CN106548284B - Operation regulation-oriented self-adaptive modular power grid safety evaluation method - Google Patents
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Abstract
The invention discloses a self-adaptive modular power grid safety early warning evaluation method for operation regulation, which comprises the following steps: constructing an alternating current-direct current hybrid power grid stability evaluation index system and forming a safety early warning evaluation module, and determining the initial module index composition by using expert experience based on a Delphi expert conference mechanism; obtaining an index evaluation result sequence in a stability evaluation index system and an evaluation result sequence of a safety early warning evaluation module; acquiring the association degree between the module evaluation result sequence and the whole index calculation result sequence based on a grey association analysis method; if the indexes with the relevance degrees exceeding the threshold value are different from the original indexes of the safety early warning evaluation module in composition, the indexes with high relevance degrees are selected to update the safety early warning evaluation module; otherwise, fusing the subjective weight and the objective weight of the indexes in the safety early warning evaluation module based on the minimum distance model to obtain a comprehensive weight, finally obtaining a comprehensive evaluation result of the safety early warning evaluation module, and giving out the safety early warning of the power grid.
Description
Technical Field
The invention belongs to the field of online operation safety evaluation of power systems, and particularly relates to an operation regulation-oriented self-adaptive modular power grid safety early warning evaluation method.
Background
With the rapid development of an extra-high voltage alternating current-direct current hybrid power grid, the form and the characteristics of the power grid face deep changes, on one hand, the electrical connection of the whole power grid is gradually tight, the coupling relation between sections is more complex, the safety and stability level is mutually restricted, the structure and the trend mode of the power grid are changed greatly, the problems of supply, demand, safety and the like need to be considered more factors, and higher requirements are provided for the lean and integrated level of analysis early warning and operation control of a power grid system; on the other hand, the technical level and complexity of the operation of the power grid are higher and higher, more and more factors are used for inducing complex faults of the power grid, the complex faults of the power grid seriously endanger the safe and stable operation of the power grid, and the accurate and rapid disposal of the complex faults of the power grid puts higher requirements on the power regulation and control work. Therefore, the effective comprehensive evaluation method for the operation safety of the power grid has important significance for online regulation and control early warning and prevention of large-area power failure accidents.
However, the existing power grid operation safety evaluation method is poor in pertinence to the problems concerned by online regulation and control operation, and the main reasons are as follows: the existing power grid safety evaluation index system only considers unilateral factors influencing the power grid operation safety, and has limited power grid operation risk reflection degree; secondly, the currently and generally adopted comprehensive evaluation method is seriously influenced by subjective factors and is difficult to objectively reflect the operation risk of the power grid; and thirdly, the existing evaluation system and the dispatching automation system lack interaction, so that the running information of the power grid is difficult to fully dig and the running risk of the power grid under the complex running condition is effectively reflected.
Authors such as zhangguohua in power grid technology 2009 (08): 30-34, an index system and a method for power grid safety evaluation, wherein a set of complete power grid safety evaluation index system is provided, the index system comprises 5 categories of safe power supply capacity, static voltage safety, topological structure vulnerability, transient safety and risk index of a power grid, the evaluation system can effectively reflect safety factors of all aspects of the power grid, but lacks pertinence to expected fault scenes and typical emergency situations of the power grid, and has little reference significance to online scheduling; the authors of wanbo et al have in grid technology 2011 (01): 40-45 'complex electric power system safety risk assessment system based on multi-factor analysis', a set of electric power system safety risk assessment system with objectivity, practicability and applicability is established by using an accident tree analysis and hierarchical analysis method, and comprehensive evaluation of hierarchical indexes is realized by using a hierarchical analysis method. The author of the construction of the Lei-Lai is in the power system automation 2013 (10): 92-97 'dispatching operation-oriented risk index system, evaluation method and application strategy of power grid security risk management control system (II)' an index system combining out-of-limit driving type risk and event driving type risk is established in the text, however, a targeted comprehensive evaluation method is lacked, and the power grid operation risk under the complex operation condition is difficult to effectively characterize.
The typical methods have good reference and inspiration significance for power grid operation safety evaluation, but due to the limitations of respective consideration, the online regulation and control early warning problem is not ideal enough.
Disclosure of Invention
Aiming at the defects in the prior art, the invention provides an operation regulation-oriented self-adaptive modular power grid safety early warning evaluation method, aiming at solving the technical problem that the existing evaluation method cannot effectively reflect the power grid operation risk under the complex operation condition because only unilateral factors are considered in an evaluation system, the evaluation method is subjectively influenced and the interaction with a dispatching system is lacked in the prior art.
In order to achieve the purpose, the invention provides an operation regulation-oriented self-adaptive modular power grid safety early warning evaluation method, which comprises the following steps of:
(1) constructing a stability evaluation index system of the alternating current-direct current hybrid power grid, and determining the initial index composition of a pth safety early warning evaluation module according to the tightness degree of indexes in the stability evaluation index system and the pth safety early warning evaluation module;
(2) obtaining the subjective weight of the initial index in the pth safety early warning evaluation module by using an analytic hierarchy process;
(3) obtaining an evaluation result of indexes in a stability evaluation index system according to the power grid operation information, and obtaining an evaluation result of a pth safety early warning evaluation module according to the evaluation result of the indexes in the stability evaluation index system and the subjective weight of each index in the pth safety early warning evaluation module;
(4) repeating the step (3) after the interval time T until the step (3) is repeated K times to obtain an evaluation result sequence of indexes in the stability evaluation index system and an evaluation result sequence of the pth safety early warning evaluation module;
(5) obtaining the association degree between the pth safety early warning evaluation module and the index in the stability evaluation index system based on a grey association analysis method according to the evaluation result sequence of the index in the stability evaluation index system and the evaluation result sequence of the pth safety early warning evaluation module;
(6) and sequencing the relevance degrees in a descending order, and judging whether the indexes of the stability evaluation index system corresponding to the first n relevance degrees are different from the indexes of the p-th safety early warning evaluation module. If the correlation degrees are different, replacing the indexes of the p-th safety early warning evaluation module with the indexes of the stability evaluation index system corresponding to the first n correlation degrees, and entering the step (3); otherwise, entering the step (7);
(7) obtaining objective weight of indexes in the pth safety early warning evaluation module according to the relevance of the indexes in the pth safety early warning evaluation module updated at the last time, and obtaining comprehensive weight of the indexes in the pth safety early warning evaluation module according to the objective weight and the subjective weight of the indexes in the pth safety early warning evaluation module;
(8) comprehensive weight of indexes in the pth safety early warning evaluation module and a comprehensive evaluation result of the pth safety early warning evaluation module of an index evaluation result in the pth safety early warning evaluation module updated last time are utilized;
the system comprises a power grid, a power failure early warning evaluation module, a low-voltage early warning evaluation module, an overvoltage early warning evaluation module, a line shutdown early warning evaluation module, a section tidal current transfer early warning evaluation module, an alternating current-direct current hybrid channel fault early warning evaluation module, a frequency early warning evaluation module, a power shortage early warning evaluation module, a power excess early warning evaluation module, a transformer safety early warning evaluation module, a system low-frequency oscillation early warning evaluation module and a transient process early warning evaluation module, wherein T is determined according to the updating time of power grid operation information, K is more than or equal to 20p, I, II, III, IV, V, VI, VII, XI, I, VIII and XI.
Further, the step (2) of obtaining the subjective weight of the initial index in the pth safety early warning evaluation module by using an analytic hierarchy process comprises the following steps:
(21) constructing a judgment matrix of indexes contained in the pth safety early warning evaluation module according to the importance degree of the indexes contained in the pth safety early warning evaluation module
(22) According to the formula
Obtaining the subjective weight w of the index contained in the pth safety early warning evaluation module1i；
(23) According to the formula
Obtaining the random consistency ratio of a judgment matrix A of the pth safety early warning evaluation module, if CR is less than 0.1, considering that the judgment matrix has satisfactory consistency, and if not, reconstructing the judgment matrix;
in the formula, A represents a judgment matrix of indexes contained in the pth safety early warning evaluation module, and element aijIs an index B contained in the pth safety early warning evaluation moduleiAnd the index B contained in the pth safety early warning evaluation modulejThe relative importance degree is that i is more than or equal to 1 and less than or equal to n, j is more than or equal to 1 and less than or equal to n, and n is the index number contained in the pth safety early warning evaluation module; RI is average consistency index, related standard data can be searched to obtain RI, CI is consistency index, and the RI is average consistency index
Is obtained according to the formula
Obtaining an approximation lambda of the maximum characteristic root of the decision matrixmax，W1＝(w11,...,w1i,...,w1n)TIs an objective weight vector, w, of an index contained in the item p safety precaution evaluation module1iAnd the subjective weight of the index contained in the pth safety early warning evaluation module.
Further, the step (3) of obtaining the subjective weight of each index in the pth safety early warning evaluation module includes the following steps:
(31) judging whether each index in the pth safety early warning evaluation module is the same as each initial index in the pth safety early warning evaluation module during the last updating, if so, the subjective weight of each index in the pth safety early warning evaluation module is the subjective weight of each initial index in the pth safety early warning evaluation module, and if not, entering the step (32);
(32) and (3) obtaining the subjective weight of each index in the pth safety early warning evaluation module according to the subjective weight of each initial index in the pth safety early warning evaluation module in the step (2) and the correlation degree of each index in the pth safety early warning evaluation module.
Further, the step (32) of obtaining the subjective weight of each index in the pth safety early warning evaluation module includes the following steps:
(321) the indexes in the pth safety early warning evaluation module are sorted from big to small according to the degree of association as B1...Bu...Bn；
(322) B 'sorting the initial indexes in the p-th safety early warning evaluation module in the step (2) from big to small according to subjective weight'1...B'u...B'n；
(323) Index B 'in item p safety early warning evaluation module'uThe subjective weight of the evaluation module is equal to the initial index B in the pth safety early warning evaluation moduleu(ii) subjective weight of;
in the formula, u is more than or equal to 1 and less than or equal to n, and n is the index number contained in the pth safety early warning evaluation module.
Further, the step (5) of obtaining the correlation degree between the p-th safety early warning evaluation module and the indexes in the stability evaluation index system based on a grey correlation analysis method comprises the following steps:
(51) according to the formula
Nondimensionalizing the evaluation result sequence of indexes in stability evaluation index system
The evaluation result sequence of the pth safety early warning evaluation module is dimensionless;
(52) according to the formula
Calculating the correlation coefficient between the kth evaluation result in the index in the stability evaluation index system and the kth evaluation result in the evaluation result sequence of the pth safety early warning evaluation module,
(53) according to the formula
Obtaining the correlation degree r between the pth safety early warning evaluation module and the indexes in the stability evaluation index systemm；
Xm(k) The k item of the evaluation result sequence of indexes in the stability evaluation index system, Y (k) is the k item of the evaluation result sequence of the p item safety early warning evaluation module, and xm(k) the k item of the evaluation result sequence of the indexes in the stability evaluation index system after non-dimensionalization, y (k) the k item of the evaluation result sequence of the safety early warning evaluation module after the p item of the safety early warning evaluation system after non-dimensionalization, rho is called a resolution coefficient, ξm(k) And M is 1,2, …, M, K is 1,2, …, K is sequence length, and M is the number of indexes contained in the stability index system.
Go toStep (7) is according to the formula
Obtaining the comprehensive weight w of the indexes of the pth safety early warning evaluation modulei，αtiUsing t method to obtain linear combination coefficient, w of index weight of p-th safety early warning evaluation moduletiIn order to obtain the weight of the indexes of the pth safety early warning evaluation module by using a t method, according to a formula
obtaining alphatiAnd (3) obtaining a linear combination coefficient of the weight of the index of the pth safety early warning evaluation module by using a t method, wherein t is I, II is an analytic hierarchy process, and II is a gray correlation analysis process.
In general, compared with the prior art, the above technical concept according to the present invention mainly has the following technical advantages:
1. the main task of online regulation and control operation is to control the operation state of a power grid in real time, and effectively ensure the safe and stable operation of the power grid. The conventional power grid safety evaluation only carries out power grid safety early warning through a single index, the power grid emergency state is not completely reflected, the correlation influence among the indexes is difficult to reflect, and objective comprehensive judgment cannot be given.
2. The method comprises the steps of obtaining power grid operation parameters in real time, obtaining an evaluation result of a stability evaluation index, obtaining an evaluation result of a safety early warning evaluation module according to the evaluation result of the stability evaluation index, obtaining a relevance ranking result between the safety early warning evaluation module and each index in a stability evaluation index system according to the evaluation result, realizing real-time updating of index composition of the safety early warning module, realizing self-adaptive adjustment of the modules by utilizing a historical evaluation result sequence, having strong adaptability to the complex operation environment of the power grid, closely interacting with the existing dispatching automation system, and fully utilizing the online computing capability of a dispatching automation platform.
3. The subjective weight of the safety early warning module is obtained by adopting an analytic hierarchy process, the objective weight of the safety early warning module is obtained by utilizing a grey analysis method based on the relevance, and the minimum distance model is utilized to realize the organic integration of the subjective weight and the objective weight, so that the influence of subjective factors on the evaluation method can be effectively improved, and the evaluation result is more in line with the actual situation.
Drawings
Fig. 1 is a flowchart of an operation regulation-oriented adaptive modular power grid safety early warning evaluation method provided by the invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
As shown in fig. 1, the operation regulation-oriented adaptive modular power grid safety early warning evaluation method provided by the invention comprises the following steps:
(1) and constructing a stability evaluation index system of the alternating current-direct current hybrid power grid, and determining the initial index composition of the pth safety early warning evaluation module according to the closeness degree of indexes in the stability evaluation index system and the pth safety early warning evaluation module.
The stability evaluation index system for constructing the alternating current-direct current hybrid power grid refers to the power grid technology 2009(08) by authors such as zhangguohua: 30-34, an index system and a method for power grid safety evaluation, wherein a complete power grid safety evaluation index system is provided to effectively reflect safety factors of each aspect of a power grid, and a stability evaluation index system is determined in relation to five aspects of safety power supply capacity, static voltage safety, topological structure vulnerability, transient safety and risk indexes of the power grid, and the stability evaluation index system comprises M indexes.
Starting from a fault and an emergency scene concerned by power grid dispatching, critical state representation factors of the fault and the emergency scene are analyzed, and according to indexes which are closely related to the representation factors in a stability evaluation index system, the indexes form a safety early warning evaluation module. By comprehensively evaluating indexes related to the characterization factors, interaction among the characterization factors can be effectively reflected, and pointed, point-by-point and surface comprehensive evaluation is realized, so that the critical degree of the bad and urgent state of the power grid is effectively reflected.
According to the dispatching requirement, the method comprises the steps of I, II, III, IV, V, VI, VII, VIII, IX, X and XI, wherein I is a low-voltage early warning evaluation module, II is an overvoltage early warning evaluation module, III is a line shutdown early warning evaluation module, IV is a section power flow transfer early warning evaluation module, V is an alternating current-direct current parallel connection channel fault early warning evaluation module, VI is a frequency early warning evaluation module, VII is a power shortage early warning evaluation module, VIII is a power excess early warning evaluation module, IX is a transformer safety early warning evaluation module, X is a system low-frequency oscillation early warning evaluation module, and XI is a transient process early warning evaluation module.
Because the safety early warning evaluation module is composed of highly-associated indexes reflecting risks in a typical aspect of safe operation of a power grid, the indexes in the safety early warning evaluation module are determined by utilizing expert experience based on a Delphi expert conference mechanism, experts in the power industry are introduced, and especially experts with operation regulation and control experience perform professional evaluation on the relevance of the indexes formed by the modules according to own knowledge and experience and determine the indexes in the safety early warning evaluation module.
For example, for a power grid low-voltage early warning module, the criticality of the power grid in a low-voltage state is difficult to reflect in an all-around manner through simple evaluation of the power grid measured voltage, and it is necessary to comprehensively consider 8 indexes of power grid load, reactive compensation, associated power grid low-voltage margin, voltage variation trend, voltage deviation duration, total reactive power shortage, power supply surplus and load variation trend which are closely related to the power grid operating voltage risk for comprehensive analysis, so as to realize objective comprehensive evaluation of the power grid low-voltage risk.
(2) The method for obtaining the subjective weight of the initial index in the pth safety early warning evaluation module by using the analytic hierarchy process comprises the following steps:
(21) constructing a judgment matrix of the initial indexes contained in the pth safety early warning evaluation module according to the importance degree of the initial indexes contained in the pth safety early warning evaluation module
In the formula, A represents a judgment matrix of an initial index contained in the pth safety early warning evaluation module, and element aijIs an initial index B contained in the pth safety early warning evaluation moduleiAnd the initial index B contained in the pth safety early warning evaluation modulejThe relative importance degree is that i is more than or equal to 1 and less than or equal to n, j is more than or equal to 1 and less than or equal to n, and n is the initial index number contained in the pth safety early warning evaluation module.
(22) Obtaining the subjective weight w of the initial index contained in the pth safety early warning evaluation module by adopting a root finding method1i。
According to the formula
Obtaining the subjective weight w of the initial index contained in the pth safety early warning evaluation module1i；
(23) According to the formula
And obtaining the random consistency ratio of the judgment matrix A of the pth safety early warning evaluation module, if CR is less than 0.1, considering that the judgment matrix has satisfactory consistency, and if not, reconstructing the judgment matrix.
In the formula, RI is average consistency index, related standard data can be searched to obtain RI, CI is consistency index, and the RI is average consistency index
Is obtained according to the formula
Obtaining an approximation lambda of the maximum characteristic root of the decision matrixmax，W1＝(w11,...,w1i,...,w1n)TIs an objective weight vector of an initial index contained in the pth safety early warning evaluation module, A is a judgment matrix of the initial index contained in the pth safety early warning evaluation module, w1iIs an initial index B contained in the pth safety early warning evaluation moduleiN is the index number contained in the pth safety early warning evaluation module.
(3) Obtaining an evaluation result of indexes in a stability evaluation index system according to the power grid operation information, and obtaining an evaluation result of a pth safety early warning evaluation module according to the evaluation result of the indexes in the stability evaluation index system and the subjective weight of each index in the pth safety early warning evaluation module;
and (3) determining the subjective weight of each index in the pth safety early warning evaluation module according to the weight of each initial index in the pth safety early warning evaluation module in the step (2) and the association degree of each index in the pth safety early warning evaluation module.
Indexes in the stability evaluation index system can be calculated on line according to the index algorithm to obtain the evaluation result X of the indexmM is more than or equal to 1 and less than or equal to M, and M is the number of indexes contained in the stability evaluation index system
Obtaining the evaluation result of the index in the stability evaluation index system according to the power grid operation information and obtaining the evaluation result Xa of the index in the pth safety early warning evaluation moduleiIf the index B in the pth safety early warning evaluation moduleiThe same as the index in the stability evaluation index system, and the index B in the p-th safety early warning evaluation moduleiThe evaluation result of (2) is equal to the evaluation result of the index in the stability evaluation index system.
If the indexes in the pth safety early warning evaluation module are replaced according to the degree of association, the indexes in the pth safety early warning evaluation module are different from the initial indexes of the pth safety early warning evaluation module in the step (2), and the indexes in the pth safety early warning evaluation module are larger according to the degree of associationTo a small rank of B1...Bu...BnAnd sorting the initial indexes in the p-th safety early warning evaluation module in the step (2) from big to small according to subjective weight'1...B'u...B'nAnd index B 'in the item p safety early warning evaluation module'uThe subjective weight of the evaluation module is equal to the initial index B in the pth safety early warning evaluation moduleuAnd u is more than or equal to 1 and less than or equal to n, and n is the index number contained in the pth safety early warning evaluation module.
According to the formula
And obtaining an evaluation result y' of the p-th safety early warning evaluation module. In the formula, XaiThe evaluation result of the indexes in the pth safety early warning evaluation module, w1iIs the objective weight of the index in the pth safety early warning evaluation module, and n is the index B in the pth safety early warning evaluation moduleiThe number of the cells.
In order to fully reflect different importance degrees of module indexes, subjective weights of all indexes are calculated by adopting an analytic hierarchy process, and effective integration of index evaluation results is realized by adopting weighted average to obtain the comprehensive evaluation result of the safety early warning evaluation module.
(4) Repeating the step (3) after the interval time T until the step (3) is repeated K times to obtain an evaluation result sequence X of indexes in the stability evaluation index systemm＝{Xm(k) The evaluation result sequence Y of the safety precaution evaluation module of item p and the item | K ═ 1,2, …, K }, M ═ 1,2, …, M ═ Y (K) | K ═ 1,2, …, K }; wherein K is the sequence length, and M is the number of indexes contained in the stability index system. Wherein, T is determined according to the updating time of the power grid operation information, and K is more than or equal to 20 according to the requirement of engineering application.
(5) The method comprises the following steps of obtaining the association degree between the pth safety early warning evaluation module and the indexes in the stability evaluation index system based on a grey association analysis method according to the evaluation result sequence of the indexes in the stability evaluation index system and the evaluation result sequence of the pth safety early warning evaluation module, wherein the method comprises the following steps:
(51) and carrying out non-dimensionalization on the evaluation result sequence of the indexes in the stability evaluation index system and the evaluation result sequence of the pth safety early warning evaluation module.
Because the data in the factor columns in the system may be different in dimension, it is inconvenient to compare or it is difficult to obtain correct conclusion in comparison. Therefore, when the gray correlation analysis is performed, the data is subjected to non-dimensionalization processing.
According to the formula
Nondimensionalizing the evaluation result sequence of indexes in stability evaluation index system
Nondimensionalization of evaluation result sequence of item p safety early warning evaluation module, Xm(k) The k item of the evaluation result sequence of indexes in the stability evaluation index system, Y (k) is the k item of the evaluation result sequence of the p item safety early warning evaluation module, and xm(k) The evaluation result sequence is the kth item of the index in the stability evaluation index system after non-dimensionalization, y (K) is the kth item of the evaluation result sequence of the safety precaution evaluation module after p item after non-dimensionalization, M is 1,2, …, M, K is 1,2, …, K is the sequence length, and M is the number of indexes contained in the stability index system.
(52) Calculating a correlation coefficient between the kth evaluation result in the indexes in the stability evaluation index system and the kth evaluation result in the evaluation result sequence of the pth safety early warning evaluation module:
according to the formula
And calculating a correlation coefficient, wherein rho is called a resolution coefficient, the smaller rho is, the larger resolution is, and the value interval of the general rho is (0,1), and the specific value can be determined according to the situation. When ρ ≦ 0.5463, the resolution is best, and ρ is usually 0.5, xi(k) The k-th evaluation result of the indexes in the stability evaluation index system after non-dimensionalization is obtained, and the k-th evaluation result of the safety early warning evaluation module after y (k) is non-dimensionalized is obtained.
(53) And obtaining the correlation degree between the p-th safety early warning evaluation module and the indexes in the stability evaluation index system.
Because the correlation coefficient is the correlation degree value of the pth safety early warning evaluation module and the indexes in the stability evaluation index system at each moment, the number of the correlation coefficient is more than one, and the information is too dispersed to be convenient for overall comparison. Therefore, it is necessary to integrate the correlation coefficients of each time into one value, i.e. to calculate the average value of the correlation coefficients, which is used as the number representation of the correlation degree between the pth safety early warning evaluation module and the indexes in the stability evaluation index system, and the pth safety early warning evaluation module and the index C in the stability evaluation index systemmDegree of inter-relation rmThe formula is as follows:
in the formula, ξm(k) And the K is 1,2, and K is a correlation coefficient of the K evaluation result in the index in the stability evaluation index system and the K evaluation result in the evaluation result sequence of the p-th safety early warning evaluation module.
(6) And sequencing the relevance degrees in a descending order, and judging whether the indexes of the stability evaluation index system corresponding to the first n relevance degrees are different from the indexes of the p-th safety early warning evaluation module. If the correlation degrees are different, replacing the indexes of the p-th safety early warning evaluation module with the indexes of the stability evaluation index system corresponding to the first n correlation degrees, and entering the step (3); otherwise, entering the step (7);
and (4) sorting according to the correlation calculation result in the step (4), wherein the higher the correlation is, the higher the correlation degree between the p-th safety early warning module and the index in the stability evaluation index system is, if the indexes of the stability evaluation index system corresponding to the first n correlations are the same as the indexes of the p-th safety early warning evaluation module, the indexes in the stability evaluation index system corresponding to the high correlation degree are substituted for the indexes in the p-th safety early warning module, so that the high correlation index self-adaption adjustment formed by the safety early warning evaluation modules can be realized, the safety early warning evaluation modules ensure the high correlation of the module indexes in different modes, and the adaptability to the complex operation environment of the power grid is improved.
(7) And obtaining the objective weight of the indexes in the pth safety early warning evaluation module according to the relevance of the indexes in the pth safety early warning evaluation module updated at the last time, and obtaining the comprehensive weight of the indexes in the pth safety early warning evaluation module according to the objective weight and the subjective weight of the indexes in the pth safety early warning evaluation module.
And the relevance in the step (4) can substantially reflect the relative importance degree of each index in the pth safety early warning evaluation module, namely the objective weight of the index. The relevance of each index of the p-th item of safety early warning evaluation module index updated at the last time is r'iI is more than or equal to 1 and less than or equal to n, and n is the index number contained in the pth safety early warning evaluation module, the objective weight can be calculated through normalization
And obtaining the objective weight of each index in the pth safety early warning evaluation module.
In order to realize the objective and real evaluation of the pth safety early warning evaluation module, a minimum distance model is adopted to realize the effective fusion of subjective weight and objective weight. The minimum distance model can be expressed as:
in the formula: s ═ I, II, t ═ I, II, I is an analytic hierarchy process, II is a grey correlation analysis process, w istiTo obtain the weight of the index of the pth safety precaution evaluation module by using the t method, wsito obtain the weight, alpha, of the index of the pth safety precaution evaluation module by using the s methodtObtaining a linear combination coefficient of the weight of the indexes of the pth safety early warning evaluation module by using a t method;
the optimized first derivative condition of the minimum distance model is as follows:
the matrix form of the optimized first derivative condition corresponding to the system of linear equations is:
thereby obtaining the linear combination coefficient α of the weight of the index of the pth safety early warning evaluation module obtained by using the t methodti。
Then according to
Obtaining the comprehensive weight w of the indexes of the pth safety early warning evaluation modulei。
The step is an optimization process of cross-combining multiple weights to obtain the most satisfactory weight which is consistent or compromised, and objective and real evaluation of the module is realized.
(8) Comprehensive weight w of indexes in the pth safety early warning evaluation moduleiAnd index evaluation result Xa 'in the p-th item of safety early warning evaluation module updated at last time'iAnd obtaining a comprehensive evaluation result of the pth safety early warning evaluation module, wherein the formula is as follows:
the comprehensive evaluation result of the safety early warning evaluation module can represent the critical degree of the bad and urgent state of the power grid.
The index composition of the safety early warning evaluation module is determined based on the indexes in the stability evaluation index system and according to the correlation degree of the indexes in the stability evaluation index system and the safety early warning evaluation module, and the safety early warning evaluation module can effectively evaluate the capability of the power grid for dealing with the emergency or fault condition; obtaining an evaluation result of an index in a stability evaluation index system and an evaluation result of a safety early warning evaluation module according to the online operation parameters of the power grid, obtaining the correlation degree between the index in the stability evaluation index system and the safety early warning evaluation module by using a grey correlation degree-based analysis method, and updating the index in the safety early warning evaluation module according to the correlation degree, so that the method provided by the invention has stronger adaptability to the complex operation environment of the power grid, and realizes more reasonable evaluation according with the actual situation; and subjective weight of the indexes in the safety early warning evaluation module is obtained by utilizing an analytic hierarchy process, and comprehensive weight of the indexes is obtained according to the subjective weight and the objective weight of the indexes in the safety early warning evaluation module, so that the evaluation result is more in line with the actual situation.
It will be understood by those skilled in the art that the foregoing is only a preferred embodiment of the present invention, and is not intended to limit the invention, and that any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the scope of the present invention.
Claims (1)
1. An operation regulation-oriented self-adaptive modular power grid safety evaluation method is characterized by comprising the following steps:
(1) constructing a stability evaluation index system of the alternating current-direct current hybrid power grid, forming a corresponding safety evaluation module according to a scheduling requirement, and determining the initial index composition of the safety evaluation module according to the tightness degree of indexes in the stability evaluation index system and the safety evaluation module;
(2) obtaining subjective weight of the initial index in the safety evaluation module by using an analytic hierarchy process; the method specifically comprises the following steps:
(21) constructing a judgment matrix of the initial indexes contained in the safety evaluation module according to the importance degree of the initial indexes contained in the safety evaluation module
(22) According to the formula
Obtaining the subjective weight w of the initial index contained in the safety evaluation module1i；
(23) According to the formula
Obtaining the random consistency ratio of a judgment matrix A of the safety evaluation module, if CR is less than 0.1, considering that the judgment matrix has satisfactory consistency, and if not, reconstructing the judgment matrix;
wherein A represents a judgment matrix of initial indexes contained in the security evaluation module, and element aijInitial index B contained in safety evaluation moduleiAnd an initial index B contained in the safety evaluation modulejThe relative importance degree is that i is more than or equal to 1 and less than or equal to n, j is more than or equal to 1 and less than or equal to n, and n is the index number contained in the safety evaluation module; RI is average consistency index, related standard data can be searched to obtain RI, CI is consistency index, and the RI is average consistency index
Is obtained according to the formula
Obtaining an approximation lambda of the maximum characteristic root of the decision matrixmax，W1＝(w11，...，w1i，...，w1n)TAn objective weight vector, w, of the indices contained in the security evaluation module1iAn index B included in the security evaluation modulei(ii) subjective weight of;
(3) obtaining an evaluation result of indexes in a stability evaluation index system according to the power grid operation information, and obtaining an evaluation result of a safety evaluation module according to the evaluation result of the indexes in the stability evaluation index system and the subjective weight of each index in the safety evaluation module; the method for acquiring the subjective weight of each index in the safety evaluation module comprises the following steps:
(31) judging whether each index in the safety evaluation module is the same as each initial index in the safety evaluation module during the last updating, if so, the subjective weight of each index in the safety evaluation module is the subjective weight of each initial index in the safety evaluation module, otherwise, entering the step (32);
(32) according to the stepsThe subjective weight of each initial index in the safety evaluation module and the relevance ranking of each index in the safety evaluation module in the step (2) are sequenced to obtain the subjective weight of each index in the safety evaluation module; the method specifically comprises the following steps: the indexes in the security evaluation module are sorted from big to small according to the degree of correlation to be B1…Bu…Bn(ii) a Sequencing the initial indexes in the safety evaluation module in the step (2) from big to small according to subjective weight B1’…Bu’…Bn'; index B 'in safety evaluation module'uThe subjective weight of the evaluation module is equal to the initial index B in the safety evaluation moduleu(ii) subjective weight of; wherein u is more than or equal to 1 and less than or equal to n, and n is the index number contained in the safety evaluation module;
(4) repeating the step (3) at fixed time intervals according to the updating condition of the power grid operation data to obtain an evaluation result sequence of indexes in the stability evaluation index system and an evaluation result sequence of the safety evaluation module; the length of an evaluation result sequence of the indexes in the stability evaluation index system and the length of an evaluation result sequence of the safety evaluation module are both K;
(5) obtaining the association degree between the safety evaluation module and the indexes in the stability evaluation index system based on a grey association analysis method according to the evaluation result sequence of the indexes in the stability evaluation index system and the evaluation result sequence of the safety evaluation module; the method specifically comprises the following steps:
(51) according to the formula
Nondimensionalizing the evaluation result sequence of indexes in stability evaluation index system
The evaluation result sequence of the safety evaluation module is subjected to non-dimensionalization;
(52) according to the formula
Calculating the evaluation result sequence of the kth evaluation result and the safety evaluation module in the indexes in the stability evaluation index systemThe relevance coefficient of the kth evaluation result;
(53) according to the formula
Obtaining the association degree r between the indexes in the security evaluation module and the stability evaluation index systemm；
Xm(k) The k item of the evaluation result sequence of the indexes in the stability evaluation index system, Y (k) is the k item of the evaluation result sequence of the safety evaluation module, and xm(k) the k item of the evaluation result sequence of the indexes in the stability evaluation index system after the dimensionless process, y (k) the k item of the evaluation result sequence of the safety evaluation module after the dimensionless process, rho is called a resolution coefficient, rho belongs to (0,1), ξm(k) The method comprises the steps that a correlation coefficient of a K-th evaluation result in an index in a stability evaluation index system and a K-th evaluation result in an evaluation result sequence of a safety evaluation module is set, wherein M is 1,2, and M, K is 1,2, K.
(6) Sorting the relevance degrees in a descending order, and judging whether the indexes of the stability evaluation index system corresponding to the first n relevance degrees are different from the indexes of the safety evaluation module or not; if the correlation degrees are different, replacing the indexes of the safety evaluation module with the indexes in the stability evaluation index system corresponding to the first n correlation degrees, updating the module height correlation indexes, and entering the step (3); otherwise, entering the step (7);
(7) obtaining objective weight of the indexes in the safety evaluation module according to the relevance of the indexes in the safety evaluation module updated at the last time, and obtaining comprehensive weight of the indexes in the safety evaluation module according to the objective weight and the subjective weight of the indexes in the safety evaluation module; the method specifically comprises the following steps: according to the formula
Obtaining a composite weight w of an indicator of a security evaluation modulei，αtiFor obtaining a linear combination coefficient, w, of weights of indices of a security evaluation module using the t methodtiTo obtain using the t methodweight of index of security evaluation module, whereintiAccording to the formula
Obtaining t ═ I and II, wherein I is an analytic hierarchy process, and II is a gray correlation analysis process;
(8) obtaining a comprehensive evaluation result of the safety evaluation module by using the comprehensive weight of the indexes in the safety evaluation module and the last updated index evaluation result in the safety evaluation module;
wherein K is more than or equal to 20, and the safety evaluation module determined according to the scheduling requirement comprises: the system comprises a low-voltage evaluation module, an overvoltage evaluation module, a line outage evaluation module, a section tidal current transfer evaluation module, an alternating current-direct current hybrid channel fault evaluation module, a frequency evaluation module, a power shortage evaluation module, a power excess evaluation module, a transformer safety evaluation module, a system low-frequency oscillation evaluation module and a transient process evaluation module.
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