CN105207247B - Control method of electric power system and device - Google Patents
Control method of electric power system and device Download PDFInfo
- Publication number
- CN105207247B CN105207247B CN201410281490.7A CN201410281490A CN105207247B CN 105207247 B CN105207247 B CN 105207247B CN 201410281490 A CN201410281490 A CN 201410281490A CN 105207247 B CN105207247 B CN 105207247B
- Authority
- CN
- China
- Prior art keywords
- distributed power
- power
- corrected
- output
- power supply
- 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.)
- Active
Links
- 238000000034 method Methods 0.000 title claims abstract description 32
- 238000012937 correction Methods 0.000 claims description 17
- 230000000694 effects Effects 0.000 abstract description 4
- 230000009194 climbing Effects 0.000 description 7
- 238000011156 evaluation Methods 0.000 description 7
- 108010074506 Transfer Factor Proteins 0.000 description 6
- 230000005622 photoelectricity Effects 0.000 description 4
- 230000008569 process Effects 0.000 description 4
- 230000008878 coupling Effects 0.000 description 3
- 238000010168 coupling process Methods 0.000 description 3
- 238000005859 coupling reaction Methods 0.000 description 3
- 238000010586 diagram Methods 0.000 description 3
- 230000006870 function Effects 0.000 description 3
- 238000012986 modification Methods 0.000 description 3
- 230000004048 modification Effects 0.000 description 3
- 238000010248 power generation Methods 0.000 description 3
- NAWXUBYGYWOOIX-SFHVURJKSA-N (2s)-2-[[4-[2-(2,4-diaminoquinazolin-6-yl)ethyl]benzoyl]amino]-4-methylidenepentanedioic acid Chemical compound C1=CC2=NC(N)=NC(N)=C2C=C1CCC1=CC=C(C(=O)N[C@@H](CC(=C)C(O)=O)C(O)=O)C=C1 NAWXUBYGYWOOIX-SFHVURJKSA-N 0.000 description 2
- 238000012935 Averaging Methods 0.000 description 2
- 230000005540 biological transmission Effects 0.000 description 2
- 238000004891 communication Methods 0.000 description 2
- 238000012545 processing Methods 0.000 description 2
- 230000002123 temporal effect Effects 0.000 description 2
- 230000008901 benefit Effects 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 230000007613 environmental effect Effects 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 230000004044 response Effects 0.000 description 1
Classifications
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16Z—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS, NOT OTHERWISE PROVIDED FOR
- G16Z99/00—Subject matter not provided for in other main groups of this subclass
Landscapes
- Engineering & Computer Science (AREA)
- Power Engineering (AREA)
- Supply And Distribution Of Alternating Current (AREA)
Abstract
The invention discloses a kind of control method of electric power system and device.Wherein, control method of electric power system includes：Obtain the historical data that distributed power source is exerted oneself in power system；The indefinite set of the distributed power source is determined according to the historical data, indefinite set is used to reflect the range of indeterminacy that the distributed power source is exerted oneself；The unbalanced power amount of the distributed power source is calculated, the unbalanced power amount is used to reflect the distributed power source in the scene extremely exerted oneself；The indefinite set is modified using the unbalanced power amount, revised indefinite set is obtained；And the operation of the power system is controlled using the revised indefinite set.By the present invention, solve Operation of Electric Systems after distributed power source access power network stability it is low the problem of, reached the effect for improving the stability of Operation of Electric Systems after distributed power source access power network.
Description
Technical Field
The invention relates to the field of power systems, in particular to a power system control method and device.
Background
In recent years, distributed power supplies such as wind, light and power are connected to a power grid in a large scale, and the distributed power supplies introduce higher-level uncertainty while improving the operating environmental benefit of a power system. In the case of its extreme forces, the system may face the problem of insufficient stepwise climbing. For this reason, the dispatcher may make a decision to cut off part of the load or turn on a high-cost quick response unit, but this violates the principles of economic, stable, and safe operation of the power system.
The high-risk event of the power system refers to an extreme output scenario that the power system cannot obtain a feasible scheduling strategy after a large-scale wind and light distributed power source is connected to a power grid, and is called as the high-risk event of the power system. Because the stability of the operation of the power system is low after the distributed power supply is connected to the power grid due to the high-risk events, it is necessary to effectively predict and evaluate the occurrence probability and the consequences of the high-risk events that the power system may face.
Aiming at the problem that the operation stability of a power system is low after a distributed power supply is connected to a power grid in the prior art, an effective solution is not provided at present.
Disclosure of Invention
The invention mainly aims to provide a method and a device for controlling a power system, which are used for solving the problem of low running stability of the power system after a distributed power supply is connected into a power grid.
In order to achieve the above object, according to one aspect of the present invention, there is provided a power system control method. The power system control method according to the present invention includes: acquiring historical data of output of a distributed power supply in a power system; determining an uncertainty set of the distributed power supply according to the historical data, wherein the uncertainty set is used for reflecting an uncertainty range of the distributed power supply output; calculating the power unbalance amount of the distributed power supply, wherein the power unbalance amount is used for reflecting the situation of the distributed power supply under the extreme output; correcting the uncertainty set by using the power unbalance to obtain a corrected uncertainty set; and controlling operation of the power system using the corrected set of uncertainties.
Further, determining the set of uncertainties for the distributed power sources from the historical data comprises: determining an upper limit and a lower limit of the distributed power output from the historical data; acquiring a preset confidence probability; determining a constraint condition of the distributed power supply output according to the upper limit and the lower limit of the distributed power supply output and the confidence probability; and determining the set of uncertainties from the upper and lower limits of distributed power generation output and the constraints.
Further, the power unbalance amount includes a first power unbalance amount and a second power unbalance amount, and correcting the uncertainty set by using the power unbalance amount includes: correcting the uncertainty set by correcting an upper limit and a lower limit of the distributed power output by using the power unbalance amount, respectively, wherein the upper limit and the lower limit of the distributed power output are corrected by the following formulas:
wherein,andrespectively representing the upper limit and the lower limit of the corrected output of the distributed power supply,andrespectively representing the upper limit and the lower limit of the distributed power output before correction,representing the amount of said first power imbalance,representing the second amount of power imbalance.
Further, after the uncertainty set is corrected by using the power unbalance amount to obtain a corrected uncertainty set, the power system control method further includes: and judging whether the corrected uncertainty set is in a preset risk range, wherein if the corrected uncertainty set is judged to be in the preset risk range, the corrected uncertainty set is utilized to control the operation of the power system.
Further, determining whether the corrected uncertainty set is within a preset risk range includes: and judging whether the corrected uncertainty set is in a preset risk range or not by judging whether the load shedding amount of the distributed power supply under the corrected uncertainty set is in a preset load shedding amount range or not, wherein if the load shedding amount of the distributed power supply under the corrected uncertainty set is judged to be in the load shedding amount range or not, the corrected uncertainty set is determined to be in the preset risk range.
In order to achieve the above object, according to another aspect of the present invention, there is provided a power system control device. The power system control device according to the present invention includes: the acquisition unit is used for acquiring historical data of distributed power supply output in the power system; the determining unit is used for determining an uncertainty set of the distributed power supply according to the historical data, wherein the uncertainty set is used for reflecting an uncertainty range of the output of the distributed power supply; the calculating unit is used for calculating the power unbalance amount of the distributed power supply, and the power unbalance amount is used for reflecting the situation of the distributed power supply under the extreme output; the correcting unit is used for correcting the uncertainty set by using the power unbalance amount to obtain a corrected uncertainty set; and a control unit for controlling the operation of the power system using the corrected set of uncertainties.
Further, the determining unit includes: a first determination module for determining an upper limit and a lower limit of the distributed power output from the historical data; the acquisition module is used for acquiring the preset confidence probability; the second determination module is used for determining the constraint conditions of the distributed power supply output according to the upper limit and the lower limit of the distributed power supply output and the confidence probability; and a third determination module for determining the uncertainty set from the upper and lower limits of distributed power output and the constraint.
Further, the power unbalance amount includes a first power unbalance amount and a second power unbalance amount, and the correction unit includes: a correction module, configured to correct the uncertainty set by respectively correcting an upper limit and a lower limit of the distributed power output by using the power imbalance, where the upper limit and the lower limit of the distributed power output are corrected by the following formulas:
wherein,andrespectively representing the upper limit and the lower limit of the corrected output of the distributed power supply,andrespectively representing the upper limit and the lower limit of the distributed power output before correction,representing the amount of said first power imbalance,representing the second amount of power imbalance.
Further, the power system control apparatus further includes: the control unit is further configured to control operation of the power system by using the corrected uncertainty set when the corrected uncertainty set is determined to be within the preset risk range.
Further, the judging unit includes: and the judging module is used for judging whether the corrected uncertainty set is in a preset risk range by judging whether the load shedding amount of the distributed power supply under the corrected uncertainty set is in a preset load shedding amount range, wherein if the load shedding amount of the distributed power supply under the corrected uncertainty set is judged to be in the load shedding amount range, the corrected uncertainty set is determined to be in the preset risk range.
According to the embodiment of the invention, the power unbalance amount of the distributed power supply is calculated by acquiring the historical data of the output of the distributed power supply in the power system, the uncertainty set is corrected by using the power unbalance amount to obtain the corrected uncertainty set, and the corrected uncertainty set is used for controlling the operation of the power system, so that the problem of low operation stability of the power system after the distributed power supply is connected into the power grid is solved, and the effect of improving the operation stability of the power system after the distributed power supply is connected into the power grid is achieved.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this application, illustrate embodiments of the invention and, together with the description, serve to explain the invention and not to limit the invention. In the drawings:
FIG. 1 is a flow chart of a power system control method according to an embodiment of the invention;
FIG. 2 is a schematic diagram of an IEEE39 node standard algorithm system according to an embodiment of the present invention;
FIG. 3 is a graphical illustration of load demand according to an embodiment of the present invention;
FIG. 4 is a graphical illustration of a distributed power processing interval according to an embodiment of the invention;
FIG. 5 is a graph illustrating the output of a distributed power source with a maximum loss of load according to an embodiment of the present invention;
FIG. 6 is a graphical illustration of distributed power output after a first modification in accordance with an embodiment of the present invention;
FIG. 7 is a graph illustrating the output of the distributed power supply when the air-abandoning amount is maximum according to the embodiment of the invention;
FIG. 8 is a graphical illustration of a distributed power output after a second correction in accordance with an embodiment of the present invention; and
fig. 9 is a schematic diagram of a power system control apparatus according to an embodiment of the present invention.
Detailed Description
It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict. The present invention will be described in detail below with reference to the embodiments with reference to the attached drawings.
In order to make the technical solutions of the present invention better understood, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It should be noted that the terms "first," "second," and the like in the description and claims of the present invention and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged under appropriate circumstances in order to facilitate the description of the embodiments of the invention herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
The embodiment of the invention provides a power system control method, which is used for a power system with a distributed power supply connected.
Fig. 1 is a flowchart of a power system control method according to an embodiment of the present invention. As shown in fig. 1, the power system control method includes the steps of:
and S102, acquiring historical data of the output of the distributed power supply in the power system. The distributed power supply outputs power, namely, the distributed power supply outputs electric energy through the distributed power supply, and the distributed power supply can be distributed power supplies of hydropower, wind power, photoelectricity and the like, wherein a power grid of a power system mainly comprises thermal power, and the hydropower, the wind power, the photoelectricity and the like are connected into the power grid of the thermal power, wherein historical data refers to data generated by the distributed power supplies in historical power supply, for example, power data and the like output by the wind power after the wind power is connected into the power grid.
And step S104, determining an uncertainty set of the distributed power supply according to the historical data, wherein the uncertainty set is used for reflecting an uncertainty range of the output of the distributed power supply.
The uncertainty set may be a pre-established uncertainty model reflecting the distributed power output, which may include parameters such as upper and lower limits of the distributed power output, and constraints thereof in the power supply process. By determining the set of uncertainties, the fluctuation range of the distributed power supply can be determined for high risk event prediction and evaluation.
And step S106, calculating the power unbalance of the distributed power supply, wherein the power unbalance is used for reflecting the situation of the distributed power supply under the extreme output.
The distributed power supply can possibly cause a high-risk event to occur in the power system under the condition of extreme output, and the power unbalance amount of the distributed power supply is calculated by determining the condition of the distributed power supply under the condition of extreme output, so that the uncertainty set is corrected conveniently to meet the condition of normal operation of the power system.
And S108, correcting the uncertainty set by using the power unbalance to obtain a corrected uncertainty set.
And step S110, controlling the operation of the power system by using the corrected uncertainty set.
And correcting the uncertainty set by using the power unbalance to obtain a corrected uncertainty set, and eliminating factors generating high-risk events, so that the power system can operate without generating risks under the corrected uncertainty set.
According to the embodiment of the invention, the power unbalance amount of the distributed power supply is calculated by acquiring the historical data of the output of the distributed power supply in the power system, the uncertainty set is corrected by using the power unbalance amount to obtain the corrected uncertainty set, and the corrected uncertainty set is used for controlling the operation of the power system, so that the problem of low operation stability of the power system after the distributed power supply is connected into the power grid is solved, and the effect of improving the operation stability of the power system after the distributed power supply is connected into the power grid is achieved.
Preferably, determining the set of uncertainties for the distributed power sources from the historical data comprises: determining an upper limit and a lower limit of the output of the distributed power supply according to historical data; acquiring a preset confidence probability; determining constraint conditions of the distributed power supply output according to the upper limit and the lower limit of the distributed power supply output and the confidence probability; and determining an uncertainty set by upper and lower limits of distributed power output and constraints.
In particular, the upper limit of distributed power outputAnd lower limitMay be derived from historical data or predictions of distributed power generation output. Since distributed power sources are typically distributed relatively widely and far apart, their contribution is expected to be less likely to reach the upper or lower limit simultaneously during the same time period, taking into account spatial averaging. Furthermore, the output of all distributed power supplies in a specific period of time has the following spatial constraints:
wherein, M represents the number of distributed power sources,the output half-interval of the distributed power supply is shown,the average value of the output of the distributed power supply is shown,Srepresenting a space uncertainty budget.
Also, given the smoothness of time, it is unlikely that the output will reach either the upper or lower output limits at different times of the day for a particular distributed power source. Further, there is a time constraint on the output of the distributed power supply at different times of the day:
wherein,Trepresenting the time uncertainty budget and T representing the scheduling period.
In formulae (1) and (2):
in the formula (3)Is determined by the following formula
Wherein, αjtRepresenting the confidence probability, sigma, of the wind power output predicted by the distributed power supply j in the period ijtTo predict the standard deviation, a distribution of prediction errors is assumed to be known, where the i period is an arbitrary period. The intervals in which the distributed power supply output can be described by equations (3) and (4) are as follows:
in equations (1) and (2), the uncertain budget is selected from
Wherein, βj，βtRespectively representing distributed power sources as not being on a spatial and temporal scaleA confidence probability of the budget is determined. Mu.ss，μh，σs，σhIs defined as follows
Definition of yjtThe following were used:
μjt，respectively represent yjtMean and variance of.
The confidence probability of the wind power output based on the uncertain space-time budget in the prediction interval range of the wind power plant can be obtained as follows:
and calculating the quantity of each parameter in the uncertainty set through the formula.
Preferably, the power unbalance amount includes a first power unbalance amount and a second power unbalance amount, and the correcting the uncertainty set by using the power unbalance amount includes:
correcting the uncertainty set by respectively correcting an upper limit and a lower limit of the distributed power output by using the power unbalance amount, wherein the upper limit and the lower limit of the distributed power output are corrected by the following formula:
wherein,andrespectively representing the upper limit and the lower limit of the corrected distributed power output,andrespectively representing the upper limit and the lower limit of the distributed power output before correction,a first amount of power imbalance is represented,representing a second amount of power imbalance.
Specifically, when a unit combination is formulated for a large-scale distributed power supply accessed power system, in order to deal with uncertainty of distributed power supply output, a method of formulating a preliminary scheme based on distributed power supply predicted output and then gradually increasing up for standby is generally adopted. And establishing a high-risk event prediction model, and correcting the uncertainty set based on the model. Specifically, taking an example of accessing a distributed power supply to a thermal power system, a description is given by way of example, and it is assumed that a unit combination scheme is determined. The high risk event prediction model is as follows:
wherein, the formula (11) is an objective function,andexpressing the relaxation variable in power balance, i.e. the amount of power imbalance, m, of equation (16)jtAnd njtIs a weight coefficient; the formula (12) is the maximum and minimum output constraint of the thermal power generating unit; formulas (13) and (14) are respectively positive and negative climbing constraints of the thermal power generating unit; equation (15) is the line flow constraint; equation 16 is the system power balance constraint, where in the above equation, N represents the number of thermal power units,the minimum output of the thermal power generating unit is shown,indicating the maximum output of the thermal power generating unit, DtIndicating load demand, FlIndicating the transmission capability of the line, piqlRepresenting the power transfer factor, pi, of the load lineilRepresenting the power transfer factor, pi, of a thermal power linejlRepresenting the distributed power line power transfer factor, pqtRepresenting loads transferred on the line, pjtRepresents distributed power output, pitIndicating thermal power output，The positive climbing capacity of the thermal power generating unit is shown,shows the negative climbing capacity u of the thermal power generating unititAnd showing a unit combination scheme.
The following equation is obtained:
equation (17) represents the upper and lower bounds of the corrected distributed power output uncertainty set.
It is known thatα 'can be calculated from formulas (3) and (4)'jt、σ'jtAnd mu'jt(ii) a Further, due toTAndSconstant, β 'can be calculated from formulas (6) - (8)'jAnd β'tη 'can be calculated from formula (10)'jtWherein, α'jt、σ'jtAnd mu'jtIn turn, αjt、σjt、μjtCorrected amount, β'jAnd β'tRespectively represent βjAnd βtCorrected amount, η'jtAnd representing the confidence probability of the corrected wind power output in the prediction interval range of the wind power plant.
Preferably, after the uncertainty set is corrected by using the power unbalance amount, and the corrected uncertainty set is obtained, the power system control method further includes: and judging whether the corrected uncertainty set is in a preset risk range, wherein if the corrected uncertainty set is judged to be in the preset risk range, the corrected uncertainty set is used for controlling the operation of the power system.
Because the risk probability of the power system can be adjusted as required, the conditions to be met by each parameter in the uncertainty set, namely the preset risk range, can be preset, and after the corrected uncertainty set is obtained, whether the uncertainty set is in the preset risk range can be judged, if yes, the requirement can be met, otherwise, the uncertainty set can be corrected again until the requirement is met.
According to the embodiment of the invention, whether the corrected uncertainty set meets the requirement can be verified by judging whether the corrected uncertainty set is in the preset risk range, so that the external risk of the power system caused by the fact that the corrected uncertainty set does not meet the requirement is avoided.
Preferably, the determining whether the corrected uncertainty set is within the preset risk range includes: and judging whether the corrected uncertainty set is in a preset risk range or not by judging whether the load shedding amount of the distributed power supply under the corrected uncertainty set is in a preset load shedding amount range or not, wherein if the load shedding amount of the distributed power supply under the corrected uncertainty set is judged to be in the load shedding amount range or not, the corrected uncertainty set is determined to be in the preset risk range.
The load shedding amount, namely the power output of the distributed power supply, can be preset in the range of the load shedding amount in the power system, so that the power supply of the power system is prevented from being influenced. After the corrected uncertainty set is obtained, whether the load shedding amount of the uncertainty set is within an allowable range or not is judged under the model of the corrected uncertainty set, namely the load shedding amount range is judged, if yes, the correction is finished, and otherwise, the uncertainty set is corrected again.
Examples of correcting the uncertainty set are described in detail below in conjunction with fig. 2-8:
in this example, in the IEEE39 node standard example system including 1 distributed power source and 24 scheduling periods, as shown in fig. 2, 10 units G are included, where the node 39 is unit 1, the node 38 is unit 2, the node 37 is unit 3, and the node … … is unit 10. The load demand curve is shown in fig. 3, and the unit combination scheme is shown in table 1.
TABLE 1
In table 1, the starting and stopping states of 10 units in 24 hours are shown in sequence from top to bottom, where "1" indicates starting and "0" indicates stopping.
First, a confidence probability α is sett＝95％,βt90% and assuming that the prediction error satisfies the normal distribution, haveTThe distributed power output curve is obtained as shown in fig. 4, where 41 denotes the upper limit of the distributed power output, 43 denotes the lower limit of the distributed power output, and 42 denotes the predicted distributed power output, 8. The abscissa indicates the time period and the ordinate indicates the load of the distributed power supply.
Then, the data is brought into the high-risk event prediction model, and the output situation of the distributed power supply when the high-risk event occurs is obtained as shown by a curve 44 in fig. 5, and the load loss is 113.5 megawatt hours at this time.
If the loss-of-load rate is zero as the evaluation criterion, the uncertainty set of distributed power output is modified as shown by curve 45 in FIG. 6. at this time, the confidence probability η for each time intervaltAs shown in table 2.
Table 2:
and (4) verifying the uncertain set in the graph 6 by using a high-risk event prediction model, wherein the load loss amount is zero, and the evaluation standard is met. Further, if the air curtailment is taken as a standard to assess the uncertainty in the figure 6In a set, the distributed power supply output scenario when the high-risk event occurs is shown as a curve 46 in fig. 7, the calculated maximum wind curtailment amount is 135.25 megawatts, and the corrected uncertainty set of the distributed power supply output is shown as a curve 47 in fig. 8, at this time, the confidence probability η of each time period istAs shown in table 3. And (4) verifying the uncertain set in the graph 8 by using a high-risk event prediction model, wherein the lost air volume is zero, and the evaluation standard is met.
TABLE 3
The embodiment of the invention also provides a control device of the power system. The apparatus may implement its functionality via a computer device. It should be noted that the power system control device according to the embodiment of the present invention may be used to execute the power system control method according to the embodiment of the present invention, and the power system control method according to the embodiment of the present invention may also be executed by the power system control device according to the embodiment of the present invention.
Fig. 9 is a schematic diagram of a power system control apparatus according to an embodiment of the present invention. As shown in fig. 9, the power system control device includes: an acquisition unit 10, a determination unit 20, a calculation unit 30, a correction unit 40, and a control unit 50.
The acquiring unit 10 is used for acquiring historical data of distributed power supply output in the power system. The distributed power supply outputs power, namely, the distributed power supply outputs electric energy through the distributed power supply, and the distributed power supply can be distributed power supplies of hydropower, wind power, photoelectricity and the like, wherein a power grid of a power system mainly comprises thermal power, and the hydropower, the wind power, the photoelectricity and the like are connected into the power grid of the thermal power, wherein historical data refers to data generated by the distributed power supplies in historical power supply, for example, power data and the like output by the wind power after the wind power is connected into the power grid.
The determining unit 20 is configured to determine an uncertainty set of the distributed power source according to the historical data, where the uncertainty set is used to reflect an uncertainty range of the distributed power source output.
The uncertainty set may be a pre-established uncertainty model reflecting the distributed power output, which may include parameters such as upper and lower limits of the distributed power output, and constraints thereof in the power supply process. By determining the set of uncertainties, the fluctuation range of the distributed power supply can be determined for high risk event prediction and evaluation.
The calculating unit 30 is configured to calculate a power imbalance of the distributed power source, where the power imbalance is used to reflect a situation of the distributed power source under an extreme output.
The distributed power supply can possibly cause a high-risk event to occur in the power system under the condition of extreme output, and the power unbalance amount of the distributed power supply is calculated by determining the condition of the distributed power supply under the condition of extreme output, so that the uncertainty set is corrected conveniently to meet the condition of normal operation of the power system.
The correcting unit 40 is configured to correct the uncertainty set by using the power imbalance amount to obtain a corrected uncertainty set.
The control unit 50 is arranged to control the operation of the power system using the corrected set of uncertainties.
And correcting the uncertainty set by using the power unbalance to obtain a corrected uncertainty set, and eliminating factors generating high-risk events, so that the power system can operate without generating risks under the corrected uncertainty set.
According to the embodiment of the invention, the power unbalance amount of the distributed power supply is calculated by acquiring the historical data of the output of the distributed power supply in the power system, the uncertainty set is corrected by using the power unbalance amount to obtain the corrected uncertainty set, and the corrected uncertainty set is used for controlling the operation of the power system, so that the problem of low operation stability of the power system after the distributed power supply is connected into the power grid is solved, and the effect of improving the operation stability of the power system after the distributed power supply is connected into the power grid is achieved.
Preferably, the determination unit includes: the first determination module is used for determining the upper limit and the lower limit of the output of the distributed power supply according to historical data; the acquisition module is used for acquiring the preset confidence probability; the second determining module is used for determining the constraint condition of the distributed power supply output according to the upper limit and the lower limit of the distributed power supply output and the confidence probability; and a third determination module for determining an uncertainty set from the upper and lower limits of distributed power output and the constraint.
In particular, the upper limit of distributed power outputAnd lower limitMay be derived from historical data or predictions of distributed power generation output. Since distributed power sources are typically distributed relatively widely and far apart, their contribution is expected to be less likely to reach the upper or lower limit simultaneously during the same time period, taking into account spatial averaging. Furthermore, the output of all distributed power supplies in a specific period of time has the following spatial constraints:
wherein, M represents the number of distributed power sources,the output half-interval of the distributed power supply is shown,the average value of the output of the distributed power supply is shown,Srepresenting a space uncertainty budget.
Also, given the smoothness of time, it is unlikely that the output will reach either the upper or lower output limits at different times of the day for a particular distributed power source. Further, there is a time constraint on the output of the distributed power supply at different times of the day:
wherein,Trepresenting the time uncertainty budget and T representing the scheduling period.
In formulae (1) and (2):
in the formula (3)Is determined by the following formula
Wherein, αjtRepresenting the confidence probability, sigma, of the wind power output predicted by the distributed power supply j in the period ijtTo predict the standard deviation, a distribution of prediction errors is assumed to be known, where the i period is an arbitrary period. The intervals in which the distributed power supply output can be described by equations (3) and (4) are as follows:
in equations (1) and (2), the uncertain budget is selected from
Wherein, βj，βtRespectively, representing the confidence probability of the distributed power supply uncertainty budget over the spatial and temporal scales. Mu.ss，μh，σs，σhIs defined as follows
Definition of yjtThe following were used:
μjt，respectively represent yjtMean and variance of.
The confidence probability of the wind power output based on the uncertain space-time budget in the prediction interval range of the wind power plant can be obtained as follows:
and calculating the quantity of each parameter in the uncertainty set through the formula.
Preferably, the power unbalance amount includes a first power unbalance amount and a second power unbalance amount, and the correction unit includes: the correction module is used for correcting the uncertainty set by respectively correcting the upper limit and the lower limit of the distributed power supply output by using the power unbalance, wherein the upper limit and the lower limit of the distributed power supply output are corrected by the following formula:
wherein,andrespectively representing the upper limit and the lower limit of the corrected distributed power output,andrespectively representing the upper limit and the lower limit of the distributed power output before correction,a first amount of power imbalance is represented,representing a second amount of power imbalance.
Specifically, when a unit combination is formulated for a large-scale distributed power supply accessed power system, in order to deal with uncertainty of distributed power supply output, a method of formulating a preliminary scheme based on distributed power supply predicted output and then gradually increasing up for standby is generally adopted. And establishing a high-risk event prediction model, and correcting the uncertainty set based on the model. Specifically, taking an example of accessing a distributed power supply to a thermal power system, a description is given by way of example, and it is assumed that a unit combination scheme is determined. The high risk event prediction model is as follows:
wherein, the formula (11) is an objective function,andexpressing the relaxation variable in power balance, i.e. the amount of power imbalance, m, of equation (16)jtAnd njtIs a weight coefficient; the formula (12) is the maximum and minimum output constraint of the thermal power generating unit; formulas (13) and (14) are respectively positive and negative climbing constraints of the thermal power generating unit; equation (15) is the line flow constraint; equation 16 is the system power balance constraint, where in the above equation, N represents the number of thermal power units,the minimum output of the thermal power generating unit is shown,indicating the maximum output of the thermal power generating unit, DtIndicating load demand, FlIndicating the transmission capability of the line, piqlRepresenting the power transfer factor, pi, of the load lineilRepresenting the power transfer factor, pi, of a thermal power linejlRepresenting the distributed power line power transfer factor, pqtRepresenting loads transferred on the line, pjtRepresents distributed power output, pitThe thermal power output is represented by the power output of the thermal power,the positive climbing capacity of the thermal power generating unit is shown,shows the negative climbing capacity u of the thermal power generating unititAnd showing a unit combination scheme.
The following equation is obtained:
equation (17) represents the upper and lower bounds of the corrected distributed power output uncertainty set.
It is known thatα 'can be calculated from formulas (3) and (4)'jt、σ'jtAnd mu'jt(ii) a Further, due toTAndSconstant, β 'can be calculated from formulas (6) - (8)'jAnd β'tη 'can be calculated from formula (10)'jtWherein, α'jt、σ'jtAnd mu'jtIn turn, αjt、σjt、μjtCorrected amount, β'jAnd β'tRespectively represent βjAnd βtCorrected amount, η'jtAnd representing the confidence probability of the corrected wind power output in the prediction interval range of the wind power plant.
Preferably, the power system control device further includes: the control unit is used for controlling the operation of the power system by using the corrected uncertainty set when judging whether the corrected uncertainty set is in the preset risk range.
Because the risk probability of the power system can be adjusted as required, the conditions to be met by each parameter in the uncertainty set, namely the preset risk range, can be preset, and after the corrected uncertainty set is obtained, whether the uncertainty set is in the preset risk range can be judged, if yes, the requirement can be met, otherwise, the uncertainty set can be corrected again until the requirement is met.
According to the embodiment of the invention, whether the corrected uncertainty set meets the requirement can be verified by judging whether the corrected uncertainty set is in the preset risk range, so that the external risk of the power system caused by the fact that the corrected uncertainty set does not meet the requirement is avoided.
Preferably, the judging unit includes: and the judging module is used for judging whether the corrected uncertainty set is in a preset risk range by judging whether the load shedding amount of the distributed power supply under the corrected uncertainty set is in a preset load shedding amount range, wherein if the load shedding amount of the distributed power supply under the corrected uncertainty set is judged to be in the load shedding amount range, the corrected uncertainty set is determined to be in the preset risk range.
The load shedding amount, namely the power output of the distributed power supply, can be preset in the range of the load shedding amount in the power system, so that the power supply of the power system is prevented from being influenced. After the corrected uncertainty set is obtained, whether the load shedding amount of the uncertainty set is within an allowable range or not is judged under the model of the corrected uncertainty set, namely the load shedding amount range is judged, if yes, the correction is finished, and otherwise, the uncertainty set is corrected again.
Examples of correcting the uncertainty set are described in detail below in conjunction with fig. 2-8:
in this example, in the IEEE39 node standard example system including 1 distributed power source and 24 scheduling periods, as shown in fig. 2, 10 units G are included, where the node 39 is unit 1, the node 38 is unit 2, the node 37 is unit 3, and the node … … is unit 10. The load demand curve is shown in fig. 3, and the unit combination scheme is shown in table 1.
TABLE 1
In table 1, the starting and stopping states of 10 units in 24 hours are shown in sequence from top to bottom, where "1" indicates starting and "0" indicates stopping.
First, a confidence probability α is sett＝95％,βt90% and assuming that the prediction error satisfies the normal distribution, haveTThe distributed power output curve is obtained as shown in fig. 4, where 41 denotes the upper limit of the distributed power output, 43 denotes the lower limit of the distributed power output, and 42 denotes the predicted distributed power output, 8. The abscissa indicates the time period and the ordinate indicates the load of the distributed power supply.
Then, the data is brought into the high-risk event prediction model, and the output situation of the distributed power supply when the high-risk event occurs is obtained as shown by a curve 44 in fig. 5, and the load loss is 113.5 megawatt hours at this time.
If the loss-of-load rate is zero as the evaluation criterion, the uncertainty set of distributed power output is modified as shown by curve 45 in FIG. 6. at this time, the confidence probability η for each time intervaltAs shown in table 2.
Table 2:
further, if the uncertain set in the graph 6 is assessed by taking the air curtailment amount as a standard, the output situation of the distributed power supply when the high-risk event occurs is shown as a curve 46 in the graph 7, the maximum air curtailment amount is calculated to be 135.25 megawatts, the output uncertain set of the distributed power supply after correction is shown as a curve 47 in the graph 8, and the confidence probability η of each time period at this time is shown as a curve 47 in the graph 8tAs shown in table 3. And (4) verifying the uncertain set in the graph 8 by using a high-risk event prediction model, wherein the lost air volume is zero, and the evaluation standard is met.
TABLE 3
It should be noted that, for simplicity of description, the above-mentioned method embodiments are described as a series of acts or combination of acts, but those skilled in the art will recognize that the present invention is not limited by the order of acts, as some steps may occur in other orders or concurrently in accordance with the invention. Further, those skilled in the art should also appreciate that the embodiments described in the specification are preferred embodiments and that the acts and modules referred to are not necessarily required by the invention.
In the foregoing embodiments, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus may be implemented in other manners. For example, the above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units is only one type of division of logical functions, and there may be other divisions when actually implementing, for example, a plurality of units or components may be combined or may be integrated into another system, or some features may be omitted, or not implemented. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection of some interfaces, devices or units, and may be an electric or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a mobile terminal, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic or optical disk, and other various media capable of storing program codes.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. A power system control method, comprising:
acquiring historical data of output of a distributed power supply in a power system;
determining an uncertainty set of the distributed power supply according to the historical data, wherein the uncertainty set is used for reflecting an uncertainty range of the distributed power supply output;
calculating the power unbalance amount of the distributed power supply, wherein the power unbalance amount is used for reflecting the situation of the distributed power supply under the extreme output;
correcting the uncertainty set by using the power unbalance to obtain a corrected uncertainty set; and
controlling operation of the power system using the corrected set of uncertainties.
2. The power system control method of claim 1, wherein determining the set of uncertainties for the distributed power sources from the historical data comprises:
determining an upper limit and a lower limit of the distributed power output from the historical data;
acquiring a preset confidence probability;
determining a constraint condition of the distributed power supply output according to the upper limit and the lower limit of the distributed power supply output and the confidence probability; and
determining the set of uncertainties from the upper and lower limits of distributed power output and the constraints.
3. The power system control method of claim 2, wherein the amount of power imbalance comprises a first amount of power imbalance and a second amount of power imbalance, and wherein correcting the set of uncertainties using the amount of power imbalance comprises:
correcting the uncertainty set by correcting an upper limit and a lower limit of the distributed power output by using the power unbalance amount, respectively, wherein the upper limit and the lower limit of the distributed power output are corrected by the following formulas:
wherein,andrespectively representing the upper limit and the lower limit of the corrected output of the distributed power supply,andrespectively representing the upper limit and the lower limit of the distributed power output before correction,representing the amount of said first power imbalance,representing the second amount of power imbalance.
4. The power system control method according to claim 1, wherein the uncertainty set is corrected by using the power unbalance amount, and after obtaining a corrected uncertainty set, the power system control method further comprises:
determining whether the corrected uncertainty set is within a preset risk range,
and if the corrected uncertainty set is judged to be in the preset risk range, controlling the operation of the power system by using the corrected uncertainty set.
5. The power system control method of claim 4, wherein determining whether the revised set of uncertainties is within a preset risk range comprises:
determining whether the corrected uncertainty set is within a preset risk range by determining whether a load shedding amount of the distributed power supply under the corrected uncertainty set is within a preset load shedding amount range,
and if the load shedding amount of the distributed power supply is in the load shedding amount range under the corrected uncertainty set, determining that the corrected uncertainty set is in the preset risk range.
6. An electric power system control device characterized by comprising:
the acquisition unit is used for acquiring historical data of distributed power supply output in the power system;
the determining unit is used for determining an uncertainty set of the distributed power supply according to the historical data, wherein the uncertainty set is used for reflecting an uncertainty range of the output of the distributed power supply;
the calculating unit is used for calculating the power unbalance amount of the distributed power supply, and the power unbalance amount is used for reflecting the situation of the distributed power supply under the extreme output;
the correcting unit is used for correcting the uncertainty set by using the power unbalance amount to obtain a corrected uncertainty set; and
a control unit for controlling the operation of the power system using the corrected set of uncertainties.
7. The power system control device according to claim 6, wherein the determination unit includes:
a first determination module for determining an upper limit and a lower limit of the distributed power output from the historical data;
the acquisition module is used for acquiring the preset confidence probability;
the second determination module is used for determining the constraint conditions of the distributed power supply output according to the upper limit and the lower limit of the distributed power supply output and the confidence probability; and
a third determining module, configured to determine the uncertainty set according to the upper limit and the lower limit of the distributed power output and the constraint condition.
8. The power system control device according to claim 7, wherein the power unbalance amount includes a first power unbalance amount and a second power unbalance amount, and the correction unit includes:
a correction module, configured to correct the uncertainty set by respectively correcting an upper limit and a lower limit of the distributed power output by using the power imbalance, where the upper limit and the lower limit of the distributed power output are corrected by the following formulas:
wherein,andrespectively representing the upper limit and the lower limit of the corrected output of the distributed power supply,andrespectively representing the upper limit and the lower limit of the distributed power output before correction,representing the amount of said first power imbalance,representing the second amount of power imbalance.
9. The power system control device according to claim 6, characterized by further comprising:
a determining unit, configured to determine whether the corrected uncertainty set is within a preset risk range after correcting the uncertainty set by using the power imbalance to obtain a corrected uncertainty set,
and the control unit is further used for controlling the operation of the power system by using the corrected uncertainty set when the corrected uncertainty set is judged to be in the preset risk range.
10. The power system control device according to claim 9, wherein the determination unit includes:
a judging module, configured to judge whether the corrected uncertainty set is within a preset risk range by judging whether the load shedding amount of the distributed power supply under the corrected uncertainty set is within a preset load shedding amount range,
and if the load shedding amount of the distributed power supply is in the load shedding amount range under the corrected uncertainty set, determining that the corrected uncertainty set is in the preset risk range.
Priority Applications (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201410281490.7A CN105207247B (en) | 2014-06-20 | 2014-06-20 | Control method of electric power system and device |
| PCT/CN2014/093193 WO2015192613A1 (en) | 2014-06-20 | 2014-12-05 | Power system control method and device |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201410281490.7A CN105207247B (en) | 2014-06-20 | 2014-06-20 | Control method of electric power system and device |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN105207247A CN105207247A (en) | 2015-12-30 |
| CN105207247B true CN105207247B (en) | 2017-08-01 |
Family
ID=54934821
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201410281490.7A Active CN105207247B (en) | 2014-06-20 | 2014-06-20 | Control method of electric power system and device |
Country Status (2)
| Country | Link |
|---|---|
| CN (1) | CN105207247B (en) |
| WO (1) | WO2015192613A1 (en) |
Families Citing this family (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107292766B (en) * | 2017-06-26 | 2023-06-20 | 国网能源研究院有限公司 | Wind power consumption-oriented power system peak regulation means economical evaluation method and system |
| CN108599148B (en) * | 2018-04-26 | 2019-11-22 | 东南大学 | The Robust Scheduling method of meter and alternating current-direct current microgrid reply Disaster Event elasticity capacity |
| CN110224399B (en) * | 2019-06-12 | 2023-06-30 | 广东电网有限责任公司 | Electric power spot market clearing method and device based on wind power plant and storage medium |
| CN110611308B (en) * | 2019-08-30 | 2022-05-06 | 贵州电网有限责任公司 | Method for correcting and determining minimum active power of new energy station participating in direct electricity purchase of large users |
| CN111310121A (en) * | 2019-11-14 | 2020-06-19 | 中国电力科学研究院有限公司 | New energy output probability prediction method and system |
| CN110889650B (en) * | 2019-12-16 | 2022-11-08 | 国网青海省电力公司经济技术研究院 | Quantitative evaluation method and device for output stationarity of multi-element new energy power system |
| CN113078688B (en) * | 2021-04-06 | 2023-02-14 | 中国南方电网有限责任公司 | Day-ahead thermal power starting optimization method and system for preventing and controlling standby shortage risk |
| CN113394820B (en) * | 2021-07-14 | 2022-07-12 | 国网甘肃省电力公司电力科学研究院 | Optimized scheduling method for new energy grid-connected power system |
| CN113887989B (en) * | 2021-10-15 | 2024-01-16 | 中国南方电网有限责任公司超高压输电公司柳州局 | Power system reliability evaluation method, device, computer equipment and storage medium |
| CN114336637B (en) * | 2022-01-10 | 2023-04-07 | 合肥工业大学 | Power distribution network evidence theory power flow calculation method considering wind and light output correlation |
| CN115603319A (en) * | 2022-11-08 | 2023-01-13 | 国网湖南省电力有限公司（Cn） | Wind-solar output prediction method and prediction system for power system |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102214932A (en) * | 2011-06-09 | 2011-10-12 | 电子科技大学 | Method for distributing active power of wind-light storage transmission comprehensive power station |
| CN102684224A (en) * | 2012-05-25 | 2012-09-19 | 浙江大学 | Unit combination method for resolving and considering wind power volatility |
| CN103259285A (en) * | 2013-05-03 | 2013-08-21 | 国家电网公司 | Method for optimizing short running of electric power system comprising large-scale wind power |
Family Cites Families (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20130261817A1 (en) * | 2012-04-03 | 2013-10-03 | James Detmers | Producing and supplying stable power from renewable resources |
| CN104133995B (en) * | 2014-07-25 | 2017-02-22 | 国家电网公司 | Method for recognizing operation defects of electric power system in high-risk events |
-
2014
- 2014-06-20 CN CN201410281490.7A patent/CN105207247B/en active Active
- 2014-12-05 WO PCT/CN2014/093193 patent/WO2015192613A1/en active Application Filing
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102214932A (en) * | 2011-06-09 | 2011-10-12 | 电子科技大学 | Method for distributing active power of wind-light storage transmission comprehensive power station |
| CN102684224A (en) * | 2012-05-25 | 2012-09-19 | 浙江大学 | Unit combination method for resolving and considering wind power volatility |
| CN103259285A (en) * | 2013-05-03 | 2013-08-21 | 国家电网公司 | Method for optimizing short running of electric power system comprising large-scale wind power |
Non-Patent Citations (1)
| Title |
|---|
| 风电功率预测及微电网概率潮流分析;周松林;《中国博士学位论文全文数据库 工程科技Ⅱ辑》;20140415(第04期);C042-13 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN105207247A (en) | 2015-12-30 |
| WO2015192613A1 (en) | 2015-12-23 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN105207247B (en) | Control method of electric power system and device | |
| Hu et al. | Robust SCUC considering continuous/discrete uncertainties and quick-start units: A two-stage robust optimization with mixed-integer recourse | |
| Teng et al. | Stochastic scheduling with inertia-dependent fast frequency response requirements | |
| Wang et al. | Risk adjustable day-ahead unit commitment with wind power based on chance constrained goal programming | |
| Crăciun et al. | Frequency support functions in large PV power plants with active power reserves | |
| Antenucci et al. | Gas-constrained secure reserve allocation with large renewable penetration | |
| US10298056B2 (en) | Power control system, power control method, and recording medium | |
| Javadi et al. | Look ahead dynamic security-constrained economic dispatch considering frequency stability and smart loads | |
| He et al. | Optimising the balance between security and economy on a probabilistic basis | |
| US10615602B2 (en) | Power control system and method, and control device | |
| EP3360228A1 (en) | Power control system with power setpoint adjustment based on poi power limits | |
| US20170310140A1 (en) | System and method for reducing time-averaged peak charges | |
| SE540926C2 (en) | Converter station power set point analysis system and method | |
| JPWO2017150376A1 (en) | Power system | |
| CN111711184A (en) | Power system robust economic dispatching method based on worst scenario identification | |
| Li et al. | Risk-based distributionally robust real-time dispatch considering voltage security | |
| Zhang et al. | A multiobjective robust scheduling optimization mode for multienergy hybrid system integrated by wind power, solar photovoltaic power, and pumped storage power | |
| Banerjee et al. | Optimal scheduling with dynamic line ratings and intermittent wind power | |
| Cao et al. | Supply inadequacy risk evaluation of stand-alone renewable powered heat-electricity energy systems: a data-driven robust approach | |
| Hafiz et al. | Feasible operation region for dynamic economic dispatch and reserve monitoring | |
| JP5955581B2 (en) | Electric power supply and demand control device and electric power supply and demand control method | |
| Ross et al. | Estimating energy storage size for Nuclear-Renewable hybrid energy systems using data-driven stochastic emulators | |
| Xiao et al. | A multi‐energy complementary coordinated dispatch method for integrated system of wind‐photovoltaic‐hydro‐thermal‐energy storage | |
| Wen et al. | Optimal distributed energy storage investment scheme for distribution network accommodating high renewable penetration | |
| CN115842376A (en) | Method, device and medium for evaluating equivalent inertia trend and safety state of power system |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |