CN114580938A - Comprehensive power distribution effect evaluation method with multiple data dimensions - Google Patents
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Abstract
The invention provides a multidimensional comprehensive power distribution effect evaluation method, and belongs to the technical field of power distribution network data analysis. According to the method, through analyzing and establishing the multidimensional power distribution network evaluation index, the established index power supply capacity index, power supply reliability index and intelligent degree index are comprehensive and can adapt to new indexes of the intelligent power distribution system of the power distribution network, a comprehensive evaluation method and an improved evaluation model with high accuracy are researched and established to accurately obtain the evaluation of the grid-connected power distribution effect, and a decision is provided for the follow-up power distribution network improvement.
Description
Technical Field
The invention belongs to the technical field of power distribution network data analysis, and particularly relates to a multi-dimensional comprehensive power distribution effect evaluation method.
Background
Under the current economic social environment, the requirements of power utilization customers on power supply reliability and power supply service quality are increasingly improved, power grid enterprises face unprecedented operation pressure, the pressure is not only from the requirements of control cost, operation growth, accelerated innovation and continuous improvement of productivity, but also has important significance in evaluating the intelligent development level and the power supply reliability of a power distribution network, identifying weak links of the power distribution network and improving the satisfaction degree of users, and can provide powerful references for planning construction, power supply capacity improvement and operation optimization of a user-oriented intelligent power distribution network, reduce network loss, improve benefits and improve the operation efficiency of the power distribution network, thereby becoming an important guarantee for high-quality and reliable power supply of users.
The traditional method for evaluating the treatment capacity of the power quality treatment equipment lacks comprehensive quantitative evaluation on the equipment access power grid, evaluation indexes are not comprehensive enough, the method cannot be suitable for power distribution effect evaluation of the smart power grid, and the evaluation method is laggard, so that a comprehensive evaluation method and an evaluation model with high accuracy need to be researched and established to accurately obtain grid-connected power distribution effect evaluation.
Disclosure of Invention
The invention aims to solve the problems in the prior art and provides a multidimensional comprehensive power distribution effect evaluation method.
The invention is realized by the following technical scheme: the power distribution network effect evaluation method mainly comprises the following steps:
s1, designing and establishing a power distribution effect evaluation index of the power distribution network suitable for the smart grid; specifically comprises indexes of power supply capacity a, power supply reliability b and intelligent degree index c;
s2, obtaining the circuit, main transformer equipment and the basic data related to the index of the power grid within a certain time;
s3, filtering and denoising the acquired data, eliminating values obviously exceeding a normal range, and supplementing missing values by using normal values of other time points;
s4, calculating the index value of the last layer by obtaining the three-dimensional index of the numerical distribution, obtaining the evaluation score value by the index value, and normalizing the evaluation index score values of all levels;
s5, establishing a comprehensive evaluation model and obtaining the index weights of all levels;
and S6, obtaining the effect evaluation result of the power distribution network according to the comprehensive evaluation model, wherein the result comprises good, common, poor and poor results, the result score is good at 86-100, good at 71-85, common at 61-70, poor at 51-60 and poor below 50.
The calculation formula of the comprehensive evaluation model is as follows:
The alternative evaluation method further comprises a step S7 of analyzing the power distribution effect disadvantage items according to the evaluation result and correspondingly proposing improvement measures.
Further, in step S5 of the present invention, a comprehensive evaluation model is established and index weights at each level are obtained, and the obtaining steps of the index weights at the same level in each dimension in the model are as follows: s51: acquiring a structural judgment matrix at the same level by an analytic hierarchy process, and performing hierarchical order and consistency check on the hierarchical order, wherein the weight wc is obtained after the consistency is passed;
s52, calculating the information entropy after the index data of the same level are standardized, and determining the weight of each index as Ws according to an entropy method;
s53, establishing a pairwise comparison table of the same level index ordered comparison, and calculating according to the weight of the sequence chart to obtain Wy;
s54, calculating the contrast strength and the conflict of each index data in the same level index, multiplying the contrast strength by the conflict index, and carrying out normalization processing to obtain the final CRITIC weight wcr;
s55: weight confidence correlation coefficient
Calculating, namely calculating confidence correlation coefficients of the weight vector obtained by each measured mode and the weight vectors obtained by other modes respectively, wherein Wa is the weight vector obtained by one of the measured calculation modes, Wi is the weight vector obtained by the other modes, and the total correlation between each mode and the other modes is obtained
Sequentially calculating the correlation xi of other weight calculation modestotalIn order of magnitude, the relevance xi is selectedtotalAnd averaging the weights of each index to obtain the weight wi of the final evaluation model.
The index evaluation weights of the levels under other dimensions are calculated in the same manner as the steps S51-S55; and weighting and summing the rating results of the next-level indexes to obtain the evaluation score of the previous-level index, performing layer-by-layer index calculation to obtain the scores a, b and c of the indexes of the power supply capacity, the power supply reliability and the intelligent degree in the comprehensive evaluation model, and finally obtaining the score of the evaluation result according to the comprehensive evaluation model.
Specifically, the evaluation indexes established by the evaluation method comprise three-dimensional evaluation indexes, specifically comprising a power distribution network power supply capacity index (a), a power supply reliability index (b) and an intelligent degree index (c).
Specifically, the power supply capacity index (a) comprises a capacity-load ratio (11), a load rate (12) and a power supply equipment utilization rate (13);
the capacity-load ratio comprises 110kV capacity-load ratio and 35kV capacity-load ratio;
the load ratio comprises an average load ratio of 10kV lines, an average load ratio of 10kV distribution transformer, a maximum load light load ratio of 110kV lines, a maximum load light load ratio of 35kV lines, a maximum load heavy load ratio of 35kV lines, a maximum load light load ratio of 10kV lines and a maximum load heavy load ratio of 10kV lines;
the utilization rate of the power supply equipment comprises equipment power utilization rate, equipment electric quantity utilization rate and equipment life cycle utilization rate;
the equipment power utilization rate index is used for evaluating the size condition of the power distribution network passing through equipment at a certain time section, and comprises 6 secondary indexes including the actual equipment utilization rate, the upper limit equipment utilization rate and the relative equipment utilization rate of a main transformer and a line.
(1) Actual utilization rate of equipment
The actual utilization index of the equipment is defined as the ratio of the maximum power value of the load actually carried by the equipment to the ultimate load capacity of the equipment;
(2) upper limit utilization of equipment
The equipment upper limit utilization rate index is defined as the ratio of the power upper limit value of the power grid equipment to the limit capacity of the equipment when the power distribution network meets the safe and stable operation constraint condition;
(3) relative utilization of equipment
The equipment relative utilization index is defined as the ratio of the maximum power value of the load actually carried by the equipment to the safe load capacity of the equipment under the operation constraint condition;
the equipment electric quantity utilization rate can evaluate the quantity of the equipment transmission electric quantity in a certain time scale of the power distribution network, and the quantity comprises 4 secondary indexes including capacity factors of main transformers and lines and equipment operation efficiency.
(1) Capacity factor
The capacity factor is an international general index for calculating the utilization rate of the power equipment, and can evaluate the utilization rate of the in-service equipment, and is equal to the ratio of the actual electric quantity passing through the equipment to the maximum theoretical electric quantity in a certain time period. The utilization rate of the equipment in a fixed period can be evaluated, and the utilization rate of the equipment can be evaluated from a uniform level. Compared with the power index, the index considers the influence of time scale, reflects the average utilization rate of equipment in a certain fixed period, and takes the fluctuation of load and the randomness of load development into account.
(2) Efficiency of plant operation
The Equipment operating Efficiency (EER) is based on the load continuous curve, the deviation of the actual operating condition of the Equipment relative to the economic operating interval can be quantitatively calculated, and then the index value is calculated.
The equipment life cycle utilization rate, the equipment life cycle utilization rate index is used for evaluating the economic utilization condition of the power distribution network equipment from the time of operation to the time of recovering life, and the secondary index comprises the life cycle utilization rate of a main transformer and a line and the asset cost of unit electric quantity.
(1) Life cycle utilization
The life cycle utilization index is defined as the ratio of the actual transmission electric quantity to the theoretical transmission electric quantity in the life cycle of the equipment or the expected effective life cycle of the equipment;
(2) cost per unit electricity asset
The life cycles corresponding to the devices with different investment costs are different, and the unit electric quantity asset cost is established for evaluating the utilization condition of the device assets and is defined as the ratio of the total investment cost of the device to the theoretical transmission electric quantity in the life cycle of the device or the expected effective life cycle of the device.
The intelligent power distribution and supply indexes of the invention are as follows:
and the three-level index of the capacity-load ratio, the three-level index of the load rate and the four-level index of the utilization rate of the power supply equipment are directly used as evaluation score values according to calculated values.
Power supply reliability index (b)
The method comprises the steps of line equipment failure rate, equipment failure recovery time, average user power failure time and average annual household power failure times;
the line fault rate is an important index for reflecting the operation management level of a distribution network and the health level of distribution equipment, and the lower the fault rate is, the higher the power supply reliability level of the power grid is;
the fault rate of the transformer substation is an important index for reflecting the operation management level of a distribution network and the health level of distribution equipment, and the lower the fault rate is, the higher the power supply reliability level of the power grid is; the reliability level of the power supply bureau is directly influenced by the fault outage rate.
The equipment fault recovery time is the time interval from the time when the equipment is timed to the time when the equipment is recovered to normal operation, and the longer the equipment fault recovery time is, the worse the reliability and stability of power distribution are.
The average power failure time of the user refers to the average power failure hours of the user in the counting period.
The annual average power failure frequency refers to the ratio of the total annual power failure frequency sum of each household of a power grid with the same voltage class in a certain power supply area to the total number of households in the power supply area. Smaller values mean better equipment quality and higher power supply reliability.
The invention has the following indexes of all levels of power supply reliability:
the calculation score of the four-level index of the line and equipment fault rate in the reliability index can be the ratio of the number of lines or main transformers with faults under the voltage level to the total number of lines or main transformers of the power distribution network; the equipment failure recovery time four-level index calculation can adopt the ratio of the shortest recovery time of the power distribution network to the recovery time; similarly, the average power failure time of the user and the average power failure times of the user per year can be qualitatively defined into 4 degree ranges, and the high, medium, normal and low scores are respectively 0.3, 0.5, 0.7 and 1.
Power supply intelligent index (c)
The intelligent indexes comprise: the system comprises a Distribution Automation System (DAS) rate, an intelligent device coverage rate, an intelligent device utilization rate, an intelligent terminal online rate, a remote control success rate, a communication accuracy rate, a communication packet loss rate, a communication delay level and an information safety protection level;
the fault detection method also comprises self-healing indexes of lines and equipment, wherein the self-healing indexes comprise self-healing rate and self-healing speed, and various faults such as short circuit, open circuit and the like are easy to occur due to a plurality of reasons such as misoperation, insulation aging, overvoltage and the like in the operation process of the power system. After the fault occurs, whether the power system can realize self-recovery without human participation represents the level of power grid automation. The fault rate in the evaluation of the power distribution effect of the smart grid has great influence on the self-healing evaluation. The self-healing requirement on the power grid is higher at places with higher fault rates, and the self-healing requirement on the power grid is lower at places with lower fault rates.
The self-healing speed is the time for whether the power system can realize self-healing without the participation of people after the fault occurs, and when the self-healing speed of the system is calculated, the self-healing reliability of some loads is not high, which means that the loads may not self-heal after the fault occurs between the power grids. If the cure rate of such a load is incorporated into the calculation of the self-healing rate of the system, distortion is evident. Therefore, a self-healing reliability threshold S2 may be designed to eliminate consideration of the self-healing speed of loads below this threshold, only consider the self-healing speed of loads equal to or above this threshold, and finally obtain the self-healing speed of the system.
The system comprises a Distribution Automation System (DAS) rate, an intelligent equipment coverage rate, an intelligent equipment utilization rate, a master station system online rate, an intelligent terminal online rate, a remote control success rate, a communication accuracy rate, a communication packet loss rate, a communication delay rate and a communication safety protection level, and comprises communication safety operation time length, communication interference and attack times. The intelligent power supply indexes of the invention are as follows:
for the power supply intelligent indexes, the calculation of the communication delay rate, the communication packet loss rate, the communication interference rate and the attack rate in the three-level indexes is in inverse proportion to the scores of the indexes, and the indexes can be divided into high, medium, common and low according to the degree range, wherein the scores are respectively 0.3, 0.5, 0.7 and 1. And the other index scores adopt index calculation results as score results.
Compared with the prior art, the invention has the beneficial effects that: according to the method, through analyzing and establishing the multidimensional power distribution network evaluation index, the established index power supply capacity index, power supply reliability index and intelligent degree index are comprehensive and can adapt to new indexes of the intelligent power distribution system of the power distribution network, a comprehensive evaluation method and an improved evaluation model with high accuracy are researched and established to accurately obtain the evaluation of the grid-connected power distribution effect, and a decision is provided for the follow-up power distribution network improvement.
Drawings
Fig. 1 shows a flow of a power distribution effect evaluation method according to the present invention.
Detailed Description
With reference to fig. 1, the method for evaluating the effect of the power distribution network in the embodiment of the present invention mainly includes the following steps:
s1, designing and establishing a power distribution effect evaluation index of the power distribution network suitable for the smart grid; specifically, the method comprises the following steps of a, each index of power supply capacity, b, power supply reliability index and c, intelligent degree index;
s2, obtaining the circuit, main transformer equipment and the basic data related to the index of the power grid within a certain time;
s3, filtering and denoising the acquired data, eliminating values obviously exceeding a normal range, and supplementing missing values by using normal values of other time points;
s4, calculating the index value of the last layer by obtaining the three-dimensional index of the numerical distribution, obtaining the evaluation score value by the index value, and normalizing the evaluation index score values of all levels;
s5, establishing a comprehensive evaluation model and obtaining index weights of all levels;
and S6, obtaining the effect evaluation result of the power distribution network according to the comprehensive evaluation model, wherein the result comprises good, common, poor and poor results, the result score is good at 86-100, good at 71-85, common at 61-70, poor at 51-60 and poor below 50.
The calculation formula of the comprehensive evaluation model is as follows:
The alternative evaluation method further comprises a step S7 of analyzing the power distribution effect disadvantage items according to the evaluation result and correspondingly proposing improvement measures.
Further, the method for obtaining the index weight of the same level under each dimension in the comprehensive evaluation model comprises the following steps: the load rate (12) of the secondary indexes in the power supply capacity index and the weight calculation of the utilization rate (13) of the power supply equipment are taken as examples.
S51: acquiring a structure judgment (pair comparison) matrix of a secondary index by an analytic hierarchy process, performing level single sorting and consistency check of the level single sorting, and obtaining a capacity-load ratio (11) after the consistency is passed, wherein the weights of the load rate (12) and the utilization rate (13) of the power supply equipment are wc1, wc2 and wc3 respectively;
s52, calculating the information entropy of each index standard after data normalization, and determining the weight of each index as Ws1, Ws2 and Ws3 according to an entropy method;
s53, establishing an ordered comparison pairwise comparison table, and calculating according to the weight of the sequence diagram to obtain Wy1, Wy2 and Wy 3;
s54, calculating the contrast intensity and the conflict of each index data, multiplying the contrast intensity and the conflict index, and carrying out normalization processing to obtain the final CRITIC weight wcr1, wcr2 and wcr 3;
s55: weight confidence correlation coefficient
Calculating, namely calculating confidence correlation coefficients of the weight vector obtained by each measured mode and the weight vectors obtained by other modes respectively, wherein Wa is the weight vector obtained by one of the measured calculation modes, Wi is the weight vector obtained by the other modes, and the total correlation between each mode and the other modes is obtained
Sequentially calculating correlation of other weight calculation modesXi naturetotalIn order of magnitude, the relevance xi is selectedtotalAnd averaging the weights of each index to obtain the weight wi of the final evaluation model.
The index evaluation weights of the respective levels in the other dimensions are also calculated in the same manner as in S51 to S55 described above. And weighting and summing the rating results of the next-level indexes to obtain the evaluation result of the previous-level indexes, performing layer-by-layer index calculation to obtain the scores a, b and c of the indexes of the power supply capacity, the power supply reliability and the intelligent degree in the comprehensive evaluation model, and finally obtaining the scores of the evaluation results according to the comprehensive evaluation model.
Specifically, the evaluation indexes established by the evaluation method comprise three-dimensional evaluation indexes, specifically comprise a power distribution network power supply capacity index (a), a power supply reliability index (b) and an intelligent degree index (c).
Specifically, the power supply capacity index (a) comprises a capacity-load ratio (11), a load rate (12) and a power supply equipment utilization rate (13);
the capacity-load ratio comprises 110kV capacity-load ratio and 35kV capacity-load ratio;
the load ratio comprises an average load ratio of 10kV lines, an average load ratio of 10kV distribution transformer, a maximum load light load ratio of 110kV lines, a maximum load light load ratio of 35kV lines, a maximum load heavy load ratio of 35kV lines, a maximum load light load ratio of 10kV lines and a maximum load heavy load ratio of 10kV lines;
the utilization rate of the power supply equipment comprises equipment power utilization rate, equipment electric quantity utilization rate and equipment full life cycle utilization rate;
the equipment power utilization rate index is used for evaluating the size condition of the power distribution network passing through equipment at a certain time section, and comprises 6 secondary indexes including the actual equipment utilization rate, the upper limit equipment utilization rate and the relative equipment utilization rate of a main transformer and a line.
(1) Actual utilization rate of equipment
The actual utilization index of the equipment is defined as the ratio of the maximum power value of the load actually carried by the equipment to the ultimate load capacity of the equipment;
(2) upper limit utilization of equipment
The equipment upper limit utilization rate index is defined as the ratio of the power upper limit value of the power grid equipment to the limit capacity of the equipment when the power distribution network meets the safe and stable operation constraint condition;
(3) relative utilization of equipment
The equipment relative utilization index is defined as the ratio of the maximum power value of the load actually carried by the equipment to the safe load capacity of the equipment under the operation constraint condition;
the equipment electric quantity utilization rate can evaluate the quantity of the equipment transmission electric quantity in a certain time scale of the power distribution network, and the quantity comprises 4 secondary indexes including capacity factors of main transformers and lines and equipment operation efficiency.
(1) Capacity factor
The capacity factor is an international general index for calculating the utilization rate of the power equipment, and can evaluate the utilization rate of the in-service equipment, and is equal to the ratio of the actual electric quantity passing through the equipment to the maximum theoretical electric quantity in a certain time period. The utilization rate of the equipment in a fixed period can be evaluated, and the utilization rate of the equipment can be evaluated from a uniform level. Compared with the power index, the index considers the influence of time scale, reflects the average utilization rate of equipment in a certain fixed period, and takes the fluctuation of load and the randomness of load development into account.
(2) Efficiency of plant operation
The Equipment operating Efficiency (EER) is based on the load continuous curve, the deviation of the actual operating condition of the Equipment relative to the economic operating interval can be quantitatively calculated, and then the index value is calculated.
The equipment life cycle utilization rate, the equipment life cycle utilization rate index is used for evaluating the economic utilization condition of the power distribution network equipment from the time of operation to the time of recovering life, and the secondary index comprises the life cycle utilization rate of a main transformer and a line and the asset cost of unit electric quantity.
(1) Life cycle utilization
The life cycle utilization index is defined as the ratio of the actual transmission electric quantity to the theoretical transmission electric quantity in the life cycle of the equipment or the expected effective life cycle of the equipment;
(2) cost per unit electricity asset
The life cycles corresponding to the devices with different investment costs are different, and the unit electric quantity asset cost is established for evaluating the utilization condition of the device assets and is defined as the ratio of the total investment cost of the device to the theoretical transmission electric quantity in the life cycle of the device or the expected effective life cycle of the device.
The intelligent power distribution and supply indexes of the invention are as follows:
and the three-level index of the capacity-load ratio, the three-level index of the load rate and the four-level index of the utilization rate of the power supply equipment are directly used as evaluation score values according to calculated values.
Index of reliability of Power supply (b)
The method comprises the steps of line equipment failure rate, equipment failure recovery time, average user power failure time and average annual household power failure times;
the line fault rate is an important index for reflecting the operation management level of a distribution network and the health level of distribution equipment, and the lower the fault rate is, the higher the power supply reliability level of the power grid is;
the fault rate of the transformer substation is an important index for reflecting the operation management level of a distribution network and the health level of distribution equipment, and the lower the fault rate is, the higher the power supply reliability level of the power grid is; the reliability level of a power supply office is directly influenced by the fault outage rate.
The equipment fault recovery time is the time interval from the time when the equipment is timed to the time when the equipment is recovered to normal operation, and the longer the equipment fault recovery time is, the worse the reliability and stability of power distribution are.
The average power failure time of the user refers to the average power failure hours of the user in the counting period.
The annual average power failure frequency refers to the ratio of the total annual power failure frequency sum of each household of a power grid with the same voltage class in a certain power supply area to the total number of the households in the power supply area. Smaller values mean better equipment quality and higher power supply reliability.
The invention has the following indexes of all levels of power supply reliability:
the calculation score of the four-level index of the line and equipment fault rate in the reliability index can be the ratio of the number of lines or main transformers with faults under the voltage level to the total number of lines or main transformers of the power distribution network; the four-level index calculation of the equipment fault recovery time can adopt the ratio of the shortest recovery time of the power distribution network to the recovery time; similarly, the average power failure time of the user and the average power failure times of the user per year can be qualitatively defined into 4 degree ranges, and the high, medium, normal and low scores are respectively 0.3, 0.5, 0.7 and 1.
Power supply intelligent index (c)
The intelligent indexes comprise: the system comprises a Distribution Automation System (DAS) rate, an intelligent device coverage rate, an intelligent device utilization rate, an intelligent terminal online rate, a remote control success rate, a communication accuracy rate, a communication packet loss rate, a communication delay level and an information safety protection level;
the fault detection method also comprises self-healing indexes of lines and equipment, wherein the self-healing indexes comprise self-healing rate and self-healing speed, and various faults such as short circuit, open circuit and the like are easy to occur due to a plurality of reasons such as misoperation, insulation aging, overvoltage and the like in the operation process of the power system. After the fault occurs, whether the power system can realize self-recovery without human participation represents the level of power grid automation. The fault rate in the evaluation of the power distribution effect of the smart grid has great influence on the self-healing evaluation. The self-healing requirement on the power grid is higher at places with higher fault rates, and the self-healing requirement on the power grid is lower at places with lower fault rates.
The self-healing speed is the time for whether the power system can realize self-healing without human participation after a fault occurs, and when the self-healing speed of the system is calculated, the self-healing credibility of some loads is not high, which means that the self-healing cannot be realized after the fault occurs between the power grids. If the cure rate of such a load is incorporated into the calculation of the self-healing rate of the system, distortion is evident. Therefore, a self-healing reliability threshold S2 may be designed to eliminate consideration of the self-healing speed of loads below this threshold, only consider the self-healing speed of loads equal to or above this threshold, and finally obtain the self-healing speed of the system.
The system comprises a Distribution Automation System (DAS) rate, an intelligent device coverage rate, an intelligent device utilization rate, a main station system online rate, an intelligent terminal online rate, a remote control success rate, a communication accuracy rate, a communication packet loss rate, a communication delay rate and a communication safety protection level, and comprises a communication safety operation time length, and communication interference and attack times. The intelligent power supply indexes of the invention are as follows:
for the power supply intelligent index, the calculation of the communication delay rate, the communication packet loss rate, the communication interference and the attack rate in the three-level index is in inverse proportion to the scores, and the scores can be divided into high, medium, normal and low according to the degree range, and are respectively 0.3, 0.5, 0.7 and 1. And the other index scores adopt index calculation results as score results.
In the description of the present invention, it is to be noted that, unless otherwise explicitly specified or limited, the terms "connected" and "connected" are to be interpreted broadly, e.g., as being fixed or detachable or integrally connected; can be mechanically or electrically connected; may be directly connected or indirectly connected through an intermediate. The specific meanings of the above terms in the present invention can be understood by those skilled in the art according to specific situations.
In the description of the present invention, unless otherwise specified, the terms "upper", "lower", "left", "right", "inner", "outer", and the like indicate orientations or positional relationships based on those shown in the drawings, and are only for convenience of description and simplicity of description, but do not indicate or imply that the referred device or element must have a specific orientation, be constructed in a specific orientation, and be operated, and thus, should not be construed as limiting the present invention.
Finally, it should be noted that the above-mentioned technical solution is only one embodiment of the present invention, and it will be apparent to those skilled in the art that various modifications and variations can be easily made based on the application method and principle of the present invention disclosed herein, and the method is not limited to the method described in the above-mentioned embodiment of the present invention, so that the above-mentioned embodiment is only preferred and not restrictive.
Claims (6)
1. A multidimensional comprehensive power distribution effect evaluation method is characterized by comprising the following steps:
s1, designing and establishing a power distribution effect evaluation index of the power distribution network suitable for the smart grid; specifically comprises indexes of power supply capacity a, power supply reliability b and intelligent degree index c;
s2, obtaining the circuit, main transformer equipment and the basic data related to the index of the power grid within a certain time;
s3, filtering and denoising the acquired data, eliminating values obviously exceeding a normal range, and supplementing missing values by using normal values of other time points;
s4, calculating the index value of the last layer by obtaining the three-dimensional index of the numerical distribution, obtaining the evaluation score value by the index value, and normalizing the evaluation index score values of all levels;
s5, establishing a comprehensive evaluation model and obtaining index weights of all levels;
s6, obtaining the effect evaluation result of the power distribution network according to the comprehensive evaluation model, wherein the calculation formula of the comprehensive evaluation model is as follows:
in step S5, the step of calculating the peer index weight in each dimension of the comprehensive evaluation model specifically includes:
s51: acquiring a structural judgment matrix at the same level by an analytic hierarchy process, and performing hierarchical order and consistency check on the hierarchical order, wherein the weight wc is obtained after the consistency is passed;
s52, calculating the information entropy after the index data of the same level are standardized, and determining the weight of each index as Ws according to an entropy method;
s53, establishing a pairwise comparison table of the same level index ordered comparison, and calculating according to the weight of the sequence chart to obtain Wy;
s54, calculating the contrast strength and the conflict of each index data in the same level index, multiplying the contrast strength by the conflict index, and carrying out normalization processing to obtain the final CRITIC weight wcr;
s55: weight confidence correlation coefficient
Calculating, namely calculating confidence correlation coefficients of the weight vector obtained by each measured mode and the weight vectors obtained by other modes respectively, wherein Wa is the weight obtained by one of the measured calculation modes, Wi is the weight in the other modes, and the total correlation between each mode and the other modes is obtained
Sequentially calculating the correlation xi of other weight calculation modestotalIn order of magnitude, the relevance xi is selectedtotalAnd averaging the weights of each index to obtain the weight wi of the final evaluation model.
The index evaluation weights of the levels under other dimensions are calculated in the same manner as the steps S51-S55; and weighting and summing the next-level index rating results to obtain the evaluation score of the previous-level index, performing layer-by-layer index calculation to obtain the score a of each index of the power supply capacity, the score b of the power supply reliability index and the score c of the intelligent degree index in the comprehensive evaluation model, and finally obtaining the score of the evaluation result according to the comprehensive evaluation model.
2. The method of claim 1, wherein the evaluation result is: good, general, poor, and bad, wherein the score of the result is good at 86-100, good at 71-85, general at 61-70, bad at 51-60, and bad at less than 50.
3. The method of claim 1, wherein the method comprises: the power supply capability index (a) includes a capacity-to-load ratio (11), a load factor (12), and a power supply equipment utilization rate (13).
4. The method of claim 1, wherein the method comprises: the power supply reliability index (b) comprises line equipment failure rate, equipment failure recovery time, average user power failure time and average annual household power failure times.
5. The method of claim 1, wherein the method comprises: the power supply intelligent index (c) includes: the system comprises a Distribution Automation System (DAS) rate, an intelligent device coverage rate, an intelligent device utilization rate, an intelligent terminal online rate, a remote control success rate, a communication accuracy rate, a communication packet loss rate, a communication delay level and an information safety protection level.
6. The method of claim 1, wherein the method comprises: the evaluation method further comprises a step S7 of analyzing the power distribution effect disadvantage items according to the evaluation results and correspondingly proposing improvement measures.
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| CN115169990A (en) * | 2022-09-02 | 2022-10-11 | 南京华盾电力信息安全测评有限公司 | Electric power comprehensive intelligent energy service management system based on user side |
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