrated optical charging, storage and replacement station and power distribution method therefor |
| CN207868872U (en) * | 2018-03-16 | 2018-09-14 | 国家电网公司 | Electric network information processing unit based on embedded technology |
| JP6591133B1 (en) * | 2018-06-14 | 2019-10-16 | 三菱電機株式会社 | Power management system |
| CN111612326A (en) * | 2020-05-18 | 2020-09-01 | 国网河北省电力有限公司电力科学研究院 | Comprehensive evaluation method for power supply reliability of distribution transformer |
| CN114157034A (en) * | 2021-12-08 | 2022-03-08 | 国网四川省电力公司电力科学研究院 | Comprehensive monitoring method for multidimensional state of distribution automation terminal |
| CN114325495A (en) * | 2021-12-20 | 2022-04-12 | 山东汇能电气有限公司 | Operation protection method for distribution transformer based on loss comparison |
| CN115728642A (en) * | 2022-11-14 | 2023-03-03 | 宁波三星医疗电气股份有限公司 | Method and device for determining percentage of electric quantity of battery, electric energy meter and storage medium |
| WO2023035499A1 (en) * | 2021-09-10 | 2023-03-16 | 国网上海市电力公司 | Method and system for comprehensive evaluation of resilience of power distribution network |
| CN116106675A (en) * | 2021-11-10 | 2023-05-12 | 国网河南省电力公司周口供电公司 | Distribution line fault positioning and monitoring platform based on distributed intelligent terminal |
| CN117347772A (en) * | 2023-12-04 | 2024-01-05 | 深圳市铭瑞达五金制品有限公司 | Fault monitoring system and method for graphene radiator |
| CN117526577A (en) * | 2024-01-05 | 2024-02-06 | 国网山西省电力公司营销服务中心 | Distributed photovoltaic grid-connected power quality monitoring system and method |
Patent Citations (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20100102824A1 (en) * | 2007-04-18 | 2010-04-29 | Mario Tremblay | Electrical network fault location by distributed voltage measurements |
| JP2014045636A (en) * | 2012-08-29 | 2014-03-13 | Daiwa House Industry Co Ltd | Power supply system |
| CN104269844A (en) * | 2014-09-10 | 2015-01-07 | 国家电网公司 | Power distribution network state estimation abnormality recognition method and device |
| WO2018014706A1 (en) * | 2016-07-21 | 2018-01-25 | 蔚来汽车有限公司 | Integrated optical charging, storage and replacement station and power distribution method therefor |
| CN207868872U (en) * | 2018-03-16 | 2018-09-14 | 国家电网公司 | Electric network information processing unit based on embedded technology |
| JP6591133B1 (en) * | 2018-06-14 | 2019-10-16 | 三菱電機株式会社 | Power management system |
| CN111612326A (en) * | 2020-05-18 | 2020-09-01 | 国网河北省电力有限公司电力科学研究院 | Comprehensive evaluation method for power supply reliability of distribution transformer |
| WO2023035499A1 (en) * | 2021-09-10 | 2023-03-16 | 国网上海市电力公司 | Method and system for comprehensive evaluation of resilience of power distribution network |
| CN116106675A (en) * | 2021-11-10 | 2023-05-12 | 国网河南省电力公司周口供电公司 | Distribution line fault positioning and monitoring platform based on distributed intelligent terminal |
| CN114157034A (en) * | 2021-12-08 | 2022-03-08 | 国网四川省电力公司电力科学研究院 | Comprehensive monitoring method for multidimensional state of distribution automation terminal |
| CN114325495A (en) * | 2021-12-20 | 2022-04-12 | 山东汇能电气有限公司 | Operation protection method for distribution transformer based on loss comparison |
| CN115728642A (en) * | 2022-11-14 | 2023-03-03 | 宁波三星医疗电气股份有限公司 | Method and device for determining percentage of electric quantity of battery, electric energy meter and storage medium |
| CN117347772A (en) * | 2023-12-04 | 2024-01-05 | 深圳市铭瑞达五金制品有限公司 | Fault monitoring system and method for graphene radiator |
| CN117526577A (en) * | 2024-01-05 | 2024-02-06 | 国网山西省电力公司营销服务中心 | Distributed photovoltaic grid-connected power quality monitoring system and method |
Non-Patent Citations (2)
| Title |
|---|
| LIWEN QIN 等: "Topology Identification Method of Low-voltage Distribution Network Based on Improved Pearson Correlation Coefficient Method", 《2021 IEEE 2ND CHINA INTERNATIONAL YOUTH CONFERENCE ON ELECTRICAL ENGINEERING (CIYCEE)》, 20 January 2022 (2022-01-20), pages 1 - 6 * |
| 刘海金 等: "含高比例分布式电源的直流配电系统故障恢复过电压机理及其抑制", 《电测与仪表》, vol. 60, no. 11, 14 November 2023 (2023-11-14), pages 45 - 52 * |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN107271764B (en) | Method and device for detecting abnormal power consumption of electrical appliance | |
| CN115603453B (en) | Take intelligent monitoring system's direct current generating line group control device | |
| JP2013502831A (en) | Method and system for distributed generator message aggregation | |
| CN103471729A (en) | Device temperature early warning method and application thereof | |
| CN117332215B (en) | High-low voltage power distribution cabinet abnormal fault information remote monitoring system | |
| CN113112136A (en) | Comprehensive evaluation method and system for reliability of power distribution network | |
| CN106849064B (en) | Regional power grid load prediction management system based on meteorological data | |
| CN117872027B (en) | Power distribution network state sensing method for photovoltaic connection | |
| CN112098715B (en) | Electric energy monitoring and early warning system based on 5G and correction GCN graph neural network | |
| CN117650628B (en) | Energy efficiency management system based on self-adaptive preconditioning scene | |
| CN108108871B (en) | Type selection method for wind power plant group power transmission equipment | |
| CN117872027A (en) | Power distribution network state sensing method for photovoltaic connection | |
| CN110108983B (en) | Intelligent cable state online measurement and control management method | |
| CN112994002B (en) | Electric movable load identification method | |
| JP2023500471A (en) | Method and apparatus for microgrid tertiary control with integrated overcurrent protection | |
| CN113361802A (en) | Power load identification and prediction method based on artificial intelligence | |
| DE112018006999T5 (en) | Determination device, determination method and determination program | |
| CN114336594B (en) | Energy aggregation customer monitoring and demand response scheduling system and method | |
| CN116452367B (en) | Intelligent power supply management system | |
| CN117118087B (en) | Power equipment monitoring and early warning system and method | |
| CN107482779B (en) | Electric power system with good operation | |
| CN117035173B (en) | Heat exchange system daily load prediction method and system based on six-parameter model | |
| CN116191458B (en) | Frequency control method and system based on isolated network operation of thermal power generating unit | |
| CN110390495B (en) | Economical evaluation method and system for maximum allowable temperature of power transmission line | |
| CN118194185A (en) | Impedance-correlation-based method for diagnosing abnormal line loss of transformer area |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant |