CN111242420A - Comprehensive performance multi-dimensional evaluation method - Google Patents

Comprehensive performance multi-dimensional evaluation method Download PDF

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CN111242420A
CN111242420A CN201911396266.1A CN201911396266A CN111242420A CN 111242420 A CN111242420 A CN 111242420A CN 201911396266 A CN201911396266 A CN 201911396266A CN 111242420 A CN111242420 A CN 111242420A
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安柏楠
李勇
曹一家
左薇
罗隆福
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Abstract

The invention discloses a comprehensive performance multi-dimensional evaluation method, which is used for a rail transit power supply system with a bilateral power supply structure and comprises the following steps: establishing a multi-dimensional comprehensive evaluation index of a system power quality dimension, a system application economy dimension and a system operation stability dimension; different evaluation algorithms are adopted for different system evaluation dimensions, including a projection pursuit method based on a genetic algorithm is adopted for evaluating the comprehensive power quality of the system, an approximate ideal solution sorting method based on an application variation coefficient method is adopted for evaluating the application economy of the system, and an approximate ideal solution sorting method based on a mean square error method is adopted for evaluating the operation stability of the system; and according to the requirements of the system operation scene, distributing weights to all dimension index evaluation results to obtain comprehensive performance multi-dimension evaluation results of the rail transit power supply system finally used for the bilateral power supply structure. The method provided by the invention can be used for obviously improving the correctness, rationality, scientificity, effectiveness and comprehensiveness of the evaluation method.

Description

Comprehensive performance multi-dimensional evaluation method
Technical Field
The invention relates to the technical field of system performance comprehensive evaluation and power supply systems, in particular to a comprehensive performance multi-dimensional evaluation method for a rail transit power supply system with a bilateral power supply structure.
Background
The construction of the rail transit makes a great contribution to the development of urban rail transit. As an important component of the rail transit system, the rail transit power supply system converts and transmits electric energy required by rail transit locomotives. Meanwhile, the electric energy loss of the traction network is low, the electric energy loss of the rail transit locomotive is low when the rail transit locomotive runs in a live-line mode, the traction network can be ensured to supply power continuously when a certain traction substation is disconnected in a fault mode, and the bilateral power supply structure is the most common and stable structure and is widely applied to a rail transit power supply system. On the other hand, with the large-scale construction and application of the rail transit power supply system for the bilateral power supply structure, the comprehensive performance of the system under different demand scenes is difficult to be quantitatively and comprehensively evaluated, so that the overall and integral evaluation on the operation level of the conventional rail transit power supply system is difficult to be performed, and a powerful design theoretical basis is also lacked when the novel rail transit power supply system is newly built, reconstructed and upgraded. Therefore, it is necessary to adopt a reasonable and effective multidimensional evaluation method for the comprehensive performance of a typical rail transit power supply system for a bilateral power supply structure to comprehensively evaluate the rail transit power supply system with a multi-attribute architecture, so as to provide powerful theoretical bases for equipment model selection, capacity design, structure planning and the like in different demand scenarios,
the conventional system has more comprehensive evaluation methods, but the evaluation methods aiming at the comprehensive performance of the rail transit power supply system with the bilateral power supply structure are few, so that the system is difficult to scientifically and effectively evaluate. In addition, the existing comprehensive evaluation method of the system still has the following defects: the existing comprehensive performance evaluation method only focuses on the performance of equipment in the system, but ignores the overall operation condition of the system; the existing comprehensive performance evaluation method only adopts a single evaluation algorithm to evaluate system indexes with different attributes, so that the evaluation result of each system dimension index generates deviation, and the evaluation accuracy of the overall performance is influenced; the rail transit power supply systems for the bilateral power supply structure in different demand scenes have different comprehensive performances, and the conventional comprehensive performance evaluation method is often used for qualitatively evaluating the system in a single demand scene, so that the evaluation result is lack of comprehensiveness.
Disclosure of Invention
In view of the above, it is necessary to provide a multi-dimensional evaluation method for comprehensive performance of a rail transit power supply system with a bilateral power supply structure, so as to solve the above-mentioned drawbacks in the background art, such as few evaluation index dimensions, single evaluation method, fixed evaluation scene, and excessive subjective evaluation factor ratio.
In order to solve the technical problems, the technical scheme adopted by the invention is as follows:
a comprehensive performance multi-dimensional evaluation method is used for a rail transit power supply system with a bilateral power supply structure, and comprises the following steps:
establishing a multi-dimensional comprehensive evaluation index of a system power quality dimension, a system application economy dimension and a system operation stability dimension;
different evaluation algorithms are adopted for different system evaluation dimensions, including a projection pursuit method based on a genetic algorithm is adopted for evaluating the comprehensive power quality of the system, an approximate ideal solution sorting method based on an application variation coefficient method is adopted for evaluating the application economy of the system, and an approximate ideal solution sorting method based on a mean square error method is adopted for evaluating the operation stability of the system;
and according to the requirements of the system operation scene, distributing weights to all dimension index evaluation results to obtain comprehensive performance multi-dimension evaluation results of the rail transit power supply system finally used for the bilateral power supply structure.
Further, aiming at different operation scene requirements of the system, different system comprehensive power quality evaluation weights, system application economy evaluation weights and system operation stability evaluation weights are distributed.
Furthermore, the power supply of the rail transit power supply system with the bilateral power supply structure is from two different external urban power grids, and the power is converted and transmitted to an uplink contact net and a downlink contact net through a traction power transformation system so as to meet the power demand of rail transit locomotives; for a station with a traction power supply system, the power supply system comprises a traction substation and an auxiliary power supply and distribution system for electric lighting mainly comprising a step-down substation; for a station of a low-voltage distribution system, a power supply system of the station is an auxiliary power supply and distribution system for electric lighting which mainly comprises a step-down transformer substation;
the rail transit power supply system with the bilateral power supply structure comprises 2 stations with traction power supply systems and 3-5 stations with low-voltage power distribution systems, wherein the rail transit stations of the low-voltage power distribution systems are positioned between the 2 stations with the traction power supply systems; 2 the station electric energy with the traction power supply system is supplied by different external city power grids, and the converted direct current electric energy is supplied to the same uplink contact net and the same downlink contact net; the traction power supply system comprises a traction substation, a rectifier, power monitoring, a wired network and protection equipment; the low-voltage distribution system comprises a step-down transformer station, a low-voltage bus, distribution equipment, a cable and electrical equipment;
the voltage grade of the bus of the external urban power grid is alternating current 110kV, the voltage grade of the bus at the side of the rail transit station network is alternating current 35kV, and the voltage grade of the uplink and downlink contact networks is direct current 1500V.
Further, the system power quality dimension evaluation index comprises a traction substation I power quality index and a traction substation II power quality index, namely a 110kV alternating current bus I power quality index, a 110kV alternating current bus II power quality index, a 35kV alternating current bus I power quality index, a 35kV alternating current bus II power quality index and a 1500V direct current bus power quality index; the electric energy quality indexes of the 110kV alternating-current bus I and the 110kV alternating-current bus II comprise power supply three-phase voltage deviation, power supply frequency deviation, total harmonic distortion of three-phase voltage, total harmonic distortion of three-phase current, unbalance degree of three-phase voltage and unbalance degree of three-phase current; the 35kV alternating-current bus I electric energy quality index and the 35kV alternating-current bus II electric energy quality index comprise power supply three-phase voltage deviation, power supply frequency deviation, three-phase voltage total harmonic distortion, three-phase current total harmonic distortion, three-phase voltage unbalance and three-phase current unbalance; the 1500V direct current bus power quality index comprises power supply voltage deviation and a maximum voltage deviation rate.
Further, the system application economic evaluation index comprises system initial investment cost, system occupied area, system operation loss, system maintenance cost and system equipment life cycle.
Further, the system operation stability evaluation index comprises a system average power shortage index (ANES), a user average power outage duration index (CAIDI), a user average power outage frequency index (CAIFI), an expected energy shortage value (EENS), a system average power outage duration index (SAIDI) and a system average power outage frequency index (SAIFI).
Further, a projection pursuit method based on a genetic algorithm is adopted for the comprehensive power quality of the system, and the calculation steps are as follows:
classifying and grading the 110kV alternating current bus I electric energy quality index, the 110kV alternating current bus II electric energy quality index, the 35kV alternating current bus I electric energy quality index, the 35kV alternating current bus II electric energy quality index and the 1500V direct current bus electric energy quality index, and selecting the 95% probability value of the 110kV alternating current bus I electric energy quality index sample, the 95% probability value of the 110kV alternating current bus II electric energy quality index sample, the 95% probability value of the 35kV alternating current bus I electric energy quality index sample, the 95% probability value of the 35kV alternating current bus II electric energy quality index sample and the 95% probability value of the 1500V direct current bus electric energy quality index sample as electric energy quality evaluation sample
Figure BDA0002346400240000041
And carrying out standardization treatment;
Figure BDA0002346400240000042
wherein xijFor normalized index, xmaxjThe maximum value in the voltage level sample is n and m are the number of the initial random projection indexes and the evaluation indexes; suppose dj(j ═ 1,2 … m) and
Figure BDA0002346400240000043
for the corresponding projection direction and rating, then the one-dimensional projection value ziThe calculation is shown below:
Figure BDA0002346400240000051
calculating ziStandard deviation of (S)zAnd ziAnd
Figure BDA0002346400240000052
coefficient of correlation between Rzω：
Figure BDA0002346400240000053
Wherein EzIs the sequence [ zi]Average value, EωIs a sequence
Figure BDA0002346400240000054
Average value of (d); calculating a projection objective function f (d),
f(d)＝Sz|Rzω| (4)
according to equation (4), the projection objective function f (d) will depend on the projection direction djIs changed, the optimal projection direction d is calculated by solving the maximum of the projection objective function f (d)*：
Figure BDA0002346400240000055
Calculating the projection direction d by using a global optimization method based on a genetic algorithmjAnd the obtained optimal projection direction d is obtained*Substituting into formula (2), drawing scatter diagram of each index sample setObtaining the corresponding endpoint value of each level of the scatter diagram, and simultaneously carrying out piecewise linear interpolation approximation on the curve to obtain a piecewise continuous function; according to the obtained piecewise continuous function, the power quality rating of a 110kV alternating current bus I, the power quality rating of a 110kV alternating current bus II, the power quality rating of a 35kV alternating current bus I, the power quality rating of a 35kV alternating current bus II and the power quality rating of a 1500V direct current bus can be obtained; according to the rating of each voltage grade, the system power quality of the rail transit power supply system for the bilateral power supply structure can be evaluated by adopting a characteristic value weighting method, and a corresponding quantitative calculation result and rating are obtained.
Further, an approximate ideal solution sorting method based on an application coefficient of variation method is adopted aiming at the system application economy, and the calculation steps are as follows:
firstly, determining an evaluation matrix according to economic dimension indexes of system application, assuming that the number of evaluation indexes is w, and each evaluation index is ywThen the evaluation matrix Y is expressed as:
Y＝[y1,y2,y3,L,ypL,yw],p＝1,2,L w (6)
similarly, the evaluation weight matrix corresponding to the index
Figure BDA0002346400240000061
Expressed as:
Figure BDA0002346400240000062
different from the power quality index of the system, the application economy index of part of the system has negative property, namely the smaller the index is, the better the application economy is; therefore, the negative index needs to be located and converted into a positive index for evaluation, and the positive index is formulated as:
Figure BDA0002346400240000063
wherein y'p(p ═ 1,2, …, w) is an evaluation index for the economics of the system application after conversion, γ is the conversion coefficient,typically a value of 0.1; in addition, because the economic index units of the systems are different, in order to ensure the evaluation accuracy and correctness, the converted indexes are further normalized, and the dimensions of the converted indexes are removed by calculation so as to normalize the indexes; the normalized calculation formula is:
Figure BDA0002346400240000064
wherein y "p(p is 1,2, …, w) is an economic evaluation index of the debulked system application, and the corresponding debulked standard matrix is Y'; so that the average value thereof can be calculated
Figure BDA0002346400240000065
And standard deviation SP：
Figure BDA0002346400240000071
And (3) calculating the system application economic evaluation index variation coefficient V by combining the formula (9) and the formula (10)pAnd evaluating the weights
Figure BDA0002346400240000072
Figure BDA0002346400240000073
After determining the weight of the economic evaluation index applied by the system, the economic evaluation index matrix Y' applied by the weighting system is expressed as:
Figure BDA0002346400240000074
obtaining an economic evaluation index matrix Y 'applied to the weighting system, namely, carrying out comprehensive evaluation on the economic evaluation index matrix Y' by adopting an approximate ideal solution sorting method; if the index is regarded as a variable in a coordinate system, a high-dimensional space is geometrically formed, and each evaluated object is geometrically determined in the space by a plurality of index values reflecting the evaluated objectOne point, and the comprehensive evaluation problem becomes the sorting and evaluation of the spatial points; firstly, determining reference points in space, including optimal and worst points, then calculating the distance between each evaluation object and the reference points, wherein the closer to the optimal point or the farther from the worst point, the better the comprehensive characteristics of the evaluated object are; since all the system application economic evaluation indexes are normalized and dimensionless, the maximum value in the indexes constitutes a positive ideal index
Figure BDA0002346400240000075
The minimum value of each index constitutes a negative ideal index
Figure BDA0002346400240000076
Then the economic evaluation index is applied to the system to the positive ideal index
Figure BDA0002346400240000077
Negative and positive ideal index
Figure BDA0002346400240000078
Is expressed as
Figure BDA0002346400240000081
Calculating relative proximity
Figure BDA0002346400240000082
Figure BDA0002346400240000083
Wherein
Figure BDA0002346400240000084
To evaluate the index to a positive ideal index
Figure BDA0002346400240000085
The distance of (a) to (b),
Figure BDA0002346400240000086
to evaluate the index to a positive ideal index
Figure BDA0002346400240000087
The distance of (d); according to the calculation result obtained by the formula (14), effectively performing quantitative evaluation on the application economy of the system; wherein relative proximity is
Figure BDA0002346400240000088
The larger the evaluation result, the smaller the relative distance between the evaluation object and the ideal index, and the better the corresponding evaluation result.
Further, an approximate ideal solution sorting method based on a mean square error method is adopted for the operation stability of the system, and the calculation steps are as follows:
according to the topological structure and system parameters of the rail transit power supply system for the bilateral power supply structure, PowerFactory software is used for modeling the topological structure and the system parameters, the whole line power transformation equipment is simulated and modeled, software simulation is performed on various protocols and control algorithms of the whole line, and the operation working conditions of all levels of power transformation substations of the whole line of the rail transit and the lower end charge are simulated comprehensively and really; simulating and recording various faults or abnormal operation states of a rail transit power supply system through simulation operation conditions, and obtaining system operation stability evaluation indexes, wherein the system operation stability evaluation indexes comprise an average power shortage index (ANES) of a system, an average power failure duration index (CAIDI) of a user, an average power failure frequency index (CAIFI) of the user, an expected energy shortage value (EENS), an average power failure duration (SAIDI) of the system and an average power failure frequency index (SAIFI) of the system;
establishing an evaluation matrix R according to the evaluation index of the system operation stability and assuming that the number of the evaluation indexes is s,
R＝[R1,R2,R3,L,RqL,Rs],q＝1,2,L s (15)
similarly, the evaluation weight matrix corresponding to the index
Figure BDA0002346400240000091
Expressed as:
Figure BDA0002346400240000092
considering that the evaluation index of the running stability of part of the system is a negative index, each index needs to be positively changed, and the corresponding calculation formula is as follows:
Figure BDA0002346400240000093
wherein R'q(p ═ 1,2, …, s) is an index for evaluating the operation stability of the system after conversion, γ is a conversion coefficient, and usually takes a value of 0.1; on the other hand, the system operation stability evaluation indexes such as CAIDI and SAIDI have small values, and the unit of the system operation stability evaluation indexes is different, and it needs to be de-dimensioned and normalized, and the calculation formula is as follows:
Figure BDA0002346400240000094
wherein R "q(q is 1,2, …, s) is a dimensionless system operation stability evaluation index, and a corresponding dimensionless standard matrix is R'; and (3) obtaining a standard matrix as an average value of evaluation indexes in R':
Figure BDA0002346400240000095
and calculating the evaluation index weight of the running stability of the system by combining the evaluation index average value and utilizing a mean variance method:
Figure BDA0002346400240000096
after the system operation stability evaluation index weight is obtained, the weighting system applies an economic evaluation index matrix R' to be expressed as:
Figure BDA0002346400240000101
similar systems employ economic evaluation methods, using approximationsThe ideal solution sorting method evaluates the evaluation index of the system operation stability, and the weighting system applies an economic evaluation index matrix R'InThe maximum value and the minimum value in the index respectively form a positive ideal index
Figure BDA0002346400240000102
And negative ideal index
Figure BDA0002346400240000103
From the evaluation index to the positive ideal index
Figure BDA0002346400240000104
Negative and positive ideal index
Figure BDA0002346400240000105
The distance of (d) is expressed as:
Figure BDA0002346400240000106
wherein
Figure BDA0002346400240000107
To evaluate the index to a positive ideal index
Figure BDA0002346400240000108
The distance of (a) to (b),
Figure BDA0002346400240000109
to evaluate the index to a positive ideal index
Figure BDA00023464002400001010
The distance of (d); computing system application economy evaluation index relative closeness
Figure BDA00023464002400001011
Figure BDA00023464002400001012
A meter obtained according to the formula (23)Calculating a result, and effectively carrying out quantitative evaluation on the operation stability of the system; wherein relative proximity is
Figure BDA00023464002400001013
The larger the evaluation result, the smaller the relative distance between the evaluation object and the ideal index, and the better the corresponding evaluation result.
Compared with the prior art, the invention has the beneficial effects that:
according to the invention, different evaluation algorithms are adopted to respectively evaluate different dimensions according to different system evaluation dimension characteristics, so that the comprehensive performance of the rail transit power supply system for the bilateral power supply structure can be comprehensively, objectively and quantitatively evaluated, and meanwhile, multi-dimensional index weight distribution can be carried out under the requirements of any system scene, and an accurate system evaluation result is obtained. Aiming at the characteristics that the system has more power quality dimension evaluation indexes and different evaluation standards of each voltage grade bus, a projection pursuit method based on a genetic algorithm is adopted for evaluation; aiming at the characteristics that the system application economic indicators have no fixed evaluation standard and the system application economic indicators have different orders and dimensions, an approximate ideal solution sorting method based on an application variation coefficient method is adopted for evaluation; aiming at the system operation stability error caused by the simulation of the Power Factory software, an approximate ideal solution sorting method based on the mean square error method is adopted to eliminate the error and evaluate each system stability index. The method can intelligently extract the index characteristics of each dimension of the system, does not need any artificial empowerment in the evaluation process, has objective and reasonable evaluation result and high reliability, can reflect the basic attribute and the overall development degree of the rail transit power supply system with the bilateral power supply structure, provides scientific guidance for the scientific planning and construction of urban rail transit construction, and opens up a new way for the intelligent development of the comprehensive performance evaluation work of the rail transit power supply system.
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FIG. 1 is a flow chart of comprehensive performance multi-dimensional evaluation of a rail transit power supply system for a bilateral power supply architecture;
FIG. 2 is a rail transit power supply system of a typical bilateral power supply configuration;
FIG. 3 is a flow chart of the comprehensive evaluation of the power quality of the system in the comprehensive performance multi-dimensional evaluation method;
FIG. 4 is a flow chart of system application economy evaluation in a comprehensive performance multi-dimensional evaluation method;
FIG. 5 is a flow chart of system operation stability evaluation in the comprehensive performance multi-dimensional evaluation method.
Detailed Description
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in detail below. It should be noted that the described embodiments are only a part of the embodiments of the present invention, and not all embodiments, and all other embodiments obtained by those skilled in the art without any inventive work based on the embodiments of the present invention belong to the protection scope of the present invention.
Examples
The invention provides a comprehensive performance multi-dimensional evaluation method which is used for a rail transit power supply system with a bilateral power supply structure, and a flow chart is shown in figure 1. Establishing multi-dimensional comprehensive evaluation indexes related to the system power quality dimension, the system application economy dimension and the system operation stability dimension, and distributing weights to evaluation results of all the dimension indexes according to the system operation scene requirements to obtain the comprehensive performance multi-dimensional evaluation result of the rail transit power supply system finally used for the bilateral power supply structure.
Meanwhile, the invention adopts different evaluation algorithms aiming at different system evaluation dimensions, comprises the steps of evaluating the comprehensive power quality of the system by adopting a projection pursuit method based on a genetic algorithm, evaluating the system application economy by adopting an approximate ideal solution sorting method based on an application variation coefficient method, and evaluating the system operation stability by adopting an approximate ideal solution sorting method based on a mean square error method.
The system power quality dimension evaluation indexes comprise a traction substation I power quality index and a traction substation II power quality index, namely a 110kV alternating current bus I power quality index, a 110kV alternating current bus II power quality index, a 35kV alternating current bus I power quality index, a 35kV alternating current bus II power quality index and a 1500V direct current bus power quality index. The electric energy quality indexes of the 110kV alternating-current bus I and the 110kV alternating-current bus II comprise power supply three-phase voltage deviation, power supply frequency deviation, total harmonic distortion of three-phase voltage, total harmonic distortion of three-phase current, unbalance degree of three-phase voltage and unbalance degree of three-phase current; the 35kV alternating-current bus I electric energy quality index and the 35kV alternating-current bus II electric energy quality index comprise power supply three-phase voltage deviation, power supply frequency deviation, three-phase voltage total harmonic distortion, three-phase current total harmonic distortion, three-phase voltage unbalance and three-phase current unbalance; the 1500V direct current bus power quality index comprises power supply voltage deviation and a maximum voltage deviation rate.
The system application economic evaluation indexes comprise system initial investment cost, system occupied area, system operation loss, system maintenance cost and system equipment life cycle.
The system operation stability evaluation indexes comprise an average power shortage index (ANES), an average power outage duration index (CAIDI), an average power outage frequency index (CAIFI), an expected energy shortage value (EENS), an average power outage duration index (SAIDI) and an average power outage frequency index (SAIFI).
Aiming at different operation scene requirements of the system, different system comprehensive power quality evaluation weights, system application economy evaluation weights and system operation stability evaluation weights are distributed. Further, the comprehensive performance of the rail transit power supply system for the bilateral power supply structure under the system operation scene requirement is calculated according to the system comprehensive power quality evaluation result, the system application economy evaluation result and the system operation stability evaluation result.
The topological structure of the rail transit power supply system with the bilateral power supply structure is shown in fig. 2, and a power supply of the rail transit power supply system is usually from two different external urban power grids, and electric energy is converted and transmitted to an uplink contact net and a downlink contact net through a traction power transformation system so as to meet the power consumption requirement of rail transit locomotives. For a station with a traction power supply system, the power supply system mainly comprises a traction substation and an auxiliary power supply and distribution system such as electric lighting and the like which mainly comprises a step-down substation; for a station of a low-voltage distribution system, a power supply system of the station is mainly an auxiliary power supply and distribution system such as electric lighting and the like which mainly comprises a step-down transformer substation.
The track traffic power supply system development of the bilateral power supply structure generally comprises 2 stations with traction power supply systems and 3-5 stations with low-voltage power distribution systems, wherein the track traffic stations of the low-voltage power distribution systems are positioned between the 2 stations with the traction power supply systems; and 2, the station electric energy with the traction power supply system is supplied by different external urban power grids, and the converted direct current electric energy is supplied to the same uplink contact network and the same downlink contact network. The traction power supply system mainly comprises a traction substation, a rectifier, electric power monitoring, a wired network, protection equipment and the like; the low-voltage distribution system mainly comprises a step-down transformer station, a low-voltage bus, distribution equipment, a cable, electrical equipment and the like.
The voltage grade of the bus of the external urban power grid is alternating current 110kV, the voltage grade of the bus at the side of the rail transit station network is alternating current 35kV, and the voltage grade of the uplink and downlink contact networks is direct current 1500V.
A projection pursuit method based on a genetic algorithm is adopted for the comprehensive power quality of the system, the flow chart of the method is shown in figure 3, and the calculation steps are as follows:
classifying and grading the 110kV alternating current bus I electric energy quality index, the 110kV alternating current bus II electric energy quality index, the 35kV alternating current bus I electric energy quality index, the 35kV alternating current bus II electric energy quality index and the 1500V direct current bus electric energy quality index, and simultaneously classifying and grading the 95% probability value of the 110kV alternating current bus I electric energy quality index sample and the 110kV alternating current bus II electric energy quality indexSelecting a standard sample 95% probability value, a 35kV alternating current bus I electric energy quality index sample 95% probability value, a 35kV alternating current bus II electric energy quality index sample 95% probability value and a 1500V direct current bus electric energy quality index sample 95% probability value as electric energy quality evaluation sample
Figure BDA0002346400240000141
And carrying out standardization treatment;
Figure BDA0002346400240000142
wherein xijFor normalized index, xmaxjN and m are the numbers of the initial random projection indexes and the evaluation indexes, which are the maximum values in the voltage level samples. Suppose dj(j ═ 1,2 … m) and
Figure BDA0002346400240000143
for the corresponding projection direction and rating, then the one-dimensional projection value ziIt can be calculated as shown below:
Figure BDA0002346400240000144
calculating ziStandard deviation of (S)zAnd ziAnd
Figure BDA0002346400240000151
coefficient of correlation between Rzω：
Figure BDA0002346400240000152
Wherein EzIs the sequence [ zi]Average value, EωIs a sequence
Figure BDA0002346400240000153
Average value of (a). Further, a projection objective function f (d) is calculated:
f(d)＝Sz|Rzω| (04)
according to equation (04), the projection objective function f (d) will be based on the projection direction djSo that the optimal projection direction d can be calculated by solving the maximum of the projection objective function f (d)*：
Figure BDA0002346400240000154
Further, a global optimization method based on a genetic algorithm is adopted to calculate the projection direction djAnd the obtained optimal projection direction d is obtained*And substituting the formula (05) into the formula, drawing a scatter diagram of each index sample set, solving end point values corresponding to each layer of the scatter diagram, and simultaneously performing piecewise linear interpolation approximation on the curve to obtain a piecewise continuous function. According to the obtained piecewise continuous function, the power quality rating of the 110kV alternating current bus I, the power quality rating of the 110kV alternating current bus II, the power quality rating of the 35kV alternating current bus I, the power quality rating of the 35kV alternating current bus II and the power quality rating of the 1500V direct current bus can be obtained. According to the rating of each voltage grade, the system power quality of the rail transit power supply system for the bilateral power supply structure can be evaluated by further adopting a characteristic value weighting method, and a corresponding quantitative calculation result and rating are obtained.
The method for approximating ideal solution sorting based on the application coefficient of variation method aiming at the system application economy is shown in a flow chart of the method in figure 4, and comprises the following calculation steps:
firstly, determining an evaluation matrix according to economic dimension indexes of system application, assuming that the number of evaluation indexes is w, and each evaluation index is ywThen the evaluation matrix Y is expressed as:
Y＝[y1,y2,y3,L,ypL,yw],p＝1,2,L w (06)
similarly, the evaluation weight matrix corresponding to the index
Figure BDA0002346400240000161
Can be expressed as:
Figure BDA0002346400240000162
different from the power quality index of the system, the application economy index of part of the system has negative property, namely the smaller the index is, the better the application economy is. Therefore, the negative index needs to be located and converted into a positive index for evaluation, and the positive index is formulated as:
Figure BDA0002346400240000163
wherein y'p(p ═ 1,2, …, w) is an index for evaluating the economy of the system after conversion, and γ is a conversion coefficient, and usually 0.1. In addition, because the economic index units applied by the systems are different, in order to ensure the evaluation accuracy and correctness, the converted indexes are further normalized, and the dimensions of the converted indexes are removed through calculation so as to normalize the indexes. The normalized calculation formula is:
Figure BDA0002346400240000164
wherein y "pAnd (p is 1,2, …, w) is an economic evaluation index applied to the system after dimension removal, and the corresponding standard matrix after dimension removal is Y'. So that the average value thereof can be calculated
Figure BDA0002346400240000165
And standard deviation SP：
Figure BDA0002346400240000171
By combining the formula (09) and the formula (10), the system application economy evaluation index variation coefficient V can be calculatedpAnd evaluating the weights
Figure BDA0002346400240000172
Figure BDA0002346400240000173
After determining the weight of the economic evaluation index applied by the system, the economic evaluation index matrix Y ″ applied by the weighting system can be expressed as:
Figure BDA0002346400240000174
and (5) obtaining an economic evaluation index matrix Y 'applied to the weighting system, namely, carrying out comprehensive evaluation on the economic evaluation index matrix Y' by adopting an approximate ideal solution sorting method. If the index is regarded as a variable in a coordinate system, a high-dimensional space is geometrically formed, each evaluated object is a point determined in the space by a plurality of index values reflecting the evaluated object from a geometrical point of view, and the comprehensive evaluation problem becomes the sorting and evaluation of the spatial points. Firstly, determining reference points in space, including optimal and worst points, and then calculating the distance between each evaluation object and the reference points, wherein the closer to the optimal point or the farther from the worst point indicates the better comprehensive characteristics of the evaluated object. Since all the system application economic evaluation indexes are normalized and dimensionless, the maximum value in the indexes constitutes a positive ideal index
Figure BDA0002346400240000175
The minimum value of each index constitutes a negative ideal index
Figure BDA0002346400240000176
Then the economic evaluation index is applied to the system to the positive ideal index
Figure BDA0002346400240000177
Negative and positive ideal index
Figure BDA0002346400240000178
The distance of (d) can be expressed as:
Figure BDA0002346400240000181
further, a relative proximity may be calculated
Figure BDA0002346400240000182
Figure BDA0002346400240000183
Wherein
Figure BDA0002346400240000184
To evaluate the index to a positive ideal index
Figure BDA0002346400240000185
The distance of (a) to (b),
Figure BDA0002346400240000186
to evaluate the index to a positive ideal index
Figure BDA0002346400240000187
The distance of (d); according to the calculation result obtained by the formula (14), the application economy of the system can be effectively and quantitatively evaluated. Wherein relative proximity is
Figure BDA0002346400240000188
The larger the evaluation result, the smaller the relative distance between the evaluation object and the ideal index, and the better the corresponding evaluation result.
An approximate ideal solution sorting method based on a mean square error method is adopted for the operation stability of the system, the flow chart of the method is shown in figure 5, and the calculation steps are as follows:
according to the topological structure and system parameters of the rail transit power supply system for the bilateral power supply structure, PowerFactory software is used for modeling the topological structure and the system parameters, the whole-line power transformation equipment is simulated and modeled, software simulation is performed on various protocols and control algorithms of the whole line, and the operation working conditions of all levels of power transformation substations of the rail transit and the lower end charge are simulated comprehensively and really. The method comprises the steps of recording various faults or abnormal operation states of a rail transit power supply system in a simulation mode through simulation operation conditions, and obtaining system operation stability evaluation indexes, wherein the system operation stability evaluation indexes comprise an average power shortage index (ANES), an average power failure duration index (CAIDI) of a user, an average power failure frequency index (CAIFI) of the user, an expected energy shortage value (EENS), an average power failure duration (SAIDI) of the system and an average power failure frequency index (SAIFI) of the system.
According to the system operation stability evaluation index, assuming that the number of the evaluation indexes is s, establishing an evaluation matrix R:
R＝[R1,R2,R3,L,RqL,Rs],q＝1,2,L s (15)
similarly, the evaluation weight matrix corresponding to the index
Figure BDA0002346400240000189
Can be expressed as:
Figure BDA0002346400240000191
considering that the evaluation index of the running stability of part of the system is a negative index, each index needs to be positively changed, and the corresponding calculation formula is as follows:
Figure BDA0002346400240000192
wherein R'q(p ═ 1,2, …, s) is an index for evaluating the stability of the system operation after conversion, and γ is a conversion coefficient, and usually 0.1. On the other hand, the system operation stability evaluation indexes such as CAIDI and SAIDI have small values, and the unit of the system operation stability evaluation indexes is different, and it needs to be de-dimensioned and normalized, and the calculation formula is as follows:
Figure BDA0002346400240000193
wherein R "qAnd (q is 1,2, …, s) is a dimensionless system operation stability evaluation index, and the corresponding dimensionless standard matrix is R'. Further, the standard matrix can be obtained as the average value of the evaluation indexes in R':
Figure BDA0002346400240000194
and calculating the evaluation index weight of the running stability of the system by combining the evaluation index average value and utilizing a mean variance method:
Figure BDA0002346400240000195
after the system operation stability evaluation index weight is obtained, the weighting system application economy evaluation index matrix R ″ can be expressed as:
Figure BDA0002346400240000196
the similar system applies an economic evaluation method, an approximate ideal solution ordering method is used for evaluating the evaluation index of the system operation stability, and the weighting system applies an economic evaluation index matrix R "InThe maximum value and the minimum value in the index respectively form a positive ideal index
Figure BDA0002346400240000201
And negative ideal index
Figure BDA0002346400240000202
From the evaluation index to the positive ideal index
Figure BDA0002346400240000203
Negative and positive ideal index
Figure BDA0002346400240000204
The distance of (d) can be expressed as:
Figure BDA0002346400240000205
wherein
Figure BDA0002346400240000206
To evaluate the index to a positive ideal index
Figure BDA0002346400240000207
The distance of (a) to (b),
Figure BDA0002346400240000208
to evaluate the index to a positive ideal index
Figure BDA0002346400240000209
The distance of (c). Further, the relative closeness of the system application economy evaluation index can be calculated
Figure BDA00023464002400002010
Figure BDA00023464002400002011
According to the calculation result obtained by the formula (23), the operation stability of the system can be effectively and quantitatively evaluated. Wherein relative proximity is
Figure BDA00023464002400002012
The larger the evaluation result, the smaller the relative distance between the evaluation object and the ideal index, and the better the corresponding evaluation result.
According to the requirements of the system operation scene, the dimension index weights of all the systems can be distributed, and the comprehensive performance of the system under the scene can be quantitatively and accurately evaluated.
The system operation scene requirements are distribution schemes of all system dimension index weights, namely, a system comprehensive power quality evaluation weight, a system application economy evaluation weight and a system operation stability evaluation weight are distributed. Further, the comprehensive performance of the rail transit power supply system for the bilateral power supply structure under the system operation scene requirement is calculated according to the system comprehensive power quality evaluation result, the system application economy evaluation result and the system operation stability evaluation result. Therefore, by the comprehensive performance multi-dimensional evaluation method for the rail transit power supply system with the bilateral power supply structure, the comprehensive performance of the system can be effectively and quantitatively evaluated. On the other hand, by adjusting the distribution proportion of the system comprehensive power quality evaluation weight, the system application economy evaluation weight and the system operation stability evaluation weight, the comprehensive performance evaluation result of the rail transit power supply system for the bilateral power supply structure in multiple scenes can be obtained, and powerful theoretical reference is provided for the actual operation and construction of the system.
The invention provides a comprehensive performance multi-dimensional evaluation method for a track traffic power supply system of a bilateral power supply structure aiming at a system structure, equipment type selection, design parameters and the like of the track traffic power supply system of the bilateral power supply structure. And meanwhile, the index weights of all the system dimensions are distributed, comprehensive calculation is carried out again according to the evaluation results of all the system dimensions, and the comprehensive performance of the rail transit power supply system for the bilateral power supply structure under the scene is evaluated quantitatively and accurately in a comprehensive mode. The method can effectively improve the defects of single evaluation method, few index dimensions, high subjective evaluation factor ratio and the like in the traditional evaluation method, can realize effective evaluation on the comprehensive performance of the rail transit power supply system with the bilateral power supply structure, obviously improves the correctness, reasonability, scientificity, effectiveness and comprehensiveness of the evaluation method, and provides powerful theoretical reference for the construction and application of the rail transit power supply system. On the other hand, aiming at the established rail transit power supply system, the comprehensive performance and the dimensional state of the system can be truly reflected according to the calculation result of each dimensional index, weak links can be effectively found for improvement, the theoretical basis is improved for the transformation and the upgrading of the rail transit power supply system, and the method is suitable for industrial application.
According to the invention, different evaluation algorithms are adopted to respectively evaluate different dimensions according to different system evaluation dimension characteristics, so that the comprehensive performance of the rail transit power supply system for the bilateral power supply structure can be comprehensively, objectively and quantitatively evaluated, and meanwhile, multi-dimensional index weight distribution can be carried out under the requirements of any system scene, and an accurate system evaluation result is obtained. Aiming at the characteristics that the system has more power quality dimension evaluation indexes and different evaluation standards of each voltage grade bus, a projection pursuit method based on a genetic algorithm is adopted for evaluation; aiming at the characteristics that the system application economic indicators have no fixed evaluation standard and the system application economic indicators have different orders and dimensions, an approximate ideal solution sorting method based on an application variation coefficient method is adopted for evaluation; aiming at the system operation stability error caused by the simulation of the Power Factory software, an approximate ideal solution sorting method based on the mean square error method is adopted to eliminate the error and evaluate each system stability index. The method can intelligently extract the index characteristics of each dimension of the system, does not need any artificial empowerment in the evaluation process, has objective and reasonable evaluation result and high reliability, can reflect the basic attribute and the overall development degree of the rail transit power supply system with the bilateral power supply structure, provides scientific guidance for the scientific planning and construction of urban rail transit construction, and opens up a new way for the intelligent development of the comprehensive performance evaluation work of the rail transit power supply system.
The above-mentioned embodiments only express several embodiments of the present invention, and the description thereof is more specific and detailed, but not construed as limiting the scope of the present invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the inventive concept, which falls within the scope of the present invention. Therefore, the protection scope of the present patent shall be subject to the appended claims.

Claims (9)

1. A comprehensive performance multi-dimensional evaluation method is used for a rail transit power supply system with a bilateral power supply structure, and is characterized in that: the method comprises the following steps:
establishing a multi-dimensional comprehensive evaluation index of a system power quality dimension, a system application economy dimension and a system operation stability dimension;
different evaluation algorithms are adopted for different system evaluation dimensions, including a projection pursuit method based on a genetic algorithm is adopted for evaluating the comprehensive power quality of the system, an approximate ideal solution sorting method based on an application variation coefficient method is adopted for evaluating the application economy of the system, and an approximate ideal solution sorting method based on a mean square error method is adopted for evaluating the operation stability of the system;
and according to the requirements of the system operation scene, distributing weights to all dimension index evaluation results to obtain comprehensive performance multi-dimension evaluation results of the rail transit power supply system finally used for the bilateral power supply structure.
2. The comprehensive performance multidimensional assessment method according to claim 1, characterized in that: aiming at different operation scene requirements of the system, different system comprehensive power quality evaluation weights, system application economy evaluation weights and system operation stability evaluation weights are distributed.
3. The comprehensive performance multidimensional assessment method according to claim 1, characterized in that: the power supply of the rail transit power supply system with the bilateral power supply structure is from two different external urban power grids, and the power is converted and transmitted to an uplink contact net and a downlink contact net through a traction power transformation system so as to meet the power consumption requirement of rail transit locomotives; for a station with a traction power supply system, the power supply system comprises a traction substation and an auxiliary power supply and distribution system for electric lighting mainly comprising a step-down substation; for a station of a low-voltage distribution system, a power supply system of the station is an auxiliary power supply and distribution system for electric lighting which mainly comprises a step-down transformer substation;
the rail transit power supply system with the bilateral power supply structure comprises 2 stations with traction power supply systems and 3-5 stations with low-voltage power distribution systems, wherein the rail transit stations of the low-voltage power distribution systems are positioned between the 2 stations with the traction power supply systems; 2 the station electric energy with the traction power supply system is supplied by different external city power grids, and the converted direct current electric energy is supplied to the same uplink contact net and the same downlink contact net; the traction power supply system comprises a traction substation, a rectifier, power monitoring, a wired network and protection equipment; the low-voltage distribution system comprises a step-down transformer station, a low-voltage bus, distribution equipment, a cable and electrical equipment;
the voltage grade of the bus of the external urban power grid is alternating current 110kV, the voltage grade of the bus at the side of the rail transit station network is alternating current 35kV, and the voltage grade of the uplink and downlink contact networks is direct current 1500V.
4. The comprehensive performance multidimensional assessment method according to claim 1, characterized in that: the system power quality dimension evaluation indexes comprise a traction substation I power quality index and a traction substation II power quality index, namely a 110kV alternating current bus I power quality index, a 110kV alternating current bus II power quality index, a 35kV alternating current bus I power quality index, a 35kV alternating current bus II power quality index and a 1500V direct current bus power quality index; the electric energy quality indexes of the 110kV alternating-current bus I and the 110kV alternating-current bus II comprise power supply three-phase voltage deviation, power supply frequency deviation, total harmonic distortion of three-phase voltage, total harmonic distortion of three-phase current, unbalance degree of three-phase voltage and unbalance degree of three-phase current; the 35kV alternating-current bus I electric energy quality index and the 35kV alternating-current bus II electric energy quality index comprise power supply three-phase voltage deviation, power supply frequency deviation, three-phase voltage total harmonic distortion, three-phase current total harmonic distortion, three-phase voltage unbalance and three-phase current unbalance; the 1500V direct current bus power quality index comprises power supply voltage deviation and a maximum voltage deviation rate.
5. The comprehensive performance multidimensional assessment method according to claim 1, characterized in that: the system application economic evaluation indexes comprise system initial investment cost, system occupied area, system operation loss, system maintenance cost and system equipment life cycle.
6. The comprehensive performance multidimensional assessment method according to claim 1, characterized in that: the system operation stability evaluation indexes comprise an average power shortage index (ANES), an average power outage duration index (CAIDI), an average power outage frequency index (CAIFI), an expected energy shortage value (EENS), an average power outage duration index (SAIDI) and an average power outage frequency index (SAIFI).
7. The comprehensive performance multidimensional assessment method according to claim 1, characterized in that: aiming at the comprehensive power quality of the system, a projection pursuit method based on a genetic algorithm is adopted, and the calculation steps are as follows:
classifying and grading the 110kV alternating current bus I electric energy quality index, the 110kV alternating current bus II electric energy quality index, the 35kV alternating current bus I electric energy quality index, the 35kV alternating current bus II electric energy quality index and the 1500V direct current bus electric energy quality index, and selecting the 95% probability value of the 110kV alternating current bus I electric energy quality index sample, the 95% probability value of the 110kV alternating current bus II electric energy quality index sample, the 95% probability value of the 35kV alternating current bus I electric energy quality index sample, the 95% probability value of the 35kV alternating current bus II electric energy quality index sample and the 95% probability value of the 1500V direct current bus electric energy quality index sample as electric energy quality evaluation sample
Figure FDA0002346400230000031
And carrying out standardization treatment;
Figure FDA0002346400230000032
wherein xijFor normalized index, xmaxjThe maximum value in the voltage level sample is n and m are the number of the initial random projection indexes and the evaluation indexes; suppose dj(j ═ 1,2 … m) and
Figure FDA0002346400230000033
for the corresponding projection direction and rating, then the one-dimensional projection value ziThe calculation is shown below:
Figure FDA0002346400230000034
calculating ziStandard deviation of (S)zAnd ziAnd
Figure FDA0002346400230000035
coefficient of correlation between Rzω：
Figure FDA0002346400230000036
Wherein EzIs the sequence [ zi]Average value, EωIs a sequence
Figure FDA0002346400230000037
Average value of (d); calculating a projection objective function f (d),
f(d)＝Sz|Rzω| (4)
according to equation (4), the projection objective function f (d) will depend on the projection direction djIs changed, the optimal projection direction d is calculated by solving the maximum of the projection objective function f (d)*：
Figure FDA0002346400230000041
Calculating the projection direction d by using a global optimization method based on a genetic algorithmjAnd the obtained optimal projection direction d is obtained*Substituting the data into a formula (2), drawing a scatter diagram of each index sample set, solving end point values corresponding to each level of the scatter diagram, and simultaneously performing piecewise linear interpolation approximation on the curve to obtain a piecewise continuous function; according to the obtained piecewise continuous function, the power quality rating of a 110kV alternating current bus I, the power quality rating of a 110kV alternating current bus II, the power quality rating of a 35kV alternating current bus I, the power quality rating of a 35kV alternating current bus II and the power quality rating of a 1500V direct current bus can be obtained; according to the rating of each voltage grade, the system power quality of the rail transit power supply system for the bilateral power supply structure can be evaluated by adopting a characteristic value weighting method, and a corresponding quantitative calculation result and rating are obtained.
8. The comprehensive performance multidimensional assessment method according to claim 1, characterized in that: aiming at the system application economy, an approximate ideal solution sorting method based on an application coefficient of variation method is adopted, and the calculation steps are as follows:
firstly, determining an evaluation matrix according to economic dimension indexes of system application, assuming that the number of evaluation indexes is w, and each evaluation index is ywThen the evaluation matrix Y is expressed as:
Y＝[y1,y2,y3,L,ypL,yw],p＝1,2,L w (6)
similarly, the evaluation weight matrix corresponding to the index
Figure FDA0002346400230000042
Expressed as:
Figure FDA0002346400230000043
different from the power quality index of the system, the application economy index of part of the system has negative property, namely the smaller the index is, the better the application economy is; therefore, the negative index needs to be located and converted into a positive index for evaluation, and the positive index is formulated as:
Figure FDA0002346400230000051
wherein y'p(p ═ 1,2, …, w) is an index for evaluating the economy of the system after conversion, γ is a conversion coefficient, and usually takes a value of 0.1; in addition, because the economic index units of the systems are different, in order to ensure the evaluation accuracy and correctness, the converted indexes are further normalized, and the dimensions of the converted indexes are removed by calculation so as to normalize the indexes; the normalized calculation formula is:
Figure FDA0002346400230000052
wherein y "p(p is 1,2, …, w) is the amount removedThe post-dimensional system applies an economic evaluation index, and a corresponding standard matrix after dimension removal is Y'; so that the average value thereof can be calculated
Figure FDA0002346400230000053
And standard deviation SP：
Figure FDA0002346400230000054
And (3) calculating the system application economic evaluation index variation coefficient V by combining the formula (9) and the formula (10)pAnd evaluating the weights
Figure FDA0002346400230000055
Figure FDA0002346400230000056
After determining the weight of the economic evaluation index applied by the system, the economic evaluation index matrix Y' applied by the weighting system is expressed as:
Figure FDA0002346400230000061
obtaining an economic evaluation index matrix Y 'applied to the weighting system, namely, carrying out comprehensive evaluation on the economic evaluation index matrix Y' by adopting an approximate ideal solution sorting method; if the index is regarded as a variable in a coordinate system, a high-dimensional space is formed geometrically, each evaluated object is a point determined by a plurality of index values reflecting the evaluated object in the space from the geometrical point of view, and the comprehensive evaluation problem becomes the sequencing and evaluation of the space points; firstly, determining reference points in space, including optimal and worst points, then calculating the distance between each evaluation object and the reference points, wherein the closer to the optimal point or the farther from the worst point, the better the comprehensive characteristics of the evaluated object are; since all the system application economic evaluation indexes are normalized and dimensionless, the maximum value in the indexes constitutes a positive ideal index
Figure FDA0002346400230000062
The minimum value of each index constitutes a negative ideal index
Figure FDA0002346400230000063
Then the economic evaluation index is applied to the system to the positive ideal index
Figure FDA0002346400230000064
Negative and positive ideal index
Figure FDA0002346400230000065
Is expressed as
Figure FDA0002346400230000066
Calculating relative proximity
Figure FDA0002346400230000067
Figure FDA0002346400230000068
Wherein
Figure FDA0002346400230000069
To evaluate the index to a positive ideal index
Figure FDA00023464002300000610
The distance of (a) to (b),
Figure FDA00023464002300000611
to evaluate the index to a positive ideal index
Figure FDA00023464002300000612
The distance of (d); according to the calculation result obtained by the formula (14), effectively performing quantitative evaluation on the application economy of the system; in which phaseTo degree of closeness
Figure FDA00023464002300000613
The larger the evaluation result, the smaller the relative distance between the evaluation object and the ideal index, and the better the corresponding evaluation result.
9. The comprehensive performance multidimensional assessment method according to claim 1, characterized in that: aiming at the operation stability of the system, an approximate ideal solution sorting method based on a mean square error method is adopted, and the calculation steps are as follows:
according to the topological structure and system parameters of the rail transit power supply system for the bilateral power supply structure, PowerFactory software is used for modeling the topological structure and the system parameters, the whole line power transformation equipment is simulated and modeled, software simulation is performed on various protocols and control algorithms of the whole line, and the operation working conditions of all levels of power transformation substations of the whole line of the rail transit and the lower end charge are simulated comprehensively and really; simulating and recording various faults or abnormal operation states of a rail transit power supply system through simulation operation conditions, and obtaining system operation stability evaluation indexes, wherein the system operation stability evaluation indexes comprise an average power shortage index (ANES) of a system, an average power failure duration index (CAIDI) of a user, an average power failure frequency index (CAIFI) of the user, an expected energy shortage value (EENS), an average power failure duration (SAIDI) of the system and an average power failure frequency index (SAIFI) of the system;
establishing an evaluation matrix R according to the evaluation index of the system operation stability and assuming that the number of the evaluation indexes is s,
R＝[R1,R2,R3,L,RqL,Rs],q＝1,2,L s (15)
similarly, the evaluation weight matrix corresponding to the index
Figure FDA0002346400230000071
Expressed as:
Figure FDA0002346400230000072
considering that the evaluation index of the running stability of part of the system is a negative index, each index needs to be positively changed, and the corresponding calculation formula is as follows:
Figure FDA0002346400230000073
wherein R'q(p ═ 1,2, …, s) is an index for evaluating the operation stability of the system after conversion, γ is a conversion coefficient, and usually takes a value of 0.1; on the other hand, the system operation stability evaluation indexes such as CAIDI and SAIDI have small values, and the unit of the system operation stability evaluation indexes is different, and it needs to be de-dimensioned and normalized, and the calculation formula is as follows:
Figure FDA0002346400230000081
wherein R "q(q is 1,2, …, s) is a dimensionless system operation stability evaluation index, and a corresponding dimensionless standard matrix is R'; and (3) obtaining a standard matrix as an average value of evaluation indexes in R':
Figure FDA0002346400230000082
and calculating the evaluation index weight of the running stability of the system by combining the evaluation index average value and utilizing a mean variance method:
Figure FDA0002346400230000083
after the system operation stability evaluation index weight is obtained, the weighting system applies an economic evaluation index matrix R' to be expressed as:
Figure FDA0002346400230000084
the similar system applies an economic evaluation method, an approximate ideal solution sorting method is used for evaluating the evaluation index of the system operation stability, and the application economy of the system is weightedEvaluation index matrix R'InThe maximum value and the minimum value in the index respectively form a positive ideal index
Figure FDA0002346400230000085
And negative ideal index
Figure FDA0002346400230000086
From the evaluation index to the positive ideal index
Figure FDA0002346400230000087
Negative and positive ideal index
Figure FDA0002346400230000088
The distance of (d) is expressed as:
Figure FDA0002346400230000089
wherein
Figure FDA00023464002300000810
To evaluate the index to a positive ideal index
Figure FDA00023464002300000811
The distance of (a) to (b),
Figure FDA00023464002300000812
to evaluate the index to a positive ideal index
Figure FDA00023464002300000813
The distance of (d); computing system application economy evaluation index relative closeness
Figure FDA00023464002300000814
Figure FDA0002346400230000091
Effectively and quantitatively evaluating the operation stability of the system according to the calculation result obtained by the formula (23); wherein relative proximity is
Figure FDA0002346400230000092
The larger the evaluation result, the smaller the relative distance between the evaluation object and the ideal index, and the better the corresponding evaluation result.
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