CN106887839B - Distribution terminal distribution optimization method considering data transmission error influence of information link - Google Patents

Distribution terminal distribution optimization method considering data transmission error influence of information link Download PDF

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CN106887839B
CN106887839B CN201710137585.5A CN201710137585A CN106887839B CN 106887839 B CN106887839 B CN 106887839B CN 201710137585 A CN201710137585 A CN 201710137585A CN 106887839 B CN106887839 B CN 106887839B
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stage
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CN106887839A (en
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罗凤章
张天宇
魏冠元
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Tianjin University
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    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02H—EMERGENCY PROTECTIVE CIRCUIT ARRANGEMENTS
    • H02H7/00—Emergency protective circuit arrangements specially adapted for specific types of electric machines or apparatus or for sectionalised protection of cable or line systems, and effecting automatic switching in the event of an undesired change from normal working conditions
    • H02H7/26—Sectionalised protection of cable or line systems, e.g. for disconnecting a section on which a short-circuit, earth fault, or arc discharge has occured
    • H02H7/261—Sectionalised protection of cable or line systems, e.g. for disconnecting a section on which a short-circuit, earth fault, or arc discharge has occured involving signal transmission between at least two stations
    • H02H7/262—Sectionalised protection of cable or line systems, e.g. for disconnecting a section on which a short-circuit, earth fault, or arc discharge has occured involving signal transmission between at least two stations involving transmissions of switching or blocking orders
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
    • H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/001—Methods to deal with contingencies, e.g. abnormalities, faults or failures

Abstract

A distribution terminal distribution optimization method considering the influence of data transmission errors in an information link. It comprises a setting module; dividing feeder line types; distribution terminal deployment configuration division; dividing fault conditions; data acquisition required by quantitative modeling calculation; quantitative modeling calculation; dividing data transmission error events of an information link; collecting information data; correcting the calculation process; and obtaining a distribution planning result of the feeder line power distribution terminal. The method can effectively guide and analyze the influence of the 'three remote' function on the system power failure time, the comprehensive economic cost and the deployment position of the power distribution terminal, is beneficial to better improving the power supply reliability and the voltage quality of the power grid, improves the management efficiency of the power distribution terminal, and has guiding significance for improving the power distribution automation level in China and promoting the construction of the intelligent power grid in China.

Description

Distribution terminal distribution optimization method considering data transmission error influence of information link
Technical Field
The invention belongs to the technical field of feeder distribution automatic terminal configuration, and particularly relates to a distribution terminal distribution optimization method considering the influence of data transmission errors in an information link.
Background
Distribution Automation (DA) Systems can be regarded as a typical Cyber-Physical Systems (CPS), and their information links have a non-negligible impact on the safe and reliable power supply of the managed Physical power Distribution system. In practical application, the characteristics of the distribution automation terminals under different classification standards are often combined, and the distribution automation terminals are generally divided into two categories, namely 'three-remote' distribution terminals and 'two-remote' distribution terminals. Wherein, the 'three remote' function refers to remote signaling, remote measuring and remote control functions. The distribution automation is different from the requirements of full coverage of power grid nodes and full monitoring of equipment of a main network dispatching automation (EMS), and due to the characteristics of multi-surface and wide-radial operation of distribution network equipment points, investment and other reasons, the construction of the distribution automation generally adopts the modes of partial node remote control and partial node remote measurement to realize 10kV distribution network information acquisition, and the full coverage of distribution network information and the control of 10kV key nodes are completed through data sharing. As an important part of distribution automation planning in distribution network planning, reasonable configuration of the remote measurement and control terminal has a crucial influence on the development of distribution automation benefits.
The information link represented by power distribution communication is an important component for realizing power distribution automation. At present, most of research aiming at the link of distribution automation information focuses on distribution automation communication network technology (1 Korea political affairs, Chonliang, IEC 61850-based high-level distribution automation open communication system [ J ]. power grid technology, 2011, 35 (4): 183) 186.[2] iriluhua, Liujian. mixed communication scheme of distribution automation system [ J ]. power system automation, 2001, 25 (23): 52-54.[3] Liujian, Zhang Qihua, Zhang Xiaoqing, etc., distribution network fault processing of relay protection and distribution automation coordination [ J ]. power system protection and control, 2011, 39 (16): 53-57.), distribution automation fault processing application technology (3 ] Liujian, Zhang Qiqing, etc.. distribution network fault processing of relay protection and distribution automation coordination [ J ]. power system protection and control, 2011, 39(16): 53-57 [4] liujian, zhangxiaoqing, zhao tree benevolence, etc. power distribution automation fault handling performance master station injection test method [ J ] power system automation, 2012, 36 (18): 67-71) and architecture and construction design of communication systems ([5] liuwenxia, tension euphoria ] power distribution automation system information security level assessment based on FAHP and improved D-S theory [ J ]. east china power, 2010, 38 (1): 67-71), how to consider the influence of information links in the power distribution automation system, there are still many basic works to be developed to study the number planning of terminals and the point arrangement planning of specific deployment positions of the CPS system. Liu Xiao faithful (distribution automation communication system design and implementation [ D ] based on EPON technology, Beijing: North China Power university, 2014) proposes that an effective communication means is adopted in distribution automation to improve the accuracy of data transmission, so that the distribution terminal equipment can accurately reflect the operation instruction of an operator, and further improve the reliability of distribution network. Wulin et al (application of wireless private network communication in large-scale distribution automation [ J ]. electric power system communication, 2012, 22 (231): 107-. The design and implementation of the distribution automation communication system [ J ] electric power system communication 2003, (12): 45-47) of the tourmaline provides requirements and implementation methods of a distribution automation hierarchical structure, a communication mode and the like on the basis of analyzing the functional requirements of the distribution automation communication system. Wang scholan et al (information safety research [ C ] in distribution automation design, China Motor engineering society annual meeting, Sichuan Chengdu, 2013) propose a set of intelligent distribution network information safety design scheme aiming at a distribution automation network information safety technology. The forest Yongfeng and the like (a power distribution automation terminal information safety risk evaluation method research [ J ]. automation and instrument 2015, (12): 11-14) analyze possible risk problems from a system layer, a communication layer and a configuration layer of power distribution automation, provide a set of information safety evaluation method and evaluation process, have guiding significance for solving the information safety problem of the power distribution automation terminal, and provide a platform for safety evaluation and vulnerability detection of the power distribution automation system.
In summary, research on the distribution automation information link mainly focuses on information security assessment, distribution automation system architecture design and the like at present, but research on a distribution point optimal configuration method of a distribution terminal specific deployment position considering reliability and economy of a distribution system is developed without considering the influence of the information link from the overall view of a distribution automation CPS.
Disclosure of Invention
In order to solve the above problems, an object of the present invention is to provide a distribution terminal distribution optimization method considering the influence of data transmission errors in information links.
In order to achieve the above purpose, the power distribution terminal stationing optimization method considering the influence of error in data transmission of the information link provided by the invention comprises the following steps in sequence:
1) firstly, according to the content of the planning of the configuration quantity of the power distribution terminals in the power distribution automation system, preliminarily calculating the quantity of the power distribution terminals required to be configured for a feeder line to be analyzed, and then setting and executing modules required by the power distribution terminal distribution optimization method considering the error influence of data transmission in an information link, wherein the modules comprise: the system comprises a feeder line type dividing module, a distribution terminal deployment configuration dividing module, a fault condition dividing module, a data acquisition module, a quantitative calculation module, a distribution terminal distribution planning module, a data error event dividing module, an information link data acquisition module, an information link quantitative correction module and a three-remote function influence analysis module;
2) the feeder line type division module is used for dividing the feeder lines into ① feeder lines without the tie switch and ② feeder lines with the tie switch according to whether the tie switch is installed on the feeder lines;
3) the configuration of the power distribution terminals is divided into three types by using a power distribution terminal deployment configuration dividing module, wherein ① all configures three remote power distribution terminals, ② all configures two remote power distribution terminals, ③ mixedly configures the three remote power distribution terminals and the two remote power distribution terminals;
4) the fault condition dividing module is utilized to divide the fault treatment after the fault occurs into three stages, namely ① fault positioning stage, ② artificial fault isolation stage, ③ fault repair stage;
5) acquiring required data for quantitative modeling calculation of system power failure time and power failure load in three fault processing stages of two types of feeders under the configuration condition of the three types of power distribution terminals by using a data acquisition module according to results in the steps 2), 3) and 4), wherein the required data comprises: the number and the positions of the section switches on the feeder line, the number and the positions of the connection switches on the feeder line, the fault rate, the length of each section of the feeder line, the sum of equivalent loads connected with the section area, fault positioning time, artificial fault isolation time and fault repair time;
6) carrying out quantitative modeling calculation on the system power failure time and the power failure load in three fault stages of the two types of feeders under the configuration condition of the three types of power distribution terminals by utilizing a quantitative calculation module according to the results in the steps 2), 3) and 4) and the data acquired in the step 5), wherein the quantitative modeling calculation of the system power failure time and the power failure load comprises the quantitative modeling calculation of the system power failure time and the power failure load of the feeder of which ① is not provided with the interconnection switch;
7) the data transmission error event of the information link is divided by a data error event dividing module, wherein ① event A refers to error but no error in remote control of a power distribution terminal, ② event B refers to error but no error in remote control, ③ event C refers to error in remote control and remote control;
8) acquiring data required by quantitative modeling calculation of the divided events in the step 7) by using an information link data acquisition module according to results in the step 2) to the step 7), wherein the required data comprises: time for checking the remote signaling function and correcting the information; checking and correcting the remote control information and carrying out isolation processing on the fault again for the required time; checking and correcting the functions and information of remote control and remote signaling, and carrying out isolation processing on the fault for the required time; checking the remote measuring function, correcting the information, and manually searching the time for positioning the correct fault position; correcting the telemetering information, and judging the time of the fault type again; the probability of occurrence of each event;
9) performing quantitative modeling calculation on all sub-events in the step 7) by using an information link quantitative correction module according to results in the steps 2) to 7) and data acquired in the step 8), and correcting a calculation process;
10) performing optimized configuration on the specific distribution position of the distribution automation terminal device on the feeder line according to the results of the steps 2) to 9) by using a 'three-remote' function influence analysis module, establishing a target function by using the power failure load of each configuration condition on the basis of the given distribution terminal configuration quantity, and further obtaining a distribution planning result of the feeder line distribution terminal by using the power supply reliability condition as a constraint; and effectively guides and analyzes the influence of the three-remote function on the system power failure time, the comprehensive economic cost and the distribution terminal deployment position.
The distribution terminal point-placement optimization method considering the influence of the error of the data transmission of the information link, provided by the invention, introduces the influence of the error of the data transmission of the information link in the stages of fault positioning, artificial fault isolation and fault repair, provides a corresponding reliability index correction model and a correction strategy, can carry out optimization configuration on the specific point-placement position of the distribution terminal on a feeder line, can effectively guide and analyze the influence of the 'three remote' function on the system power failure time, the comprehensive economic cost and the distribution terminal deployment position, is favorable for better improving the power supply reliability and the voltage quality of a power grid, improves the management efficiency of the distribution terminal, and has guiding significance for improving the distribution automation level of China and promoting the construction of the intelligent power grid of China.
Drawings
Fig. 1 is a flowchart of a distribution terminal stationing optimization method considering the influence of error in data transmission in an information link according to the present invention.
Fig. 2-1 is a feed line diagram without a tie switch.
Fig. 2-2 is a feed line diagram with tie switches present.
Fig. 3 is a schematic diagram of a feeder line used in the embodiment of the present invention.
Fig. 4-1 is a schematic diagram illustrating the influence of the accuracy of three remotes on the system power-off time and the comprehensive economic cost.
Fig. 4-2 is a schematic diagram illustrating the influence of the remote signaling accuracy on the distribution terminal distribution position optimization result.
Fig. 4-3 are schematic diagrams illustrating the effect of telemetry accuracy on the optimization result of the distribution terminal placement position.
Fig. 4-4 are schematic diagrams illustrating the influence of remote control accuracy on the distribution terminal placement position optimization result.
Detailed Description
The following describes in detail a distribution terminal point placement optimization method considering the influence of error in data transmission in an information link, which is provided by the present invention, with reference to the accompanying drawings and embodiments.
As shown in fig. 1, the power distribution terminal stationing optimization method considering the influence of error in data transmission in the information link provided by the present invention includes the following steps in sequence:
1) first, the number of power distribution terminals in a power distribution automation system is planned according to configuration (liujian, etc.. power system automation, 2013, 37 (12): 44-50), preliminarily calculating the number of the power distribution terminals required to be configured for the feeder line to be analyzed, and then setting modules required for executing the power distribution terminal distribution optimization method considering the data transmission error influence of the information link, wherein the modules comprise: the system comprises a feeder line type dividing module, a distribution terminal deployment configuration dividing module, a fault condition dividing module, a data acquisition module, a quantitative calculation module, a distribution terminal distribution planning module, a data error event dividing module, an information link data acquisition module, an information link quantitative correction module and a three-remote function influence analysis module;
2) the feeder is divided into ① feeders without tie switches as shown in figure 2-1, ② feeders with tie switches as shown in figure 2-2, and feeder with m-1 line section switches (excluding outlet switch z) as shown in figures 2-1 and 2-2 according to whether tie switches are installed on the feeders1) Is divided into m sections and simultaneously comprises n interconnection switches (generally m is more than or equal to n); i is the number of the segment area; y isnA representative tie switch;
3) the configuration of the power distribution terminals is divided into three types by using a power distribution terminal deployment configuration dividing module, wherein ① all configures three remote power distribution terminals, ② all configures two remote power distribution terminals, ③ mixedly configures the three remote power distribution terminals and the two remote power distribution terminals;
4) the fault condition dividing module is utilized to divide the fault treatment after the fault occurs into three stages, namely ① fault positioning stage, ② artificial fault isolation stage, ③ fault repair stage;
5) acquiring required data for quantitative modeling calculation of system power failure time and power failure load in three fault processing stages of two types of feeders under the configuration condition of the three types of power distribution terminals by using a data acquisition module according to results in the steps 2), 3) and 4), wherein the required data comprises: the number and the positions of the section switches on the feeder line, the number and the positions of the connection switches on the feeder line, the fault rate, the length of each section of the feeder line, the sum of equivalent loads connected with the section area, fault positioning time, artificial fault isolation time and fault repair time;
6) carrying out quantitative modeling calculation on the system power failure time and the power failure load in three fault stages of the two types of feeders under the configuration condition of the three types of power distribution terminals by utilizing a quantitative calculation module according to the results in the steps 2), 3) and 4) and the data acquired in the step 5), wherein the quantitative modeling calculation of the system power failure time and the power failure load comprises the quantitative modeling calculation of the system power failure time and the power failure load of the feeder of which ① is not provided with the interconnection switch;
① the quantitative modeling calculation of the system power failure time and power failure load of the feeder without the contact switch is divided into three types according to the configuration condition of the power distribution terminal, namely, a quantitative modeling calculation of the system power failure time and power failure load when the 'three remote' power distribution terminal is completely configured, b quantitative modeling calculation of the system power failure time and power failure load when the 'two remote' power distribution terminal is completely configured, c, quantitative modeling calculation of the system power failure time and power failure load when the 'three remote' and the 'two remote' power distribution terminals are mixed;
a. the quantitative modeling calculation steps of the system power failure time and the power failure load when the three-remote power distribution terminal is completely configured are as follows: (1) in the fault positioning stage, the system power failure time and the power failure load are quantitatively modeled and calculated; (2) carrying out quantitative modeling calculation on system power failure time and power failure load in the manual fault isolation stage; (3) in the fault repairing stage, the system power failure time and the power failure load are quantitatively modeled and calculated; (4) in the fault processing stage, the system power failure time and the power failure load are quantitatively modeled and calculated;
(1) and (3) carrying out quantitative modeling calculation on the system power failure time and the power failure load in the fault positioning stage:
the system power failure time corresponding to the fault location stage of the ith section of regional line fault is as follows:
Figure BDA0001241847340000051
in the formula, T1iRepresenting the system power failure time t corresponding to the fault location stage of the i section area line fault1iFor fault location time of i-th zone, UiRepresenting the total number of users supplying power to the ith section; liRepresenting the equivalent line length of the ith section area; f. ofiRepresenting the failure rate of equivalent equipment in the ith section of area, and the unit is sub/km & a; m represents the number of sections of the feeder line;
fault location phaseCorresponding system power off time T1Comprises the following steps:
Figure BDA0001241847340000052
the corresponding system power failure load is as follows:
Figure BDA0001241847340000061
in the formula, E1iSystem outage load, P, corresponding to fault location phase representing i-th section area line faultiThe sum of equivalent loads of all loads for supplying power to the ith section of area is represented;
system power failure load E corresponding to fault location stage1Comprises the following steps:
Figure BDA0001241847340000062
(2) and (3) carrying out quantitative modeling calculation on system power failure time and power failure load in the manual fault isolation stage:
the system power failure time corresponding to the artificial fault isolation stage of the i section of regional line fault is as follows:
Figure BDA0001241847340000063
in the formula, T2iRepresenting the system power failure time t corresponding to the artificial fault isolation stage of the i section area line fault2iThe artificial fault isolation time of the ith section of area;
system power failure time T corresponding to manual fault isolation stage2Comprises the following steps:
Figure BDA0001241847340000064
the corresponding system power failure load is as follows:
Figure BDA0001241847340000065
in the formula, E2iRepresenting the system power failure load corresponding to the artificial fault isolation stage of the i section of regional line fault;
system power failure load E corresponding to manual fault isolation stage2Comprises the following steps:
Figure BDA0001241847340000066
(3) and (3) quantitative modeling calculation of system power failure time and power failure load in the fault repair stage:
the system power failure time corresponding to the fault repair stage of the i section of regional line fault is as follows:
Figure BDA0001241847340000067
in the formula, T3iRepresenting the system power failure time t corresponding to the fault repair stage of the i section area line fault3iThe fault repair time of the ith section of area; z is a radical ofk0 denotes the corresponding location at which the distribution terminal is configured, z k1 represents that no power distribution terminal is arranged at the corresponding position;
system power failure time T corresponding to fault repair stage3Comprises the following steps:
Figure BDA0001241847340000071
the corresponding system power failure load is as follows:
Figure BDA0001241847340000072
in the formula, E3iRepresenting the system power failure load corresponding to the fault repair stage of the i section of regional line fault;
system power failure load E corresponding to fault repair stage3Comprises the following steps:
Figure BDA0001241847340000073
(4) and (3) carrying out quantitative modeling calculation on the system power failure time and the power failure load in the fault processing stage:
T＝T1+T2+T3(13)
in the formula, T is the system power failure time corresponding to the whole fault processing stage, and is a unit h; t is1、T2And T3Respectively corresponding to the system power failure time of the fault positioning stage, the manual fault isolation stage and the fault repairing stage, wherein the unit is h;
E＝E1+E2+E3(14)
in the formula, E is the system power failure load corresponding to the whole fault processing stage, and the unit kWh; e1、E2And E3Respectively corresponding to the system power failure loads of the fault positioning stage, the manual fault isolation stage and the fault repairing stage, wherein the unit is kWh;
b. the quantitative modeling calculation steps of the system power failure time and the power failure load when the 'two remote' power distribution terminal is completely configured are as follows: (1) in the fault positioning stage, the system power failure time and the power failure load are quantitatively modeled and calculated; (2) carrying out quantitative modeling calculation on system power failure time and power failure load in the manual fault isolation stage; (3) in the fault repairing stage, the system power failure time and the power failure load are quantitatively modeled and calculated; (4) in the fault processing stage, the system power failure time and the power failure load are quantitatively modeled and calculated;
(1) the quantitative modeling calculation formula of the system power failure time and the power failure load at the fault positioning stage is consistent with the formula (1) -4, but the artificial fault load isolation time t of each section of area2iNot 0, so the calculation result is not 0;
(2) the quantitative modeling calculation formula of the system power failure time and the power failure load at the artificial fault isolation stage is consistent with the formula (5) -8, but the artificial fault load isolation time t of each section of area2iNot 0, so the calculation result is not 0;
(3) the quantitative modeling calculation formula of the system power failure time and the power failure load in the fault repair stage is consistent with the formula (9) -12;
(4) the quantitative modeling calculation formula of the system power failure time and the power failure load in the fault processing stage is consistent with the formulas (13) and (14).
c. The quantitative modeling calculation steps of the system power failure time and the power failure load when the three-remote power distribution terminal and the two-remote power distribution terminal are configured in a mixed mode are as follows: (1) in the fault positioning stage, the system power failure time and the power failure load are quantitatively modeled and calculated; (2) carrying out quantitative modeling calculation on system power failure time and power failure load in the manual fault isolation stage; (3) in the fault repairing stage, the system power failure time and the power failure load are quantitatively modeled and calculated; (4) in the fault processing stage, the system power failure time and the power failure load are quantitatively modeled and calculated;
(1) the quantitative modeling calculation formula of the system power failure time and the power failure load at the fault positioning stage is consistent with the formula (1) -4, but the artificial fault load isolation time t of each section of area2iNot 0, so the calculation result is not 0;
(2) and (3) quantitative modeling calculation of system power failure time and power failure load in the artificial fault isolation stage:
firstly, assuming that the number of line section switches of the 'three-remote' power distribution terminal is M-1, the number of 'three-remote' areas obtained by dividing all the line section switches of the 'three-remote' power distribution terminal is M. For analyzing the system power failure time and power failure load in the manual fault isolation stage, omega is usedi’Represents the set of loads in the ith 'triple-remote' distribution terminal area, | Ωi’L is the total number of users in the area; event set W ═ W1,w2,…,w2i’-1,w2i’,…,w2M-1,w2M) The configuration conditions of the region determined by the "three-remote" distribution terminal at the fault position and the "two-remote" distribution terminal device in the region collectively include 2M events, which are specifically expressed as:
w2i’-1: the fault occurs in an area determined by the ith 'three remote' power distribution terminal, and a 'two remote' power distribution terminal is configured in the area;
w2i’: the fault occurs in the area determined by the ith 'three remote' power distribution terminal, but the 'two remote' power distribution terminal is not configured in the area;
the system power failure time corresponding to the artificial fault isolation stage of the i-th section of regional line fault is as follows:
Figure BDA0001241847340000081
Figure BDA0001241847340000082
the corresponding system power failure load is as follows:
Figure BDA0001241847340000091
Figure BDA0001241847340000092
(3) and the quantitative modeling calculation formula of the system power failure time and the power failure load in the fault repair stage is consistent with the formula (9) -12.
(4) The quantitative modeling calculation formula of the system power failure time and the power failure load in the fault processing stage is consistent with the formulas (13) and (14).
② the modeling calculation of the system power failure time and power failure load of the feeder line with the interconnection switch is divided into three types according to the configuration condition of the power distribution terminal, namely, a quantitative modeling calculation of the system power failure time and power failure load when the 'three remote' power distribution terminal is completely configured, b quantitative modeling calculation of the system power failure time and power failure load when the 'two remote' power distribution terminal is completely configured, c, quantitative modeling calculation of the system power failure time and power failure load when the 'three remote' power distribution terminal and the 'two remote' power distribution terminal are mixedly configured;
a. the quantitative modeling calculation steps of the system power failure time and the power failure load when the three-remote power distribution terminal is completely configured are as follows: (1) in the fault positioning stage, the system power failure time and the power failure load are quantitatively modeled and calculated; (2) carrying out quantitative modeling calculation on system power failure time and power failure load in the manual fault isolation stage; (3) in the fault repairing stage, the system power failure time and the power failure load are quantitatively modeled and calculated; (4) in the fault processing stage, the system power failure time and the power failure load are quantitatively modeled and calculated;
(1) the quantitative modeling calculation formula of the system power failure time and the power failure load at the fault positioning stage is consistent with the formula (1) -4, but the artificial fault load isolation time t of each section of area2i0, so the calculation result is 0;
(2) the quantitative modeling calculation formula of the system power failure time and the power failure load at the artificial fault isolation stage is consistent with the formula (5) -8, but the artificial fault load isolation time t of each section of area2iIs 0, so the calculation result is 0.
(3) And (3) quantitative modeling calculation of system power failure time and power failure load in the fault repair stage:
the system power failure time corresponding to the fault repair stage of the i section of regional line fault is as follows:
Figure BDA0001241847340000093
in the formula, T3iRepresenting the system power failure time t corresponding to the fault repair stage of the i section area line fault3iThe fault repair time of the ith section of area;
and the system power failure time calculation formula corresponding to the fault repair stage is consistent with the formula (10).
The corresponding system power failure load is as follows:
Figure BDA0001241847340000101
in the formula, E3iRepresenting the system power failure load corresponding to the fault repair stage of the i section of regional line fault;
and the system power failure load calculation formula corresponding to the fault repair stage is consistent with the formula (12).
(4) The quantitative modeling calculation formula of the system power failure time and the power failure load in the fault processing stage is consistent with the formulas (13) and (14).
b. The quantitative modeling calculation steps of the system power failure time and the power failure load when the 'two remote' power distribution terminal is completely configured are as follows: (1) in the fault positioning stage, the system power failure time and the power failure load are quantitatively modeled and calculated; (2) carrying out quantitative modeling calculation on system power failure time and power failure load in the manual fault isolation stage; (3) in the fault repairing stage, the system power failure time and the power failure load are quantitatively modeled and calculated; (4) in the fault processing stage, the system power failure time and the power failure load are quantitatively modeled and calculated;
(1) the quantitative modeling calculation formula of the system power failure time and the power failure load at the fault positioning stage is consistent with the formula (1) -4, but the artificial fault load isolation time t of each section of area2iNot 0, so the calculation result is not 0;
(2) the quantitative modeling calculation formula of the system power failure time and the power failure load at the artificial fault isolation stage is consistent with the formula (5) -8, but the artificial fault load isolation time t of each section of area2iNot 0, so the calculation result is not 0;
(3) the quantitative modeling calculation formula of the system power failure time and the power failure load in the fault repair stage is consistent with the formulas (10), (12), (19) and (20);
(4) the quantitative modeling calculation formula of the system power failure time and the power failure load in the fault processing stage is consistent with the formulas (13) and (14);
c. the quantitative modeling calculation steps of the system power failure time and the power failure load when the three-remote power distribution terminal and the two-remote power distribution terminal are configured in a mixed mode are as follows: (1) in the fault positioning stage, the system power failure time and the power failure load are quantitatively modeled and calculated; (2) carrying out quantitative modeling calculation on system power failure time and power failure load in the manual fault isolation stage; (3) in the fault repairing stage, the system power failure time and the power failure load are quantitatively modeled and calculated; (4) in the fault processing stage, the system power failure time and the power failure load are quantitatively modeled and calculated;
(1) the quantitative modeling calculation formula of the system power failure time and the power failure load at the fault positioning stage is consistent with the formula (1) -4, but the artificial fault load isolation time t of each section of area2i0, so the calculation result is 0;
(2) the quantitative modeling calculation formula of the system power failure time and the power failure load at the manual fault isolation stage is consistent with the formula (15) - (18);
(3) the quantitative modeling calculation formula of the system power failure time and the power failure load in the fault repair stage is consistent with the formulas (10), (12), (19) and (20);
(4) the quantitative modeling calculation formula of the system power failure time and the power failure load in the fault processing stage is consistent with the formulas (13) and (14);
7) a data error event dividing module is used for dividing information link data transmission error events, wherein ① event A is an event that a remote signaling and remote control of a power distribution terminal has errors but remote measurement is correct, ② event B is an event that a remote signaling and remote control has errors but remote measurement is correct, and ③ event C is an event that both the remote signaling and remote measurement have errors.
① event A includes sub-events of a. event A1 that the remote control information is correct but the remote signaling information is incorrect, b. event A2 that the remote control information is incorrect but the remote signaling information is correct, and c. event A3 that the remote control information is incorrect and the remote signaling information is incorrect.
② event B includes sub-events of three categories, a. event B1: a determination that a telemetry information error affects the location of a fault, B. event B2: a determination that a telemetry information error affects the type of fault, c. event B3: a determination that a telemetry information error affects both the location and the type of fault.
③ event C includes nine sub-events determined by event a and event B, a. event C1, which is that remote control information is correct but remote signaling information is incorrect and a telemetering information error affects determination of a fault location, B. event C2, which is that remote control information is correct but remote signaling information is incorrect and an information error affects determination of a fault type, C. event C3, which is that remote control information is correct but remote signaling information is incorrect and a telemetering information error affects determination of a fault location and a fault type at the same time, d. event C4, which is that remote control information is incorrect but remote signaling information is incorrect and a telemetering information error affects determination of a fault location, event C5, which is that remote control information is incorrect but remote signaling information is incorrect and an information error affects determination of a fault type, f. event C7, which remote control information is incorrect but remote signaling information is incorrect and a telemetering information error affects determination of a fault location and a fault type at the same time, g. event C7, which remote control information is incorrect and a telemetering information affects determination of a telemetering information is incorrect and a telemetering information affects determination of a fault type and a telemetering event C9, and a telemetering information error affects determination of a telemetering event C355631, and a telemetering information is incorrect and a telemetering information affects determination of.
8) Acquiring data required by quantitative modeling calculation of the divided events in the step 7) by using an information link data acquisition module according to results in the step 2) to the step 7), wherein the required data comprises: time for checking the remote signaling function and correcting the information; checking and correcting the remote control information and carrying out isolation processing on the fault again for the required time; checking and correcting the functions and information of remote control and remote signaling, and carrying out isolation processing on the fault for the required time; checking the remote measuring function, correcting the information, and manually searching the time for positioning the correct fault position; correcting the telemetering information, and judging the time of the fault type again; the probability of occurrence of each event;
9) performing quantitative modeling calculation on all sub-events in the step 7) by using an information link quantitative correction module according to results in the steps 2) to 7) and data acquired in the step 8), and correcting a calculation process;
the quantitative correction model of all the sub-events comprises the following specific steps:
① event A (let it happen with probability p1) The quantitative correction model comprises three types of quantitative correction models of events:
a. event A1 (let the probability of its occurrence be p11): when the event occurs, relative to the quantitative calculation formula of the fault repairing stage in the step 6), the fault repairing time needs to be corrected as follows:
Figure BDA0001241847340000121
in the formula (I), the compound is shown in the specification,
Figure BDA0001241847340000122
time for checking the remote signaling function and correcting the information.
b. Event A2 (let the probability of its occurrence be p12): when the event occurs, the system power failure of the artificial fault isolation stage is negative relative to the quantitative model of the artificial fault isolation stage in the step 6)The lotus is expressed as:
Figure BDA0001241847340000123
in the formula, t2”＝t2 12The time required for checking and correcting the remote control information and carrying out isolation processing on the fault again.
c. Event A3 (let the probability of its occurrence be p13): when the event occurs, compared with the quantitative calculation formula of the fault repairing stage in the step 6), the system power failure load calculation formula of the artificial fault isolation stage is consistent with the formula (22), and t in the formula is2"need to use t2 13Alternative, t2 13The time required for checking and correcting the functions and information of remote control and remote signaling and carrying out isolation processing on the fault again is shown.
② event B (let it happen with probability p2) The quantitative correction model comprises three types of quantitative correction models of events:
b. event B1 (let p be the probability of its occurrence)21): when the event occurs, relative to the quantitative calculation formula of the fault location stage in the step 6), the fault location time needs to be corrected as follows:
Figure BDA0001241847340000124
wherein, t1 21To check the telemetry function and correct the information, the time to locate the correct fault location is manually sought.
b. Event B2 (let p be the probability of its occurrence)22): when the event occurs, relative to the quantitative calculation formula of the fault location stage in the step 6), the fault location time needs to be corrected as follows:
Figure BDA0001241847340000125
wherein, t1 22For correcting telemetric informationAnd judging the time of the fault type again.
c. Event B3 (let p be the probability of its occurrence)23): when the event occurs, relative to the quantitative calculation formula of the fault location stage in the step 6), the fault location time needs to be corrected as follows:
Figure BDA0001241847340000126
③ event C quantitative modification model includes the quantitative modification models of nine types of events:
since the nine types of sub-events in the event C are formed by combining the three types of sub-events in the event a and the three types of sub-events in the event B, the time quantization modification model of the nine types of events is as follows:
a. event C1 (let the probability of its occurrence be p31)：
tC11＝t3i+t3 11(26)
tC12＝t1i+t1 21(27)
tC1＝tC11+tC12(28)
b. Event C2 (let the probability of its occurrence be p32)：
tC21＝t3i+t3 11(29)
tC22＝t1i+t1 22(30)
tC2＝tC21+tC22(31)
c. Event C3 (let the probability of its occurrence be p33)：
tC31＝t3i+t3 11(32)
tC32＝t1i+t1 21+t1 22(33)
tC3＝tC31+tC32(34)
d. Event C4 (let the probability of its occurrence be p34)：
tC41＝t2i+t2 12(35)
tC42＝t1i+t1 21(36)
tC4＝tC41+tC42(37)
e. Event C5 (let the probability of its occurrence be p35)：
tC51＝t2i+t2 12(38)
tC52＝t1i+t1 22(39)
tC5＝tC51+tC52(40)
f. Event C6 (let the probability of its occurrence be p36)：
tC61＝t2i+t2 12(41)
tC62＝t1+t1i 21+t1 22(42)
tC6＝tC61+tC62(43)
g. Event C7 (let the probability of its occurrence be p37)：
tC71＝t2i+t2 13(44)
tC72＝t1i+t1 21(45)
tC7＝tC71+tC72(46)
h. Event C8 (let the probability of its occurrence be p38)：
tC81＝t2i+t2 13(47)
tC82＝t1i+t1 22(48)
tC8＝tC81+tC82(49)
i. Event C9 (let the probability of its occurrence be p39)：
tC91＝t2i+t2 13(50)
tC92＝t1i+t1 21+t1 22(51)
tC9＝tC91+tC92(52)
Suppose the accuracy of the remote control information is pc(ii) a The accuracy of the remote signaling information is ps(ii) a Accuracy of telemetry information is pmWherein p ismAnd can be represented as:
(1-pm)＝pm1+pm2+pm3(53)
wherein p ism1Representing the probability of occurrence of an event that telemetry has a false impact on the location of the fault but does not affect the determination of the fault category; p is a radical ofm2Representing the probability of occurrence of an event in which telemetry has a false impact on the fault category but does not impact the location determination; p is a radical ofm3Representing the probability of telemetry having an event that falsely affects the fault type and location determination.
Thus, the probability of each sub-event occurrence can be expressed as:
p＝1-pm·pc·ps(54)
wherein p is the probability of data error occurrence.
p1＝(1-pc·ps)pm(55)
p2＝(1-pm)·pc·ps(56)
p3＝(1-pc·ps)·(1-pm) (57)
p11＝pc·(1-ps)·pm(58)
p12＝(1-pc)·ps·pm(59)
p13＝(1-pc)(1-ps)·pm(60)
p21＝pc·ps·pm1(61)
p22＝pc·ps·pm2(62)
p23＝pc·ps·pm3(63)
p31＝pc·(1-ps)·pm1(64)
p32＝pc·(1-ps)·pm2(65)
p33＝pc·(1-ps)·pm3(66)
p34＝(1-pc)·ps·pm1(67)
p35＝(1-pc)·ps·pm2(68)
p36＝(1-pc)·ps·pm3(69)
p37＝(1-pc)(1-ps)·pm1(70)
p38＝(1-pc)(1-ps)·pm2(71)
p39＝(1-pc)(1-ps)·pm3(72)
And correcting the time of each stage by using an expected value analysis method, wherein the corrected time is as follows under the condition that the terminal is configured with three remote terminals after correction:
① time correction of fault location phase:
Figure BDA0001241847340000151
after finishing, obtaining:
Figure BDA0001241847340000152
② time correction of manual fault isolation phase:
Figure BDA0001241847340000153
③ time correction of the failover phase:
Figure BDA0001241847340000154
substituting the corrected time into the formulae (1) to (20) in the above step 6).
10) Performing optimized configuration on the specific distribution position of the distribution automation terminal device on the feeder line according to the results of the steps 2) to 9) by using a 'three-remote' function influence analysis module, establishing a target function by using the power failure load of each configuration condition on the basis of the given distribution terminal configuration quantity, and further obtaining a distribution planning result of the feeder line distribution terminal by using the power supply reliability condition as a constraint; and effectively guides and analyzes the influence of the three-remote function on the system power failure time, the comprehensive economic cost and the distribution terminal deployment position.
The method comprises the following specific steps:
a. replacing the power outage time of the corresponding stage in the step 6) according to formulas (74) to (76) obtained in the step 7), establishing an objective function according to the power outage load obtained in the step 6), solving the objective function by adopting a genetic algorithm, and performing genetic operation; the objective function is as follows:
Figure BDA0001241847340000161
in the formula, CEPower failure loss is unit electric quantity; n is a radical of2And N3The configuration number of the distribution terminals of 'two remote' and 'three remote'; c2And C3The initial investment unit price of the power distribution terminal is 'two remote' and 'three remote'; i.e. i2And i3The investment conversion rate of the 'two remote' and 'three remote' power distribution terminals is reduced; a is2And a3The economic service life of the power distribution terminal is two remote and three remote;
b. judging whether an iteration termination condition is reached according to a fitness value in a genetic algorithm, wherein the method comprises the steps of constructing a fitness function, adding a reliability constraint condition to a target function shown in a formula (77) in a form of a penalty function, and using the reliability constraint condition as a fitness evaluation function of a genetic individual;
wherein the reliability constraint condition is a set power supply reliability threshold constraint condition, i.e.
β1＞βset(78)
Wherein, βsetPower supply reliability requirements for feeder lines β1The specific expression of the power supply reliability under a certain point distribution scheme of the power distribution terminal is shown as the formula (23):
Figure BDA0001241847340000162
wherein, T is calculated by formula (13) and formulas (74) to (76) in consideration of the influence of the information system;
c. when the continuous m generations do not meet the reliability constraint condition, returning to the step 1), and readjusting the number of the power distribution terminals required to be configured on the feeder line; otherwise, outputting the optimal distribution planning result of the feeder line power distribution terminal.
The distribution terminal point placement optimization method provided by the invention, which takes the feeder of the IEEE33 node shown in fig. 3 as an example, and considers the influence of error in data transmission of information links, is described. And by combining the universal three-remote and two-remote distribution terminals to configure the example, the bus-node 0 feeder outlet switch in fig. 3, the line section switches (the optional positions for distribution automation terminal distribution optimization) between nodes 1-2, 2-3, 4-5, 8-9 and 14-15 and the interconnection switch divide the system into 6 section areas, such as z in the figure1,z2,..,z6As shown. Load P in each segment area1,P2…,P5100kW, 400kW, 500kW, 2500kW, 400kW are sequentially arranged; the number of users in the segment area is 10, and the equivalent line length l1,l2,..,l61.275km, 0.26km, 0.108km, 0.17km, 0.09km and 0.22km in sequence; the failure rate of the feeder line is 0.23 times/km.year; fault handling time t corresponding to fault location phase, artificial fault isolation phase and fault repair phase1,t2,t3Sequentially 1h, 0.5h and 4 h; the purchase prices of the 'three remote' power distribution terminal and the 'two remote' power distribution terminal are respectively 5 ten thousand yuan and 1 ten thousand yuan; the return rate of investment of the power distribution terminal is 0.1, the service life is 20 years, and the unit electric quantity is taken to lose powerESetting power supply reliability requirement β for power supply area of the systemsetThe content was 99.9%. Firstly, the feeder line is preliminarily calculated according to the content of the distribution terminal configuration quantity planning in the distribution automation systemThe number of power distribution terminals required to be configured is 3. .
The power supply reliability requirement of the system power supply area is set to be 99.9%. Meanwhile, for the purpose of comparative analysis, the following three scenarios are considered: (1) scene one: the remote measurement and remote control accuracy is constant at 100%, and the remote signaling accuracy is changed; (2) scene two: the remote signaling and remote control accuracy is constant at 100%, and the remote measurement accuracy is changed; (3) scene three: the remote signaling and remote measuring accuracy is constant at 100%, and the remote control accuracy is changed. And setting the data information to have a false event A1,A2,A3,B1,B2The corresponding time correction is t3 11＝0.2h，t2 12＝0.4h，t2 13＝0.6h，t1 21＝0.15h，t1 22Assuming 0.15h, the probability p of three events corresponding to errors in telemetry informationm1,pm2,pm3Same, i.e. pm1＝pm2＝pm3＝(1-pm)/3。
By adopting the method, after the quantitative calculation model is corrected by considering the error influence of data transmission in the information link, the result is shown in a figure 4-1-figure 4-4 and a table 1-table 1-3:
(1) influence on system power-off time and comprehensive economic cost
When the distribution terminal configuration is constant at z2And z6Is provided with a 'two remote' distribution terminal, z5When the 'three remote' power distribution terminal is configured, the influence condition of the scene one, two and three on the system power failure time and the comprehensive economic cost is shown in the figure 4-1. It can be seen from fig. 4-1 that the accuracy of the "three remote" function affects both the comprehensive economic cost and the power off time of the system, and the comprehensive economic cost and the power off time decrease as the accuracy of the "three remote" function increases. The specific amplification ratios are shown in tables 1-1 to 1-3. From the longitudinal comparison of tables 1-1 to 1-3, the economic cost of the system and the amplification ratio of the power failure time are basically unchanged along with the reduction of the accuracy of the remote signaling function; along with the reduction of the accuracy of remote measurement, the economic cost of the system and the amplification proportion of the power failure time are slightly reduced; with reduced accuracy of remote control, the systemThe economic cost and the power failure time are greatly reduced, which shows that when the remote control accuracy is high, the system can obtain larger economic and reliability benefits. From the transverse comparison of tables 1-1 to 1-3, the accuracy of the remote control, remote measurement and remote signaling functions presents a very obvious sequential decreasing trend on the system reliability and the economic cost influence degree, which shows that under the same initial investment condition, the accuracy of the remote control function is ensured to obtain larger economic and reliability benefits.
TABLE 1-1 influence of remote signalling accuracy change on the overall economic cost and system blackout time
Figure BDA0001241847340000171
Figure BDA0001241847340000181
TABLE 1-2 Effect of telemetry accuracy Change on Integrated economic cost and System blackout time
Figure BDA0001241847340000182
TABLE 1-3 Effect of remote control accuracy Change on Integrated economic cost and System blackout time
Figure BDA0001241847340000183
(2) Impact on distribution automation terminal deployment location
Because the influence of the information error on the system reliability is relatively small, when the influence of the accuracy of the 'three remote' function on the distribution terminal distribution optimization is inspected, 99.992% is set as a threshold value required by the power supply reliability, and if the threshold value is lower than the threshold value, the distribution terminal distribution configuration scheme needs to be corrected. Fig. 4-2-4 show the effect of the change of the accuracy of the three-remote function on the distribution terminal distribution optimization result respectively.
As shown in fig. 4-2, as the remote signaling accuracy increases, the complexity of the distribution terminal increasesThe economic cost is reduced, and the power supply reliability is improved; because the power supply reliability rate meets the requirement limit of 99.992%, the distribution optimization configuration result is unchanged along with the change of the remote signaling and remote measuring accuracy rate, and both the distribution optimization configuration result and the remote measuring accuracy rate are z2And z6Is provided with a 'two remote' distribution terminal, z5And is provided with a three-remote power distribution terminal. 4-3 and 4-4, along with the improvement of the accuracy of remote measurement and remote control, the comprehensive economic cost of the power distribution terminal is reduced, and the power supply reliability is improved; when the remote control accuracy is lower than 70%, the power supply reliability is less than 99.992%; when the telemetry success rate is lower than 40%, the power supply reliability is less than 99.992%; after the correction measures are taken, the power supply reliability is obviously improved, but the required investment economic cost is increased; the result of the stationing planning is changed along with the change of the accuracy of remote control and remote measurement, when p is more than or equal to 30%c<At 35%, the configuration is z2And z6Is provided with a 'two remote' distribution terminal, z4A 'three remote' power distribution terminal is arranged; when p is less than or equal to 35 percentc<At 70%, the configuration is z5And z6Is provided with a 'two remote' distribution terminal, z2A 'three remote' power distribution terminal is arranged; when p iscWhen the power distribution terminal configuration scheme is larger than or equal to 70%, the power distribution terminal configuration scheme is an original configuration scheme; when p is more than or equal to 30%m<At 40%, the configuration is z5And z6Is provided with a 'two remote' distribution terminal, z2Is provided with a 'three remote' distribution terminal device, when pmAnd when the power distribution terminal configuration scheme is more than or equal to 40%, the power distribution terminal configuration scheme is the original configuration scheme.
The above embodiments are only for illustrating the present invention, and the steps of the method and the like can be changed, and all equivalent changes and modifications based on the technical scheme of the present invention should not be excluded from the protection scope of the present invention.

Claims (5)

1. A distribution terminal distribution optimization method considering the influence of data transmission errors in an information link is characterized by comprising the following steps: the method comprises the following steps which are carried out in sequence:
1) firstly, according to the content of the planning of the configuration quantity of the power distribution terminals in the power distribution automation system, preliminarily calculating the quantity of the power distribution terminals required to be configured for a feeder line to be analyzed, and then setting and executing modules required by the power distribution terminal distribution optimization method considering the error influence of data transmission in an information link, wherein the modules comprise: the system comprises a feeder line type dividing module, a distribution terminal deployment configuration dividing module, a fault condition dividing module, a data acquisition module, a quantitative calculation module, a distribution terminal distribution planning module, a data error event dividing module, an information link data acquisition module, an information link quantitative correction module and a three-remote function influence analysis module;
2) the feeder line type division module is used for dividing the feeder lines into ① feeder lines without the tie switch and ② feeder lines with the tie switch according to whether the tie switch is installed on the feeder lines;
3) the configuration of the power distribution terminals is divided into three types by using a power distribution terminal deployment configuration dividing module, wherein ① all configures three remote power distribution terminals, ② all configures two remote power distribution terminals, ③ mixedly configures the three remote power distribution terminals and the two remote power distribution terminals;
4) the fault condition dividing module is utilized to divide the fault treatment after the fault occurs into three stages, namely ① fault positioning stage, ② artificial fault isolation stage, ③ fault repair stage;
5) acquiring required data for quantitative modeling calculation of system power failure time and power failure load in three fault processing stages of two types of feeders under the configuration condition of the three types of power distribution terminals by using a data acquisition module according to results in the steps 2), 3) and 4), wherein the required data comprises: the number and the positions of the section switches on the feeder line, the number and the positions of the connection switches on the feeder line, the fault rate, the length of each section of the feeder line, the sum of equivalent loads connected with the section area, fault positioning time, artificial fault isolation time and fault repair time;
6) carrying out quantitative modeling calculation on the system power failure time and the power failure load in three fault stages of the two types of feeders under the configuration condition of the three types of power distribution terminals by utilizing a quantitative calculation module according to the results in the steps 2), 3) and 4) and the data acquired in the step 5), wherein the quantitative modeling calculation of the system power failure time and the power failure load comprises the quantitative modeling calculation of the system power failure time and the power failure load of the feeder of which ① is not provided with the interconnection switch;
7) the data transmission error event of the information link is divided by a data error event dividing module, wherein ① event A refers to error but no error in remote control of a power distribution terminal, ② event B refers to error but no error in remote control, ③ event C refers to error in remote control and remote control;
8) acquiring data required by quantitative modeling calculation of the divided events in the step 7) by using an information link data acquisition module according to results in the step 2) to the step 7), wherein the required data comprises: time for checking the remote signaling function and correcting the information; checking and correcting the remote control information and carrying out isolation processing on the fault again for the required time; checking and correcting the functions and information of remote control and remote signaling, and carrying out isolation processing on the fault for the required time; checking the remote measuring function, correcting the information, and manually searching the time for positioning the correct fault position; correcting the telemetering information, and judging the time of the fault type again; the probability of occurrence of each event;
9) performing quantitative modeling calculation on all sub-events in the step 7) by using an information link quantitative correction module according to results in the steps 2) to 7) and data acquired in the step 8), and correcting a calculation process;
10) performing optimized configuration on the specific distribution position of the distribution automation terminal device on the feeder line according to the results of the steps 2) to 9) by using a 'three-remote' function influence analysis module, establishing a target function by using the power failure load of each configuration condition on the basis of the given distribution terminal configuration quantity, and further obtaining a distribution planning result of the feeder line distribution terminal by using the power supply reliability condition as a constraint; and effectively guides and analyzes the influence of the three-remote function on the system power failure time, the comprehensive economic cost and the distribution terminal deployment position.
2. The power distribution terminal stationing optimization method considering the influence of errors in data transmission of the information link according to claim 1, characterized in that: in step 6), the system power failure time and the power failure load of the feeder line without the interconnection switch are quantitatively modeled and calculated according to the configuration condition of the power distribution terminal, and the system power failure time and the power failure load are divided into the following three types: a. quantitative modeling calculation of system power failure time and power failure load when all three remote power distribution terminals are configured; b. quantitative modeling calculation of system power failure time and power failure load when the 'two remote' power distribution terminal is completely configured; c. quantitative modeling calculation of system power failure time and power failure load when the three-remote power distribution terminal and the two-remote power distribution terminal are configured in a mixed mode;
a. the quantitative modeling calculation steps of the system power failure time and the power failure load when the three-remote power distribution terminal is completely configured are as follows: (1) in the fault positioning stage, the system power failure time and the power failure load are quantitatively modeled and calculated; (2) carrying out quantitative modeling calculation on system power failure time and power failure load in the manual fault isolation stage; (3) in the fault repairing stage, the system power failure time and the power failure load are quantitatively modeled and calculated; (4) in the fault processing stage, the system power failure time and the power failure load are quantitatively modeled and calculated;
(1) and (3) carrying out quantitative modeling calculation on the system power failure time and the power failure load in the fault positioning stage:
the system power failure time corresponding to the fault location stage of the ith section of regional line fault is as follows:
Figure FDA0002177264120000021
in the formula, T1iRepresenting the system power failure time t corresponding to the fault location stage of the i section area line fault1iFor fault location time of i-th zone, UiRepresenting the total number of users supplying power to the ith section; liRepresenting the equivalent line length of the ith section area; f. ofiRepresenting the failure rate of equivalent equipment in the ith section of area, and the unit is sub/km & a; m represents the number of sections of the feeder line;
system power failure time T corresponding to fault location stage1Comprises the following steps:
Figure FDA0002177264120000022
the corresponding system power failure load is as follows:
Figure FDA0002177264120000031
in the formula, E1iSystem outage load, P, corresponding to fault location phase representing i-th section area line faultiThe sum of equivalent loads of all loads for supplying power to the ith section of area is represented;
system power failure load E corresponding to fault location stage1Comprises the following steps:
Figure FDA0002177264120000032
(2) and (3) carrying out quantitative modeling calculation on system power failure time and power failure load in the manual fault isolation stage:
the system power failure time corresponding to the artificial fault isolation stage of the i section of regional line fault is as follows:
Figure FDA0002177264120000033
in the formula, T2iRepresenting the system power failure time t corresponding to the artificial fault isolation stage of the i section area line fault2iThe artificial fault isolation time of the ith section of area;
system power failure time T corresponding to manual fault isolation stage2Comprises the following steps:
Figure FDA0002177264120000034
the corresponding system power failure load is as follows:
Figure FDA0002177264120000035
in the formula, E2iRepresentsThe system power failure load corresponding to the artificial fault isolation stage of the i section of regional line fault;
system power failure load E corresponding to manual fault isolation stage2Comprises the following steps:
Figure FDA0002177264120000036
(3) and (3) quantitative modeling calculation of system power failure time and power failure load in the fault repair stage:
the system power failure time corresponding to the fault repair stage of the i section of regional line fault is as follows:
Figure FDA0002177264120000037
in the formula, T3iRepresenting the system power failure time t corresponding to the fault repair stage of the i section area line fault3iThe fault repair time of the ith section of area; z is a radical ofk0 denotes the corresponding location at which the distribution terminal is configured, zk1 represents that no power distribution terminal is arranged at the corresponding position;
system power failure time T corresponding to fault repair stage3Comprises the following steps:
Figure FDA0002177264120000041
the corresponding system power failure load is as follows:
Figure FDA0002177264120000042
in the formula, E3iRepresenting the system power failure load corresponding to the fault repair stage of the i section of regional line fault;
system power failure load E corresponding to fault repair stage3Comprises the following steps:
Figure FDA0002177264120000043
(4) and (3) carrying out quantitative modeling calculation on the system power failure time and the power failure load in the fault processing stage:
T＝T1+T2+T3(13)
in the formula, T is the system power failure time corresponding to the whole fault processing stage, and is a unit h; t is1、T2And T3Respectively corresponding to the system power failure time of the fault positioning stage, the manual fault isolation stage and the fault repairing stage, wherein the unit is h;
E＝E1+E2+E3(14)
in the formula, E is the system power failure load corresponding to the whole fault processing stage, and the unit kWh; e1、E2And E3Respectively corresponding to the system power failure loads of the fault positioning stage, the manual fault isolation stage and the fault repairing stage, wherein the unit is kWh;
b. the quantitative modeling calculation steps of the system power failure time and the power failure load when the 'two remote' power distribution terminal is completely configured are as follows: (1) in the fault positioning stage, the system power failure time and the power failure load are quantitatively modeled and calculated; (2) carrying out quantitative modeling calculation on system power failure time and power failure load in the manual fault isolation stage; (3) in the fault repairing stage, the system power failure time and the power failure load are quantitatively modeled and calculated; (4) in the fault processing stage, the system power failure time and the power failure load are quantitatively modeled and calculated;
(1) the quantitative modeling calculation formula of the system power failure time and the power failure load at the fault positioning stage is consistent with the formula (1) -4, but the artificial fault load isolation time t of each section of area2iNot 0, so the calculation result is not 0;
(2) the quantitative modeling calculation formula of the system power failure time and the power failure load at the artificial fault isolation stage is consistent with the formula (5) -8, but the artificial fault load isolation time t of each section of area2iNot 0, so the calculation result is not 0;
(3) the quantitative modeling calculation formula of the system power failure time and the power failure load in the fault repair stage is consistent with the formula (9) -12;
(4) the quantitative modeling calculation formula of the system power failure time and the power failure load in the fault processing stage is consistent with the formulas (13) and (14);
c. the quantitative modeling calculation steps of the system power failure time and the power failure load when the three-remote power distribution terminal and the two-remote power distribution terminal are configured in a mixed mode are as follows: (1) in the fault positioning stage, the system power failure time and the power failure load are quantitatively modeled and calculated; (2) carrying out quantitative modeling calculation on system power failure time and power failure load in the manual fault isolation stage; (3) in the fault repairing stage, the system power failure time and the power failure load are quantitatively modeled and calculated; (4) in the fault processing stage, the system power failure time and the power failure load are quantitatively modeled and calculated;
(1) the quantitative modeling calculation formula of the system power failure time and the power failure load at the fault positioning stage is consistent with the formula (1) -4, but the artificial fault load isolation time t of each section of area2iNot 0, so the calculation result is not 0;
(2) and (3) carrying out quantitative modeling calculation on system power failure time and power failure load in the manual fault isolation stage:
firstly, assuming that the number of line section switches configured with the three-remote power distribution terminal is M-1, the number of the three-remote areas obtained by dividing all the line section switches of the three-remote power distribution terminal is M; for analyzing the system power failure time and power failure load in the manual fault isolation stage, omega is usedi’Represents the set of loads in the ith 'triple-remote' distribution terminal area, | Ωi’L is the total number of users in the area; event set W ═ W1,w2,…,w2i’-1,w2i’,…,w2M-1,w2M) The configuration conditions of the region determined by the "three-remote" distribution terminal at the fault position and the "two-remote" distribution terminal device in the region collectively include 2M events, which are specifically expressed as:
w2i’-1: the fault occurs in an area determined by the ith 'three remote' power distribution terminal, and a 'two remote' power distribution terminal is configured in the area;
w2i’: the fault occurs in the area determined by the ith 'three remote' power distribution terminal, but the 'two remote' power distribution terminal is not configured in the area;
the system power failure time corresponding to the artificial fault isolation stage of the i-th section of regional line fault is as follows:
Figure FDA0002177264120000051
Figure FDA0002177264120000052
the corresponding system power failure load is as follows:
Figure FDA0002177264120000061
Figure FDA0002177264120000062
(3) the quantitative modeling calculation formula of the system power failure time and the power failure load in the fault repair stage is consistent with the formula (9) -12;
(4) the quantitative modeling calculation formula of the system power failure time and the power failure load in the fault processing stage is consistent with the formulas (13) and (14);
the modeling calculation of the system power failure time and the power failure load of the feeder line with the interconnection switch is divided into the following three types according to the configuration condition of the power distribution terminal: a. quantitative modeling calculation of system power failure time and power failure load when all three remote power distribution terminals are configured; b. quantitative modeling calculation of system power failure time and power failure load when the 'two remote' power distribution terminal is completely configured; c. quantitative modeling calculation of system power failure time and power failure load when the three-remote power distribution terminal and the two-remote power distribution terminal are configured in a mixed mode;
a. the quantitative modeling calculation steps of the system power failure time and the power failure load when the three-remote power distribution terminal is completely configured are as follows: (1) in the fault positioning stage, the system power failure time and the power failure load are quantitatively modeled and calculated; (2) carrying out quantitative modeling calculation on system power failure time and power failure load in the manual fault isolation stage; (3) in the fault repairing stage, the system power failure time and the power failure load are quantitatively modeled and calculated; (4) in the fault processing stage, the system power failure time and the power failure load are quantitatively modeled and calculated;
(1) fault location stepThe quantitative modeling calculation formula of the section system power failure time and the power failure load is consistent with the formula (1) -4, but the artificial fault load isolation time t of each section area2i0, so the calculation result is 0;
(2) the quantitative modeling calculation formula of the system power failure time and the power failure load at the artificial fault isolation stage is consistent with the formula (5) -8, but the artificial fault load isolation time t of each section of area2i0, so the calculation result is 0;
(3) and (3) quantitative modeling calculation of system power failure time and power failure load in the fault repair stage:
the system power failure time corresponding to the fault repair stage of the i section of regional line fault is as follows:
Figure FDA0002177264120000063
in the formula, T3iRepresenting the system power failure time t corresponding to the fault repair stage of the i section area line fault3iThe fault repair time of the ith section of area;
the system power failure time calculation formula corresponding to the fault repair stage is consistent with the formula (10);
the corresponding system power failure load is as follows:
Figure FDA0002177264120000071
in the formula, E3iRepresenting the system power failure load corresponding to the fault repair stage of the i section of regional line fault;
the system power failure load calculation formula corresponding to the fault repair stage is consistent with the formula (12);
(4) the quantitative modeling calculation formula of the system power failure time and the power failure load in the fault processing stage is consistent with the formulas (13) and (14);
b. the quantitative modeling calculation steps of the system power failure time and the power failure load when the 'two remote' power distribution terminal is completely configured are as follows: (1) in the fault positioning stage, the system power failure time and the power failure load are quantitatively modeled and calculated; (2) carrying out quantitative modeling calculation on system power failure time and power failure load in the manual fault isolation stage; (3) in the fault repairing stage, the system power failure time and the power failure load are quantitatively modeled and calculated; (4) in the fault processing stage, the system power failure time and the power failure load are quantitatively modeled and calculated;
(1) the quantitative modeling calculation formula of the system power failure time and the power failure load at the fault positioning stage is consistent with the formula (1) -4, but the artificial fault load isolation time t of each section of area2iNot 0, so the calculation result is not 0;
(2) the quantitative modeling calculation formula of the system power failure time and the power failure load at the artificial fault isolation stage is consistent with the formula (5) -8, but the artificial fault load isolation time t of each section of area2iNot 0, so the calculation result is not 0;
(3) the quantitative modeling calculation formula of the system power failure time and the power failure load in the fault repair stage is consistent with the formulas (10), (12), (19) and (20);
(4) the quantitative modeling calculation formula of the system power failure time and the power failure load in the fault processing stage is consistent with the formulas (13) and (14);
c. the quantitative modeling calculation steps of the system power failure time and the power failure load when the three-remote power distribution terminal and the two-remote power distribution terminal are configured in a mixed mode are as follows: (1) in the fault positioning stage, the system power failure time and the power failure load are quantitatively modeled and calculated; (2) carrying out quantitative modeling calculation on system power failure time and power failure load in the manual fault isolation stage; (3) in the fault repairing stage, the system power failure time and the power failure load are quantitatively modeled and calculated; (4) in the fault processing stage, the system power failure time and the power failure load are quantitatively modeled and calculated;
(1) the quantitative modeling calculation formula of the system power failure time and the power failure load at the fault positioning stage is consistent with the formula (1) -4, but the artificial fault load isolation time t of each section of area2i0, so the calculation result is 0;
(2) the quantitative modeling calculation formula of the system power failure time and the power failure load at the manual fault isolation stage is consistent with the formula (15) - (18);
(3) the quantitative modeling calculation formula of the system power failure time and the power failure load in the fault repair stage is consistent with the formulas (10), (12), (19) and (20);
(4) the quantitative modeling calculation formula of the system power failure time and the power failure load in the fault processing stage is consistent with the formulas (13) and (14).
3. The power distribution terminal stationing optimization method considering the influence of errors in data transmission of the information link according to claim 2, characterized in that: in step 7), the event a includes the following three sub-events: a. event A1: the remote control information is correct, but the remote signaling information is wrong; b. event A2: the remote control information is wrong, but the remote signaling information is correct; c. event A3: remote control information is wrong, and remote signaling information is wrong;
event B includes the following three types of sub-events: a. event B1: telemetry information errors affect the determination of the location of the fault; b. event B2: determining the type of fault influenced by the telemetering information error; c. event B3: telemetry information errors affect the determination of fault location and type simultaneously;
event C includes nine sub-events determined by event A and event B: a. event C1: the remote control information is correct, but the remote signaling information is wrong, and the fault position determination is influenced by the remote sensing information error; b. event C2: the remote control information is correct, but the remote signaling information is wrong, and the information mistake influences the determination of the fault type; c. event C3: the remote control information is correct, but the remote signaling information is wrong, and the determination of the fault position and the type is influenced by the error of the remote measurement information; d. event C4: e. remote control information is wrong, but remote signaling information is correct, and the determination of the fault position is influenced by the error of the remote monitoring information; event C5: remote control information is wrong, but remote signaling information is not wrong, and the information mistake influences the determination of the fault type; f. event C6: remote control information is wrong, but remote signaling information is correct, and the determination of fault positions and types is influenced by the error of remote monitoring information; g. event C7: remote control and remote signaling information are both wrong, and the determination of the fault position is influenced by the error of the remote signaling information; h. event C8: remote control and remote signaling information are both wrong, and the determination of the fault type is influenced by the error of the remote signaling information; i. event C9: remote control and remote signaling information are both wrong, and the determination of the fault position and type is influenced by the remote signaling information error.
4. The power distribution terminal stationing optimization method considering the influence of errors in data transmission of the information link according to claim 3, characterized in that: in step 9), the specific steps of performing quantitative modeling calculation on all the sub-events in step 7) are as follows:
① the event A quantitative modification model includes three types of event quantitative modification models:
a. event A1: when the event occurs, relative to the quantitative calculation formula of the fault repairing stage in the step 6), the fault repairing time needs to be corrected as follows:
Figure FDA0002177264120000081
in the formula (I), the compound is shown in the specification,
Figure FDA0002177264120000082
time for checking the remote signaling function and correcting the information;
b. event A2: when the event occurs, with respect to the quantitative model of the artificial fault isolation stage in the step 6), the system outage load of the artificial fault isolation stage is expressed as:
Figure FDA0002177264120000091
in the formula, t ″)2i＝t2 12Time required for checking and correcting the remote control information and carrying out isolation processing on the fault again;
c. event A3: when the event occurs, compared with the quantitative calculation formula of the fault repairing stage in the step 6), the system power failure load calculation formula of the artificial fault isolation stage is consistent with the formula (22), and t in the formula is2"need to use t2 13Alternative, t2 13The time required for checking and correcting the functions and information of remote control and remote signaling and carrying out isolation processing on the fault again is represented;
② the event B quantitative modification model comprises three types of event quantitative modification models:
a. event B1: when the event occurs, relative to the quantitative calculation formula of the fault location stage in the step 6), the fault location time needs to be corrected as follows:
Figure FDA0002177264120000092
wherein, t1 21Manually searching for time for positioning a correct fault position in order to check the remote measuring function and correct the information;
b. event B2: when the event occurs, relative to the quantitative calculation formula of the fault location stage in the step 6), the fault location time needs to be corrected as follows:
Figure FDA0002177264120000093
wherein, t1 22Judging the time of the fault type again for correcting the telemetering information;
c. event B3: when the event occurs, relative to the quantitative calculation formula of the fault location stage in the step 6), the fault location time needs to be corrected as follows:
Figure FDA0002177264120000094
③ event C quantitative modification model includes the quantitative modification models of nine types of events:
since the nine types of sub-events in the event C are formed by combining the three types of sub-events in the event a and the three types of sub-events in the event B, the time quantization modification model of the nine types of events is as follows:
a. event C1, let p be the probability of occurrence31：
tC11＝t3i+t3 11(26)
tC12＝t1i+t1 21(27)
tC1＝tC11+tC12(28)
b. Event C2, let p be the probability of occurrence32：
tC21＝t3i+t3 11(29)
tC22＝t1i+t1 22(30)
tC2＝tC21+tC22(31)
c. Event C3, let p be the probability of occurrence33：
tC31＝t3i+t3 11(32)
tC32＝t1i+t1 21+t1 22(33)
tC3＝tC31+tC32(34)
d. Event C4, let p be the probability of occurrence34：
tC41＝t2i+t2 12(35)
tC42＝t1i+t1 21(36)
tC4＝tC41+tC42(37)
e. Event C5, let p be the probability of occurrence35：
tC51＝t2i+t2 12(38)
tC52＝t1i+t1 22(39)
tC5＝tC51+tC52(40)
f. Event C6, let p be the probability of occurrence36：
tC61＝t2i+t2 12(41)
tC62＝t1+t1i 21+t1 22(42)
tC6＝tC61+tC62(43)
g. Event C7, let p be the probability of occurrence37：
tC71＝t2i+t2 13(44)
tC72＝t1i+t1 21(45)
tC7＝tC71+tC72(46)
h. Event C8, let p be the probability of occurrence38：
tC81＝t2i+t2 13(47)
tC82＝t1i+t1 22(48)
tC8＝tC81+tC82(49)
i. Event C9, let p be the probability of occurrence39：
tC91＝t2i+t2 13(50)
tC92＝t1i+t1 21+t1 22(51)
tC9＝tC91+tC92(52)
Suppose the accuracy of the remote control information is pc(ii) a The accuracy of the remote signaling information is ps(ii) a Accuracy of telemetry information is pmWherein p ismAnd can be represented as:
(1-pm)＝pm1+pm2+pm3(53)
wherein p ism1Representing the probability of occurrence of an event that telemetry has a false impact on the location of the fault but does not affect the determination of the fault category; p is a radical ofm2Representing the probability of occurrence of an event in which telemetry has a false impact on the fault category but does not impact the location determination; p is a radical ofm3Representing the probability of telemetry having an event that falsely affects the fault type and location determination;
thus, the probability of each sub-event occurrence can be expressed as:
p＝1-pm·pc·ps(54)
wherein, p is the probability of data error occurrence;
p1＝(1-pc·ps)pm(55)
p2＝(1-pm)·pc·ps(56)
p3＝(1-pc·ps)·(1-pm) (57)
p11＝pc·(1-ps)·pm(58)
p12＝(1-pc)·ps·pm(59)
p13＝(1-pc)(1-ps)·pm(60)
p21＝pc·ps·pm1(61)
p22＝pc·ps·pm2(62)
p23＝pc·ps·pm3(63)
p31＝pc·(1-ps)·pm1(64)
p32＝pc·(1-ps)·pm2(65)
p33＝pc·(1-ps)·pm3(66)
p34＝(1-pc)·ps·pm1(67)
p35＝(1-pc)·ps·pm2(68)
p36＝(1-pc)·ps·pm3(69)
p37＝(1-pc)(1-ps)·pm1(70)
p38＝(1-pc)(1-ps)·pm2(71)
p39＝(1-pc)(1-ps)·pm3(72)
and correcting the time of each stage by using an expected value analysis method, wherein the corrected time is as follows under the condition that the terminal is configured with three remote terminals after correction:
① time correction of fault location phase:
Figure FDA0002177264120000121
after finishing, obtaining:
Figure FDA0002177264120000122
② time correction of manual fault isolation phase:
Figure FDA0002177264120000123
③ time correction of the failover phase:
Figure FDA0002177264120000124
substituting the corrected time into the formulae (1) to (20) in the above step 6).
5. The power distribution terminal stationing optimization method considering the influence of errors in data transmission of the information link according to claim 4, characterized in that: in step 10), the step of using the "three remote" function influence analysis module to perform optimal configuration on the specific distribution point position of the distribution automation terminal device on the feeder according to the results of the steps 2) to 9), on the basis of the given distribution terminal configuration number, establishing a target function by using the power failure load of each configuration condition, and using the power supply reliability condition as a constraint, thereby obtaining the distribution point planning result of the feeder distribution terminal, specifically includes the following steps:
a. replacing the power outage time of the corresponding stage in the step 6) according to formulas (74) to (76) obtained in the step 7), establishing an objective function according to the power outage load obtained in the step 6), solving the objective function by adopting a genetic algorithm, and performing genetic operation; the objective function is as follows:
Figure FDA0002177264120000125
in the formula, CEPower failure loss is unit electric quantity; n is a radical of2And N3Is ' two remote ' and ' threeThe configuration number of remote power distribution terminals; c2And C3The initial investment unit price of the power distribution terminal is 'two remote' and 'three remote'; i.e. i2And i3The investment conversion rate of the 'two remote' and 'three remote' power distribution terminals is reduced; a is2And a3The economic service life of the power distribution terminal is two remote and three remote;
b. judging whether an iteration termination condition is reached according to a fitness value in a genetic algorithm, wherein the method comprises the steps of constructing a fitness function, adding a reliability constraint condition to a target function shown in a formula (77) in a form of a penalty function, and using the reliability constraint condition as a fitness evaluation function of a genetic individual;
wherein the reliability constraint condition is a set power supply reliability threshold constraint condition, i.e.
β1＞βset(78)
Wherein, βsetPower supply reliability requirements for feeder lines β1The specific expression of the power supply reliability under a certain point distribution scheme of the power distribution terminal is shown as the formula (23):
Figure FDA0002177264120000131
wherein, T is calculated by formula (13) and formulas (74) to (76) in consideration of the influence of the information system;
c. when the continuous m generations do not meet the reliability constraint condition, returning to the step 1), and readjusting the number of the power distribution terminals required to be configured on the feeder line; otherwise, outputting the optimal distribution planning result of the feeder line power distribution terminal.
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