CN117371750A - Multi-target power grid fault emergency rescue method considering man-vehicle feature matching - Google Patents

Multi-target power grid fault emergency rescue method considering man-vehicle feature matching Download PDF

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CN117371750A
CN117371750A CN202311461679.XA CN202311461679A CN117371750A CN 117371750 A CN117371750 A CN 117371750A CN 202311461679 A CN202311461679 A CN 202311461679A CN 117371750 A CN117371750 A CN 117371750A
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张澄昕
陈光宇
李颖
苏昱丹
杨帆
伍兴达
张玉卓
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Nanjing Institute of Technology
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Abstract

The invention discloses a multi-target power grid fault emergency rescue method considering man-vehicle feature matching, which comprises the following steps: 1) Acquiring the position of a fault power grid, determining rescue emergency degree, and evaluating the total load demand of a load; 2) Primarily screening the alternative disaster relief vehicles according to the total load demand of the load; 3) Establishing an evaluation index of the comprehensive capability quality of the rescue workers based on the fault power grid position and the alternative disaster relief vehicles, and obtaining the comprehensive rescue capability quality value of each rescue worker; calculating a matching coefficient of the rescue vehicle and rescue personnel; 4) Establishing a regional road network model considering the matching coefficient and the road safety coefficient, and solving the shortest running path length from the rescue starting point to the fault point by using a Dijkstra algorithm to determine the road loss time length; 5) And (3) inputting rescue emergency degree, comprehensive rescue capability quality value, matching coefficient and road loss duration solving to obtain an emergency dispatching scheme by taking optimal matching of rescue personnel and minimum comprehensive fault loss in the area as targets. The invention can optimize the dispatching of the emergency power supply and reduce the loss of power failure.

Description

Multi-target power grid fault emergency rescue method considering man-vehicle feature matching
Technical Field
The invention relates to a power grid fault rescue technology, in particular to a multi-target power grid fault emergency rescue method considering man-vehicle feature matching.
Background
With the popularization and wide use of the power grid, people generally rely on power in life and many factories, but once the power grid fails due to disaster, a large-area power failure can be caused by the condition that important loads are powered off for a long time due to disaster, so that social order and national economic benefits are seriously endangered. As a key link of an urban emergency defense system, the selection of rescue workers and the selection of rescue vehicles are critical, and the speed and regional familiarity of the rescue workers driving the rescue vehicles at critical moments greatly influence the economic loss and the influence on life caused by faults.
The existing emergency rescue scheduling method cannot consider the emergency degree of fault load, cannot establish a matching mechanism of a rescue vehicle and rescue personnel, and ignores comprehensive quality expected by the rescue personnel.
Disclosure of Invention
Aiming at the defects in the prior art, the invention provides a multi-target power grid fault emergency rescue method considering man-vehicle feature matching.
In order to achieve the above purpose, the present invention adopts the following technical scheme:
A multi-target power grid fault emergency rescue method considering man-vehicle feature matching comprises the following steps:
s1, acquiring the position of each fault power grid, determining rescue emergency degree of each fault power grid, and evaluating total load demand of each load after power grid faults in an area;
s2, primarily screening the alternative disaster relief vehicles according to the estimated total load demand of the load;
s3, based on the fault power grid position and the primary screening of the alternative disaster relief vehicles, establishing an evaluation index system of the comprehensive capability quality of the rescue workers, and obtaining the comprehensive rescue capability quality value of each rescue worker; establishing a matching model of the rescue vehicle and the rescue personnel to obtain a matching coefficient of the rescue vehicle and the rescue personnel;
s4, establishing an area road network model considering the matching coefficient and the road safety coefficient of the rescue vehicles and the rescue workers, solving the shortest running path length from the rescue starting point to the fault point in the area under the condition that the rescue vehicles are matched with different rescue workers by using a Dijkstra algorithm, and determining the road loss time from the rescue starting point to the fault point in the area under the condition that the rescue vehicles are matched with different rescue workers by combining the average driving speed;
s5, establishing a multidimensional matching rescue model aiming at the optimal matching of rescue workers and the minimum comprehensive fault loss in the area, inputting rescue emergency degree, comprehensive rescue capability quality values of the rescue workers, matching coefficients of rescue vehicles and the rescue workers and road loss time length, and solving the multidimensional matching rescue model to obtain a depth matching emergency dispatching scheme.
In order to optimize the technical scheme, the specific measures adopted further comprise:
further, S1 is specifically:
obtaining the position of each fault power grid, and calculating the respective rescue emergency degree of K fault power grids by considering the health safety, economic loss and life quality influence degree of power failure on each load, wherein the rescue emergency degree of each fault power grid is A k ，
Wherein the health and safety influence degree, economic loss influence degree and life quality influence degree of each load are respectively alpha k 、β k 、γ k Characterization, ω α Representing the weight, omega, occupied by health safety in emergency degree of fault load β Indicating the weight, ω, of the economic loss in the emergency of the fault load γ Representing the weight, omega, of quality of life in fault load emergency α +ω β +ω γ ＝1；
Assessing the electrical power demand Q of faulty grids in an area k And the total active power demand P of the kth faulty grid k The method comprises the steps of carrying out a first treatment on the surface of the Node voltage U of each fault power grid ik 0.95U is required to be satisfied ik ≤U k ≤1.05U ik Wherein U is k Rated voltage of each fault power grid; the line current flowing through each fault is I k The constraint condition is I k ≤I k，max Wherein I k，max Indicating the maximum current value allowed to pass through each faulty line.
Further, S2 is specifically:
primarily screening the alternative disaster relief vehicle according to the following standard;
the primary screening of the alternative disaster relief vehicle requires the power supply capacity of the disaster relief vehicle to at least ensure the power requirement of a fault power grid and the back and forth power consumption requirement of the disaster relief vehicle, and ensures that the voltage and the current cannot cross the boundary;
Vehicle electric quantity Q of screened c-th rescue vehicle EV，C Should at least satisfy min { Q EV，C }-Q Y，c ＞max{Q k }, wherein Q Y，c The total power consumption of the back and forth mileage of the first rescue vehicle is calculated; q (Q) k Representing the electric quantity demand of the kth fault electric network, and the discharging power P of the c-th rescue vehicle EV，C Should satisfy P EV，C ≥P k The method comprises the steps of carrying out a first treatment on the surface of the Input voltage U of important load connected to each rescue vehicle rc To meet U rc ≈U k ，0.95U ik ≤U rc ≤1.05U ik Input current I rc Is required to meet I rc ≈I k ，I rc ≤I k，max ；
State of charge S of rescue vehicle SOCK The S is required to be satisfied by 20 percent or less SOCK ≤100％；
Wherein S is SOCK (. Cndot.) represents the state of charge of the rescue vehicle, t cm The time length of the rescue support consumed by the c-th vehicle matched with the m-th rescue workers,the road loss time from the ith rescue starting point to the kth fault load is matched for the ith vehicle and the mth rescue personnel.
Further, in S3, based on the fault power grid position and the primary screening of the alternative disaster relief vehicle, an evaluation index system of the comprehensive capability quality of the rescue personnel is established, and the comprehensive rescue capability quality value of each rescue personnel is obtained specifically as follows:
establishing a first-level index, wherein the first-level index comprises a driving capability condition A, a physical and psychological quality condition B, a road safety consciousness C, a driving experience condition D and a comprehensive rescue capability E;
establishing a secondary index under the primary index, wherein the secondary index of the driving ability condition A comprises a traffic rule mastering condition A1, a driving skill mastering degree A2 and a road condition judging ability A3; the secondary indexes of the physical and psychological condition B comprise age B1, physiological disease history B2, mental disease history B3, mental condition B4, emotional intelligence condition B5 and basic ability B6; the secondary indexes of the road safety awareness C comprise safety driving awareness C1, safety driving habit C2 and safety driving tendency C3; the second-level indexes of the driving experience situation D comprise vehicle performance familiarity D1, regional road condition familiarity D2 and job entering years D3; the secondary indexes of the comprehensive rescue capability E comprise personnel treatment knowledge mastery degree E1, electrician safety knowledge mastery degree E2, maintenance technical capability E3 and communication capability E4;
Respectively calculating the comprehensive rescue ability quality value H of each of M rescue workers m ，
Wherein, the driving capability condition of the mth rescue personnel,The scoring values of physical and psychological conditions, road safety consciousness, driving experience conditions and comprehensive rescue capability are respectively G Am ，G Bm ，G Cm ，G Dm ，G Em To characterize; omega A Weight value omega representing driving ability condition accounting for first-level index score B Weight value omega representing primary index score of physical and psychological quality condition C Weight value omega representing grade of first-level index of road safety consciousness D Weight value omega representing driving experience condition accounting for first-level index score E Weight value omega representing first-level index score of comprehensive rescue capability A +ω B +ω C +ω D +ω E ＝1；
Scoring G of the driving ability of the mth rescue person Am Scoring by traffic mastery conditions G A1m Degree of mastery of driving skill G A2m Road condition judging ability G A3m Three scoring weights are obtained, G A1m ，G A2m ，G A3m ∈[0，1]；
Final score G for driving ability of mth rescuer Am The calculated expression of (2) is
Wherein omega A1 Weight value omega representing secondary index under condition of traffic rule mastering condition accounting for driving capability A2 Weight value, ω representing the second level index in the case where the driving skill grasping degree occupies the driving ability A3 Weight value omega representing secondary index under condition that road condition judging capability occupies driving capability A1 +ω A2 +ω A3 ＝1；
Figure condition score G of mth rescue worker Bm Scoring G by age interval degree B1m Shi Pingfen G for physiological diseases B2m History of mental illness score G B3m Psychological condition score G B4m Emotional mental condition score G B5m Basic ability score G B6m Weighting six items to obtain G B1m ，G B4m ，G B5m ，G B6m ∈[0，1]The method comprises the steps of carrying out a first treatment on the surface of the Considering the age of the rescue workers, dividing the rescue workers into three categories of young, strong and middle-aged, and dividing 18-25 years into young rescue workers, wherein the index G B1m 0.6;26-45 years old is a healthy person, the index G B1m 1 is shown in the specification; 45-60 years old is middle-aged rescuer, the index G B1m 0.8; physiological disease history score G B2m Taking 0 or 1, 0 if there is disease history, 1 if there is no disease history, and grading G of mental disease history B3m Taking 0 or 1, wherein the disease history is 0, and the disease history is 1;
figure of mind condition score G of mth driver Bm The calculated expression of (2) is:
wherein omega B1 Weight value omega representing secondary index under condition of age interval degree occupying physical and psychological quality B2 Weight value omega representing secondary index of physical and psychological quality of physiological disease history B3 Weight value, omega, representing secondary index of mental disease history in physical and psychological quality condition B4 Weight value omega representing secondary index of psychological condition B5 Weight value, omega representing secondary index of emotional intelligence condition in physical and psychological quality condition B6 Weight value omega representing secondary index under basic ability occupying physical and psychological quality condition B1 +ω B2 +ω B3 +ω B4 +ω B5 +ω B6 ＝1；
Road safety awareness score G of mth rescue worker Cm Awareness scoring by safe driving G C1m Safe driving habit G C2m Safe driving tendency G C3m Three scoring weights are obtained, G C1m ，G C2m ，G C3m ∈[0，1]；
Road safety awareness score G of mth rescue worker Cm The calculated expression of (2) is:
wherein omega C1 Weight value omega representing secondary index of safety driving awareness in road safety awareness C2 Weight value omega representing that safe driving habit occupies secondary index under road safety consciousness C3 Weight value omega representing that safe driving tendency occupies secondary index under road safety consciousness C1 +ω C2 +ω C3 ＝1；
Driving experience situation score G of mth rescue worker Dm Familiarity G by vehicle performance D1m Familiarity G of regional road conditions D2m Degree G of entering period D3m Three scoring weights are obtained, G D1m ，G D2m ，G D3m ∈[0，1]Entering period G D3m Dividing the time period of the first-aid staff into three time periods of 1-3 years, 4-7 years and 8 years and more, and the time period G of the first-aid staff of 1-3 years D3m The time interval G of the service life of the rescue workers of 0.4,4-7 years D3m The time interval G of the service life of the rescue workers of 0.6,8 years or more D3m 0.8, driving experience situation score G for mth rescuer Dm The expression of (2) is:
wherein omega D1 Weight value omega representing secondary index under condition that vehicle performance familiarity occupies driving experience D2 Regional road condition familiarity occupies weight value omega of secondary index under driving experience condition D3 Weight value omega representing secondary index under condition of taking up driving experience by time interval degree of job entering years D1 +ω D2 +ω D3 ＝1；
Comprehensive rescue ability score G of mth rescue personnel Em Degree of mastery score G by personnel first aid knowledge E1m Degree of mastery of electrician's safety knowledge G E2m Capability of maintenance technique G E3m Communication ability G E4m Weighting four terms to obtain G E1m ，G E2m ，G E3m ，G E4m ∈[0，1]；
Comprehensive rescue ability score G of mth rescue personnel Em The calculated expression of (2) is:
wherein omega E1 Weight value omega representing secondary index under comprehensive rescue capability of personnel first aid knowledge mastery degree E2 Weight value omega representing second-level index under comprehensive rescue capability of electrician safety knowledge mastery degree E3 Weight value omega representing secondary index under comprehensive rescue capability of maintenance technical capability E4 Weight omega representing secondary index under communication capacity accounting for comprehensive rescue capacity E1 +ω E2 +ω E3 +ω E4 ＝1。
Further, in S3, the establishing a matching model between the rescue vehicle and the rescue personnel, and the obtaining the matching coefficient between the rescue vehicle and the rescue personnel specifically includes:
establishing a matching model of the rescue vehicle and rescue personnel:
Establishing a feature set X of a c-th rescue vehicle c ，X c ＝{X 1c ，X 2c ，X 3c ，X 4c ，X 5c }，X 1c X represents the service life of the c-th rescue vehicle 2c X represents the power type condition of the c-th rescue vehicle 3c Represents the model of the c rescue vehicle, X 4c Represents the brake sensitivity, X of the c-th rescue vehicle 5c Representing the power consumption of the c-th rescue vehicle per kilometer;
establishing a feature set Y of the mth rescue personnel m ，Y m ＝{Y 1m ，Y 2m ，Y 3m ，y 4m ，Y 5m }，Y 1m Represents the age of the mth rescue worker, Y 2m Represents the service life condition of the mth rescue personnel, Y 3m Represents the driving capability condition of the mth rescue worker, Y 4m Representing the physical and psychological condition at position m, Y 5m Representing the driving experience situation of the mth rescue personnel;
and solving a matching coefficient between the rescue vehicle and the rescue personnel by using a standardized Euclidean distance, wherein the method comprises the following steps of:
using a five-dimensional vector x c (x 11 ，x 12 ，x 13 ，x 14 ，x 15 ) Spatialization characterization set X c Wherein x is 11 Feature descriptors, x, of life span of rescue vehicle 12 Feature descriptor, x, for power type of rescue vehicle 13 Feature descriptor for model of rescue vehicle, x 14 Feature descriptor, x, for rescue vehicle brake sensitivity 15 A characteristic descriptor of power consumption of the c rescue vehicle per kilometer;
the service life of the rescue vehicle is divided into four features of one year, one year to five years, five years to ten years and more than ten years, and the features are respectively corresponding to the feature descriptors x 11 The values are 1, 0.8, 0.6 and 0.5;
the power types of the rescue vehicle are divided into a pure electric vehicle, a hybrid electric vehicle and a fuel cell electric vehicle, and the corresponding feature descriptors x respectively 12 The values are 1, 0.6 and 0.5;
the model of the rescue vehicle is divided into a large model, a medium model and a small model, and the feature descriptors x respectively correspond to the model 13 1, 0.7 and 0.4;
using a five-dimensional vector y m (x 21 ，x 22 ，x 23 ，x 24 ，x 25 ) Spatially characterizing, x 21 Feature descriptors, x, representing the age of rescue workers 22 Feature descriptor, x, representing the age of rescue personnel 23 Feature descriptor, x, representing driving capability of rescue personnel 24 Feature descriptors, x, representing physical and psychological conditions 25 A feature descriptor representing a driving experience situation of the rescuer;
the ages of the rescue workers are divided into young rescue workers according to 18-25, aged rescue workers according to 26-45 and middle-aged rescue workers according to 45-60, and the corresponding feature descriptors x respectively 21 0.6, 1, 0.8;
the service life of the rescue workers is divided into 1-3 years, 4-7 years, 8 years and more, and the service life is 1-3 years of feature descriptors x 22 Feature descriptor x of 0.4, 4-7 years of job entry 22 Feature descriptor x of 0.6, more than 8 years of job entry period 22 0.8;
feature descriptor x for driving capability condition of rescue workers 23 First-level index scoring G in evaluation index system for comprehensive ability quality of rescue workers Am Is substituted by the value of (2);
feature descriptor x of physical and psychological condition of rescue workers 24 First-level index scoring G in evaluation index system for comprehensive ability quality of rescue workers Bm Is substituted by the value of (2);
feature descriptor x of driving experience situation of rescue personnel 25 First-level index scoring G in evaluation index system for comprehensive ability quality of rescue workers Dm Is substituted by the value of (2);
applying a standardized Euler distance formulaSolving for x c And y is m Wherein S is k Represents the standard deviation of the kth dimension, using D cm The matching coefficient of the c-th vehicle and the m-th rescue worker is represented.
Further, in S4, the establishing an area road network model considering the matching coefficient between the rescue vehicle and the rescue personnel and the road safety coefficient specifically includes:
modeling a fault traffic network by adopting a graph theory method:
based on graph theory, all disaster fault points are converted into an undirected graph G= (V, L, T, W) according to the positions, wherein V represents a set of all traffic nodes in an area, and V i Represents all rescue starting point sets, v k Representing all the fault point sets, L representing all the traffic road segment sets, v ik Representing a traffic road section from a rescue departure point i to a fault point k, T is a time sequence set, T represents real-time update time of road conditions, and each time An hour is divided into a time period point, less than an hour is calculated according to an hour, the time is updated 24 times a day, W represents a road section weighting value set,the weighting length of a road section from the ith rescue starting point to the kth fault point after the matching coefficient of the rescue vehicle and the rescue personnel is considered, and the road section is blocked by a fixed road +.>Time consumption coefficient delta fusing real-time traffic index representation t Matching coefficient D of rescue vehicle and rescue personnel cm The road loss time from the ith rescue departure point to the kth fault point of the mth rescue personnel matched with the c rescue vehicle is +.>Wherein->The average driving speed of the c rescue vehicle is matched with the m rescue personnel.
Further, in S5, the building of the multidimensional matching rescue model with the objective of optimal matching of rescue workers and minimal comprehensive loss of faults in the area after the power grid is damaged is specifically as follows:
comprehensive rescue capability quality value H of rescue personnel optimally considered to be dispatched in matching of rescue personnel m Matching coefficient D with rescue vehicle cm Establishing a matching objective function:
max f 1 (H m ，D cm )＝∑(H m ·ω m +D cm ·ω cm )，
wherein omega m Representing the weight, omega of the total match of the comprehensive rescue ability quality cm Representing the weight omega of the total match of the matching coefficient of the rescue personnel and the rescue vehicle m +ω cm ＝1，f 1 (H m ，D cm ) Representing a rescue personnel matching function;
rescue urgency A with minimum total loss and consideration of fault load k Road loss time to failure loadEstablishing an objective function with the lowest cost:
in the method, in the process of the invention,representing the total cost, t cm Expressed as the rescue support time consumed by the c-th vehicle together with the m-th rescue worker,>the road loss time from the ith rescue departure point to the kth fault load is matched with the mth rescue worker for the c-th vehicle; q represents the cost loss per minute of load at the time of failure, the higher the rescue emergency, the higher the cost loss of the load wound around the failure; q (Q) c Represents cost loss generated by the c-th rescue vehicle per kilometer, Q c0 Representing the running and maintenance costs generated by the fixation of the c-th vehicle.
The beneficial effects of the invention are as follows:
according to the invention, the influence of the characteristics of rescue personnel and rescue vehicles on emergency rescue scheduling when a power grid breaks down is considered, a comprehensive capability quality evaluation system of the rescue personnel and a matching model of the rescue vehicles and the rescue personnel are established, the matching coefficient between the rescue vehicles and the rescue personnel is solved based on an Euler formula, an area road network model based on the matching coefficient between the rescue vehicles and the rescue personnel and the road safety coefficient is established, the equivalent road resistance fused with the real-time traffic coefficient is solved by using a Dijkstra algorithm, and a basis is provided for solving the shortest road loss time; the invention also establishes a multidimensional matching rescue model aiming at optimal matching of rescue workers and minimum comprehensive fault loss in the area. The invention can optimize the dispatching of the emergency power supply and reduce the loss of power failure.
Drawings
FIG. 1 is a flow chart of the method of the present invention.
Detailed Description
The invention will now be described in further detail with reference to the accompanying drawings.
The invention provides a multi-target power grid fault emergency rescue method considering man-vehicle feature matching, which is shown in a figure 1 and comprises the following steps:
s1, acquiring the position of each fault power grid, determining rescue emergency degree of each fault power grid, and evaluating total load demand of each load after power grid faults in an area; the method comprises the following steps:
obtaining the position of each fault power grid, and calculating the respective rescue emergency degree of K fault power grids by considering the health safety, economic loss and life quality influence degree of power failure on each load, wherein the rescue emergency degree of each fault power grid is A k ，
Wherein the health and safety influence degree, economic loss influence degree and life quality influence degree of each load are respectively alpha k 、β k 、γ k Characterization, ω α Representing the weight, omega, occupied by health safety in emergency degree of fault load α Take 0.5, omega β Indicating the weight, ω, of the economic loss in the emergency of the fault load β Take 0.3, omega γ Representing the weight, omega, of quality of life in fault load emergency γ Taking 0.2. Omega α +ω β +ω γ =1; the rescue emergency degree of 4 fault loads is calculated to be A 1 ＝0.77，A 2 ＝0.46，A 3 ＝0.27，A 4 ＝0.42。
Table 1 four fault load rescue urgency
Assessing the electrical power demand Q of faulty grids in an area k And the total active power demand P of the kth faulty grid k The method comprises the steps of carrying out a first treatment on the surface of the Node voltage U of each fault power grid ik 0.95U is required to be satisfied ik ≤U k ≤1.05U ik Wherein U is k Rated voltage of each fault power grid; the line current flowing through each fault is I k The constraint condition is I k ≤I k，max Wherein I k，max Indicating the maximum current value allowed to pass through each faulty line.
S2, primarily screening the alternative disaster relief vehicles according to the estimated total load demand of the load; the method comprises the following steps:
primarily screening the alternative disaster relief vehicle according to the following standard;
the primary screening of the alternative disaster relief vehicle requires the power supply capacity of the disaster relief vehicle to at least ensure the power requirement of a fault power grid and the back and forth power consumption requirement of the disaster relief vehicle, and ensures that the voltage and the current cannot cross the boundary;
vehicle electric quantity Q of screened c-th rescue vehicle EV，C Should at least satisfy min { Q EV，C }-Q Y，c ＞max{Q k }, wherein Q Y，c The total power consumption of the back and forth mileage of the first rescue vehicle is calculated; q (Q) k Representing the electric quantity demand of the kth fault electric network, and the discharging power P of the c-th rescue vehicle EV，C Should satisfy P EV，C ≥P k The method comprises the steps of carrying out a first treatment on the surface of the Input voltage U of important load connected to each rescue vehicle rc To meet U rc ≈U k ，0.95U ik ≤U rc ≤1.05U ik Input current I rc Is required to meet I rc ≈I k ，I rc ≤I k，max ；
State of charge S of rescue vehicle SOCK The S is required to be satisfied by 20 percent or less SOCK ≤100％；
Wherein S is SOCK (. Cndot.) represents the state of charge of the rescue vehicle, t cm The time length of the rescue support consumed by the c-th vehicle matched with the m-th rescue workers,the road loss time from the ith rescue starting point to the kth fault load is matched for the ith vehicle and the mth rescue personnel.
S3, based on the fault power grid position and the primary screening of the alternative disaster relief vehicles, establishing an evaluation index system of the comprehensive capability quality of the rescue workers, and obtaining the comprehensive rescue capability quality value of each rescue worker; the method comprises the following steps:
establishing a first-level index, wherein the first-level index comprises a driving capability condition A, a physical and psychological quality condition B, a road safety consciousness C, a driving experience condition D and a comprehensive rescue capability E;
establishing a secondary index under the primary index, wherein the secondary index of the driving ability condition A comprises a traffic rule mastering condition A1, a driving skill mastering degree A2 and a road condition judging ability A3; the secondary indexes of the physical and psychological condition B comprise age B1, physiological disease history B2, mental disease history B3, mental condition B4, emotional intelligence condition B5 and basic ability B6; the secondary indexes of the road safety awareness C comprise safety driving awareness C1, safety driving habit C2 and safety driving tendency C3; the second-level indexes of the driving experience situation D comprise vehicle performance familiarity D1, regional road condition familiarity D2 and job entering years D3; the secondary indexes of the comprehensive rescue capability E comprise personnel treatment knowledge mastering degree E1, electrician safety knowledge mastering degree E2, maintenance technical capability E3 and communication capability E4.
The comprehensive rescue ability quality evaluation index system of the rescue workers is shown in table 2.
TABLE 2 comprehensive rescue ability quality evaluation index system for rescue workers
Respectively calculating the comprehensive rescue ability quality value H of each of M rescue workers m ，
Wherein scoring values of driving capability, physical and psychological quality, road safety consciousness, driving experience condition and comprehensive rescue capability of the mth rescue personnel are respectively G Am ，G Bm ，G Cm ，G Dm ，G Em To characterize; omega A Weight value omega representing driving ability condition accounting for first-level index score B Weight value omega representing primary index score of physical and psychological quality condition C Weight value omega representing grade of first-level index of road safety consciousness D Weight value omega representing driving experience condition accounting for first-level index score E Weight value omega representing first-level index score of comprehensive rescue capability A +ω B +ω C +ω D +ω E ＝1；
Scoring G of the driving ability of the mth rescue person Am Scoring by traffic mastery conditions G A1m Degree of mastery of driving skill G A2m Road condition judging ability G A3m Three scoring weights are obtained, G A1m ，G A2m ，G A3m ∈[0，1]；
Final score G for driving ability of mth rescuer Am The calculated expression of (2) is
Wherein omega A1 Weight value omega representing secondary index under condition of traffic rule mastering condition accounting for driving capability A2 Weight value, ω representing the second level index in the case where the driving skill grasping degree occupies the driving ability A3 Weight value omega representing secondary index under condition that road condition judging capability occupies driving capability A1 +ω A2 +ω A3 ＝1；
Figure condition score G of mth rescue worker Bm Scoring G by age interval degree B1m Shi Pingfen G for physiological diseases B2m History of mental illness score G B3m Psychological condition score G B4m Emotional mental condition score G B5m Basic ability score G B6m Weighting six items to obtain G B1m ，G B4m ，G B5m ，G B6m ∈[0，1]The method comprises the steps of carrying out a first treatment on the surface of the Considering the age of the rescue workers, dividing the rescue workers into three categories of young, strong and middle-aged, and dividing 18-25 years into young rescue workers, wherein the index G B1m 0.6;26-45 years old is a healthy person, the index G B1m 1 is shown in the specification; 45-60 years old is middle-aged rescuer, the index G B1m 0.8; physiological disease history score G B2m Taking 0 or 1, 0 if there is disease history, 1 if there is no disease history, and grading G of mental disease history B3m Taking 0 or 1, wherein the disease history is 0, and the disease history is 1;
figure of mind condition score G of mth driver Bm The calculated expression of (2) is:
wherein omega B1 Weight value omega representing secondary index under condition of age interval degree occupying physical and psychological quality B2 Weight value omega representing secondary index of physical and psychological quality of physiological disease history B3 Weight value, omega, representing secondary index of mental disease history in physical and psychological quality condition B4 Weight value omega representing secondary index of psychological condition B5 Weight value, omega representing secondary index of emotional intelligence condition in physical and psychological quality condition B6 Weight value omega representing secondary index under basic ability occupying physical and psychological quality condition B1 +ω B2 +ω B3 +ω B4 +ω B5 +ω B6 ＝1；
Road safety awareness score G of mth rescue worker Cm Awareness scoring by safe driving G C1m Safe driving habit G C2m Safe driving tendencyG C3m Three scoring weights are obtained, G C1m ，G C2m ，G C3m ∈[0，1]；
Road safety awareness score G of mth rescue worker Cm The calculated expression of (2) is:
wherein omega C1 Weight value omega representing secondary index of safety driving awareness in road safety awareness C2 Weight value omega representing that safe driving habit occupies secondary index under road safety consciousness C3 Weight value omega representing that safe driving tendency occupies secondary index under road safety consciousness C1 +ω C2 +ω C3 ＝1；
Driving experience situation score G of mth rescue worker Dm Familiarity G by vehicle performance D1m Familiarity G of regional road conditions D2m Degree G of entering period D3m Three scoring weights are obtained, G D1m ，G D2m ，G D3m ∈[0，1]Entering period G D3m Dividing the time period of the first-aid staff into three time periods of 1-3 years, 4-7 years and 8 years and more, and the time period G of the first-aid staff of 1-3 years D3m The time interval G of the service life of the rescue workers of 0.4,4-7 years D3m The time interval G of the service life of the rescue workers of 0.6,8 years or more D3m 0.8, driving experience situation score G for mth rescuer Dm The expression of (2) is:
wherein omega D1 Weight value omega representing secondary index under condition that vehicle performance familiarity occupies driving experience D2 Regional road condition familiarity occupies weight value omega of secondary index under driving experience condition D3 Weight value omega representing secondary index under condition of taking up driving experience by time interval degree of job entering years D1 +ω D2 +ω D3 ＝1；
Comprehensive rescue ability score G of mth rescue personnel Em Degree of mastery score G by personnel first aid knowledge E1m Degree of mastery of electrician's safety knowledge G E2m Capability of maintenance technique G E3m Communication ability G E4m Weighting four terms to obtain G E1m ，G E2m ，G E3m ，G E4m ∈[0，1]；
Comprehensive rescue ability score G of mth rescue personnel Em The calculated expression of (2) is:
wherein omega E1 Weight value omega representing secondary index under comprehensive rescue capability of personnel first aid knowledge mastery degree E2 Weight value omega representing second-level index under comprehensive rescue capability of electrician safety knowledge mastery degree E3 Weight value omega representing secondary index under comprehensive rescue capability of maintenance technical capability E4 Weight omega representing secondary index under communication capacity accounting for comprehensive rescue capacity E1 +ω E2 +ω E3 +ω E4 ＝1。
In this embodiment, taking 6 rescue workers as an example, the comprehensive ability quality evaluation scores of the 6 rescue workers are shown in table 3:
TABLE 3 Table 3
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The primary and secondary index weight scoring results of the 6 rescue workers are shown in table 4.
TABLE 4 Table 4
Establishing a matching model of the rescue vehicle and the rescue personnel to obtain a matching coefficient of the rescue vehicle and the rescue personnel; the method comprises the following steps:
establishing a matching model of the rescue vehicle and rescue personnel:
establishing a feature set X of a c-th rescue vehicle c ，X c ＝{X 1c ，X 2c ，X 3c ，X 4c ，X 5c }，X 1c X represents the service life of the c-th rescue vehicle 2c X represents the power type condition of the c-th rescue vehicle 3c Represents the model of the c rescue vehicle, X 4c Represents the brake sensitivity, X of the c-th rescue vehicle 5c Representing the power consumption of the c-th rescue vehicle per kilometer;
establishing a feature set Y of the mth rescue personnel m ，Y m ＝{Y 1m ，Y 2m ，Y 3m ，y 4m ，Y 5m }，Y 1m Represents the age of the mth rescue worker, Y 2m Represents the service life condition of the mth rescue personnel, Y 3m Represents the driving capability condition of the mth rescue worker, Y 4m Representing the physical and psychological condition at position m, Y 5m Representing the driving experience situation of the mth rescue personnel;
and solving a matching coefficient between the rescue vehicle and the rescue personnel by using a standardized Euclidean distance, wherein the method comprises the following steps of:
using a five-dimensional vector x c (x 11 ，x 12 ，x 13 ，x 14 ，x 15 ) Spatialization characterization set X c Wherein x is 11 Feature descriptors, x, of life span of rescue vehicle 12 Feature descriptor, x, for power type of rescue vehicle 13 Feature descriptor for model of rescue vehicle, x 14 Feature descriptor, x, for rescue vehicle brake sensitivity 15 A characteristic descriptor of power consumption of the c rescue vehicle per kilometer;
the service life of the rescue vehicle is divided into four characteristics of one year, one year to five years, five years to ten years and more than ten years, respectively corresponding to the characteristicsSyndrome descriptor x 11 The values are 1, 0.8, 0.6 and 0.5;
the power types of the rescue vehicle are divided into a pure electric vehicle, a hybrid electric vehicle and a fuel cell electric vehicle, and the corresponding feature descriptors x respectively 12 The values are 1, 0.6 and 0.5;
the model of the rescue vehicle is divided into a large model, a medium model and a small model, and the feature descriptors x respectively correspond to the model 13 1, 0.7 and 0.4.
Corresponding feature descriptor x with higher brake sensitivity of rescue vehicle 14 The closer to 1, x 14 ∈[0，1]。
Corresponding feature descriptor x for power consumption of rescue vehicle per kilometer 15 The closer to 1, x 15 ∈[0，1]。
In this embodiment, 6 candidate vehicles are taken as an example, and the feature descriptors of the 6 candidate vehicles are shown in table 5.
TABLE 5
Vehicle serial number x 11 x 12 x 13 x 14 x 14
1 1 0.5 1 0.8 0.8
2 1 1 0.7 0.9 0.6
3 0.7 1 1 0.7 0.8
4 0.4 1 1 0.6 0.4
5 1 1 0.4 0.7 0.6
6 0.7 0.6 1 0.7 0.7
Using a five-dimensional vector y m (x 21 ，x 22 ，x 23 ，x 24 ，x 25 ) Spatially characterizing, x 21 Feature descriptors, x, representing the age of rescue workers 22 Feature descriptor, x, representing the age of rescue personnel 23 Feature descriptor, x, representing driving capability of rescue personnel 24 Feature descriptors, x, representing physical and psychological conditions 25 A feature descriptor representing a driving experience situation of the rescuer;
the ages of the rescue workers are divided into young rescue workers according to 18-25, aged rescue workers according to 26-45 and middle-aged rescue workers according to 45-60, and the corresponding feature descriptors x respectively 21 0.6, 1, 0.8;
the service life of the rescue workers is divided into 1-3 years, 4-7 years, 8 years and more, and the service life is 1-3 years, and the characteristic descriptor x is a characteristic descriptor 22 Feature descriptor x of 0.4, 4-7 years of job entry 22 Feature descriptor x of 0.6, more than 8 years of job entry period 22 0.8;
feature descriptor x for driving capability condition of rescue workers 23 First-level index scoring G in evaluation index system for comprehensive ability quality of rescue workers Am Is substituted by the value of (2);
feature descriptor x of physical and psychological condition of rescue workers 24 First-level index scoring G in evaluation index system for comprehensive ability quality of rescue workers Bm Is substituted by the value of (2);
feature descriptor x of driving experience situation of rescue personnel 25 First-level index scoring G in evaluation index system for comprehensive ability quality of rescue workers Dm Is substituted by the value of (c).
The 6 rescue worker characterization sub-conditions are shown in table 6.
TABLE 6
Personnel serial number x 21 x 22 x 23 x 24 x 25
1 1 0.6 0.87 0.86 0.78
2 0.8 0.8 0.63 0.74 0.63
3 1 0.6 0.77 0.74 0.63
4 0.6 0.4 0.63 0.82 0.57
5 1 0.6 0.81 0.38 0.39
6 0.8 0.8 0.77 0.76 0.80
Applying a standardized Euler distance formula Solving for x c And y is m Wherein S is k Represents the standard deviation of the kth dimension, using D cm The matching coefficient of the c-th vehicle and the m-th rescue worker is represented. The smaller the Euler distance, the higher the matching degree, and conversely, the lower the matching degree.
The matching coefficients of the 6 candidate vehicles and the 6 rescue workers are arranged into a table as shown in table 7.
TABLE 7
S4, establishing an area road network model considering the matching coefficient and the road safety coefficient of the rescue vehicle and the rescue personnel, wherein the area road network model specifically comprises the following steps:
modeling a fault traffic network by adopting a graph theory method:
based on graph theory, all disaster fault points are converted into an undirected graph G= (V, L, T, W) according to the positions, wherein V represents a set of all traffic nodes in an area, and V i Represents all rescue starting point sets, v k Representing all the fault point sets, L representing all the traffic road segment sets, v ik The traffic road section from the rescue departure point i to the fault point k is represented by T, T is a time sequence set, T represents real-time update time of road conditions, each hour is divided into a time segment point, less than one hour is calculated according to one hour, update is carried out 24 times a day, W represents a road section weighting value set,the weighting length of a road section from the ith rescue starting point to the kth fault point after the matching coefficient of the rescue vehicle and the rescue personnel is considered, and the road section is blocked by a fixed road +. >Time consumption coefficient delta fusing real-time traffic index representation t Matching coefficient D of rescue vehicle and rescue personnel cm The road loss time from the ith rescue departure point to the kth fault point of the mth rescue personnel matched with the c rescue vehicle is +.>Wherein->The average driving speed of the c rescue vehicle is matched with the m rescue personnel.
The time consumption coefficient versus time period is shown in table 8.
TABLE 8
Suppose that rescue workers all start from the same rescue location, 16:00 time consumption coefficient delta when rescue personnel and rescue vehicle are dispatched to rescue t 1.1, the road resistances from the rescue starting point to the four fault points are respectively Kilometers.
The average driving speeds (kilometers per hour) of 6 rescue workers matched with 6 alternative rescue vehicles are shown in table 9.
TABLE 9
And solving the shortest running path length from the rescue starting point to the fault point in the area of each rescue vehicle under the condition that different rescue workers are matched by using a Dijkstra algorithm, and determining the road loss time from the rescue starting point to the fault point in the area of each rescue vehicle under the condition that different rescue workers are matched by combining the average driving speed.
The length of road loss after 6 rescue workers matched with 6 alternative rescue vehicles is shown in table 10.
Table 10
S5, establishing a multidimensional matching rescue model aiming at the optimal matching of rescue workers and the minimum comprehensive fault loss in the area, inputting rescue emergency degree, comprehensive rescue capability quality values of the rescue workers, matching coefficients of rescue vehicles and the rescue workers and road loss time length, and solving the multidimensional matching rescue model to obtain a depth matching emergency dispatching scheme.
The method comprises the following steps:
comprehensive rescue capability quality value H of rescue personnel optimally considered to be dispatched in matching of rescue personnel m Matching coefficient D with rescue vehicle cm Establishing a matching objective function:
max f 1 (H m ，D cm )＝∑(H m ·ω m +D cm ·ω cm )，
wherein omega m Representing the weight, omega of the total match of the comprehensive rescue ability quality cm Representing the weight omega of the total match of the matching coefficient of the rescue personnel and the rescue vehicle m +ω cm ＝1，f 1 (H m ，D cm ) Representing a rescue person matching function.
The values of the rescuer's matching functions are shown in table 11.
TABLE 11
The function value of a vehicle number 1 matched with a vehicle number 2 is 1.72,3, the function value of a vehicle number 1 matched with a vehicle number 1 is 1.72,4, the function value of a vehicle number 3 matched with a vehicle number 1.72,5 matched with a vehicle number 6 matched with a vehicle number 1.72,6 and the function value of a vehicle number 6 matched with a vehicle number 6 is 1.72, and the matching is preliminarily selected.
Rescue urgency A with minimum total loss and consideration of fault load k Road loss time to failure loadEstablishing an objective function with the lowest cost:
in the method, in the process of the invention,representing the total cost, t cm The length of time of the rescue support consumed by the c-th vehicle with the m-th rescuer is shown in table 12.
Table 12
t 11 1.3 t 21 1.4 t 31 1.3 t 41 1.6 t 51 1.0 t 61 1.7
t 12 1.2 t 22 1.3 t 32 1.2 t 42 1.6 t 52 0.8 t 62 1.5
t 13 1.4 t 23 1.6 t 33 0.8 t 43 1.7 t 53 0.7 t 63 1.5
t 14 1.1 t 24 1.7 t 34 1.0 t 44 1.5 t 54 0.8 t 64 1.2
t 15 1.2 t 25 1.6 t 35 1.1 t 45 1.4 t 55 1.2 t 65 1.7
t 16 1.2 t 26 1.5 t 36 1.3 t 46 1.8 t 56 1.3 t 66 1.6
The road loss time from the ith rescue departure point to the kth fault load is matched with the mth rescue worker for the c-th vehicle; q represents cost loss generated in each minute of load during fault, Q is 100 yuan/hour, and the higher the emergency degree of rescue is, the higher the cost loss of winding the fault load is; q (Q) c Represents cost loss generated by the c-th rescue vehicle per kilometer, Q c Taking 1 yuan/km, Q c0 Representing the running and maintenance costs generated by the fixation of the c-th vehicle. Q (Q) c0 Taking 100 yuan.
Through calculation, when the rescue vehicle 1 and the rescue vehicle 2 are matched with each other to go to the second fault place, the rescue vehicle 1 and the rescue vehicle 1 are matched with each other to go to the fourth fault place, the rescue vehicle 5 and the rescue vehicle 6 are matched with each other to go to the first fault place, and the rescue vehicle 6 are matched with each other to go to the third fault place to rescue, the multi-objective function is met, the maximum value of the matching function is 6.88, and the minimum value of the total cost is 1495.37.
The above is only a preferred embodiment of the present invention, and the protection scope of the present invention is not limited to the above examples, and all technical solutions belonging to the concept of the present invention belong to the protection scope of the present invention. It should be noted that modifications and adaptations to the invention without departing from the principles thereof are intended to be within the scope of the invention as set forth in the following claims.

Claims (7)

1. The multi-target power grid fault emergency rescue method considering man-vehicle feature matching is characterized by comprising the following steps of:
s1, acquiring the position of each fault power grid, determining rescue emergency degree of each fault power grid, and evaluating total load demand of each load after power grid faults in an area;
s2, primarily screening the alternative disaster relief vehicles according to the estimated total load demand of the load;
s3, based on the fault power grid position and the primary screening of the alternative disaster relief vehicles, establishing an evaluation index system of the comprehensive capability quality of the rescue workers, and obtaining the comprehensive rescue capability quality value of each rescue worker; establishing a matching model of the rescue vehicle and the rescue personnel to obtain a matching coefficient of the rescue vehicle and the rescue personnel;
s4, establishing an area road network model considering the matching coefficient and the road safety coefficient of the rescue vehicles and the rescue workers, solving the shortest running path length from the rescue starting point to the fault point in the area under the condition that the rescue vehicles are matched with different rescue workers by using a Dijkstra algorithm, and determining the road loss time from the rescue starting point to the fault point in the area under the condition that the rescue vehicles are matched with different rescue workers by combining the average driving speed;
S5, establishing a multidimensional matching rescue model aiming at the optimal matching of rescue workers and the minimum comprehensive fault loss in the area, inputting rescue emergency degree, comprehensive rescue capability quality values of the rescue workers, matching coefficients of rescue vehicles and the rescue workers and road loss time length, and solving the multidimensional matching rescue model to obtain a depth matching emergency dispatching scheme.
2. The multi-target power grid fault emergency rescue method considering man-vehicle feature matching as set forth in claim 1, wherein S1 is specifically:
obtaining the position of each fault power grid, and calculating the respective rescue emergency degree of K fault power grids by considering the health safety, economic loss and life quality influence degree of power failure on each load, wherein the rescue emergency degree of each fault power grid is A k ，
Wherein the health and safety influence degree, economic loss influence degree and life quality influence degree of each load are respectively a k 、β k Characterization of γk, ω a Representing the weight, omega, occupied by health safety in emergency degree of fault load β Indicating the weight, ω, of the economic loss in the emergency of the fault load γ Representing the weight, omega, of quality of life in fault load emergency a +ω β +ω γ ＝1；
Each fault power grid in evaluation areaIs the electricity requirement Q of (2) k And the total active power demand P of the kth faulty grid k The method comprises the steps of carrying out a first treatment on the surface of the Node voltage U of each fault power grid ik 0.95U is required to be satisfied ik ≤U k ≤1.05U ik Wherein U is k Rated voltage of each fault power grid; the line current flowing through each fault is I k The constraint condition is I k ≤I k,max Wherein I k,max Indicating the maximum current value allowed to pass through each faulty line.
3. The multi-target power grid fault emergency rescue method considering man-vehicle feature matching as set forth in claim 1, wherein S2 is specifically:
primarily screening the alternative disaster relief vehicle according to the following standard;
the primary screening of the alternative disaster relief vehicle requires the power supply capacity of the disaster relief vehicle to at least ensure the power requirement of a fault power grid and the back and forth power consumption requirement of the disaster relief vehicle, and ensures that the voltage and the current cannot cross the boundary;
vehicle electric quantity Q of screened c-th rescue vehicle EV，C Should at least satisfy min { Q EV，C }-Q Y，c ＞max{Q k }, wherein Q Y,c The total power consumption of the back and forth mileage of the first rescue vehicle is calculated; q (Q) k Representing the electric quantity demand of the kth fault electric network, and the discharging power P of the c-th rescue vehicle EV,C Should satisfy P EV,C ≥P k The method comprises the steps of carrying out a first treatment on the surface of the Input voltage U of important load connected to each rescue vehicle rc To meet U rc ≈U k ,0.95U ik ≤U rc ≤1.05U ik Input current I rc Is required to meet I rc ≈I k ,I rc ≤I k,max ；
State of charge S of rescue vehicle SOCK The S is required to be satisfied by 20 percent or less SOCK ≤100％；
Wherein S is SOCK (. Cndot.) represents the state of charge of the rescue vehicle, t cm The time length of the rescue support consumed by the c-th vehicle matched with the m-th rescue workers,the road loss time from the ith rescue starting point to the kth fault load is matched for the ith vehicle and the mth rescue personnel.
4. The multi-target power grid fault emergency rescue method considering the matching of the characteristics of the vehicles and the vehicles as claimed in claim 1, wherein in the step S3, based on the position of the fault power grid and the primary screening of the alternative disaster relief vehicles, an evaluation index system of the comprehensive capability quality of the rescue workers is established, and the comprehensive rescue capability quality value of each rescue worker is obtained specifically as follows:
establishing a first-level index, wherein the first-level index comprises a driving capability condition A, a physical and psychological quality condition B, a road safety consciousness C, a driving experience condition D and a comprehensive rescue capability E;
establishing a secondary index under the primary index, wherein the secondary index of the driving ability condition A comprises a traffic rule mastering condition A1, a driving skill mastering degree A2 and a road condition judging ability A3; the secondary indexes of the physical and psychological condition B comprise age B1, physiological disease history B2, mental disease history B3, mental condition B4, emotional intelligence condition B5 and basic ability B6; the secondary indexes of the road safety awareness C comprise safety driving awareness C1, safety driving habit C2 and safety driving tendency C3; the second-level indexes of the driving experience situation D comprise vehicle performance familiarity D1, regional road condition familiarity D2 and job entering years D3; the secondary indexes of the comprehensive rescue capability E comprise personnel treatment knowledge mastery degree E1, electrician safety knowledge mastery degree E2, maintenance technical capability E3 and communication capability E4;
Respectively calculating the comprehensive rescue ability quality value H of each of M rescue workers m ，
Wherein, the driving ability condition, physical and psychological quality of the mth rescue personnelScoring values of conditions, road safety awareness, driving experience conditions and comprehensive rescue ability are respectively G Am ,G Bm ,G Cm ,G Dm ,G Em To characterize; omega A Weight value omega representing driving ability condition accounting for first-level index score B Weight value omega representing primary index score of physical and psychological quality condition C Weight value omega representing grade of first-level index of road safety consciousness D Weight value omega representing driving experience condition accounting for first-level index score E Weight value omega representing first-level index score of comprehensive rescue capability A +ω B +ω C +ω D +ω E ＝1；
Scoring G of the driving ability of the mth rescue person Am Scoring by traffic mastery conditions G A1m Degree of mastery of driving skill G A2m Road condition judging ability G A3m Three scoring weights are obtained, G A1m ,G A2m ,G A3m ∈[0，1]；
Final score G for driving ability of mth rescuer Am The calculated expression of (2) is
Wherein omega A1 Weight value omega representing secondary index under condition of traffic rule mastering condition accounting for driving capability A2 Weight value, ω representing the second level index in the case where the driving skill grasping degree occupies the driving ability A3 Weight value omega representing secondary index under condition that road condition judging capability occupies driving capability A1 +ω A2 +ω A3 ＝1；
Figure condition score G of mth rescue worker Bm Scoring G by age interval degree B1m Shi Pingfen G for physiological diseases B2m History of mental illness score G B3m Psychological condition score G B4m Emotional mental condition score G B5m Basic ability score G B6m Weighting six items to obtain G B1m ,G B4m ,G B5m ,G B6m ∈[0，1]The method comprises the steps of carrying out a first treatment on the surface of the Considering the age of the rescue workers, dividing the rescue workers into three categories of young, strong and middle-aged, and dividing 18-25 years into young rescue workers, wherein the index G B1m 0.6;26-45 years old is a healthy person, the index G B1m 1 is shown in the specification; 45-60 years old is middle-aged rescuer, the index G B1m 0.8; physiological disease history score G B2m Taking 0 or 1, 0 if there is disease history, 1 if there is no disease history, and grading G of mental disease history B3m Taking 0 or 1, wherein the disease history is 0, and the disease history is 1;
figure of mind condition score G of mth driver Bm The calculated expression of (2) is:
wherein omega B1 Weight value omega representing secondary index under condition of age interval degree occupying physical and psychological quality B2 Weight value omega representing secondary index of physical and psychological quality of physiological disease history B3 Weight value, omega, representing secondary index of mental disease history in physical and psychological quality condition B4 Weight value omega representing secondary index of psychological condition B5 Weight value, omega representing secondary index of emotional intelligence condition in physical and psychological quality condition B6 Weight value omega representing secondary index under basic ability occupying physical and psychological quality condition B1 +ω B2 +ω B3 +ω B4 +ω B5 +ω B6 ＝1；
Road safety awareness score G of mth rescue worker Cm Awareness scoring by safe driving G C1m Safe driving habit G C2m Safe driving tendency G C3m Three scoring weights are obtained, G C1m ,G C2m ,G C3m ∈[0，1]；
Road safety awareness score G of mth rescue worker Cm The calculated expression of (2) is:
wherein omega C1 Weight value omega representing secondary index of safety driving awareness in road safety awareness C2 Weight value omega representing that safe driving habit occupies secondary index under road safety consciousness C3 Weight value omega representing that safe driving tendency occupies secondary index under road safety consciousness C1 +ω C2 +ω C3 ＝1；
Driving experience situation score G of mth rescue worker Dm Familiarity G by vehicle performance D1m Familiarity G of regional road conditions D2m Degree G of entering period D3m Three scoring weights are obtained, G D1m ,G D2m ,G D3m ∈[0，1]Entering period G D3m Dividing the time period of the first-aid staff into three time periods of 1-3 years, 4-7 years and 8 years and more, and the time period G of the first-aid staff of 1-3 years D3m The time interval G of the service life of the rescue workers of 0.4,4-7 years D3m The time interval G of the service life of the rescue workers of 0.6,8 years or more D3m 0.8, driving experience situation score G for mth rescuer Dm The expression of (2) is:
wherein omega D1 Weight value omega representing secondary index under condition that vehicle performance familiarity occupies driving experience D2 Regional road condition familiarity occupies weight value omega of secondary index under driving experience condition D3 Weight value omega representing secondary index under condition of taking up driving experience by time interval degree of job entering years D1 +ω D2 +ω D3 ＝1；
Comprehensive rescue ability score G of mth rescue personnel Em Degree of mastery score G by personnel first aid knowledge E1m Degree of mastery of electrician's safety knowledge G E2m Capability of maintenance technique G E3m Communication ability G E4m Weighting four terms to obtain G E1m ,G E2m ,G E3m ,G E4m ∈[0，1]；
Comprehensive rescue ability score G of mth rescue personnel Em The calculated expression of (2) is:
wherein omega E1 Weight value omega representing secondary index under comprehensive rescue capability of personnel first aid knowledge mastery degree E2 Weight value omega representing second-level index under comprehensive rescue capability of electrician safety knowledge mastery degree E3 Weight value omega representing secondary index under comprehensive rescue capability of maintenance technical capability E4 Weight omega representing secondary index under communication capacity accounting for comprehensive rescue capacity E1 +ω E2 +ω E3 +ω E4 ＝1。
5. The multi-target power grid fault emergency rescue method considering the characteristic matching of the vehicles and the vehicles according to claim 1, wherein in the step S3, a matching model of the rescue vehicles and the rescue workers is established, and the matching coefficients of the rescue vehicles and the rescue workers are obtained specifically as follows:
Establishing a matching model of the rescue vehicle and rescue personnel:
establishing a feature set X of a c-th rescue vehicle c ，X c ＝{X 1c ,X 2c ,X 3c ,X 4c ,X 5c }，X 1c X represents the service life of the c-th rescue vehicle 2c X represents the power type condition of the c-th rescue vehicle 3c Represents the model of the c rescue vehicle, X 4c Represents the brake sensitivity, X of the c-th rescue vehicle 5c Representing the power consumption of the c-th rescue vehicle per kilometer;
establishing a feature set Y of the mth rescue personnel m ，Y m ＝{Y 1m ,Y 2m ,Y 3m ,Y 4m ,Y 5m }，Y 1m Represents the age of the mth rescue worker, Y 2m Represents the service life condition of the mth rescue personnel, Y 3m Representing the driving ability of the mth rescue personnelIn case of Y 4m Representing the physical and psychological condition at position m, Y 5m Representing the driving experience situation of the mth rescue personnel;
and solving a matching coefficient between the rescue vehicle and the rescue personnel by using a standardized Euclidean distance, wherein the method comprises the following steps of:
using a five-dimensional vector x c (x 11 ,x 12 ,x 13 ,x 14 ,x 15 ) Spatialization characterization set X c Wherein x is 11 Feature descriptors, x, of life span of rescue vehicle 12 Feature descriptor, x, for power type of rescue vehicle 13 Feature descriptor for model of rescue vehicle, x 14 Feature descriptor, x, for rescue vehicle brake sensitivity 15 A characteristic descriptor of power consumption of the c rescue vehicle per kilometer;
the service life of the rescue vehicle is divided into four features of one year, one year to five years, five years to ten years and more than ten years, and the features are respectively corresponding to the feature descriptors x 11 The values are 1, 0.8, 0.6 and 0.5;
the power types of the rescue vehicle are divided into a pure electric vehicle, a hybrid electric vehicle and a fuel cell electric vehicle, and the corresponding feature descriptors x respectively 12 The values are 1, 0.6 and 0.5;
the model of the rescue vehicle is divided into a large model, a medium model and a small model, and the feature descriptors x respectively correspond to the model 13 1, 0.7 and 0.4;
using a five-dimensional vector y m (x 21 ,x 22 ,x 23 ,x 24 ,x 25 ) Spatially characterizing, x 21 Feature descriptors, x, representing the age of rescue workers 22 Feature descriptor, x, representing the age of rescue personnel 23 Feature descriptor, x, representing driving capability of rescue personnel 24 A feature descriptor representing a physical and psychological condition, x25 representing a feature descriptor of a driving experience situation of a rescuer;
the ages of the rescue workers are divided into young rescue workers according to 18-25, aged rescue workers according to 26-45 and middle-aged rescue workers according to 45-60, and the corresponding feature descriptors x respectively 21 0.6, 1, 0.8;
the service life of the rescue workers is divided into 1-3 years, 4-7 years, 8 years and more, and the service life is 1-3 years, and the characteristic descriptor x is a characteristic descriptor 22 Feature descriptor x of 0.4, 4-7 years of job entry 22 Feature descriptor x of 0.6, more than 8 years of job entry period 22 0.8;
feature descriptor x for driving capability condition of rescue workers 23 First-level index scoring G in evaluation index system for comprehensive ability quality of rescue workers Am Is substituted by the value of (2);
feature descriptor x of physical and psychological condition of rescue workers 24 First-level index scoring G in evaluation index system for comprehensive ability quality of rescue workers Bm Is substituted by the value of (2);
feature descriptor x of driving experience situation of rescue personnel 25 First-level index scoring G in evaluation index system for comprehensive ability quality of rescue workers Dm Is substituted by the value of (2);
applying a standardized Euler distance formulaSolving for x c And y is m Wherein S is k Represents the standard deviation of the kth dimension, using D cm The matching coefficient of the c-th vehicle and the m-th rescue worker is represented.
6. The multi-target power grid fault emergency rescue method considering the matching of the characteristics of the vehicles and the vehicles according to claim 1, wherein in the step S4, the building of the regional road network model considering the matching coefficient of the rescue vehicles and the rescue personnel and the road safety coefficient is specifically as follows:
modeling a fault traffic network by adopting a graph theory method:
based on graph theory, all disaster fault points are converted into an undirected graph G= (V, L, T, W) according to the positions, wherein V represents a set of all traffic nodes in an area, and V i Representation houseWith a set of rescue starting points, v k Representing all the fault point sets, L representing all the traffic road segment sets, v ik The traffic road section from the rescue departure point i to the fault point k is represented by T, T is a time sequence set, T represents real-time update time of road conditions, each hour is divided into a time segment point, less than one hour is calculated according to one hour, update is carried out 24 times a day, W represents a road section weighting value set,the weighting length of a road section from the ith rescue starting point to the kth fault point after the matching coefficient of the rescue vehicle and the rescue personnel is considered, and the road section is blocked by a fixed road +.>Time consumption coefficient delta fusing real-time traffic index representation t Matching coefficient D of rescue vehicle and rescue personnel cm The road loss time from the ith rescue departure point to the kth fault point of the mth rescue personnel matched with the c rescue vehicle is +.>Wherein->The average driving speed of the c rescue vehicle is matched with the m rescue personnel.
7. The multi-objective power grid fault emergency rescue method considering man-vehicle feature matching according to claim 1, wherein in S5, the building of the multi-dimensional matching rescue model aiming at optimal matching of rescue workers and minimum comprehensive loss of faults in an area after the power grid is damaged is specifically as follows:
comprehensive rescue capability quality value H of rescue personnel optimally considered to be dispatched in matching of rescue personnel m Matching coefficient D with rescue vehicle cm Establishing a matching objective function:
maxf 1 (H m ,D cm )＝∑(H m ·ω m +D cm ·ω cm )，
wherein omega m Representing the weight, omega of the total match of the comprehensive rescue ability quality cm Representing the weight omega of the total match of the matching coefficient of the rescue personnel and the rescue vehicle m +ω cm ＝1，f 1 (H m ,D cm ) Representing a rescue personnel matching function;
rescue urgency A with minimum total loss and consideration of fault load k Road loss time to failure loadEstablishing an objective function with the lowest cost:
in the method, in the process of the invention,representing the total cost, t cm Expressed as the rescue support time consumed by the c-th vehicle together with the m-th rescue worker,>the road loss time from the ith rescue departure point to the kth fault load is matched with the mth rescue worker for the c-th vehicle; q represents the cost penalty per minute that the load incurs in the event of a fault; q (Q) c Represents cost loss generated by the c-th rescue vehicle per kilometer, Q c0 Representing the running and maintenance costs generated by the fixation of the c-th vehicle.
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