CN112101754B - Electric power emergency guarantee capability evaluation method - Google Patents
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Abstract
The invention discloses a power emergency guarantee capability evaluation method, which relates to the technical field of emergency guarantee capability of important power supply units in cities, and comprises the following steps: s1, analyzing the reliability of different emergency measures; s2, establishing an emergency guarantee capability evaluation index system of the power supply unit; s3, establishing an important power supply user loss model through a power supply unit emergency guarantee capability evaluation index system; s4, judging the emergency guarantee capacity according to the emergency guarantee participation user loss condition calculated by the important power supply user loss model and through the emergency guarantee capacity grade, wherein the evaluation system and the model method provided by the invention can clearly and comprehensively reflect the emergency guarantee capacity, guide the planning and transformation of a power grid more comprehensively and reduce the power failure loss.
Description
Technical Field
The invention relates to the technical field of emergency guarantee capability of an important power supply unit in a city, in particular to an electric power emergency guarantee capability evaluation method.
Background
The method has the advantages of building an electric power emergency management platform, and establishing and perfecting an electric power emergency guarantee capability evaluation mechanism, so that the method has significance in improving the emergency guarantee capability of the electric power system. How to consider the evaluation of the important degree of importance of the urban important power supply unit and the emergency guarantee capability from the actual emergency guarantee situation so as to improve the emergency treatment capability of the urban power system, and further, the method has very important research significance for reducing the power failure loss to the maximum extent.
The existing research mainly focuses on the construction of an emergency index system, the construction of an emergency platform and the optimization strategy of a single emergency power source, for example, an emergency evaluation index system is established in the literature from the aspects of emergency early warning construction before an emergency accident, recovery means in the accident, recovery capacity after the accident and the like; or constructing an emergency guarantee platform from the lack of sampling information in a literature; then or a literature starts from actual emergency of the power enterprise, and an emergency evaluation index system is built from various aspects of personnel, materials and materials; the emergency guarantee system is also constructed from aspects of organization system, technology and system. The prior researches have less researches on the system emergency guarantee capability corresponding to specific emergency strategies and emergency means after the emergency event occurs, and the problems of losing the emergency power supply guarantee capability of an important unit in a city under the emergency power failure accident are solved, so far, related research reports are not seen, but the problems are often seen in actual emergency guarantee and cannot be avoided.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provides an electric power emergency guarantee capability evaluation method.
The aim of the invention is realized by the following technical scheme:
the electric power emergency guarantee capability evaluation method comprises the following steps:
s1, analyzing the reliability of different emergency measures;
s2, establishing an emergency guarantee capability evaluation index system of the power supply unit;
s3, establishing an important power supply user loss model through a power supply unit emergency guarantee capability evaluation index system;
and S4, judging the emergency guarantee capacity according to the emergency guarantee participation user loss condition calculated by the important power supply user loss model and through the emergency guarantee capacity grade.
Preferably, said step S3 comprises the substeps of
S3.1, calculating unit power loss of the important user power supply unit;
s3.2, calculating the comprehensive weight of the emergency guarantee capability evaluation index system of the power supply unit;
and S3.3, establishing an important power supply user loss model by combining the emergency guarantee capability evaluation index after the comprehensive weight is calculated with the single power loss of the important user power supply unit.
Preferably, the calculating the unit power loss of the important user power supply unit includes the following steps:
s3.1.1, determining a user importance level;
s3.1.2, establishing an importance degree model according to the importance level of the user;
s3.1.3, determining and calculating the unit power loss of the important user power supply unit according to the importance degree model and the unit time and unit power basic power failure loss.
Preferably, the calculating the comprehensive weight of the emergency guarantee capability evaluation index system of the power supply unit comprises the following steps:
s3.2.1, data normalization;
s3.2.1, obtaining subjective weights by solving through an analytic hierarchy process, and obtaining objective weights by solving through an inverse entropy weight process;
s2.2.2, determining the comprehensive weight of the emergency guarantee capability evaluation index system through the subjective weight and the objective weight.
Preferably, the importance degree model is:
wherein: a, a j ，β j ，ε j The influence factors of the loss of the j-th user load on life safety, economy, administration and specificity are respectively; w (w) a ，w β ，/>w ε Weights respectively occupied for life safety, economy and specificity in evaluation of importance of users and satisfies +.>
The calculating the unit power loss of the important user power supply unit comprises the following steps:
basic power failure loss C of unit power per unit time and unit degree of importance of user j ' determining a loss of Power value C per unit time per unit power for an important user j j I.e.
C j ＝I j C j '。
Preferably, the data normalization means that each index generates a "raw data" result, but the measurement units and grades of the "raw data" are different, and all the "raw data" must be converted into a unified standard, namely, index evaluation, and the specific method is as follows: for the forward index:
for the reverse index:
wherein: s is S j (k) To x jk Normalizing the processed data, x max The maximum value in the middle feature number of the jth cluster factor is the minimum value in the middle feature number of the jth cluster factor.
Preferably, the analytic hierarchy process includes the following:
constructing a judgment matrix, wherein A represents a target u i 、u j Representing factors, u ij Represents u i For u j Is of relative importance and is represented by u ij Forming an A-U judgment matrix P;
calculating importance ranking, and according to the judgment matrix, obtaining the maximum characteristic root lambda max The corresponding feature vector w, equation is as follows:
Pw＝λ max w
the feature vector w is normalized, namely the importance ranking of each evaluation factor, namely the weight distribution; consistency test, whether the weight distribution obtained above is reasonable or not, and consistency test is needed to be carried out on the judgment matrix, and the test using formula is as follows:
CR＝CI/RI
wherein CR is the random consistency ratio of the judgment matrix; CI is a general consistency index of the judgment matrix, and is given by the following formula, wherein CI= (lambda max-n)/(n-1), RI is an average random consistency index of the judgment matrix, and a subjective calculation result of the analytic hierarchy process is a subjective weight vector w' of an index set U:
w'＝[w 1 ',…,w i ',…,w n ']
wherein: i=1, … n; the method comprises the steps of carrying out a first treatment on the surface of the n is U in index set U i Is the number of (3); w (w) i Is U (U) i Subjective weight relative to U.
Preferably, the inverse entropy weighting method comprises the following steps:
the inverse entropy value is calculated by adopting the gravity center value difference of the same index in different partitions, t partitions are selected for the index set U, and a difference matrix is established
The gravity center value of the index Ui is defined as follows:
calculate each U i Inverse entropy h of (2) i ；
Wherein:determining an objective weight vector:
w”＝[w 1 ”,…,w i ”,…,w n ”]
in the middle ofIs U i Objective weights for U.
Preferably, the comprehensive weight of the emergency guarantee capability evaluation index system determined by subjective weight and objective weight comprises the following contents:
further determining the comprehensive weight vector of the index set U
w'＝[w 1 ',…,w i ',…,w n ']
In the middle ofIs U i The integrated weights for U.
Preferably, the important power supply user loss model is:
wherein: j=1, 2..n represents the number of important units in the emergency area; i=1, 2,3,4 represents the class of important units; q i Indicating the index of the total power loss amount in the index of the important unit class i, w j1 q i Representing the importance degree of the j-th important power supply unit in the category i under the total index system; same reason w j2 h、w j3 t、 w j4 p i 、w j5 y i 、w j6 l i Indicating the importance of the remaining indicators in category i with respect to the overall indicator system.
The beneficial effects of the invention are as follows:
the invention starts from measures such as network back supply, distributed power supply, demand side response, mobile emergency vehicle, ups and the like, and a set of evaluation index system for evaluating the emergency guarantee capability of the important power supply unit in the city is constructed by considering the states before and after the emergency guarantee of the power supply unit. Firstly, analyzing the reliability of different emergency measures from the aspects of response speed, response capacity, response grade and flexibility, then calculating the importance degree of the unit from the aspects of life safety, economy, political treatment, military and the like for a power supply unit to establish response outage loss, and finally establishing a complete evaluation model of the emergency guarantee outage loss of the important power supply unit by combining an anti-entropy weight method with an analytic hierarchy process. The evaluation system and the model method provided by the invention can clearly and comprehensively reflect the emergency guarantee capacity, more comprehensively guide the planning and transformation of the power grid and reduce the power failure loss.
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FIG. 1 is a flow chart of the method of the present invention.
Detailed Description
The technical solution of the present invention will be described in further detail with reference to the accompanying drawings, but the scope of the present invention is not limited to the following description.
As shown in fig. 1, the invention provides a power emergency guarantee capability evaluation method, which comprises the following steps:
s1, analyzing the reliability of different emergency measures;
firstly, analyzing the reliability of different emergency measures from the aspects of response speed, response capacity, response grade and mechanical flexibility according to the reliability analysis of the emergency guarantee measures, as shown in table 1:
TABLE 1
S2, establishing an emergency guarantee capability evaluation index system of the power supply unit;
according to the state before and after the emergency guarantee of the power supply unit, the power grid is combined with the characteristics of the power grid to construct an evaluation index system for the emergency guarantee capability of the power supply unit, as shown in table 2:
TABLE 2
S3, establishing an important power supply user loss model through a power supply unit emergency guarantee capability evaluation index system;
and (3) testing the emergency guarantee capability of the important power supply unit by using an IEEE33 node system, and dividing the importance level of the emergency unit user according to the method. P1 determines the importance level of the user:
the power outage loss of unit power is closely related to the importance degree, and the more important users, the larger the power outage loss of unit time and unit power, the more rapidly the power supply is required to be recovered. Therefore, to determine the outage loss per unit time and per unit power of a user, it is necessary to first analyze the importance of the outage loss, which needs to comprehensively consider the impact of the outage of the user on life safety, economic benefit, politics, military and the like. The influence factor is used to reflect the influence degree of the loss of the load on life safety, economic benefit, politics and military, and the influence degree is classified into 5 grades, and the importance degree is sequentially increased according to {1,2,3,4,5 }. For example: the hospital load has great influence on life safety, so the value can be 5; the loss of the load of a large-scale factory can cause larger economic loss, so the value can be 5;
p2 importance degree model establishment:
the epsilon is used for representing the specificity of the load, for example, the power failure loss of military enterprises is higher due to the specificity, and the gamma value can be 5, so that alpha, beta and beta can be compensatedDefects caused by the importance degree of the load cannot be completely reflected. Thus, for the jth power-down user, its importance level I j The formula can be expressed as:
wherein: a, a j ，β j ，ε j The influence factors of the loss of the j-th user load on life safety, economy, administration and specificity are respectively; w (w) a ，w β ，/>w ε Weights respectively occupied for life safety, economy and specificity in evaluation of importance of users and satisfies +.>
P3, calculating power failure loss per unit time and unit power:
basic power failure loss C of unit power per unit time and unit degree of importance of user j ' determining a loss of Power value C per unit time per unit power for an important user j j I.e.
C j ＝I j C j '
In the actual power emergency problem, the basic power outage loss C of unit time and unit power j The questionnaire can be designed and investigated according to the power outage characteristics of various users, and then the power outage loss conditions of various users are synthesized to finally determine the statistical value of the basic power outage loss.
And according to the power outage loss of the user in unit time and unit power under the corresponding importance level, a certain typical emergency guarantee resource allocation scheme is formulated by combining emergency measures, and is shown in the following table.
TABLE 3 Table 3
The scene is as follows: (a) The main power source of the whole network is lost due to the failure of the power source side, the power network rapidly cuts off the failure, and the expected failure recovery time is 6h; (b) the UPS of the critical power unit is immediately put into operation; (c) The power grid rapidly isolates other loads through the intelligent switch, emergency power supply is carried out on the important cells by using DG and ESS, and response time is 10min; (d) Reducing emergency load demand in the failure time by demand response; (e) The two mobile emergency power generation vehicles supply power according to a plan, and the response time is determined according to the geographic position and the traffic condition. Obtaining emergency load demand response diagrams of important power supply units of all levels according to an emergency strategy, and then calculating index data
Calculating the weight of the emergency index before and after the emergency event by adopting an anti-entropy weight method and an analytic hierarchy process, and normalizing the Q1 data:
each index generates a 'raw data' result, but the measurement units and grades among the 'raw data' are different, and all the 'raw data' must be converted into a unified standard, namely index evaluation. The specific method comprises the following steps:
for the forward index:
for the reverse index:
wherein: s is S j (k) To x jk Normalizing the processed data, x max The maximum value of the number of the middle features of the jth cluster factor is the jth cluster factorThe minimum of the number of features in (a).
Q2 analytic hierarchy process and inverse entropy weighting method weight solving:
analytical hierarchy process:
(1) And constructing a judgment matrix. Target u is denoted by A i 、u j Representing the factors. u (u) ij Represents u i For u j Is a relative importance value of (2). And is composed of u ij And forming an A-U judgment matrix P.
(2) An importance ranking is calculated. According to the judgment matrix, find out the maximum characteristic root lambda max The corresponding feature vector w. The equation is as follows:
Pw＝λ max w
the feature vector w is normalized, and the importance ranking of each evaluation factor, namely the weight distribution is achieved.
(3) And (5) consistency inspection. Whether the weight distribution obtained above is reasonable or not, and consistency test is needed to be carried out on the judgment matrix. The test uses the formula:
CR＝CI/RI
wherein CR is the random consistency ratio of the judgment matrix; CI is a general consistency index of the judgment matrix. It is given by CI= (λmax-n)/(n-1), RI is the average random consistency index of the judgment matrix, and RI values of the judgment matrix of 1-9 steps are shown in Table 4.
TABLE 4 values of the consistency index RI
The subjective calculation result of the analytic hierarchy process is the subjective weight vector w' of the index set U:
w'＝[w 1 ',…,w i ',…,w n ']
wherein: i=1, … n; the method comprises the steps of carrying out a first treatment on the surface of the n is U in index set U i Is the number of (3); w (w) i Is U (U) i Subjective weight relative to U.
Inverse entropy weighting method:
(1) The inverse entropy value is calculated by adopting the gravity center value difference of the same index in different partitions. For the index set U, t partitions are selected, and a difference matrix is established
The gravity center value of the index Ui is defined as follows:
calculate each U i Inverse entropy h of (2) i ；
Wherein:
(2) Determining an objective weight vector;
w”＝[w 1 ”,…,w i ”,…,w n ”]
in the middle ofIs U i Objective weights for U.
Q3 weight synthesis:
further determining the comprehensive weight vector of the index set U
w'＝[w 1 ',…,w i ',…,w n ']
In the middle ofIs U i For the comprehensive weight of U, the index weight of each importance level user is shown in Table 5.
TABLE 5
Calculating the user loss by combining the index with the unit power loss of the important user power supply unit:
because the main purpose of the power emergency process is to restore the power supply of multiple users as soon as possible, and the use value of the emergency power supply to important users is mainly represented by minimizing the loss caused by power failure, the objective function of the emergency power supply scheduling problem is the total power failure loss cost of the important power failure users. The total loss and total power loss, complete power loss time, continuous power supply time, emergency maximum satisfaction rate, emergency minimum satisfaction rate, emergency average satisfaction rate and other indexes are as follows
The weight loss of important users of the system, which is possibly caused after various emergency safeguard measures of various important units are used together, is as follows:
wherein: j=1, 2..n represents the number of important units in the emergency area; i=1, 2,3,4 represents the class of important units; q i Indicating the index of the total power loss amount in the index of the important unit class i, w j1 q i Representing the importance degree of the j-th important power supply unit in the category i under the total index system; same reason w j2 h、w j3 t、w j4 p i 、 w j5 y i 、w j6 l i Indicating the importance of the remaining indicators in category i with respect to the overall indicator system.
And S4, judging the emergency guarantee capacity according to the emergency guarantee participation user loss condition calculated by the important power supply user loss model and through the emergency guarantee capacity grade.
When calculating the emergency guarantee capacity of a certain area, firstly calculating the total loss of users under the condition that the area is completely powered off, and evaluating the failure loss after the accident occurs under the certain typical emergency guarantee configuration as shown in table 6
TABLE 6
Meanwhile, the full power loss condition is taken as the worst basis, the security capability level classification is established, for example, when emergency measures can enable the user loss after security to account for 0% -5% of the user loss in the full power loss condition, and the emergency security capability level is excellent. Specific grade differentiation is shown in table 7 below:
TABLE 7
The emergency guarantee capacity level can be judged according to the loss condition of the user after the emergency guarantee participation according to the emergency guarantee capacity level, as shown in table 8
TABLE 8
The results of the table show that the emergency guarantee capability of the developed area is relatively deficient, the emergency meeting rate of high-grade load is mainly deficient, the available force of the mobile emergency rescue vehicle, the energy storage or the distributed voltage can be properly increased in the future emergency guarantee capability construction, and meanwhile, available electric power emergency resources are reasonably scheduled to reduce the loss caused by power failure as much as possible.
The foregoing is merely a preferred embodiment of the invention, and it should be understood that the described embodiments are some, but not all, of the embodiments of the invention. All other embodiments, which can be made by one of ordinary skill in the art without undue burden on the person of ordinary skill in the art based on the embodiments of the present invention, are within the scope of the present invention. The invention is not limited to the forms disclosed herein, but is not to be construed as limited to the embodiments set forth herein, but is capable of use in various other combinations, modifications and environments and is capable of changes within the scope of the inventive concept, either as a result of the foregoing teachings or as a result of the knowledge or skills in the relevant art. And that modifications and variations which do not depart from the spirit and scope of the invention are intended to be within the scope of the appended claims.
Claims (1)
1. The electric power emergency guarantee capability evaluation method is characterized by comprising the following steps of:
s1, analyzing the reliability of different emergency measures;
s2, establishing an emergency guarantee capability evaluation index system of the power supply unit;
s3, establishing an important power supply user loss model through a power supply unit emergency guarantee capability evaluation index system;
s4, judging the emergency guarantee capacity according to the emergency guarantee participation user loss condition calculated by the important power supply user loss model and the emergency guarantee capacity grade;
said step S3 comprises the following substeps
S3.1, calculating unit power loss of the important user power supply unit;
s3.2, calculating the comprehensive weight of the emergency guarantee capability evaluation index system of the power supply unit;
s3.3, establishing an important power supply user loss model by combining the emergency guarantee capability evaluation index after comprehensive weight calculation with the unit power loss of the important user power supply unit;
the calculating the unit power loss of the important user power supply unit comprises the following steps:
s3.1.1, determining a user importance level;
s3.1.2, establishing an importance degree model according to the importance level of the user;
s3.1.3, determining and calculating the unit power loss of the important user power supply unit according to the importance degree model and the unit time and the unit power basic power failure loss;
the comprehensive weight of the emergency guarantee capability evaluation index system of the power supply unit comprises the following steps:
s3.2.1, data normalization;
s3.2.1, obtaining subjective weights by solving through an analytic hierarchy process, and obtaining objective weights by solving through an inverse entropy weight process;
s2.2.2, determining the comprehensive weight of the emergency guarantee capability evaluation index system through the subjective weight and the objective weight;
the importance degree model is as follows:
wherein: a, a j ，β j ，ε j Factors affecting life safety, economy, politics and specificity of losing jth user load respectively; w (w) a ，w β ，/>w ε Weights respectively occupied for life safety, economy and specificity in evaluation of importance of users and satisfies +.>
The calculating the unit power loss of the important user power supply unit comprises the following steps:
basic power failure loss C of unit power per unit time and unit degree of importance of user j ' determining a loss of Power value C per unit time and per unit power of an important user j j I.e.
C j ＝I j C j '；
The data normalization means that each index generates a 'raw data' result, but the measurement units and grades among the 'raw data' are different, and all the 'raw data' must be converted into a unified standard, namely index evaluation, and the specific method is as follows: for the forward index:
for the reverse index:
wherein: s is S j To x j Normalizing the processed data, x max For the maximum value in the number of the middle characteristics of the jth cluster factor, x min The minimum value in the number of the middle features of the jth cluster factor;
the analytic hierarchy process comprises the following contents:
constructing a judgment matrix, wherein A represents a target u i 、u j Representing factors, u ij Represents u i For u j And is composed of u ij Forming an A-U judgment matrix P; i=1, 2,3, …, n; j=1, 2,3, …, n;
calculating importance ranking, and according to the judgment matrix, obtaining the maximum characteristic root lambda max The corresponding eigenvector w, equation is as follows:
Pw＝λ max w
the feature vector w is normalized, namely the importance ranking of each evaluation factor, namely the weight distribution;
consistency test, whether the weight distribution obtained above is reasonable or not, and consistency test is needed to be carried out on the judgment matrix, and the test uses the formula:
CR＝CI/RI
wherein CR is the random consistency ratio of the judgment matrix; CI is a general consistency index of the judgment matrix, and is given by the following formula, wherein CI= (lambda max-n)/(n-1), RI is an average random consistency index of the judgment matrix, and a subjective calculation result of the analytic hierarchy process is a subjective weight vector w' of an index set U:
w'＝[w 1 ',…,w i ',…,w n ']
wherein: i=1, … n; n is an indexU in U collection i Is the number of (3); w (w) i Is U (U) i Subjective weight relative to U;
the anti-entropy weight method comprises the following steps:
the inverse entropy value is calculated by adopting the gravity center value difference of the same index in different partitions, t partitions are selected for the index set U, and a difference matrix is established
The gravity center value of the index Ui is defined as follows:
calculate each U i Inverse entropy h of (2) i ；
Wherein:
determining an objective weight vector:
w”＝[w 1 ”,…,w i ”,…,w n ”]
in the middle ofIs U i Objective weights for U;
the comprehensive weight for determining the emergency guarantee capability evaluation index system through the subjective weight and the objective weight comprises the following contents:
further determining the comprehensive weight vector of the index set U
w'＝[w 1 ',…,w i ',…,w n ']
In the middle ofIs U i Comprehensive weights for U;
the important power supply user loss model is as follows:
wherein: j=1, 2..n represents the number of important units in the emergency area; i=1, 2,3,4 represents the class of important units; q i Indicating the index of the total power loss amount in the index of the important unit class i, w j1 q i Representing the importance degree of the j-th important power supply unit in the category i under the total index system; same reason w j2 h i 、w j3 t i 、w j4 p i 、w j5 y i 、w j6 l i Indicating the importance of the remaining indicators in category i with respect to the overall indicator system.
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