CN108647845A - A kind of power distribution network operation risk assessment method and apparatus containing distributed generation resource - Google Patents
A kind of power distribution network operation risk assessment method and apparatus containing distributed generation resource Download PDFInfo
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Abstract
The power distribution network operation risk assessment method and apparatus containing distributed generation resource that the present invention provides a kind of first calculating the probability of malfunction of the probability of malfunction of distribution line and distributed generation resource under different weather type and service life under different weather type；Then according to distribution line and the probability of malfunction of distributed generation resource, the operating status of power distribution network is emulated by the distributed generation resource output model built in advance；Finally the operation risk of power distribution network is assessed according to simulation result.The present invention considers distributed electrical Source Type, improves the operation risk assessment accuracy of power distribution network.The present invention calculates under different weather type and service life photovoltaic generating system, wind turbine and the respective probability of malfunction of gas turbine in distribution line and distributed generation resource, consider comprehensive, it can ensure the accuracy of power distribution network operation risk assessment with the probability of malfunction of accurate response distribution line and distributed generation resource.
Description
Technical field
The present invention relates to distributed generation resources to access optimisation technique, and in particular to a kind of distribution network operation containing distributed generation resource
Methods of risk assessment and device.
Background technology
It the features such as intermittence and uncontrollability that distributed generation resource generates electricity by way of merging two or more grid systems, is introduced to the safe operation etc. of power distribution network
New problem.Conventional electrical distribution net is single supply radial networks, under normal operational condition, is gradually dropped along feeder line direction of tide voltage
It is low.After distributed generation resource accesses, power supply is reduced to the transimission power of load direction on feeder line, and distribution line pressure drop reduces, from
And the raising of some node voltages or even variation may be caused exceeded, the on-position of variation and distributed generation resource connects
Enter capacity and power supply type is related.Access point is in feeder terminal, when distributed generation resource contributes larger, at this moment if distribution wire
Road is lightly loaded, and the voltage at distributed power access point will be raised obviously, then the voltage at the point will cross the upper limit.
In the radial distribution networks accessed without distributed generation resource, trend flows to each branch from higher level's power supply along feeder line and bears
The flow direction of lotus, trend is certain, and distribution line load is lighter.It is preferentially negative to periphery after large-scale distributed plant-grid connection
Lotus supplies electric energy, and power distribution network will be reduced with the trend at main network interface, and the trend of distribution line increases around distributed generation resource
Add.When power distribution network the whole network is in light load conditions and distributed generation resource contributes larger, larger dump power will be from distribution
The installation point of formula power supply flows to feeder line first section along feeder line, and trend is sent in formation.Distribution line or change are very likely resulted in when serious
Depressor overload, and easily cause the damage of transformer.
In the prior art about the operation risk assessment of power distribution network primarily focus on controller switching equipment in failure stoppage in transit probability and
Modeling in terms of failure effect severity, such as the risk assessment of distribution line, transformer, breaker and interconnection switch equipment refer to
Mark system.It is seldom about the operation risk assessment research containing distributed power distribution network, usually only using distributed generation resource as one
A GU Generic Unit considers, causes the operation risk assessment accuracy of power distribution network poor.
Invention content
Operation risk assessment accuracy in order to overcome the shortcomings of above-mentioned power distribution network in the prior art is poor, and the present invention provides one
Power distribution network operation risk assessment method and apparatus of the kind containing distributed generation resource, first calculate the event of distribution line under different weather type
Hinder the probability of malfunction of distributed generation resource under probability and different weather type and service life；Then according to distribution line and distribution
The probability of malfunction of formula power supply emulates the operating status of power distribution network by the distributed generation resource output model built in advance；
Finally the operation risk of power distribution network is assessed according to simulation result, it is contemplated that distributed electrical Source Type improves power distribution network
Operation risk assessment accuracy.
In order to achieve the above-mentioned object of the invention, the present invention adopts the following technical scheme that：
On the one hand, the present invention provides a kind of power distribution network operation risk assessment method containing distributed generation resource, including：
It calculates and is distributed under the probability of malfunction of distribution line and different weather type and service life under different weather type
The probability of malfunction of formula power supply；
According to the distribution line and the probability of malfunction of distributed generation resource, pass through the distributed generation resource output mould built in advance
Type emulates the operating status of power distribution network；
The operation risk of power distribution network is assessed according to simulation result.
Weather pattern includes normal weather and bad weather；
The probability of malfunction of distribution line is calculated as follows under different weather type：
Wherein, λLnIndicate the probability of malfunction of distribution line under normal weather, λLsIndicate the event of distribution line under bad weather
Hinder probability, λlIndicate that the mean failure rate probability of distribution line, r indicate that the ratio of bad weather number of days in setting time, R expressions are set
It fixes time the ratio of interior normal weather number of days, F indicates the probability that distribution line breaks down under bad weather.
The weather pattern includes normal weather and bad weather, and the service life includes running-in period and wear period, institute
The type for stating distributed generation resource includes one or more in photovoltaic generating system, wind turbine and gas turbine；
The probability of malfunction of photovoltaic generating system is calculated as follows under different weather type and service life：
Wherein, λPVn1Indicate the probability of malfunction of normal weather and running-in period photovoltaic generating system；λPVn2Indicate normal weather and
The probability of malfunction of wear period photovoltaic generating system；λPVs1Indicate the probability of malfunction of bad weather and running-in period photovoltaic generating system；
λPVs2Indicate the probability of malfunction of bad weather and wear period photovoltaic generating system；λpvIndicate that single photovoltaic is inverse in photovoltaic generating system
Become the probability of malfunction of device group；K indicates the quantity of photovoltaic DC-to-AC converter group in photovoltaic generating system；kRIIndicate running-in period failure rate system
Number, kWIndicate wear period failure coefficient, andK0Indicate impact factor most
Big value, tRIIndicate that the running-in period number of days of photovoltaic generating system, t indicate the work age of photovoltaic generating system, tWIndicate photovoltaic hair
The wear period number of days of electric system, tLIndicate that the service life of photovoltaic generating system, α indicate the coefficient of waste of photovoltaic generating system；R is indicated
The ratio of normal weather number of days in setting time, F indicate the probability that distribution line breaks down under bad weather；
The probability of malfunction of wind turbine is calculated as follows under different weather type and service life：
Wherein, λWn1Indicate the probability of malfunction of normal weather and running-in period wind turbine, λWn2Indicate normal weather and wear period wind
The probability of malfunction of machine, λWs1Indicate the probability of malfunction of bad weather and running-in period wind turbine, λWs2Indicate bad weather and wear period wind
The probability of malfunction of machine, λwIndicate the probability of malfunction of wind wheel, λgIndicate the probability of malfunction of generator, λeIndicate power electronics transverter
Probability of malfunction.
The probability of malfunction of gas turbine is calculated as follows under different weather type and service life：
λGTn1=kRIλgt
λGTn2=kWλgt
λGTs1=kRIλgt
λGTs1=kWλgt
Wherein, λGTn1Indicate the probability of malfunction of normal weather and running-in period gas turbine, λGTn2Indicate normal weather and abrasion
The probability of malfunction of phase gas turbine, λGTs1Indicate the probability of malfunction of bad weather and running-in period gas turbine, λGTs1Indicate severe day
The probability of malfunction of gas and wear period gas turbine, λgtIndicate the mean failure rate probability of gas turbine.
According to the distribution line and the probability of malfunction of distributed generation resource, pass through the distributed generation resource output mould built in advance
Type emulates the operating status of power distribution network, including：
Using Monte Carlo method to weather pattern, distribution line operating status, distributed generation resource operating status and distribution
Power supply output is sampled, and obtains sampling results；The distribution line operating status and distributed generation resource operating status include
Normal condition and malfunction；
According to the probability of malfunction of the distribution line and distributed generation resource, distribution line and distribution in sampling results are corrected
The probability of malfunction of power supply；The probability of malfunction of distribution line is according to the distribution line quantity in malfunction in the sampling results
It is determined with distribution line sum, the probability of malfunction of distributed generation resource is according to such point in malfunction in the sampling results
Cloth number of power sources is determined with such distributed generation resource sum；
According to the sampling results after probability of malfunction and the distributed generation resource output model that builds in advance is corrected, pass through power train
System simulation software emulates the operating status of power distribution network, obtains simulation result.
The distributed generation resource output model includes photovoltaic generating system output model, wind turbine output model and gas turbine
It is one or more in output model；
The photovoltaic generating system output model is built as the following formula：
PM=xA η
Wherein, PMIndicate that the output of photovoltaic generating system, A indicate the solar cell side being made of solar cell module
The area of battle array, η indicate that the photoelectric conversion efficiency of solar cell array, x indicate intensity of illumination；
The wind turbine output model is built as the following formula：
Wherein, v indicates wind speed, PW(v) output of wind turbine when wind speed is v, P are indicatedRIndicate the nominal output of wind turbine, vRTable
Show rated wind speed, vciIndicate incision wind speed, vcoIndicate cut-out wind speed；
The Gas Turbine Output model is built as the following formula：
Wherein, PGTIndicate the output of gas turbine；V indicates the output voltage of distributed generation resource invariable power model；VEIt indicates
The net terminal voltage of distributed generation resource invariable power model；X indicates the connection reactance between distributed generation resource and distrbution network；M is indicated
Controling parameter, δ indicate generator rotor angle.
The simulation result includes the power and bus nodes voltage of distribution line；
It is described that the operation risk of power distribution network is assessed according to simulation result, including：
The overload risk threshold value of power distribution network is determined according to the overload values of transmission line of electricity, and it is true according to distribution network voltage to get over limit value
Determine the voltage limit risk threshold value of power distribution network；
If the power of distribution line is less than the overload risk threshold value of power distribution network and bus nodes voltage is less than voltage out-of-limit wind
Dangerous threshold value, then there is no operation risks for power distribution network；Otherwise power distribution network is in operation risk.
The overload risk threshold value and voltage limit risk threshold value of power distribution network determine as the following formula respectively：
Wherein, RODIndicate the overload risk threshold value of power distribution network, RLVIndicate the voltage limit risk threshold value of power distribution network；SODl
(C/E) the overload severity of transmission line of electricity is indicated, andLODIndicate the overload values of transmission line of electricity, LOD=
L-0.8, L indicate that the electric current for flowing through distribution line accounts for the ratio of its rated current；SLVb(C/E) indicate that distribution network voltage is out-of-limit tight
Severe, andLLVIndicate that distribution network voltage gets over limit value, LLV=V-1.05, V indicate node voltage；I tables
Show that the malfunction number of distribution line, NF indicate that the malfunction sum of distribution line, l indicate overload distribution line number,
NFlIndicate that overload distribution line sum, b indicate the bus nodes number of voltage out-of-limit, NFbIndicate the bus nodes of voltage out-of-limit
Sum, p (i) indicate the probability of i-th of malfunction of distribution line.
On the other hand, the present invention provides a kind of power distribution network operation risk assessment device containing distributed generation resource, including：
Computing module, for calculating the probability of malfunction of distribution line and different weather type and fortune under different weather type
The probability of malfunction of distributed generation resource under the row service life；
Emulation module passes through point built in advance for the probability of malfunction according to the distribution line and distributed generation resource
Cloth power supply output model emulates the operating status of power distribution network；
Evaluation module, for being assessed the operation risk of power distribution network according to simulation result.
Weather pattern includes normal weather and bad weather；
The computing module includes：
First computing unit, the probability of malfunction for distribution line under different weather type to be calculated as follows：
Wherein, λLnIndicate the probability of malfunction of distribution line under normal weather, λLsIndicate the event of distribution line under bad weather
Hinder probability, λlIndicate that the mean failure rate probability of distribution line, r indicate that the ratio of bad weather number of days in setting time, R expressions are set
It fixes time the ratio of interior normal weather number of days, F indicates the probability that distribution line breaks down under bad weather.
The weather pattern includes normal weather and bad weather, and the service life includes running-in period and wear period；Institute
The type for stating distributed generation resource includes one or more in photovoltaic generating system, wind turbine and gas turbine；
The computing module includes：
Second computing unit, the failure for photovoltaic generating system under different weather type and service life to be calculated as follows
Probability：
Wherein, λPVn1Indicate the probability of malfunction of normal weather and running-in period photovoltaic generating system；λPVn2Indicate normal weather and
The probability of malfunction of wear period photovoltaic generating system；λPVs1Indicate the probability of malfunction of bad weather and running-in period photovoltaic generating system；
λPVs2Indicate the probability of malfunction of bad weather and wear period photovoltaic generating system；λpvIndicate that single photovoltaic is inverse in photovoltaic generating system
Become the probability of malfunction of device group；K indicates the quantity of photovoltaic DC-to-AC converter group in photovoltaic generating system；kRIIndicate running-in period failure rate system
Number, kWIndicate wear period failure coefficient, andK0Indicate impact factor most
Big value, tRIIndicate that the running-in period number of days of photovoltaic generating system, t indicate the work age of photovoltaic generating system, tWIndicate photovoltaic hair
The wear period number of days of electric system, tLIndicate that the service life of photovoltaic generating system, α indicate the coefficient of waste of photovoltaic generating system；R is indicated
The ratio of normal weather number of days in setting time, F indicate the probability that distribution line breaks down under bad weather；
Third computing unit, the probability of malfunction for wind turbine under different weather type and service life to be calculated as follows：
Wherein, λWn1Indicate the probability of malfunction of normal weather and running-in period wind turbine, λWn2Indicate normal weather and wear period wind
The probability of malfunction of machine, λWs1Indicate the probability of malfunction of bad weather and running-in period wind turbine, λWs2Indicate bad weather and wear period wind
The probability of malfunction of machine, λwIndicate the probability of malfunction of wind wheel, λgIndicate the probability of malfunction of generator, λeIndicate power electronics transverter
Probability of malfunction；
4th computing unit, the failure for gas turbine under different weather type and service life to be calculated as follows are general
Rate：
λGTn1=kRIλgt
λGTn2=kWλgt
λGTs1=kRIλgt
λGTs1=kWλgt
Wherein, λGTn1Indicate the probability of malfunction of normal weather and running-in period gas turbine, λGTn2Indicate normal weather and abrasion
The probability of malfunction of phase gas turbine, λGTs1Indicate the probability of malfunction of bad weather and running-in period gas turbine, λGTs1Indicate severe day
The probability of malfunction of gas and wear period gas turbine, λgtIndicate the mean failure rate probability of gas turbine.
Emulation module includes：
Sampling unit, for being run to weather pattern, distribution line operating status, distributed generation resource using Monte Carlo method
State and distributed generation resource output are sampled, and obtain sampling results；The distribution line operating status and distributed generation resource fortune
Row state includes normal condition and malfunction；
Amending unit is corrected and is matched in sampling results for the probability of malfunction according to the distribution line and distributed generation resource
The probability of malfunction of electric line and distributed generation resource；The probability of malfunction of distribution line is according in malfunction in the sampling results
Distribution line quantity and distribution line sum determine that the probability of malfunction of distributed generation resource is according in former in the sampling results
Such distributed generation resource quantity of barrier state is determined with such distributed generation resource sum；
Simulation unit, for according to correcting the sampling results after probability of malfunction and the distributed generation resource output mould that builds in advance
Type emulates the operating status of power distribution network by power system simulation software, obtains simulation result.
Emulation module includes：
Modeling unit, for establishing distributed generation resource output model, including photovoltaic generating system output model, wind turbine output
It is one or more in model and Gas Turbine Output model；
The photovoltaic generating system output model is built as the following formula：
PM=xA η
Wherein, PMIndicate that the output of photovoltaic generating system, A indicate the solar cell side being made of solar cell module
The area of battle array, η indicate that the photoelectric conversion efficiency of solar cell array, x indicate intensity of illumination；
The wind turbine output model is built as the following formula：
Wherein, v indicates wind speed, PW(v) output of wind turbine when wind speed is v, P are indicatedRIndicate the nominal output of wind turbine, vRTable
Show rated wind speed, vciIndicate incision wind speed, vcoIndicate cut-out wind speed；
The Gas Turbine Output model is built as the following formula：
Wherein, PGTIndicate the output of gas turbine；V indicates the output voltage of distributed generation resource invariable power model；VEIt indicates
The net terminal voltage of distributed generation resource invariable power model；X indicates the connection reactance between distributed generation resource and distrbution network；M is indicated
Controling parameter, δ indicate generator rotor angle.
The simulation result includes the power and bus nodes voltage of distribution line；
The evaluation module includes：
Determination unit, the overload risk threshold value for determining power distribution network according to the overload values of transmission line of electricity, and according to distribution
Net voltage out-of-limit value determines the voltage limit risk threshold value of power distribution network；
Assessment unit, if the power for distribution line is less than the overload risk threshold value of power distribution network and bus nodes voltage is small
In voltage limit risk threshold value, then there is no operation risks for power distribution network；Otherwise power distribution network is in operation risk.
The determination unit is specifically used for：
The overload risk threshold value and voltage limit risk threshold value of power distribution network are determined according to the following formula：
Wherein, RODIndicate the overload risk threshold value of power distribution network, RLVIndicate the voltage limit risk threshold value of power distribution network；SODl
(C/E) the overload severity of transmission line of electricity is indicated, andLODIndicate the overload values of transmission line of electricity, LOD=
L-0.8, L indicate that the electric current for flowing through distribution line accounts for the ratio of its rated current；SLVb(C/E) indicate that distribution network voltage is out-of-limit tight
Severe, andLLVIndicate that distribution network voltage gets over limit value, LLV=V-1.05, V indicate node voltage；I tables
Show that the malfunction number of distribution line, NF indicate that the malfunction sum of distribution line, l indicate overload distribution line number,
NFlIndicate that overload distribution line sum, b indicate the bus nodes number of voltage out-of-limit, NFbIndicate the bus nodes of voltage out-of-limit
Sum, p (i) indicate the probability of i-th of malfunction of distribution line.
Compared with the immediate prior art, technical solution provided by the invention has the advantages that：
In power distribution network operation risk assessment method provided by the invention containing distributed generation resource, different weather type is first calculated
The probability of malfunction of distributed generation resource under the probability of malfunction and different weather type and service life of lower distribution line；Then basis
The probability of malfunction of distribution line and distributed generation resource, the operation by the distributed generation resource output model that builds in advance to power distribution network
State is emulated；Finally the operation risk of power distribution network is assessed according to simulation result, the present invention has fully considered distribution
The service life of formula power supply type, weather pattern and distributed generation resource improves the operation risk assessment accuracy of power distribution network；
Power distribution network operation risk assessment device provided by the invention containing distributed generation resource includes computing module, emulation module
And evaluation module, computing module, for calculating the probability of malfunction of distribution line and different weather type under different weather type
With the probability of malfunction of distributed generation resource under service life；Emulation module is used for the probability of malfunction of distribution line and distributed generation resource,
The operating status of power distribution network is emulated by the distributed generation resource output model built in advance；Evaluation module is used for basis
Simulation result assesses the operation risk of power distribution network, the present invention fully considered distributed electrical Source Type, weather pattern with
And the service life of distributed generation resource, improve the operation risk assessment accuracy of power distribution network；
The present invention also determines the risk threshold value of power distribution network in terms of overloading with voltage out-of-limit two, particular by power distribution network
Overload severity determines the overload risk threshold value of power distribution network, and obtains voltage out-of-limit severity by power distribution network and determine power distribution network
Voltage limit risk threshold value, and the power of distribution line and bus nodes voltage that emulation is obtained respectively with the overload of power distribution network
Risk threshold value and voltage limit risk threshold value are compared, and ensure the accuracy of power distribution network operation risk assessment.
Description of the drawings
Fig. 1 is the power distribution network operation risk assessment method flow diagram containing distributed generation resource in the embodiment of the present invention 1；
Fig. 2 is IEEE33 node power distributions net schematic diagram in the embodiment of the present invention 2；
Fig. 3 is that distributed electrical source category overloads venture influence schematic diagram to distribution line in the embodiment of the present invention 2；
Fig. 4 be in the embodiment of the present invention 2 distributed electrical source category to the out-of-limit venture influence schematic diagram of distribution network voltage；
Fig. 5 is that the distribution of distributed generation resource capacity overloads venture influence schematic diagram to distribution line in the embodiment of the present invention 2；
Fig. 6 is that distributed generation resource capacity is distributed to the out-of-limit venture influence schematic diagram of distribution network voltage in the embodiment of the present invention 2.
Specific implementation mode
Invention is further described in detail below in conjunction with the accompanying drawings.
Embodiment 1
The embodiment of the present invention 1 provides a kind of power distribution network operation risk assessment method containing distributed generation resource, and flow chart is such as
Shown in Fig. 1, detailed process is as follows：
S101：Calculate different weather type under distribution line probability of malfunction and different weather type and service life under
The probability of malfunction of distributed generation resource；
S102：According to distribution line and the probability of malfunction of distributed generation resource, contributed by the distributed generation resource built in advance
Model emulates the operating status of power distribution network；
S103：The simulation result obtained according to S102 assesses the operation risk of power distribution network.
Weather pattern in above-mentioned S101 includes normal weather and bad weather, and service life includes running-in period and abrasion
The type of phase, distributed generation resource include one or more in photovoltaic generating system, wind turbine and gas turbine；
By calculating under different weather type and service life in distribution line and distributed generation resource in the embodiment of the present invention
Photovoltaic generating system, wind turbine and the respective probability of malfunction of gas turbine, consideration is comprehensive, can be with accurate response distribution line and distribution
The probability of malfunction of formula power supply ensures the accuracy of power distribution network operation risk assessment, is as follows：
The probability of malfunction of distribution line is calculated as follows under different weather type：
Wherein, λLnIndicate the probability of malfunction of distribution line under normal weather, λLsIndicate the event of distribution line under bad weather
Hinder probability, λlIndicate that the mean failure rate probability of distribution line, r indicate that the ratio of bad weather number of days in setting time, R expressions are set
It fixes time the ratio of interior normal weather number of days, F indicates the probability that distribution line breaks down under bad weather.
1) probability of malfunction of photovoltaic generating system is calculated as follows under different weather type and service life：
Wherein, λPVn1Indicate the probability of malfunction of normal weather and running-in period photovoltaic generating system；λPVn2Indicate normal weather and
The probability of malfunction of wear period photovoltaic generating system；λPVs1Indicate the probability of malfunction of bad weather and running-in period photovoltaic generating system；
λPVs2Indicate the probability of malfunction of bad weather and wear period photovoltaic generating system；λpvIndicate that single photovoltaic is inverse in photovoltaic generating system
Become the probability of malfunction of device group；K indicates the quantity of photovoltaic DC-to-AC converter group in photovoltaic generating system；kRIIndicate running-in period failure rate system
Number, kWIndicate wear period failure coefficient, andK0Indicate impact factor most
Big value, tRIIndicate that the running-in period number of days of photovoltaic generating system, t indicate the work age of photovoltaic generating system, tWIndicate photovoltaic hair
The wear period number of days of electric system, tLIndicate that the service life of photovoltaic generating system, α indicate the coefficient of waste of photovoltaic generating system.
2) probability of malfunction of wind turbine is calculated as follows under different weather type and service life：
Wherein, λWn1Indicate the probability of malfunction of normal weather and running-in period wind turbine, λWn2Indicate normal weather and wear period wind
The probability of malfunction of machine, λWs1Indicate the probability of malfunction of bad weather and running-in period wind turbine, λWs2Indicate bad weather and wear period wind
The probability of malfunction of machine, λwIndicate the probability of malfunction of wind wheel, λgIndicate the probability of malfunction of generator, λeIndicate power electronics transverter
Probability of malfunction.
3) probability of malfunction of gas turbine is calculated as follows under different weather type and service life：
λGTn1=kRIλgt
λGTn2=kWλgt
λGTs1=kRIλgt
λGTs1=kWλgt
Wherein, λGTn1Indicate the probability of malfunction of normal weather and running-in period gas turbine, λGTn2Indicate normal weather and abrasion
The probability of malfunction of phase gas turbine, λGTs1Indicate the probability of malfunction of bad weather and running-in period gas turbine, λGTs1Indicate severe day
The probability of malfunction of gas and wear period gas turbine, λgtIndicate the mean failure rate probability of gas turbine.
In above-mentioned S102, according to distribution line and the probability of malfunction of distributed generation resource, pass through the distributed electrical built in advance
Source output model emulates the operating status of power distribution network, and detailed process is as follows：
1) use Monte Carlo method to weather pattern, distribution line operating status, distributed generation resource operating status and distribution
Formula power supply output is sampled, and obtains sampling results；The distribution line operating status and distributed generation resource operating status are wrapped
Include normal condition and malfunction；
2) according to the probability of malfunction of the distribution line and distributed generation resource, distribution line and distribution in sampling results are corrected
The probability of malfunction of formula power supply；The probability of malfunction of distribution line is according to the distribution wire way in malfunction in the sampling results
Amount and distribution line sum determine, in the sampling results probability of malfunction of distributed generation resource according to be in malfunction such
Distributed generation resource quantity is determined with such distributed generation resource sum；
3) according to the sampling results after probability of malfunction and the distributed generation resource output model that builds in advance is corrected, pass through electric power
Softwares of System Simulation emulates the operating status of power distribution network, obtains simulation result.
Distributed generation resource output model includes photovoltaic generating system output model, wind turbine output model and combustion in above-mentioned S102
It is one or more in gas-turbine output model；
1) photovoltaic generating system output model is built as the following formula：
PM=xA η
Wherein, PMIndicate that the output of photovoltaic generating system, A indicate the solar cell side being made of solar cell module
The area of battle array, η indicate that the photoelectric conversion efficiency of solar cell array, x indicate intensity of illumination；
2) wind turbine output model is built as the following formula：
Wherein, v indicates wind speed, PW(v) output of wind turbine when wind speed is v, P are indicatedRIndicate the nominal output of wind turbine, vRTable
Show rated wind speed, vciIndicate incision wind speed, vcoIndicate cut-out wind speed；
3) Gas Turbine Output model is built as the following formula：
Wherein, PGTIndicate the output of gas turbine；V indicates the output voltage of distributed generation resource invariable power model；VEIt indicates
The net terminal voltage of distributed generation resource invariable power model；X indicates the connection reactance between distributed generation resource and distrbution network；M is indicated
Controling parameter, δ indicate generator rotor angle.
In above-mentioned S102, according to distribution line under different weather type and service life and the respective failure of distributed generation resource
Probability, sampling results and the distributed generation resource output model that builds in advance emulate the operating status of power distribution network, specifically
According to distribution line under different weather type and service life and the respective probability of malfunction of distributed generation resource, sampling results and in advance
The distributed generation resource output model of structure, and the operating status of power distribution network is emulated by power system simulation software, it obtains
To simulation result, simulation result includes the power and bus nodes voltage of distribution line.
In above-mentioned S103, simulation result includes the power and bus nodes voltage of distribution line, is gone back in the embodiment of the present invention
The risk threshold value of power distribution network, and the power and busbar for the distribution line that emulation is obtained are determined in terms of overloading with voltage out-of-limit two
Node voltage is compared with the overload risk threshold value of power distribution network and voltage limit risk threshold value respectively, to ensure distribution network operation
The accuracy of risk assessment, detailed process are as follows：
1) the overload risk threshold value of power distribution network is determined according to the overload values of transmission line of electricity, and limit value is got over according to distribution network voltage
Determine the voltage limit risk threshold value of power distribution network；
2) if the power of distribution line is less than the overload risk threshold value of power distribution network and bus nodes voltage is less than voltage out-of-limit
Risk threshold value, then there is no operation risks for power distribution network；Otherwise power distribution network is in operation risk.
It is above-mentioned 1) in, the overload risk threshold value and voltage limit risk threshold value of power distribution network determine as the following formula respectively：
Wherein, RODIndicate the overload risk threshold value of power distribution network, RLVIndicate the voltage limit risk threshold value of power distribution network；SODl
(C/E) the overload severity of transmission line of electricity is indicated, andLODIndicate the overload values of transmission line of electricity, LOD=
L-0.8, L indicate that the electric current for flowing through distribution line accounts for the ratio of its rated current；SLVb(C/E) indicate that distribution network voltage is out-of-limit tight
Severe, andLLVIndicate that distribution network voltage gets over limit value, LLV=V-1.05, V indicate node voltage；I tables
Show that the malfunction number of distribution line, NF indicate that the malfunction sum of distribution line, l indicate overload distribution line number,
NFlIndicate that overload distribution line sum, b indicate the bus nodes number of voltage out-of-limit, NFbIndicate the bus nodes of voltage out-of-limit
Sum, p (i) indicate the probability of i-th of malfunction of distribution line.
Based on the above-mentioned same inventive concept of power distribution network operation risk assessment method containing distributed generation resource, the present invention implement
Example 1 also provides a kind of power distribution network operation risk assessment device containing distributed generation resource, including computing module, emulation module and assessment
Module is separately below described in detail the function of this 3 modules：
Computing module therein, for calculating the probability of malfunction of distribution line and different weather class under different weather type
The probability of malfunction of distributed generation resource under type and service life；
Emulation module therein passes through what is built in advance for the probability of malfunction according to distribution line and distributed generation resource
Distributed generation resource output model emulates the operating status of power distribution network；
Evaluation module therein, for being assessed the operation risk of power distribution network according to simulation result.
Weather pattern includes normal weather and bad weather.
Above-mentioned computing module includes：
First computing unit, the probability of malfunction for distribution line under different weather type to be calculated as follows：
Wherein, λLnIndicate the probability of malfunction of distribution line under normal weather, λLsIndicate the event of distribution line under bad weather
Hinder probability, λlIndicate that the mean failure rate probability of distribution line, r indicate that the ratio of bad weather number of days in setting time, R expressions are set
It fixes time the ratio of interior normal weather number of days, F indicates the probability that distribution line breaks down under bad weather.
The type of above-mentioned distributed generation resource includes one or more in photovoltaic generating system, wind turbine and gas turbine；
Weather pattern includes normal weather and bad weather, and service life includes running-in period and wear period.
Above-mentioned computing module includes：
1) the second computing unit, the event for photovoltaic generating system under different weather type and service life to be calculated as follows
Hinder probability：
Wherein, λPVn1Indicate the probability of malfunction of normal weather and running-in period photovoltaic generating system；λPVn2Indicate normal weather and
The probability of malfunction of wear period photovoltaic generating system；λPVs1Indicate the probability of malfunction of bad weather and running-in period photovoltaic generating system；
λPVs2Indicate the probability of malfunction of bad weather and wear period photovoltaic generating system；λpvIndicate that single photovoltaic is inverse in photovoltaic generating system
Become the probability of malfunction of device group；K indicates the quantity of photovoltaic DC-to-AC converter group in photovoltaic generating system；kRIIndicate running-in period failure rate system
Number, kWIndicate wear period failure coefficient, andK0Indicate impact factor most
Big value, tRIIndicate that the running-in period number of days of photovoltaic generating system, t indicate the work age of photovoltaic generating system, tWIndicate photovoltaic hair
The wear period number of days of electric system, tLIndicate that the service life of photovoltaic generating system, α indicate the coefficient of waste of photovoltaic generating system.
2) third computing unit, the probability of malfunction for wind turbine under different weather type and service life to be calculated as follows：
Wherein, λWn1Indicate the probability of malfunction of normal weather and running-in period wind turbine, λWn2Indicate normal weather and wear period wind
The probability of malfunction of machine, λWs1Indicate the probability of malfunction of bad weather and running-in period wind turbine, λWs2Indicate bad weather and wear period wind
The probability of malfunction of machine, λwIndicate the probability of malfunction of wind wheel, λgIndicate the probability of malfunction of generator, λeIndicate power electronics transverter
Probability of malfunction.
3) the 4th computing unit, the failure for gas turbine under different weather type and service life to be calculated as follows are general
Rate：
λGTn1=kRIλgt
λGTn2=kWλgt
λGTs1=kRIλgt
λGTs1=kWλgt
Wherein, λGTn1Indicate the probability of malfunction of normal weather and running-in period gas turbine, λGTn2Indicate normal weather and abrasion
The probability of malfunction of phase gas turbine, λGTs1Indicate the probability of malfunction of bad weather and running-in period gas turbine, λGTs1Indicate severe day
The probability of malfunction of gas and wear period gas turbine, λgtIndicate the mean failure rate probability of gas turbine.
Above-mentioned emulation module includes：
Sampling unit, for being run to weather pattern, distribution line operating status, distributed generation resource using Monte Carlo method
State and distributed generation resource output are sampled, and obtain sampling results；The distribution line operating status and distributed generation resource fortune
Row state includes normal condition and malfunction；
Amending unit is corrected and is matched in sampling results for the probability of malfunction according to the distribution line and distributed generation resource
The probability of malfunction of electric line and distributed generation resource；The probability of malfunction of distribution line is according in malfunction in the sampling results
Distribution line quantity and distribution line sum determine that the probability of malfunction of distributed generation resource is according in former in the sampling results
Such distributed generation resource quantity of barrier state is determined with such distributed generation resource sum；
Simulation unit, for according to correcting the sampling results after probability of malfunction and the distributed generation resource output mould that builds in advance
Type emulates the operating status of power distribution network by power system simulation software, obtains simulation result.
Emulation module further includes modeling unit, and modeling unit is for establishing distributed generation resource output model, including photovoltaic hair
It is one or more in electric system output model, wind turbine output model and Gas Turbine Output model；
Photovoltaic generating system output model therein is built as the following formula：
PM=xA η
Wherein, PMIndicate that the output of photovoltaic generating system, A indicate the solar cell side being made of solar cell module
The area of battle array, η indicate that the photoelectric conversion efficiency of solar cell array, x indicate intensity of illumination；
Wind turbine output model therein is built as the following formula：
Wherein, v indicates wind speed, PW(v) output of wind turbine when wind speed is v, P are indicatedRIndicate the nominal output of wind turbine, vRTable
Show rated wind speed, vciIndicate incision wind speed, vcoIndicate cut-out wind speed；
Gas Turbine Output model therein is built as the following formula：
Wherein, PGTIndicate the output of gas turbine；V indicates the output voltage of distributed generation resource invariable power model；VEIt indicates
The net terminal voltage of distributed generation resource invariable power model；X indicates the connection reactance between distributed generation resource and distrbution network；M is indicated
Controling parameter, δ indicate generator rotor angle, adjust the size of distributed power source output power by controlling δ and m, and keep distributed generation resource
Output power is constant.
Simulation result includes the power and bus nodes voltage of distribution line, and above-mentioned evaluation module includes：
1) determination unit, the overload risk threshold value for determining power distribution network according to the overload values of transmission line of electricity, and according to
Power grid out-of-limit value determines the voltage limit risk threshold value of power distribution network；
2) assessment unit, if being less than the overload risk threshold value and bus nodes voltage of power distribution network for the power of distribution line
Less than voltage limit risk threshold value, then there is no operation risks for power distribution network；Otherwise power distribution network is in operation risk.
Determination unit determines the overload risk threshold value and voltage limit risk threshold value of power distribution network according to the following formula：
Wherein, RODIndicate the overload risk threshold value of power distribution network, RLVIndicate the voltage limit risk threshold value of power distribution network；SODl
(C/E) the overload severity of transmission line of electricity is indicated, andLODIndicate the overload values of transmission line of electricity, LOD=
L-0.8, L indicate that the electric current for flowing through distribution line accounts for the ratio of its rated current；SLVb(C/E) indicate that distribution network voltage is out-of-limit tight
Severe, andLLVIndicate that distribution network voltage gets over limit value, LLV=V-1.05, V indicate node voltage；I tables
Show that the malfunction number of distribution line, NF indicate that the malfunction sum of distribution line, l indicate overload distribution line number,
NFlIndicate that overload distribution line sum, b indicate the bus nodes number of voltage out-of-limit, NFbIndicate the bus nodes of voltage out-of-limit
Sum, p (i) indicate the probability of i-th of malfunction of distribution line.
Embodiment 2
The embodiment of the present invention 2 provides a kind of power distribution network operation risk assessment method containing distributed generation resource, is suitable for dividing
The high scene of cloth power supply permeability, is specifically divided into following two situations：
(1) being directed to different distributions formula power supply type influences power distribution network power supply safety：
Different type distributed generation resource is accessed to individual node, in IEEE33 node power distribution nets as shown in Figure 2, DG1,
DG2, DG3 indicate distributed generation resource, and 3 Fans, 3 photo-voltaic power supplies, 3 micro-gas-turbines are respectively connected in 7,17,30 nodes
Machine.The ratio of each distributed generation resource nominal output is respectively 2：5：3.Probe into permeability be respectively 0.15,0.25,0.35,0.45,
When 0.6, influence of the distributed generation resource to power distribution network obtains distributed electrical source category as shown in Figure 3 and overloads wind to distribution line
Danger influences schematic diagram and distributed electrical source category as shown in Figure 4 to the out-of-limit venture influence schematic diagram of distribution network voltage.
(2) a variety of lower capacity of distributed generation resource mixing access are distributed the influence to power distribution network：
In IEEE33 node power distribution nets as shown in Figure 2, accesses 1 typhoon power generator in 7 nodes, accesses 1 in 17 nodes
Platform photo-voltaic power supply accesses a miniature gas turbine in 30 nodes, probe into permeability be respectively 0.15,0.25,0.35,0.45,
When 0.6, influence of the distributed generation resource to system obtains distributed generation resource capacity distribution as shown in Figure 5 and is overloaded to distribution line
Venture influence schematic diagram and distributed generation resource capacity shown in fig. 6 distribution are to the out-of-limit venture influence schematic diagram of distribution network voltage.
For convenience of description, each section of apparatus described above is divided into various modules with function or unit describes respectively.
Certainly, each module or the function of unit can be realized in same or multiple softwares or hardware when implementing the application.
It should be understood by those skilled in the art that, embodiments herein can be provided as method, system or computer program
Product.Therefore, complete hardware embodiment, complete software embodiment or reality combining software and hardware aspects can be used in the application
Apply the form of example.Moreover, the application can be used in one or more wherein include computer usable program code computer
The computer program production implemented in usable storage medium (including but not limited to magnetic disk storage, CD-ROM, optical memory etc.)
The form of product.
The application is with reference to method, the flow of equipment (system) and computer program product according to the embodiment of the present application
Figure and/or block diagram describe.It should be understood that can be realized by computer program instructions every first-class in flowchart and/or the block diagram
The combination of flow and/or box in journey and/or box and flowchart and/or the block diagram.These computer programs can be provided
Instruct the processor of all-purpose computer, special purpose computer, Embedded Processor or other programmable data processing devices to produce
A raw machine so that the instruction executed by computer or the processor of other programmable data processing devices is generated for real
The device for the function of being specified in present one flow of flow chart or one box of multiple flows and/or block diagram or multiple boxes.
These computer program instructions, which may also be stored in, can guide computer or other programmable data processing devices with spy
Determine in the computer-readable memory that mode works so that instruction generation stored in the computer readable memory includes referring to
Enable the manufacture of device, the command device realize in one flow of flow chart or multiple flows and/or one box of block diagram or
The function of being specified in multiple boxes.
These computer program instructions also can be loaded onto a computer or other programmable data processing device so that count
Series of operation steps are executed on calculation machine or other programmable devices to generate computer implemented processing, in computer or
The instruction executed on other programmable devices is provided for realizing in one flow of flow chart or multiple flows and/or block diagram one
The step of function of being specified in a box or multiple boxes.
Finally it should be noted that：The above embodiments are merely illustrative of the technical scheme of the present invention and are not intended to be limiting thereof, institute
The those of ordinary skill in category field with reference to above-described embodiment still can to the present invention specific implementation mode modify or
Equivalent replacement, these are applying for this pending hair without departing from any modification of spirit and scope of the invention or equivalent replacement
Within bright claims.
Claims (14)
1. a kind of power distribution network operation risk assessment method containing distributed generation resource, which is characterized in that including：
Calculate different weather type under distribution line probability of malfunction and different weather type and service life under distributed electrical
The probability of malfunction in source；
According to the distribution line and the probability of malfunction of distributed generation resource, pass through the distributed generation resource output model pair built in advance
The operating status of power distribution network is emulated；
The operation risk of power distribution network is assessed according to simulation result.
2. the power distribution network operation risk assessment method according to claim 1 containing distributed generation resource, which is characterized in that described
Weather pattern includes normal weather and bad weather；
The probability of malfunction of distribution line is calculated as follows under different weather type：
Wherein, λLnIndicate the probability of malfunction of distribution line under normal weather, λLsIndicate that the failure of distribution line under bad weather is general
Rate, λlIndicate the mean failure rate probability of distribution line, r indicates the ratio of bad weather number of days in setting time, when R indicates setting
The ratio of interior normal weather number of days, F indicate the probability that distribution line breaks down under bad weather.
3. the power distribution network operation risk assessment method according to claim 1 containing distributed generation resource, which is characterized in that described
The type of distributed generation resource includes photovoltaic generating system；
Probability of malfunction is calculated as follows under different weather type and service life：
Wherein, λPVn1Indicate the probability of malfunction of normal weather and running-in period photovoltaic generating system；λPVn2Indicate normal weather and abrasion
The probability of malfunction of phase photovoltaic generating system；λPVs1Indicate the probability of malfunction of bad weather and running-in period photovoltaic generating system；λPVs2Table
Show the probability of malfunction of bad weather and wear period photovoltaic generating system；λpvIndicate single photovoltaic DC-to-AC converter group in photovoltaic generating system
Probability of malfunction；K indicates the quantity of photovoltaic DC-to-AC converter group in photovoltaic generating system；kRIIndicate running-in period failure rate coefficient, kWTable
Show wear period failure coefficient, andK0Indicate the maximum value of impact factor, tRI
Indicate that the running-in period number of days of photovoltaic generating system, t indicate the work age of photovoltaic generating system, tWIndicate photovoltaic generating system
Wear period number of days, tLIndicate that the service life of photovoltaic generating system, α indicate the coefficient of waste of photovoltaic generating system；R indicates setting time
The ratio of interior normal weather number of days, F indicate the probability that distribution line breaks down under bad weather；
The type of the distributed generation resource includes wind turbine, and probability of malfunction is calculated as follows under different weather type and service life：
Wherein, λWn1Indicate the probability of malfunction of normal weather and running-in period wind turbine, λWn2Indicate normal weather and wear period wind turbine
Probability of malfunction, λWs1Indicate the probability of malfunction of bad weather and running-in period wind turbine, λWs2Indicate bad weather and wear period wind turbine
Probability of malfunction, λwIndicate the probability of malfunction of wind wheel, λgIndicate the probability of malfunction of generator, λeIndicate the event of power electronics transverter
Hinder probability；
The probability of malfunction of gas turbine is calculated as follows under different weather type and service life：
λGTn1=kRIλgt
λGTn2=kWλgt
λGTs1=kRIλgt
λGTs1=kWλgt
Wherein, λGTn1Indicate the probability of malfunction of normal weather and running-in period gas turbine, λGTn2Indicate normal weather and wear period combustion
The probability of malfunction of gas-turbine, λGTs1Indicate the probability of malfunction of bad weather and running-in period gas turbine, λGTs1Indicate bad weather and
The probability of malfunction of wear period gas turbine, λgtIndicate the mean failure rate probability of gas turbine.
4. the power distribution network operation risk assessment method according to claim 1 containing distributed generation resource, which is characterized in that according to
The probability of malfunction of the distribution line and distributed generation resource, by the distributed generation resource output model that builds in advance to power distribution network
Operating status is emulated, including：
Using Monte Carlo method to weather pattern, distribution line operating status, distributed generation resource operating status and distributed generation resource
Output is sampled, and obtains sampling results；The distribution line operating status and distributed generation resource operating status include normal
State and malfunction；
According to the probability of malfunction of the distribution line and distributed generation resource, distribution line and distributed generation resource in sampling results are corrected
Probability of malfunction；The probability of malfunction of distribution line according to the distribution line quantity for being in malfunction and is matched in the sampling results
Electric line sum determines that the probability of malfunction of distributed generation resource is according to such distribution in malfunction in the sampling results
Number of power sources is determined with such distributed generation resource sum；
According to the sampling results after probability of malfunction and the distributed generation resource output model that builds in advance is corrected, imitated by electric system
True software emulates the operating status of power distribution network, obtains simulation result.
5. the power distribution network operation risk assessment method according to claim 1 or 4 containing distributed generation resource, which is characterized in that
The distributed generation resource output model includes photovoltaic generating system output model, wind turbine output model and Gas Turbine Output model
In it is one or more；
The photovoltaic generating system output model is built as the following formula：
PM=xA η
Wherein, PMIndicate that the output of photovoltaic generating system, A indicate the solar cell array being made of solar cell module
Area, η indicate that the photoelectric conversion efficiency of solar cell array, x indicate intensity of illumination；
The wind turbine output model is built as the following formula：
Wherein, v indicates wind speed, PW(v) output of wind turbine when wind speed is v, P are indicatedRIndicate the nominal output of wind turbine, vRExpression volume
Determine wind speed, vciIndicate incision wind speed, vcoIndicate cut-out wind speed；
The Gas Turbine Output model is built as the following formula：
Wherein, PGTIndicate the output of gas turbine；V indicates the output voltage of distributed generation resource invariable power model；VEIndicate distribution
The net terminal voltage of formula power supply invariable power model；X indicates the connection reactance between distributed generation resource and distrbution network；M indicates control
Parameter, δ indicate generator rotor angle.
6. the power distribution network operation risk assessment method according to claim 1 containing distributed generation resource, which is characterized in that described
Simulation result includes the power and bus nodes voltage of distribution line；
It is described that the operation risk of power distribution network is assessed according to simulation result, including：
The overload risk threshold value of power distribution network is determined according to the overload values of transmission line of electricity, and limit value determination is got over according to distribution network voltage and is matched
The voltage limit risk threshold value of power grid；
If the power of distribution line is less than the overload risk threshold value of power distribution network and bus nodes voltage is less than voltage limit risk threshold
Value, then there is no operation risks for power distribution network；Otherwise there are operation risks for power distribution network.
7. the power distribution network operation risk assessment method according to claim 6 containing distributed generation resource, which is characterized in that described
The overload risk threshold value and voltage limit risk threshold value of power distribution network determine as the following formula respectively：
Wherein, RODIndicate the overload risk threshold value of power distribution network, RLVIndicate the voltage limit risk threshold value of power distribution network；SODl(C/E) table
Show the overload severity of transmission line of electricity, andLODIndicate the overload values of transmission line of electricity, LOD=L-0.8, L
Indicate that the electric current for flowing through distribution line accounts for the ratio of its rated current；SLVb(C/E) the out-of-limit severity of distribution network voltage is indicated, andLLVIndicate that distribution network voltage gets over limit value, LLV=V-1.05, V indicate node voltage；I indicates distribution wire
The malfunction on road is numbered, and NF indicates that the malfunction sum of distribution line, l indicate overload distribution line number, NFlIt indicated
Distribution line sum is carried, b indicates the bus nodes number of voltage out-of-limit, NFbIndicate the bus nodes sum of voltage out-of-limit, p (i)
Indicate the probability of i-th of malfunction of distribution line.
8. a kind of power distribution network operation risk assessment device containing distributed generation resource, which is characterized in that including：
Computing module, for calculating the probability of malfunction of distribution line and different weather type and operation longevity under different weather type
The probability of malfunction of the lower distributed generation resource of life；
Emulation module passes through the distribution built in advance for the probability of malfunction according to the distribution line and distributed generation resource
Power supply output model emulates the operating status of power distribution network；
Evaluation module, for being assessed the operation risk of power distribution network according to simulation result.
9. the power distribution network operation risk assessment device according to claim 8 containing distributed generation resource, which is characterized in that described
Weather pattern includes normal weather and bad weather；
The computing module includes：
First computing unit, the probability of malfunction for distribution line under different weather type to be calculated as follows：
Wherein, λLnIndicate the probability of malfunction of distribution line under normal weather, λLsIndicate that the failure of distribution line under bad weather is general
Rate, λlIndicate the mean failure rate probability of distribution line, r indicates the ratio of bad weather number of days in setting time, when R indicates setting
The ratio of interior normal weather number of days, F indicate the probability that distribution line breaks down under bad weather.
10. the power distribution network operation risk assessment device according to claim 8 containing distributed generation resource, which is characterized in that institute
It includes normal weather and bad weather to state weather pattern, and the service life includes running-in period and wear period, the distributed electrical
The type in source includes one or more in photovoltaic generating system, wind turbine and gas turbine；
The computing module includes：
Second computing unit, the failure for photovoltaic generating system under different weather type and service life to be calculated as follows are general
Rate：
Wherein, λPVn1Indicate the probability of malfunction of normal weather and running-in period photovoltaic generating system；λPVn2Indicate normal weather and abrasion
The probability of malfunction of phase photovoltaic generating system；λPVs1Indicate the probability of malfunction of bad weather and running-in period photovoltaic generating system；λPVs2Table
Show the probability of malfunction of bad weather and wear period photovoltaic generating system；λpvIndicate single photovoltaic DC-to-AC converter group in photovoltaic generating system
Probability of malfunction；K indicates the quantity of photovoltaic DC-to-AC converter group in photovoltaic generating system；kRIIndicate running-in period failure rate coefficient, kWTable
Show wear period failure coefficient, andK0Indicate the maximum value of impact factor, tRI
Indicate that the running-in period number of days of photovoltaic generating system, t indicate the work age of photovoltaic generating system, tWIndicate photovoltaic generating system
Wear period number of days, tLIndicate that the service life of photovoltaic generating system, α indicate the coefficient of waste of photovoltaic generating system；R indicates setting time
The ratio of interior normal weather number of days, F indicate the probability that distribution line breaks down under bad weather；
Third computing unit, the probability of malfunction for wind turbine under different weather type and service life to be calculated as follows：
Wherein, λWn1Indicate the probability of malfunction of normal weather and running-in period wind turbine, λWn2Indicate normal weather and wear period wind turbine
Probability of malfunction, λWs1Indicate the probability of malfunction of bad weather and running-in period wind turbine, λWs2Indicate bad weather and wear period wind turbine
Probability of malfunction, λwIndicate the probability of malfunction of wind wheel, λgIndicate the probability of malfunction of generator, λeIndicate the event of power electronics transverter
Hinder probability；
The computing module includes：
4th computing unit, the probability of malfunction for gas turbine under different weather type and service life to be calculated as follows：
λGTn1=kRIλgt
λGTn2=kWλgt
λGTs1=kRIλgt
λGTs1=kWλgt
Wherein, λGTn1Indicate the probability of malfunction of normal weather and running-in period gas turbine, λGTn2Indicate normal weather and wear period combustion
The probability of malfunction of gas-turbine, λGTs1Indicate the probability of malfunction of bad weather and running-in period gas turbine, λGTs1Indicate bad weather and
The probability of malfunction of wear period gas turbine, λgtIndicate the mean failure rate probability of gas turbine.
11. the power distribution network operation risk assessment device according to claim 8 containing distributed generation resource, which is characterized in that institute
Stating emulation module includes：
Sampling unit, for using Monte Carlo method to weather pattern, distribution line operating status, distributed generation resource operating status
It is sampled with distributed generation resource output, obtains sampling results；The distribution line operating status and distributed generation resource run shape
State includes normal condition and malfunction；
Amending unit corrects distribution wire in sampling results for the probability of malfunction according to the distribution line and distributed generation resource
The probability of malfunction on road and distributed generation resource；The probability of malfunction of distribution line is according to matching in malfunction in the sampling results
Electric line quantity and distribution line sum determine that the probability of malfunction of distributed generation resource is according in failure shape in the sampling results
Such distributed generation resource quantity of state is determined with such distributed generation resource sum；
Simulation unit, for according to correcting the sampling results after probability of malfunction and the distributed generation resource output model that builds in advance,
The operating status of power distribution network is emulated by power system simulation software, obtains simulation result.
12. the power distribution network operation risk assessment device containing distributed generation resource according to claim 8 or 11, feature exist
In the emulation module includes：
Modeling unit, for establishing distributed generation resource output model, including photovoltaic generating system output model, wind turbine output model
With it is one or more in Gas Turbine Output model；
The photovoltaic generating system output model is built as the following formula：
PM=xA η
Wherein, PMIndicate that the output of photovoltaic generating system, A indicate the solar cell array being made of solar cell module
Area, η indicate that the photoelectric conversion efficiency of solar cell array, x indicate intensity of illumination；
The wind turbine output model is built as the following formula：
Wherein, v indicates wind speed, PW(v) output of wind turbine when wind speed is v, P are indicatedRIndicate the nominal output of wind turbine, vRExpression volume
Determine wind speed, vciIndicate incision wind speed, vcoIndicate cut-out wind speed；
The Gas Turbine Output model is built as the following formula：
Wherein, PGTIndicate the output of gas turbine；V indicates the output voltage of distributed generation resource invariable power model；VEIndicate distribution
The net terminal voltage of formula power supply invariable power model；X indicates the connection reactance between distributed generation resource and distrbution network；M indicates control
Parameter, δ indicate generator rotor angle.
13. the power distribution network operation risk assessment device according to claim 8 containing distributed generation resource, which is characterized in that institute
State the power and bus nodes voltage that simulation result includes distribution line；
The evaluation module includes：
Determination unit, the overload risk threshold value for determining power distribution network according to the overload values of transmission line of electricity, and according to power distribution network electricity
Pressure gets over the voltage limit risk threshold value that limit value determines power distribution network；
Assessment unit, if the power for distribution line is less than the overload risk threshold value of power distribution network and bus nodes voltage is less than electricity
Out-of-limit risk threshold value is pressed, then operation risk is not present in power distribution network；Otherwise there are operation risks for power distribution network.
14. the power distribution network operation risk assessment device according to claim 13 containing distributed generation resource, which is characterized in that institute
Determination unit is stated to be specifically used for：
The overload risk threshold value and voltage limit risk threshold value of power distribution network are determined according to the following formula：
Wherein, RODIndicate the overload risk threshold value of power distribution network, RLVIndicate the voltage limit risk threshold value of power distribution network；SODl(C/E) table
Show the overload severity of transmission line of electricity, andLODIndicate the overload values of transmission line of electricity, LOD=L-0.8, L
Indicate that the electric current for flowing through distribution line accounts for the ratio of its rated current；SLVb(C/E) the out-of-limit severity of distribution network voltage is indicated, andLLVIndicate that distribution network voltage gets over limit value, LLV=V-1.05, V indicate node voltage；I indicates distribution wire
The malfunction on road is numbered, and NF indicates that the malfunction sum of distribution line, l indicate overload distribution line number, NFlIt indicated
Distribution line sum is carried, b indicates the bus nodes number of voltage out-of-limit, NFbIndicate the bus nodes sum of voltage out-of-limit, p (i)
Indicate the probability of i-th of malfunction of distribution line.
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| CN116780529A (en) * | 2023-06-30 | 2023-09-19 | 国网北京市电力公司 | Power distribution network fault recovery method, device, equipment and medium |
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| CN103279807A (en) * | 2013-05-06 | 2013-09-04 | 国家电网公司 | Static risk assessment method for power grid in severe weather |
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| CN112671045A (en) * | 2019-12-24 | 2021-04-16 | 国网新疆电力有限公司伊犁供电公司 | Distributed power supply optimal configuration method based on improved genetic algorithm |
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