CN115714459A - Online early warning method and device for transient state power angle stability of wind power system - Google Patents
Online early warning method and device for transient state power angle stability of wind power system Download PDFInfo
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Abstract
The invention discloses an online early warning method and device for transient state power angle stability of a wind power system, belonging to the technical field of stability analysis of a power system, wherein the method comprises the following steps: when the system is switched to a stable operation state along with a starting mode and the like, firstly, off-line simulation is carried out on each expected fault to obtain key information. And secondly, calculating electromagnetic power curves before, during and after the wind power system fault, and further calculating the critical equivalent inertia of the system under an expected fault set. And finally, calculating a transient critical inertia index according to the equivalent inertia and the critical equivalent inertia of the current running state of the system, and early warning the instability risk of the system. The invention can avoid the defect of insufficient rapidity of a large amount of simulation of a complex system, provides practical early warning indexes for measuring the current safety state of the system for operators to refer to when the system is not in fault, and can adopt regulation and control means in advance to avoid transient state power angle instability caused by the fault, thereby improving the safety of the power system and having strong engineering practicability.
Description
Technical Field
The invention belongs to the technical field of power system stability analysis, and particularly relates to an online early warning method and device for transient power angle stability of a wind power system.
Background
Transient power angle stability is one of the important issues for safety and stability of power systems. Under the drive of a double-carbon target, the permeability of new energy represented by wind power is rapidly increased, the inertia characteristics of a power grid are changed, and complexity is injected for the problem of transient power angle stability. Meanwhile, large-scale power failure accidents caused by system step loss occur frequently, and the loss is serious. When the system is in fault, the time for judging the stability of the system and taking stability control measures is urgent, and the measures such as a relay protection device and the like have the action refusing risk.
In recent years, a Wide Area Monitoring System (WAMS) is widely equipped in an actual power grid, and the power grid operation information is rapidly acquired in real time. In addition, an inertia online monitoring system is built in 2019 in the northwest power grid, and a data basis is provided for transient power angle stability online judgment. At present, the transient power angle stability online judging method of the system mainly comprises the following steps: time domain simulation, response trajectory, artificial intelligence, direct, etc. Due to the fact that the network structure of the new energy system is complex, the rapidity of the time domain simulation method cannot meet requirements, and quantitative safety margin is difficult to achieve through a response track and an artificial intelligence method. The direct method comprises an Extended Equal Area Criterion (EEAC) and a transient energy function, and has the characteristic of good quantization effect. However, the existing transient power angle online determination method uses the system information after the fault, and needs to be implemented some time after the fault occurs. In addition, the main applicable object of the transient stability judging method is still the conventional system.
The existing research on the transient state power angle stability of the wind power system mainly aims at the qualitative analysis of the transient state power angle stability after the wind power is connected, and a practical index quantitative evaluation method is not provided. In summary, the existing online transient stability judgment of the wind power system has the defects of insufficient consideration and lack of practicability quantization indexes depending on system data after faults and transient characteristics of the wind power plant.
Disclosure of Invention
Aiming at the defects or improvement requirements in the prior art, the invention provides an online early warning method and device for transient state power angle stability of a wind power system, and aims to calculate a transient state critical inertia index by using the current equivalent inertia and the critical equivalent inertia before the wind power system fails; by means of the risk of transient power angle instability of the quantitative early warning system, the technical problem that dependence on system data after faults and transient characteristics of a wind power plant are not considered fully in online transient stability judgment of the wind power system is solved.
In order to achieve the above object, according to an aspect of the present invention, an online early warning method for transient power angle stability of a wind power system based on critical inertia is provided, wherein when a transition to a new stable state is made, the following steps are performed:
and a data updating stage: s1: updating an online data set and an expected fault set acquired by a power grid wide area monitoring system to obtain inertia information;
an off-line simulation stage: s2: performing off-line simulation on each expected fault in the expected fault set by using the inertia information; the off-line simulation relates to the instability of an attack angle, so that unit groups, fan transient response curves and fan end voltage information during the faults under the expected faults are obtained;
and a critical inertia calculation stage: s3: calculating corresponding current equivalent inertia under each expected fault by using the inertia information and the unit grouping result; s4: calculating electromagnetic power curves before, continuously neutralizing and eliminating the wind power system fault by using the unit groups, the fan transient response curve and fan terminal voltage information during the fault to obtain a system equivalent limit cut-off angle, and further calculating the critical equivalent inertia of the system under an expected fault set; s5: calculating a transient critical inertia index by using the current equivalent inertia and the critical equivalent inertia;
a risk early warning stage: s6: and early warning the transient power angle instability risk of the system according to the transient critical inertia index.
In one embodiment, the expression of the current equivalent inertia in S3 is:
wherein H OMIB Equivalent inertia of a single infinite system, S B Is a reference capacity, S sys Is the equivalent capacity of the transient power angle stability of the system under a grouping.
In one embodiment, the S sys The expression of (a) is:
wherein S is Ni 、S Nj The rated capacities of the ith generator of the leading group S and the jth generator of the lagging group A are respectively set.
In one embodiment, the S4 includes:
calculating an electromagnetic power curve containing the wind power system before fault, the wind power system continues to be in a middle state and after the fault is eliminated through a power system stability analysis and control EEAC theory considering the characteristics of the wind power plant;
calculating the equivalent limit cut-off angle of the system by adopting a piecewise approximate linear method, and further calculating the critical equivalent inertia H of the system under the expected fault set sysmin 。
In one embodiment, the S5 includes:
the transient critical inertia index TCiI is calculated by the following formula:
in one embodiment, the updating the online data set in the data phase includes: the inertia of each unit, the terminal voltage and current phasor of each synchronous unit acquired by the PMU, the currently running system admittance matrix and the input power of each unit.
In one embodiment, the S6 includes:
when the transient critical inertia index TCiI is less than 0, namely the current equivalent inertia of the system is less than the critical equivalent inertia, the power angle difference in the acceleration stage exceeds a limit cut-off angle, and the transient power angle of the system is unstable;
when the transient critical inertia index TCiI is greater than 0, the current equivalent inertia of the system is greater than the critical equivalent inertia, the power angle difference in the acceleration stage is smaller than the limit cutting angle, and the transient power angle of the system is stable;
wherein, the smaller TCiI is, the weaker transient power angle stability of the system is.
According to another aspect of the present invention, an online early warning device for transient power angle stability of a wind power system based on critical inertia is provided, which is configured to execute the online early warning method for transient power angle stability of a wind power system based on critical inertia when a transition is made to a new stable state, and includes:
the updating data module is used for updating an online data set and an expected fault set acquired by the power grid wide area monitoring system to obtain inertia information;
the offline simulation module is used for performing offline simulation on each expected fault in the expected fault set by using the inertia information; the off-line simulation relates to the instability of an attack angle, so that unit groups, a transient response curve of the wind turbine and wind turbine terminal voltage information during the fault under each expected fault are obtained;
the critical inertia calculation module is used for calculating corresponding current equivalent inertia under each expected fault by using the inertia information and the unit grouping result; calculating electromagnetic power curves before, after continuous neutralization and clearing of the wind power system fault by using the unit groups, the fan transient response curves and fan end voltage information during the fault to obtain a system equivalent limit cut-off angle, and further calculating the critical equivalent inertia of the system under an expected fault set; calculating a transient critical inertia index by using the current equivalent inertia and the critical equivalent inertia;
and the risk early warning module is used for early warning the transient power angle instability risk of the system according to the transient critical inertia index.
According to another aspect of the invention, an electronic device is provided, comprising a memory storing a computer program and a processor implementing the steps of the method when executing the computer program.
According to another aspect of the invention, a computer-readable storage medium is provided, on which a computer program is stored which, when being executed by a processor, carries out the steps of the method.
In general, compared with the prior art, the above technical solution contemplated by the present invention can achieve the following beneficial effects:
1. the method fully considers the equivalent external characteristics of multiple stages of the wind power plant fault, and combines a WAMS system and a small amount of simulation to obtain key data information. Meanwhile, the invention takes the system inertia level as the basis, provides practical inertia indexes and quantitatively warns the risk of transient power angle instability of the system, thereby providing important reference basis for operators to know the system stability level and take safety and stability measures in time.
2. The invention innovatively integrates the transient power angle instability risk early warning method with online rolling updating, starts from the change of a running time at fixed intervals or a system to a new stable state due to a starting mode and the like, and fully combines and utilizes the real-time running data of the system from the application of an actual system, thereby enabling the analysis result to be more practical and being applicable to engineering practice.
3. The invention simplifies the complex and unsolvable nonlinear stage into a multi-stage uniform acceleration process by utilizing a piecewise equivalent theory, and adopts an iteration method to fully link the initial value and the final value of the piecewise process, thereby greatly reducing the complexity of analysis and calculation.
4. The influence of multiple stages of the wind power plant before, during and after the fault on the transient power angle stability of the system is comprehensively considered; reasonably classifying and assuming, and specially discussing special problems; the accurate early warning range of the method is quantitatively obtained, so that the analysis has pertinence and high reliability and accuracy.
Drawings
Fig. 1 is a flowchart of an online early warning method for transient power angle stability of a wind power system based on critical inertia according to an embodiment of the present invention;
fig. 2 is a grid diagram of a system in which a wind farm is connected to four machines and two areas according to an embodiment of the present invention;
fig. 3a is a graph of power angle swing of each unit corresponding to a fault clearing time of 0.50s according to an embodiment of the present invention; fig. 3b is a graph of power angle swing of each unit corresponding to a fault clearing time of 0.51s according to an embodiment of the present invention;
fig. 4 is a diagram of transient power output of the doubly-fed wind turbine according to an embodiment of the present invention;
FIG. 5 is an equivalent diagram of an acceleration stage segment according to an embodiment of the present invention;
fig. 6a is a graph illustrating an equivalent power angle characteristic under a critical stability condition corresponding to a barrier removal time of 0.50s according to an embodiment of the present invention;
fig. 6b is a graph of the equivalent power angle characteristic under the critical stability with the barrier clearing time of 0.51s according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention. In addition, the technical features involved in the respective embodiments of the present invention described below may be combined with each other as long as they do not conflict with each other.
Referring to fig. 1, the online early warning method for transient state power angle stability of a wind power system based on critical inertia, provided by the invention, comprises the following steps when the operation changes to a new stable state at every fixed interval or in a system startup mode and the like:
s1, updating input data of online data information acquired by a WAMS (wireless local area network system) and an expected fault set established according to research and experience;
in particular, it is envisaged that the type of fault is selected as the most severe three-phase metallic short circuit and the fault location is selected at the tie-line lead, i.e. the tie-lines 8-9 near the bus bar 8 node. The fault time is 1s, and one of the double-circuit lines 8-9 is cut off after the expected fault lasts for a period of time, namely a fault clearing stage. The fault clearing time here illustrates the accuracy of the invention in the case of a critical stability situation of 0.50s and 0.51s, respectively.
S2, performing off-line simulation for each expected fault for 3-5 seconds, setting longer fault clearing time, wherein power angle instability needs to occur in the simulation, and obtaining unit groups, a transient response curve of the fan and fan terminal voltage information during the fault under the expected fault;
specifically, according to the expected failure, the following information is determined by performing off-line simulation for 3 seconds at first: (1) The leading group under the fault is synchronous generators G1 and G2, and the lagging group is G3 and G4, refer to fig. 3a and 3b; (2) The wind power plant terminal voltage at the initial stage of the fault duration is 0.49p.u., so that the wind turbine is converted into constant impedance by a constant power source during calculation at the stage; (3) The wind power plant transient response characteristics in three stages of before fault, in continuation and after fault clearing are obtained through a formula by fitting a function to the output power of the wind power plant after fault clearing
Middle undetermined coefficient k Δ1 ＝1.033、k Δ2 ＝13.78。
S3, calculating the current equivalent inertia of the operating system under different expected faults by using the inertia information in the S1 and the clustering result obtained in the S2;
specifically, the equivalent capacity of the transient power angle stability of the system under the grouping is calculated:
calculating the current equivalent capacity S of the system sys Is 900MVA. Reference capacity S B The current equivalent inertia of the system is further calculated for 100 MVA:
calculating the current equivalent inertia H of the system sys Calculated from the clustering case was 6.346s.
S4, calculating an electromagnetic power curve containing the wind power system before, during and after the fault is eliminated by using the information obtained in the S1, and solving an equivalent limit cut-off angle of the system so as to calculate the critical equivalent inertia of the system under an expected fault set;
specifically, each equivalent electromagnetic power in each section of the acceleration process is constant by adopting section equivalence, namely each section is in uniform acceleration motion, and the section time and the section end rotating speed are solved section by section, as shown in fig. 5. Calculating t if the transient fluctuation characteristic of the wind power plant is not considered through a formula c =0.50s, critical inertia H of the system sysmin 5.546s; t is t c H when =0.51s sysmin It was 5.768s. Taking into account the transient fluctuation characteristic of the wind farm, t c Critical inertia H of system at 0.50s sysmin Is 6.334s; t is t c H when =0.51s sysmin Was 6.588s.
S5, calculating a transient critical inertia index TCiI by using the current equivalent inertia calculated in the S3 and the critical equivalent inertia calculated in the S4, and calculating the transient critical inertia index TCiI of the system for different expected faults sys Is the minimum value of each TCiI;
in particular, by formula
And calculating the transient critical inertia index TCiI of the system. If the transient fluctuation characteristic of the wind power plant is not considered, t c TCiI is 0.126 when =0.50 s; t is t c When =0.51s, TCiI is 0.091. Taking into account the transient fluctuation characteristic of the wind farm, t c TCiI is 0.002 when =0.50 s; t is t c TCiI is-0.038 when =0.51 s.
S6, early warning the risk of transient power angle instability of the system according to the transient critical inertia index TCiI of S5;
specifically, when the TCiI is less than 0, the current equivalent inertia of the system is less than the critical equivalent inertia, the power angle difference in the acceleration stage exceeds the limit cut-off angle, and the transient power angle of the system is unstable; when TCiI is greater than 0, the current equivalent inertia of the system is larger than the critical equivalent inertia, the power angle difference in the acceleration stage is smaller than the limit cutting angle, and the transient power angle of the system is stable. Smaller TCiI indicates weaker transient power angle stability of the system. The multi-level safety early warning risk with stable transient power angle of the power system is divided into 4 levels, as shown in table 1.
TABLE 1 transient state power angle stability early warning risk division
| Transient critical inertia index | State of system inertia | Destabilization risk partitioning |
| TCiI>C2 | High inertia | Low risk |
| C1<TCiI ≤ C2 | Middle inertia | |
| 0<TCiI ≤ C1 | Low inertia | |
| TCiI | ||
| ≤ 0 | Ultra low inertia | Ultra high risk |
Risk partition threshold coefficient C of system 1 、C 2 Take 0.10 and 0.40, respectively. If the transient fluctuation characteristic of the wind power plant is not considered, t c If =0.50s, the system is judged to be stable and in a medium risk state; t is t c And =0.51s, the system is determined to be stable and in a high risk state. Taking into account the transient fluctuation characteristic of the wind farm, t c If =0.50s, the system is judged to be stable and in a high risk state; t is t c If it is not less than 0.51s, the system is judged to be unstable and is in a state of excessA high risk state.
As shown in fig. 2, the test system is a double-fed wind power plant access four-machine two-area system, the synchronous generator adopts a three-order model, the DFIG model comprises machine side and grid side converter control, the machine side converter adopts MPPT control, the double-fed wind power plant adopts multiple single DFIG aggregation equivalents with the rated power of 2MW, and the load adopts a constant impedance model. The bus 6 is connected into a double-fed wind power plant with the rated power of 300MW, the DFIG adopts a five-order model, the DFIG and the synchronous generator G2 are connected into the node 5 together, the load power is 1700MW, and the wind power permeability is 17.65%.
Under the preset fault, when the fault clearing time is 0.50s, the power angles of the synchronous units are initially swung and separated to a certain extent, and then gradually approach, so that the transient power angle of the system is stable, as shown in fig. 3a; when the fault clearing time is 0.51s, the power angles of the synchronous units gradually approach separation, and the transient power angle of the system is unstable, as shown in fig. 3b. The transient response characteristics of the wind power plant in the three stages of before fault, in the middle of duration and after clearing are shown in FIG. 4.
As shown in FIG. 5, P eIII And P' eIII Respectively calculating curves P for electromagnetic power theory without considering and considering transient fluctuation characteristics of wind power plant in fault clearing stage e Is an electromagnetic power actual curve, area A 3 The reduced deceleration area is the transient fluctuation characteristic of the wind power plant. According to the actual electromagnetic power curve, when the clearing time is 0.50s, the system is stable; at the clearing time of 0.51s, the system is unstable; through the early warning steps, the condition that instability and missing judgment exist in the transient fluctuation characteristic of the wind power plant is not considered, the wind power plant characteristic is fully considered, and the early warning method is accurate in judgment. FIG. 6a is a graph of the equivalent power angle characteristic under critical stability when the failure clear time is 0.50 s; fig. 6b is a graph of the equivalent power angle characteristic at critical stability for a failure clearing time of 0.51 s.
The reliability of the method provided by the invention is further verified, the rated power outputs of the wind power plant are respectively adjusted to be 100MW, 300MW and 600MW by changing the number of the accessed DFIGs, and the wind power permeabilities of the corresponding systems are respectively 5.88%, 17.65% and 35.29%. And (4) judging the stability of the transient power angle under different wind power permeabilities, wherein the judgment result is shown in a table 2.
TABLE 2 stability early warning results under different wind power permeabilities
According to the results, if the transient fluctuation characteristics of the wind power plant are not considered, the system has the condition of missing judgment under different permeabilities, the critical inertia judgment method provided by the invention can accurately pre-judge the system stability condition, quantize the transient power angle stability safety margin according to the system inertia, and define the system safety risk. In addition, according to analysis of test results, as the permeability of the wind power plant accessed by the transmission end of the interconnected system is continuously increased, the influence on the transient stability of the system is not monotonous.
The invention relates to an online early warning method for transient state power angle stability of a wind power system based on critical inertia, which does not need to judge after an actual fault occurs. Aiming at the problem of transient power angle stability, the output power of the wind power plant has fluctuation characteristics in a short period after the fault is cleared, and the transient power angle stability is analyzed and judged to be non-negligible. The equivalent inertia of the system has a close relation with the transient power angle stability, and the test of the system of an example shows that the quantitative index of the transient critical inertia index has higher stability judgment accuracy. The method is based on expected faults and a WAMS system, has the characteristics of instantaneity, prejudgment and indexing, and provides system safety indexes for regulating and controlling personnel. The method combines data and models, and has wide prospect in the aspect of practical large-scale power grid application.
It will be understood by those skilled in the art that the foregoing is only an exemplary embodiment of the present invention, and is not intended to limit the invention to the particular forms disclosed, since various modifications, substitutions and improvements within the spirit and scope of the invention are possible and within the scope of the appended claims.
Claims (10)
1. An online early warning method for transient power angle stability of a wind power system based on critical inertia is characterized in that when the transient power angle stability changes to a new stable state, the following steps are executed:
and a data updating stage: s1: updating an online data set and an expected fault set acquired by a power grid wide area monitoring system to obtain inertia information;
an off-line simulation stage: s2: performing off-line simulation on each expected fault in the expected fault set by using the inertia information; the off-line simulation relates to the instability of an attack angle, so that unit groups, a transient response curve of the wind turbine and wind turbine terminal voltage information during the fault under each expected fault are obtained;
and a critical inertia calculation stage: s3: calculating corresponding current equivalent inertia under each expected fault by using the inertia information and the unit grouping result; s4: calculating electromagnetic power curves before, continuously neutralizing and eliminating the wind power system fault by using the unit groups, the fan transient response curve and fan terminal voltage information during the fault to obtain a system equivalent limit cut-off angle, and further calculating the critical equivalent inertia of the system under an expected fault set; s5: calculating a transient critical inertia index by using the current equivalent inertia and the critical equivalent inertia;
a risk early warning stage: s6: and early warning the transient power angle instability risk of the system according to the transient critical inertia index.
2. The critical inertia-based wind power system transient state power angle stability online early warning method according to claim 1, wherein the expression of the current equivalent inertia in S3 is as follows:
wherein H OMIB Equivalent inertia of a single infinite system, S B Is a reference capacity, S sys Is the equivalent capacity of the transient power angle stability of the system under a grouping.
3. The critical inertia-based wind power system-containing transient power angle stability online early warning method according to claim 2,s is sys The expression of (a) is:
wherein S is Ni 、S Nj Rated capacities of the ith power generator of the leading group S and the jth power generator of the lagging group A are respectively set.
4. The critical inertia-based online early warning method for transient power angle stability of a wind power system according to claim 2, wherein the S4 comprises:
calculating an electromagnetic power curve containing the wind power system before fault, the wind power system continues to be in a middle state and after the fault is eliminated through a power system stability analysis and control EEAC theory considering the characteristics of the wind power plant;
calculating the equivalent limit cut-off angle of the system by adopting a piecewise approximate linear method, and further calculating the critical equivalent inertia H of the system under the expected fault set sysmin 。
5. The critical inertia-based wind power system transient state power angle stability online early warning method according to claim 4, wherein the S5 comprises:
the transient critical inertia index TCiI is calculated by the following formula:
6. the critical inertia-based online early warning method for transient power angle stability of wind power systems according to claim 1, wherein the updating of the online data set in the data phase comprises: the system comprises the inertia of each unit, the voltage and current phasor at the generator end of each synchronous unit acquired by a PMU, a currently running system admittance matrix and the input power of each unit.
7. The critical inertia-based online early warning method for transient state power angle stability of a wind power system according to any one of claims 1 to 6, wherein S6 comprises:
when the transient critical inertia index TCiI is less than 0, namely the current equivalent inertia of the system is less than the critical equivalent inertia, the power angle difference in the acceleration stage exceeds a limit cut-off angle, and the transient power angle of the system is unstable;
when the transient critical inertia index TCiI is greater than 0, the current equivalent inertia of the system is greater than the critical equivalent inertia, the power angle difference in the acceleration stage is smaller than the limit cutting angle, and the transient power angle of the system is stable;
wherein, the smaller the TCiI, the weaker the transient power angle stability of the system.
8. An online early warning device for transient state power angle stability of a wind power system based on critical inertia, which is used for executing the online early warning method for transient state power angle stability of a wind power system based on critical inertia according to any one of claims 1 to 7 when changing to a new stable state, and comprises:
the updating data module is used for updating an online data set and an expected fault set acquired by the power grid wide area monitoring system to obtain inertia information;
the offline simulation module is used for performing offline simulation on each expected fault in the expected fault set by using the inertia information; the off-line simulation relates to the instability of an attack angle, so that unit groups, a transient response curve of the wind turbine and wind turbine terminal voltage information during the fault under each expected fault are obtained;
the critical inertia calculation module is used for calculating corresponding current equivalent inertia under each expected fault by using the inertia information and the unit grouping result; calculating electromagnetic power curves before, continuously neutralizing and eliminating the wind power system fault by using the unit groups, the fan transient response curve and fan terminal voltage information during the fault to obtain a system equivalent limit cut-off angle, and further calculating the critical equivalent inertia of the system under an expected fault set; calculating a transient critical inertia index by using the current equivalent inertia and the critical equivalent inertia;
and the risk early warning module is used for early warning the transient power angle instability risk of the system according to the transient critical inertia index.
9. An electronic device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor realizes the steps of the method of any one of claims 1 to 7 when executing the computer program.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 7.
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