CN110472371A - A kind of appraisal procedure of the power system component different degree based on restoring force - Google Patents
A kind of appraisal procedure of the power system component different degree based on restoring force Download PDFInfo
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Abstract
The invention discloses a kind of power system component different degree appraisal procedures based on restoring force: 1) determining the property of the type and generation of disaster；2) fallible component type and relevant probability of malfunction under disaster are obtained；3) the fault configuration situation of element in system after disaster occurs is obtained using non-sequential Monte Carlo simulation；4) optimal recovery policy model after calamity is established, proposes objective function and constraint condition；5) recovery process after calamity repeatedly simulate and obtain each element reparation moment and be ranked up using the ranking method of Aaron Copland, to obtain component importance sequence.Electric system can be sought in all kinds of natural calamities and the component importance under man-made disaster using the method for the invention, finding process has taken into account Disasters Type and feature.It can provide to refer to for the determination of element Scheme of Strengthening before the formulation and calamity of recovery policy after calamity using the component importance result that this method obtains and build.
Description
Technical field
The invention belongs to power system security planning operation fields, and in particular to a kind of electric system member based on restoring force
The appraisal procedure of part different degree.
Background technique
Keeping high power supply reliability is requirement one of of the people for modern power systems.In recent years, climate change adds
Play, extreme natural calamity occurrence frequency are continuously increased, and are caused severe jamming to the normal operation of electric system, are caused to have a power failure on a large scale
Frequent Accidents.Power system recovery power can be understood as electric system and precisely predict the disaster that can suffer from disturbance, come in disaster
It can restore rapidly after mitigating system equipment and load loss, disaster before facing with a variety of effective measures are taken in Hazard processes
The ability of normal condition before to failure, the natural calamity increasingly to take place frequently, network attack and artificial attack just threaten electric system
Reliability service, promote restoring force and have become the inevitable requirement of power system development.
It is assessed by component importance, can identify key element and network structure necessary to maintaining system resilience,
And then determine risk level and the contribution to system totality restoring force locating for each element of system.It is built to reinforce grid structure
If, improve recovery policy, improve the efficiency of resource allocation of preventing and reducing natural disasters, the power system component weight based on restoring force need be carried out
Spend assessment.
However the prior art not correlative study about component importance assessment.
Summary of the invention
In order to solve the problems existing in the prior art, the purpose of the present invention is to provide a kind of electric system based on restoring force
The appraisal procedure of component importance.This method can provide the importance sorting of element in system, according to ranking results, extreme
Event element reparation sequence bigger to restoring force of sening as an envoy to after occurring, can provide the reinforcing of element between extreme event generation
Scheme, enhancing power grid elasticity.
To achieve the above object, the invention adopts the following technical scheme:
A kind of appraisal procedure of the power system component different degree based on restoring force, comprising the following steps:
Determine the type of electric system disaster and the property of generation；
Obtain fallible component type and relevant probability of malfunction under corresponding Disasters Type；
It is sampled using non-sequential Monte Carlo simulation and obtains the fault configuration situation of element in system after disaster occurs；
Optimal recovery policy model after disaster is established, proposes objective function and constraint condition；
To recovery process after disaster carry out repeatedly simulation obtain each element repair the moment and using the ranking method of Aaron Copland into
Row sequence, to obtain component importance sequence.
As a further improvement of the present invention, make that the event of fallible component should be obtained for long-term disaster
Barrier rate λ and probability of malfunction p；Under storm environment, the failure rate of element is
The probability of malfunction of element is
Wherein,
W (t) is t moment wind speed；α is scale coefficient；λwind(w (t)) is the failure rate of t moment element；λnormBe positive reason
The failure rate of element under condition；wcritWind speed when being begun to ramp up for failure rate；pijFor the probability of malfunction of element ij；TyFor with failure
The rate unit matched time.
As a further improvement of the present invention, make to obtain using non-sequential Monte Carlo simulation first in system after disaster occurs
The fault configuration situation of part specifically:
It for the state for obtaining each element, is sampled using non-sequential Monte Carlo simulation, non-sequential Monte Carlo simulation is taken out
The process of sample are as follows:
Obtain the random number rand of [0,1] space uniform distributioni, pijFor probability of malfunction, route is obtained after extreme disaster
Operating status s when the process of repairing startsij(0):
Wherein, it 1 indicates to work normally, 0 indicates failure.
As a further improvement of the present invention, making the component importance sequence is the element by determining recovery process
Reparation sequence is come so that the restoring force of recovery process is maximum, and carries out component importance sequence according to this recovery sequence.
As a further improvement of the present invention, make to establish optimal recovery policy model after calamity, propose objective function and constraint
Condition are as follows:
Restoring force is defined as in recovery process to the cumulant of recovery system performance accounting, system performance are defined as load
The sum of the power flow that node is an actually-received, objective function are as follows:
In formula, fj(t) power flow that load bus j is actually received is indicated；VDIndicate the set of load bus；F(td) indicate
The minimum value of system performance after experience extreme event；Indicate the power flow that load bus j is received under normal circumstances；T table
Show that entire reparation duration, whole process are considered to be a time discrete process；
State constraint condition are as follows:
In formula, sij(t) state of the representation element ij in moment t；E is the set of element；The set of E ' representing fault element；
Constraining (5) indicates that element represents working properly, 0 representation element damage there are two types of state, 1；After constraint (6) indicates that element is fixed
It will not damage again；Constraint (7) indicates that fault element is damage in t=0；
Power-balance constraint condition are as follows:
In formula, fij(t) power flow of element ij is flowed through for moment t；ViFor the set with node connected node；VSFor power generation
The set of machine node；VTFor the set of transmission node；VDFor the set of load bus；Pi SFor the maximum generating watt of generator；
For the transmission capacity of element ij；Constraint (8), (9) and (10) is respectively the power of generator node, transmission node and load bus
Constraints of Equilibrium；The power flow that constraint (11) expression load bus is an actually-received is no more than power needed for the load bus
Stream；Constraint (12) indicates that the power flow flowed on element receives the influence of element state；
Traveling time constraint condition are as follows:
In formula, xm,nIt indicates whether maintenance personal from element m is moved to element n, if it is being equal to 1, is otherwise equal to 0；
At the time of indicating that maintenance personal reaches element m；Indicate that maintenance personal repairs the time required for element m；Indicate maintenance people
Member is moved to the time spent by element n from element m；fm,tIndicate element m whether fixed in moment t, if it is be equal to 1, it is no
Then it is equal to 0；Constraint (13) and (14) indicate that maintenance personal can only go fault element 1 time, can only also leave primary；Constrain (15) benefit
Make the route of maintenance personal continuous with large M；Constraining (16) indicates that at the beginning of recovery process, maintenance personal is repairing
Center；Constraint (17) indicates that element can only be fixed at a time, and can only be fixed primary；Constraining (18) indicatesWith
fm,tRelationship；Constraint (19) is for coupling fm,tWith element state sm(t)。
As a further improvement of the present invention, make for each extreme disaster, all can with non-sequential monte carlo method into
The reparation moment of each element can be obtained to obtain a MLIP problem in the sampling of row failure after solution MLIP problem.
As a further improvement of the present invention, make MILP problem such as following formula:
G (x, s (t))=0
h(x,s(t))≥0
Wherein, parameter interpretation is as follows:
T is the repair process time；
fj(t) power flow actually received for load bus j；
The power flow received under normal circumstances for load bus j；
F(td) be meet with extreme event after system performance minimum value；
VDFor the set of load bus；
G (x, s (t))=0 is equality constraint；
H (x, s (t)) >=0 is inequality constraints；
X is system variable, such as power.
Above-mentioned objective function and constraint one MILP problem of composition, you can get it after solution in order to keep entire recovery process extensive
The reparation moment of the multiple maximum each element of power.
As a further improvement of the present invention, ranking method is obtained using Aaron Copland to be ranked up according to the following formula:
Wherein, parameter interpretation is as follows:
Sm,n,k-1For the Aaron Copland moral score of element m after -1 comparison of kth；
Sm,n,kFor the Aaron Copland moral score of element m after kth time comparison；
qk(m) the kth position percentage for being element m；
E' is fault element set.
By comparing each element Aaron Copland score to get arrive component importance ranking results.
Compared with prior art, the beneficial effects of the present invention are embodied in:
The present invention is established for the purpose of improving restoring force based on the considerations of Complex Networks Theory maintenance personal's traveling time
Optimal Restoration model, optimal element reparation sequence can be found according to this model；By the classification of given assessment disaster with
Property is studied extreme disaster to the probability of malfunction for influencing simultaneously computing element of element failure rate, is imitated using non-sequential Monte Carlo
Really obtain element state change procedure.It is formed by MILP problem by repeatedly simulating and solving optimal Restoration model, obtains member
Part restores the distribution function at moment, is ranked up eventually by Aaron Copland moral ranking method to component importance.It is mentioned using the present invention
The component importance evaluation method based on elasticity out, the importance sorting of available element, and come temporarily in next disaster,
It can not have to calculate optimal Restoration model, element correcting strategy is directly formulated according to component importance, saves the plenty of time.In the past
Correcting strategy be mostly qualitatively, model proposed by the present invention can provide a kind of quantitative recovery policy, and the strategy is extensive
Play the role of compromise between the raising and computational efficiency of multiple power.It can be to electric system all kinds of using the method for the invention
Natural calamity is sought with the component importance under man-made disaster, and finding process has taken into account Disasters Type and feature.Utilize this
The component importance result that method obtains can provide ginseng for the determination of element Scheme of Strengthening before the formulation and calamity of recovery policy after calamity
It examines and builds.According to ranking results, to the element reparation sequence that restoring force of sening as an envoy to is bigger after extreme event generation, sent out in extreme event
The Scheme of Strengthening of element, enhancing power grid elasticity can be provided between life.
Detailed description of the invention
Fig. 1 is curve of the system performance in entire extreme Hazard processes；
Fig. 2 is that restoring force defines schematic diagram；
Fig. 3 is appraisal procedure flow chart；
Fig. 4 is 14 system schematic of IEEE；
Fig. 5 is 14 grid topological diagram of IEEE；
Fig. 6 is the Aaron Copland moral score of each element in 14 system of IEEE；
Fig. 7 is the distribution function that typical element repairs the moment in IEEE 14.
Specific embodiment
It elaborates with reference to the accompanying drawings and examples to the present invention.
Referring to Fig. 3, the power system component different degree appraisal procedure of the present invention based on restoring force passes through given assessment
The classification and property of disaster, study extreme disaster to element failure rate influence and computing element probability of malfunction, using it is non-when
Sequence Monte Carlo simulation obtains element state change procedure.MILP is formed by by repeatedly simulating and solving optimal Restoration model
Problem obtains the distribution function that element restores the moment, is ranked up eventually by Aaron Copland moral ranking method to component importance.Tool
Body the following steps are included:
1. determining the type of electric system disaster and the property of generation
Different disaster properties differ greatly, to system after electric system destructive process, the harm size that may cause, calamity
It is also far from each other to restore difficulty.When analyzing the ability of electric system resisting nature disaster, need clearly to be analyzed the shadow of disaster generation
Ring the information such as region, duration, disaster intensity.
2. obtaining fallible component type and relevant probability of malfunction under corresponding Disasters Type
Influence of the different disasters to system element is that have very big difference.Determine the damage for the electric system that disaster occurs
Mechanism determines that the type of fallible component under disaster is very necessary.For example, electric system is when by mountain fire disaster, it is maximum
The problem of be insulation breakdown；When by network attack, should pay close attention to communication equipment and information storing device (such as EMS and
SCADA)；When an earthquake occurs, substation can be destroyed；When in face of storm, it be easy to cause wire breaking and tower falling.It is longer for the duration
Disaster, the failure rate λ and probability of malfunction p of fallible component should be obtained.
Under storm environment, the failure rate of element is
The probability of malfunction of element is
Wherein, parameter interpretation is as follows:
W (t) is t moment wind speed；
α is scale coefficient；
λwind(w (t)) is the failure rate of t moment element；
λnormFor the failure rate of element under normal circumstances；
wcritWind speed when being begun to ramp up for failure rate；
pijFor the probability of malfunction of element ij；
TyFor with the failure unit matched time,
3. obtaining the fault configuration situation of element in system after disaster occurs with non-sequential Monte Carlo simulation
It for the state for obtaining each element, is sampled using non-sequential Monte Carlo simulation, non-sequential Monte Carlo simulation is taken out
The process of sample are as follows:
Obtain the random number rand of [0,1] space uniform distributioni, pijFor probability of malfunction, route is obtained after extreme disaster
Operating status s when the process of repairing startsij(0):
Wherein, it 1 indicates to work normally, 0 indicates failure.
4. optimal recovery policy model after establishing calamity proposes objective function and constraint condition
The whole process for meeting with extreme disaster can be by Fig. 1 shows this method is led in the case where considering personnel's traveling time
It crosses and determines recovery process (tsElement reparation sequence later) comes so that the restoring force of recovery process is maximum, and is restored according to this
Sequence carries out component importance sequence.
4.1) objective function
Restoring force is defined as in recovery process the cumulant of recovery system performance accounting, i.e. area S1 is than upper in Fig. 2
Area (S1+S2), system performance are defined as the sum of the power flow that load bus is an actually-received, objective function are as follows:
Wherein, fj(t) power flow that load bus j is actually received is indicated；VDIndicate the set of load bus；F(td) indicate
The minimum value of system performance after experience extreme event；Indicate the power flow that load bus j is received under normal circumstances；T table
Show that entire reparation duration, whole process are considered to be a time discrete process.
4.2) constraint condition
State constraint:
Wherein, sij(t) state of the representation element ij in moment t；E is the set of element；The set of E ' representing fault element.
Constraint (5) illustrates that element represents working properly, 0 representation element damage there are two types of state, 1；Constraint (6) illustrates that element is fixed
After will not damage again；Constraint (7) illustrates that fault element is damage in t=0.
Power-balance constraint:
Wherein, fij(t) power flow of element ij is flowed through for moment t；ViFor the set with node connected node；VSFor power generation
The set of machine node；VTFor the set of transmission node；VDFor the set of load bus；Pi SFor the maximum generating watt of generator；
For the transmission capacity of element ij.Constraint (8), (9) and (10) is respectively the power of generator node, transmission node and load bus
Constraints of Equilibrium；Constraint (11) illustrates power flow that load bus is an actually-received no more than power needed for the load bus
Stream；Constraint (12) illustrates that the power flow flowed on element receives the influence of element state.
Traveling time constraint:
Since the maintenance center for contributing big element that may set out from maintenance personal whole system restoring force is distant, such as
Fruit only considers to contribute, and the restoring force that may result in entire recovery process becomes smaller.For example there are two element A, B, A to be connected to one
The load of 60MW and B are connected to the load of a 30WM.A element 7 hours from maintenance center, B element 2 hours from maintenance center,
AB distance 10 hours.It first repairs and contributes big A that can expend 7*60+ (10+7) * 30=930MWh restoring force, 2* can be expended by repairing B
30+ (2+10) * 60=780MWh.So only considering that contribution does not consider that traveling time is unscientific.
Wherein, xm,nIt indicates whether maintenance personal from element m is moved to element n, if it is being equal to 1, is otherwise equal to 0.
At the time of indicating that maintenance personal reaches element m；Indicate that maintenance personal repairs the time required for element m；Indicate maintenance people
Member is moved to the time spent by element n from element m；fm,tIndicate element m whether fixed in moment t, if it is be equal to 1, it is no
Then it is equal to 0.Constraint (13) and (14) indicate that maintenance personal can only go fault element 1 time, can only also leave primary；Constrain (15) benefit
Make the route of maintenance personal continuous with large M；Constraining (16) indicates that at the beginning of recovery process, maintenance personal is repairing
Center；Constraint (17) indicates that element can only be fixed at a time, and can only be fixed primary；Constraining (18) indicatesWith
fm,tRelationship；Constraint (19) is for coupling fm,tWith element state sm(t)。
5. after pair calamity recovery process carry out repeatedly simulation obtain each element repair the moment and using the ranking method of Aaron Copland into
Row sequence, to obtain component importance sequence:
For each extreme disaster, all failure sampling can be carried out with non-sequential monte carlo method, to obtain one
MLIP (Mixed Integer Linear programming) problem, can be obtained the reparation moment of each element after solution.Obviously,
The reparation moment of element is more early, which can be more important.By repeatedly simulating, available each element repairs the distribution letter at moment
Number, obtains ranking method using Aaron Copland and is ranked up.As shown in formula (20) and (21), it is in contrast with one kind that Aaron Copland, which obtains ranking method,
Compared with method, gives a mark by comparing multiple characteristic quantities of two objects, calculate total score, i.e. Aaron Copland after all object comparisons
Moral score.Object can be ranked up according to Aaron Copland moral score.Here taking object is the distribution letter that each element repairs the moment
Number, feature measure the percentile of each distribution function, and component importance sequence can be obtained.
Wherein, parameter interpretation is as follows:
Sm,n,k-1For the Aaron Copland moral score of element m after -1 comparison of kth；
Sm,n,kFor the Aaron Copland moral score of element m after kth time comparison；
qk(m) the kth position percentage for being element m；
E' is fault element set.
Wherein, MILP problem such as following formula:
G (x, s (t))=0
h(x,s(t))≥0
Wherein, parameter interpretation is as follows:
T is the repair process time；
fj(t) power flow actually received for load bus j；
The power flow received under normal circumstances for load bus j；
F(td) be meet with extreme event after system performance minimum value；
VDFor the set of load bus；
G (x, s (t))=0 is equality constraint；
H (x, s (t)) >=0 is inequality constraints；
X is system variable, such as power.
Above-mentioned objective function and constraint one MILP problem of composition, you can get it after solution in order to keep entire recovery process extensive
The reparation moment of the multiple maximum each element of power.
Sample calculation analysis:
IEEE-14 standard example is used for the power system component different degree assessment side proposed by the invention based on restoring force
The example of method, as shown in Figure 4.It is as shown in Figure 5 to be abstracted as a complex network.For simplicity, under normal circumstances, false
If whole network works under the conditions of such one group of operational factor: by all load bus VDPower demand be set as 10 function
Rate unit,By all generator node VSMaximum power generation be set as 16 and power unit, Pi S=
16,16 power units are set by the capacity of all element (i, j) ∈ E,It will be each
The repair time of element (i, j) ∈ E is set as 1 chronomere,The position of general headquarters dep will be repaired
Region in Fig. 5 is set 2..
Assessment result is as shown in Figure 6.The distribution function for choosing the reparation moment of several elements is shown in Fig. 7, can be seen
Out, element<6,11>the reparation moment (element between 6 nodes and 11 nodes) always less than 8；And when the repairing of element<4,7>
Between always can be greater than 12.<6,11 obviously,>than<4,7>more important, because if<6,11>earlier than<4,7>are fixed, and system will
Obtain bigger restoring force.However, the relatively important sexual intercourse of not all element so can intuitively judge.Such as
<6,12>intersect with the reparation moment distribution function of<6,13>, and different degree relationship is difficult to judge.Therefore, it is arranged using Aaron Copland moral
Sequence method carries out ranking to the different degree of these elements.The significance level of element<9,14>is really than the significance level of element<2,3>
It is high；Element<3,4>has highest different degree really in the entire network.The different degree of some elements is easy intuitively from when repairing
Between distribution function find out that extreme four class components of comparison taken out in whole network below are discussed respectively:
A) probability of malfunction is high and influences on network big
The Aaron Copland moral score of this class component comes out at the top, very big on the influence of the recovery process of system, and significance level compares
It is high.Such as element<3,4 of highest scoring>, it is because 1) probability of malfunction of the element is larger why it is so high, which obtain branch,；
2) distance maintenance general headquarters it is closer, maintenance personal from maintenance general headquarters do not need expend the time can reach the element；3) this yuan
Part is affected to entire recovery process, because if it breaks down after disaster, the power demand of node 4 is difficult to reach
To (generator node 1,2,6 can be mainly responsible for the load bus of region 1., 3., 5. and 6.), so if going out from maintenance general headquarters
The maintenance personal come goes to repair the element at the first time, then load bus 4 and load bus 9 can restore most of function at once
Rate is horizontal.Element very high for this kind of priority, we should just take it reinforcing scheme, and focus in resource allocation
Consider this kind of node.
B) probability of malfunction is low but influences on network big
The Aaron Copland moral score of this class component is also relatively high, is affected to the recovery process of system, different degree degree compared with
It is high.Such as the higher element<4,9 of score>with element<7,9>, the higher reason of their scores is mainly: 1) they from maintenance people
The maintenance general headquarters that member sets out are closer, and the time for being not required to expend maintenance personal can reach；2) the two elements are entire IEEE-
The bridge of 14 network high voltage appearance hierarchical networks and low-voltage-grade network communication.Some failure is not among the two elements
When being repaired, 1. another element, which will overload, (when element<4,9>failure, the power and generator node S8 come is flowed from region
The power of sending all will by element<7,9>, lead to element<7,9>overload；Vice versa)；However, when two elements all failures
2. 4. time domain is unable to get power with region substantially.
C) probability of malfunction is high but influences on network small
The Aaron Copland moral score of this class component is relatively low, smaller on the influence of the recovery process of system, and different degree degree is lower.
Such as the lower element<2,3 of Aaron Copland moral score>, it why score it is lower be because are as follows:
1) they are not so close from the maintenance general headquarters that maintenance personal sets out, and need to expend maintenance personal's certain time just can be with
It reaches；Although 2) probability of its failure is relatively high, it is the connection between two generator nodes, and power between generator
It exchanges natively smaller.In addition the substitute of this element is relatively more, element<2,4>with element<2,5>is all its substitute,
And the influence all than this element to network is big, because they are directly connected to two load bus for needing power.
D) probability of malfunction is low and influences on network small
The Aaron Copland moral score of this class component is very low, smaller on the influence of the recovery process of system, and different degree degree is very low.Than
As the last element<4,7 of score rank>, it why score it is rebasing be because are as follows: 1) it probability of malfunction itself is with regard to very low；
Although 2) it is close from the maintenance general headquarters that maintenance personal sets out, two elements<4,9 beside it>and<7,9>it can generation
For its function.As long as element<4,9>and<7,9>after being fixed, 1. flowed through from region the power flow come can by element<
4,9 > flow to region 2. with region 4.；The power flow issued from generator node S8 can flow to region by element<7,9>
2. 4. with region.
Protection scope of the present invention is not limited to the above embodiments, for those of ordinary skill in the art, if
If to the various changes that carry out of the present invention and deformation belong to the claims in the present invention ask and equivalent technologies within the scope of, it is of the invention
It is intended to including also changing and deform comprising these.
Claims (8)
1. a kind of appraisal procedure of the power system component different degree based on restoring force, which comprises the following steps:
Determine the type of electric system disaster and the property of generation；
Obtain fallible component type and relevant probability of malfunction under corresponding Disasters Type；
It is sampled using non-sequential Monte Carlo simulation and obtains the fault configuration situation of element in system after disaster occurs；
Optimal recovery policy model after disaster is established, proposes objective function and constraint condition；
Recovery process after disaster repeatedly simulate and obtains each element reparation moment and is arranged using the ranking method of Aaron Copland
Sequence, to obtain component importance sequence.
2. the power system component different degree appraisal procedure according to claim 1 based on restoring force, which is characterized in that right
In long-term disaster, the failure rate λ and probability of malfunction p of fallible component should be obtained；Under storm environment, the event of element
Barrier rate is
The probability of malfunction of element is
Wherein,
W (t) is t moment wind speed；α is scale coefficient；λwind(w (t)) is the failure rate of t moment element；λnormFor under normal circumstances
The failure rate of element；wcritWind speed when being begun to ramp up for failure rate；pijFor the probability of malfunction of element ij；TyFor with failure rate list
The position matched time.
3. the power system component different degree appraisal procedure according to claim 1 in restoring force, which is characterized in that utilize
Non-sequential Monte Carlo simulation obtains the fault configuration situation of element in system after disaster occurs specifically:
For the state for obtaining each element, sampled using non-sequential Monte Carlo simulation, the sampling of non-sequential Monte Carlo simulation
Process are as follows:
Obtain the random number rand of [0,1] space uniform distributioni, pijFor probability of malfunction, obtains route and repaired after extreme disaster
Operating status s when process startsij(0):
Wherein, it 1 indicates to work normally, 0 indicates failure.
4. the appraisal procedure of the power system component different degree according to claim 1 based on restoring force, which is characterized in that
The described component importance sequence be by determine the element reparation sequence of recovery process come so that the restoring force of recovery process most
Greatly, and according to this recovery sequence component importance sequence is carried out.
5. the appraisal procedure of the power system component different degree according to claim 4 based on restoring force, which is characterized in that
Optimal recovery policy model after calamity is established, proposes objective function and constraint condition are as follows:
Restoring force is defined as in recovery process to the cumulant of recovery system performance accounting, system performance are defined as load bus
The sum of power flow being an actually-received, objective function are as follows:
In formula, fj(t) power flow that load bus j is actually received is indicated；VDIndicate the set of load bus；F(td) indicate to meet with
The minimum value of system performance after extreme event；Indicate the power flow that load bus j is received under normal circumstances；T indicates whole
A reparation duration, whole process are considered to be a time discrete process；
State constraint condition are as follows:
In formula, sij(t) state of the representation element ij in moment t；E is the set of element；The set of E ' representing fault element；Constraint
(5) indicate that element represents working properly, 0 representation element damage there are two types of state, 1；Constraint (6) indicates will not after element is fixed
It damages again；Constraint (7) indicates that fault element is damage in t=0；
Power-balance constraint condition are as follows:
In formula, fij(t) power flow of element ij is flowed through for moment t；ViFor the set with node connected node；VSFor generator section
The set of point；VTFor the set of transmission node；VDFor the set of load bus；Pi SFor the maximum generating watt of generator；For member
The transmission capacity of part ij；Constraint (8), (9) and (10) is respectively the power-balance of generator node, transmission node and load bus
Constraint；The power flow that constraint (11) expression load bus is an actually-received is no more than power flow needed for the load bus；About
Beam (12) indicates that the power flow flowed on element receives the influence of element state；
Traveling time constraint condition are as follows:
In formula, xm,nIt indicates whether maintenance personal from element m is moved to element n, if it is being equal to 1, is otherwise equal to 0；Indicate dimension
At the time of repairing personnel arrival element m；Indicate that maintenance personal repairs the time required for element m；Indicate maintenance personal from member
Part m is moved to the time spent by element n；fm,tIndicate whether element m is fixed in moment t, if it is being equal to 1, is otherwise equal to
0；Constraint (13) and (14) indicate that maintenance personal can only go fault element 1 time, can only also leave primary；It constrains (15) and utilizes big M
Method makes the route of maintenance personal continuous；Constraining (16) indicates that at the beginning of recovery process, maintenance personal is in maintenance center；
Constraint (17) indicates that element can only be fixed at a time, and can only be fixed primary；Constraining (18) indicatesWith fm,t's
Relationship；Constraint (19) is for coupling fm,tWith element state sm(t)。
6. the appraisal procedure of the power system component different degree according to claim 1 based on restoring force, which is characterized in that
For each extreme disaster, all failure sampling can be carried out with non-sequential monte carlo method, to obtain a MLIP problem, asked
The reparation moment of each element can be obtained after solution MLIP problem.
7. the appraisal procedure of the power system component different degree according to claim 6 based on restoring force, which is characterized in that
MILP problem such as following formula:
G (x, s (t))=0
h(x,s(t))≥0
Wherein, parameter interpretation is as follows:
T is the repair process time；
fj(t) power flow actually received for load bus j；
The power flow received under normal circumstances for load bus j；
F(td) be meet with extreme event after system performance minimum value；
VDFor the set of load bus；
G (x, s (t))=0 is equality constraint；
H (x, s (t)) >=0 is inequality constraints；
X is system variable；
Above-mentioned objective function and constraint one MILP problem of composition, you can get it after solution in order to make entire recovery process restoring force
The reparation moment of maximum each element.
8. the appraisal procedure of the power system component different degree according to claim 1 or 6 based on restoring force, feature exist
In,
Ranking method is obtained using Aaron Copland to be ranked up according to the following formula:
Wherein, parameter interpretation is as follows:
Sm,n,k-1For the Aaron Copland moral score of element m after -1 comparison of kth；
Sm,n,kFor the Aaron Copland moral score of element m after kth time comparison；
qk(m) the kth position percentage for being element m；
E' is fault element set；
By comparing each element Aaron Copland score to get arrive component importance ranking results.
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Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111553825A (en) * | 2020-04-28 | 2020-08-18 | 西南交通大学 | Regional rail transit key node identification method based on system elasticity |
| CN111581794A (en) * | 2020-04-26 | 2020-08-25 | 北京航空航天大学 | Novel elastic importance measuring method |
| CN112686440A (en) * | 2020-12-28 | 2021-04-20 | 广东电网有限责任公司广州供电局 | Method, device and equipment for determining deployment position of high-temperature superconducting cable |
| CN112861383A (en) * | 2021-03-17 | 2021-05-28 | 哈尔滨工业大学 | Railway station anti-seismic toughness evaluation method and system |
| CN113312761A (en) * | 2021-05-17 | 2021-08-27 | 广东电网有限责任公司广州供电局 | Method and system for improving toughness of power distribution network |
| CN114662328A (en) * | 2022-03-30 | 2022-06-24 | 国网浙江省电力有限公司经济技术研究院 | Power system resilience assessment method considering network attack |
| CN115374654A (en) * | 2022-10-24 | 2022-11-22 | 国网四川省电力公司电力科学研究院 | Method and system for evaluating elasticity of power system |
| CN115879833A (en) * | 2023-03-02 | 2023-03-31 | 国网山东省电力公司威海供电公司 | Double-layer power distribution network toughness evaluation method and system considering disaster response and recovery |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103701120A (en) * | 2013-12-23 | 2014-04-02 | 华北电力大学 | Method for evaluating reliability of large power grid comprising wind power station |
| US20160154061A1 (en) * | 2014-11-28 | 2016-06-02 | State Grid Corporation Of China | Method of assessing risk of power system with high penetration of wind power |
| US20170007044A1 (en) * | 2015-07-06 | 2017-01-12 | Eleframes, Llc | Picture mounting apparatus, system and method |
| CN108512226A (en) * | 2018-05-21 | 2018-09-07 | 西安交通大学 | A kind of method of power system recovery force estimation under disaster |
| CN108631306A (en) * | 2018-05-21 | 2018-10-09 | 西安交通大学 | The appraisal procedure of recovery capability after a kind of electric system calamity |
-
2019
- 2019-09-06 CN CN201910844406.0A patent/CN110472371A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103701120A (en) * | 2013-12-23 | 2014-04-02 | 华北电力大学 | Method for evaluating reliability of large power grid comprising wind power station |
| US20160154061A1 (en) * | 2014-11-28 | 2016-06-02 | State Grid Corporation Of China | Method of assessing risk of power system with high penetration of wind power |
| US20170007044A1 (en) * | 2015-07-06 | 2017-01-12 | Eleframes, Llc | Picture mounting apparatus, system and method |
| CN108512226A (en) * | 2018-05-21 | 2018-09-07 | 西安交通大学 | A kind of method of power system recovery force estimation under disaster |
| CN108631306A (en) * | 2018-05-21 | 2018-10-09 | 西安交通大学 | The appraisal procedure of recovery capability after a kind of electric system calamity |
Non-Patent Citations (1)
| Title |
|---|
| GENGFENG LI 等: "Component importance assessment of power systems for improving resilience under wind storms", 《JOURNAL OF MODERN POWER SYSTEMS AND CLEAN ENERGY》 * |
Cited By (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111581794A (en) * | 2020-04-26 | 2020-08-25 | 北京航空航天大学 | Novel elastic importance measuring method |
| CN111581794B (en) * | 2020-04-26 | 2022-03-15 | 北京航空航天大学 | Novel elastic importance measuring method |
| CN111553825A (en) * | 2020-04-28 | 2020-08-18 | 西南交通大学 | Regional rail transit key node identification method based on system elasticity |
| CN112686440A (en) * | 2020-12-28 | 2021-04-20 | 广东电网有限责任公司广州供电局 | Method, device and equipment for determining deployment position of high-temperature superconducting cable |
| CN112686440B (en) * | 2020-12-28 | 2023-11-14 | 广东电网有限责任公司广州供电局 | Method, device and equipment for determining deployment position of superconducting cable |
| CN112861383A (en) * | 2021-03-17 | 2021-05-28 | 哈尔滨工业大学 | Railway station anti-seismic toughness evaluation method and system |
| CN113312761B (en) * | 2021-05-17 | 2023-05-30 | 广东电网有限责任公司广州供电局 | Method and system for improving toughness of power distribution network |
| CN113312761A (en) * | 2021-05-17 | 2021-08-27 | 广东电网有限责任公司广州供电局 | Method and system for improving toughness of power distribution network |
| CN114662328A (en) * | 2022-03-30 | 2022-06-24 | 国网浙江省电力有限公司经济技术研究院 | Power system resilience assessment method considering network attack |
| CN114662328B (en) * | 2022-03-30 | 2024-04-26 | 国网浙江省电力有限公司经济技术研究院 | Power system restoring force evaluation method considering network attack |
| CN115374654B (en) * | 2022-10-24 | 2023-01-06 | 国网四川省电力公司电力科学研究院 | Method and system for evaluating elasticity of power system |
| CN115374654A (en) * | 2022-10-24 | 2022-11-22 | 国网四川省电力公司电力科学研究院 | Method and system for evaluating elasticity of power system |
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