CN112183944B - Power grid extension planning adaptability analysis method considering customer appeal - Google Patents

Power grid extension planning adaptability analysis method considering customer appeal Download PDF

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CN112183944B
CN112183944B CN202010919940.6A CN202010919940A CN112183944B CN 112183944 B CN112183944 B CN 112183944B CN 202010919940 A CN202010919940 A CN 202010919940A CN 112183944 B CN112183944 B CN 112183944B
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罗涛
孙阔
闫大威
迟福建
张梁
王魁
张天宇
胡源
李桂鑫
梁海深
王庆彪
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State Grid Tianjin Electric Power Co Ltd
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Abstract

The invention relates to a power grid expansion planning adaptability analysis method considering customer requirements, which comprises the following steps: acquiring the reliability complaint times of the total annual users, the average power supply reliability, the user load grade, the average system power failure frequency, the voltage grade and the node capacity; determining influence factors of annual total user reliability complaint times on adaptability
Figure DDA0002666366390000011
Influence factor A of average power supply reliability on adaptabilityASAIInfluence factor A of user load level on adaptabilitylInfluence factor A of average system power failure frequency on adaptabilityfVoltage class influence factor on adaptability
Figure DDA0002666366390000012
Influence factor A of node capacity on adaptabilityQi(ii) a Determining a final fitness measure
Figure DDA0002666366390000013
If the A value is larger than 0, the method has stronger adaptability; if the value of A is equal to 0, the adaptability is indicated; if the value of A is less than 0, it indicates no adaptability. The method can effectively evaluate the adaptation degree of the power grid planning considering the customer appeal, and provides a basis for deciding whether to adjust the power grid planning scheme.

Description

Power grid extension planning adaptability analysis method considering customer appeal
Technical Field
The invention belongs to the technical field of power grid extension planning in a power system, and particularly relates to a power grid extension planning adaptability analysis method considering customer appeal.
Background
Distribution and transmission of electric energy in an electric power system are mainly realized by means of power grid planning, in the electric power system, the power consumption, electric power facilities, users and the like in different areas of China are greatly different, the electric power system does not have a fixed mode, a traditional power grid planning scheme can not adapt to the complex and variable characteristics in a modern market environment, and relevant indexes such as economy, adaptability, reliability and the like in a new period are not provided. Because the large environment of the power market is complex and changeable, and many uncertain factors are present, the difficulty is increased when the power grid planning scheme is evaluated, and the feasibility of the planning scheme can be improved as much as possible only by taking full consideration.
Therefore, based on the problems, the power grid extension planning adaptability analysis method which can effectively evaluate the adaptability degree of the power grid planning considering the customer appeal and provides a basis for deciding whether to adjust the power grid planning scheme and considering the customer appeal has important practical significance.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provide a power grid extension planning adaptability analysis method which can effectively evaluate the adaptability of power grid planning considering customer appeal and provides a basis for deciding whether a power grid planning scheme needs to be adjusted or not and considering the customer appeal.
The technical problem to be solved by the invention is realized by adopting the following technical scheme:
the power grid expansion planning adaptability analysis method considering the customer appeal comprises the following steps:
acquiring the reliability complaint times of the total annual users, the average power supply reliability, the user load grade, the average system power failure frequency, the voltage grade and the node capacity;
determining influence factors of annual total user reliability complaint times on adaptability
Figure BDA0002666366370000021
Influence factor A of average power supply reliability on adaptabilityASAIInfluence factor A of user load level on adaptabilitylInfluence factor A of average system power failure frequency on adaptabilityfVoltage class influence factor on adaptability
Figure BDA0002666366370000022
Factor of influence of node capacity on adaptability
Figure BDA0002666366370000023
Determining the final adaptability index A:
Figure BDA0002666366370000024
and (3) judging the power grid expansion planning adaptability: if the A value is larger than 0, the method has stronger adaptability; if the value of A is equal to 0, the adaptability is indicated; if the value of A is less than 0, it indicates no adaptability.
Further, the influence factor of the annual total user reliability complaint frequency on the adaptability
Figure BDA0002666366370000025
Comprises the following steps:
Figure BDA0002666366370000026
wherein N isuc_nThe total number of complaints of the annual users, N is a positive integer, Nuc_minFor the minimum value of the total number of reliability-related annual user complaints in the last N years of the evaluation subject, Nuc_maxIn order to evaluate the maximum value of the total number of annual user complaints related to reliability in the last n years of the subject,
Figure BDA0002666366370000027
is the sum of complaints of the past years.
Further, the influence factor A of the average power supply reliability on the adaptabilityASAIComprises the following steps:
Figure BDA0002666366370000028
wherein, tq、mqThe power failure time and the number of power failure users in the power failure of the qth time, M is the total number of users, and T is the statistical time.
Further, the influence factor A of the user load level on the adaptabilitylComprises the following steps:
Figure BDA0002666366370000031
wherein, D is the user load grade, and the user load grade is divided into a first grade, a second grade and a third grade, namely D is 1, 2 and 3; y is the number of users, YmaxThe number of users of all load grades.
Further, the influence factor A of the average power failure frequency of the system on the adaptabilityfComprises the following steps:
Af＝lg(|100SAIFI-25|*10)
SAIFI is the average number of power failures a user of the system is subjected to per unit time.
Further, the influence factor of the voltage level on the adaptability
Figure BDA0002666366370000032
Comprises the following steps:
Figure BDA0002666366370000033
wherein, UkFor the current voltage class, UiIs the node voltage.
Further, the influence factor of the node capacity on the adaptability
Figure BDA0002666366370000034
Comprises the following steps:
Figure BDA0002666366370000035
wherein i is a node at a certain position, UkFor the current voltage class, UiIs the node voltage, QiInstalled capacity, P, after planning for grid expansioniIs the rated power.
Further, the voltage level UkMay be any one of 220kV, 110kV, 35kV, 10kV, 6kV, 380V and 220V.
The invention has the advantages and positive effects that:
the method mainly collects the data related to customer complaints and power supply reliability, and comprises the following steps: the method comprises the following steps of 1, carrying out detailed adaptive index algorithm design on the data of the reliability complaints times of the total annual users, the average power supply reliability, the user load grade, the system average power failure frequency, the voltage grade and the node capacity, judging the adaptive condition after power grid planning according to the adaptive index size, and providing electric energy for the users more reasonably; based on the method provided by the invention, a power grid planner should analyze and consider the influence of the adaptability of the power grid extension planning demanded by a client, so as to decide whether to adjust the power grid planning scheme, help to adopt a proper construction and transformation scheme for the situation without adaptability, and lay a foundation for realizing economic operation.
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The technical solutions of the present invention will be described in further detail below with reference to the accompanying drawings and examples, but it should be understood that these drawings are designed for illustrative purposes only and thus do not limit the scope of the present invention. Furthermore, unless otherwise indicated, the drawings are intended to be illustrative of the structural configurations described herein and are not necessarily drawn to scale.
FIG. 1 is a flow chart of an adaptive analysis based on Monte Carlo simulation provided in an embodiment of the present invention;
FIG. 2 is a comparison of voltage stability for an adaptive analysis using two protocols as provided in an example of the present invention;
Detailed Description
First, it should be noted that the specific structures, features, advantages, etc. of the present invention will be specifically described below by way of example, but all the descriptions are for illustrative purposes only and should not be construed as limiting the present invention in any way. Furthermore, any single feature described or implicit in any embodiment or any single feature shown or implicit in any drawing may still be combined or subtracted between any of the features (or equivalents thereof) to obtain still further embodiments of the invention that may not be directly mentioned herein.
It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict.
The power grid extension planning adaptability analysis method considering the customer appeal provided by the embodiment comprises the following steps of:
acquiring the reliability complaint times of the total annual users, the average power supply reliability, the user load grade, the average system power failure frequency, the voltage grade and the node capacity;
determining influence factors of annual total user reliability complaint times on adaptability
Figure BDA0002666366370000054
Influence factor A of average power supply reliability on adaptabilityASAIInfluence factor A of user load level on adaptabilitylSystem average blackout frequency to adaptabilityInfluencing factor AfVoltage class influence factor on adaptability
Figure BDA0002666366370000053
Factor of influence of node capacity on adaptability
Figure BDA0002666366370000052
Determining the final adaptability index A:
Figure BDA0002666366370000051
and (3) judging the power grid expansion planning adaptability: if the A value is larger than 0, the method has stronger adaptability; if the value of A is equal to 0, the adaptability is indicated; if the value of A is less than 0, it indicates no adaptability.
Wherein:
the degree of matching with the power supply reliability requirement of the user needs to be considered in the adaptability influence on the power grid expansion planning, the reliability level of the power grid expansion planning is considered based on the user requirement under the current condition, whether the current reliability meets the user requirement is analyzed, and the reliability level is used as a scientific basis for implementing the power grid expansion planning. Total number of complaints N of annual usersuc_nBased on the data, a maximum value N related to the reliability complaints in N years is summarizeduc_maxAnd a minimum value Nuc_minDeviation value considering reliability complaint frequency
Figure BDA0002666366370000061
Using the arctangent relationship
Figure BDA0002666366370000062
Main influence coefficient of the complaint times on the adaptability of the power grid expansion planning is combined with the sum of the complaint times in the past year
Figure BDA0002666366370000063
Deducing the influence factor of the reliability complaint frequency of the total annual users on the adaptability
Figure BDA0002666366370000064
Figure BDA0002666366370000065
Wherein N isuc_nThe total number of complaints of the annual users, N is a positive integer, Nuc_minFor the minimum value of the total number of reliability-related annual user complaints in the last N years of the evaluation subject, Nuc_maxIn order to evaluate the maximum value of the total number of annual user complaints related to reliability in the last n years of the subject,
Figure BDA0002666366370000066
is the sum of complaints of the past years.
The power supply reliability is a main evaluation index of power supply reliability, the power supply reliability is represented by the continuous power supply service capability of a power supply enterprise to a client and the enterprise comprehensive management level, the ratio of the total hours of the effective power supply time of a user to the hours in the statistical period is an index reflecting the reliability of the power supply system to the power supply of the user, and the average power supply reliability is
Figure BDA0002666366370000067
On the basis, the sine function of average power failure users is utilized
Figure BDA0002666366370000068
Cosine function of value and average outage time
Figure BDA0002666366370000069
The value comprehensively considers the adaptive influence factors of the average power supply reliability on the power grid expansion planning:
Figure BDA0002666366370000071
wherein, tq、mqThe power failure time and the number of power failure households for the q-th power failure, M is the total number of users, TThe statistical time is obtained.
The user load grade standard is divided into a first level, a second level and a third level according to importance, wherein the first level load refers to a user who has personal casualties, major economic losses, serious disorder of public place order and major political influences caused by power supply interruption; the secondary load refers to a user with large political influence, large economic loss and disordered public place order caused by power supply interruption; the three-stage load means that the power supply is not required to be specially supplied, and the power supply is allowed to be temporarily interrupted when a power supply system fails. The loss of social benefits caused by high-level load power failure is more serious, the reliability requirement is higher, the user load grade reflects the user requirement of reliability planning through the importance degree and social value side of the user load, and the ratio of the user load grade to all load grades
Figure BDA0002666366370000072
Defining the influence coefficient of the number of load users on the adaptability through an arc tangent function and a logarithm function, and then defining the influence coefficient of the number of load users through the tangent function
Figure BDA0002666366370000073
The value of (A) comprehensively considers the user load grade as the adaptability evaluation index after the power grid expansion planning, and the influence factor A of the user load grade on the adaptability is obtained by quantizing the standardlComprises the following steps:
Figure BDA0002666366370000074
wherein, D is user load grade, and the user load grade is divided into one grade, two grades and three grades, namely D is 1, 2 and 3, Y is the number of usersmaxThe number of users of all load grades.
The average power failure frequency is a main evaluation index of power supply reliability, the power supply reliability level after power grid expansion planning can be basically reflected through the average power failure frequency, and the influence factor A of the average power failure frequency of the system on the adaptabilityfComprises the following steps:
Af＝lg(|100SAIFI-25|*10)
SAIFI is the average number of power failures a user of the system is subjected to per unit time.
Considering the adaptability evaluation of the voltage under each voltage level to the power grid expanding planning, the change of the voltage represents the increasing proportion of the voltage deviation overproof node and the change situation of the power quality when the power grid expands the planning, and the actual voltage level U is utilizedkAnd node voltage UiDeviation relationship between them
Figure BDA0002666366370000081
The main influence factor is used as the main influence factor of the power grid expansion planning adaptability, and the influence factor of the voltage grade on the power grid expansion planning adaptability is determined by multiplying a certain coefficient
Figure BDA0002666366370000082
Figure BDA0002666366370000083
Wherein, UkFor the current voltage class, UiIs the node voltage.
The difference of the transmission capacity of the lines in the power grid expansion planning is caused by the transmission capacity of the lines, and some lines can be overloaded and some lines can continue to operate normally for the same change. With actual output active power PiThe weight used as the voltage transfer coefficient can become one of the factors of the power grid expansion planning adaptability influence factor, and according to the characteristic that when the active power of a certain node i changes, the active power on a power grid branch circuit changes, under the condition of considering the voltage change, the voltage transfer coefficient is defined by using the arctangent relation of arctanx
Figure BDA0002666366370000084
Next consider the node i injected power PiAnd capacity QiThe relation between the two factors is used as another factor of the adaptability influence factor of the power grid expansion planning, and the sine relation is utilized
Figure BDA0002666366370000085
The pi value comprehensively considers the adaptive influence factor of the power grid expansion planning, and finally determines
Figure BDA0002666366370000086
Smaller values represent smaller impact on grid planning; factor of influence of the node capacity on the adaptability
Figure BDA0002666366370000087
Comprises the following steps:
Figure BDA0002666366370000091
wherein i is a node at a certain position, UkFor the current voltage class, UiIs the node voltage, QiInstalled capacity, P, after planning for grid expansioniIs the rated power.
The voltage class UkMay be any one of 220kV, 110kV, 35kV, 10kV, 6kV, 380V and 220V.
By way of example, in the present embodiment, the method of the present invention is used to analyze the power grid extension planning adaptability:
the power grid expansion plan is 10kV voltage level, the capacity is 31.5MVA, the total number of users is 2000, the number of first-level load users is 400, the average power failure frequency of the system is 0.01, the power supply reliability reaches 90%, and the reliability complaint times of the total users in the year are reduced to below 50.
(1) Influence factor of annual total user reliability complaint times on adaptability
Figure BDA0002666366370000095
And (3) calculating: n is 3, the number of reliable complaints of the user in the last three years is 10, 100 and 37 respectively, and then N is obtaineduc_n37 times, Nuc_min is 10 times, Nuc_max100 times by formula
Figure BDA0002666366370000092
To obtain
Figure BDA0002666366370000093
(2) Average power supply reliability on adaptive influence factor AASAIAnd (3) calculating: t is tq＝2h，mq100, M2000, T24 h, by formula
Figure BDA0002666366370000094
To obtain AASAI＝0.15
(3) Adaptive influence factor A of user load grade on power grid expansion planninglAnd (3) calculating: the load grade is one grade, namely D is 1, the number of users of the load is 400, the number of users of all load grades is 2000, and the formula is used for solving the problem that the load grade is one grade, namely D is 1, the number of users of the load is 400, and the number of users of all load grades is 2000
Figure BDA0002666366370000101
Obtaining: a. thel＝1.62
(4) Adaptive influence factor A of system average power failure frequency on power grid expansion planningfAnd (3) calculating: SAIFI ═ 0.01 by the formula:
Af＝lg(|100SAIFI-25|*10)
obtaining: a. thef＝2.38
(5) Voltage-to-power grid expansion planning adaptability influence factor
Figure BDA0002666366370000102
And (3) calculating: u shapek＝10kV， Ui10.5kV by formula:
Figure BDA0002666366370000103
Figure BDA0002666366370000104
(6) capacity to power grid expansion planning adaptability influence factor
Figure BDA0002666366370000105
And (3) calculating: u shapekInstalled capacity Q after power grid extension planning is 10kVi＝31.5MVA，Ui10.5kV, rated power Pi30000kW, S1 by the formula:
Figure BDA0002666366370000106
obtaining:
Figure BDA0002666366370000107
(7) will be provided with
Figure BDA0002666366370000111
AASAI＝0.15，Al＝1.62，Af＝2.38，
Figure BDA0002666366370000112
By the formula
Figure BDA0002666366370000113
The final adaptability index A is obtained to be 0.0229, and the value A is greater than 0, which represents that the adaptability is stronger.
For comparison, the adaptability analysis is performed by using a monte carlo simulation method, which requires indexes: the system comprises a power grid, a market and a unit, wherein the 3 indexes can reflect the risk degree of a power grid planning scheme under an uncertain environment to a certain extent, and the power grid is calculated and analyzed from 3 aspects: the load flow at the highest load point, the daily average utilization rate and the load flow at the lowest load point. The bearing capacity of the network is compared with the peak value to judge, and if the peak value is obviously higher than the bearing capacity of the network, the conclusion that the power grid planning scheme is not strong in adaptability can be obtained, and a power grid system can possibly face higher risks; in another case, the valley value is lower than the bearing capacity of the network, and then the conclusion that the power grid planning scheme has no obvious effect can be drawn, and in this case, resources are generally wasted.
The Monte Carlo simulation method is to simulate the functional condition and the operation rule of a real system by analyzing a randomly generated method, and summarize and analyze the operation rule of the system. At present, there are well established theories and methods to simulate the electricity market and the production of electricity systems. When the Monte Carlo simulation method is used for simulating the process of power grid evaluation, the two simulation tools also need to be combined, so that when the simulation mode is considered in research, the two simulation methods need to be combined for design. The Monte Carlo simulation method can carry out certain design and arrangement on all uncertainty factors collected by a sampling mode, so that continuous scheme parameters of several days are formed, and calculation of one-time multiple simulation can be completed, as shown in figure 1; the analysis method of the two methods is subjected to simulation comparison, as shown in fig. 2, wherein in fig. 2: the method comprises the following steps that a scheme 1 is an adaptability analysis method of Monte Carlo simulation, a scheme 2 is an adaptability analysis method of the method, and a simulation result shows that when transient voltage instability occurs, the voltage recovery speed of a node in the scheme 2 is small in reduction amplitude and can keep the transient voltage stable, and the voltage recovery speed of the node in the scheme 2 is higher than that in the scheme 1.
The present invention has been described in detail with reference to the above examples, but the description is only for the preferred examples of the present invention and should not be construed as limiting the scope of the present invention. All equivalent changes and modifications made within the scope of the present invention shall fall within the scope of the present invention.

Claims (8)

1. The power grid expansion planning adaptability analysis method considering the customer appeal is characterized by comprising the following steps of:
acquiring the reliability complaint times of the total annual users, the average power supply reliability, the user load grade, the average system power failure frequency, the voltage grade and the node capacity;
determining influence factors of annual total user reliability complaint times on adaptability
Figure FDA0002666366360000014
Influence factor A of average power supply reliability on adaptabilityASAIInfluence factor A of user load level on adaptabilitylInfluence factor A of average system power failure frequency on adaptabilityfVoltage class influence factor on adaptability
Figure FDA0002666366360000015
Influence factor A of node capacity on adaptabilityQi；
Determining the final adaptability index A:
Figure FDA0002666366360000011
and (3) judging the power grid expansion planning adaptability: if the A value is larger than 0, the method has stronger adaptability; if the value of A is equal to 0, the adaptability is indicated; if the value of A is less than 0, it indicates no adaptability.
2. The power grid extension planning adaptability analysis method considering customer appeal as claimed in claim 1, wherein: influence factor of reliability complaint frequency of total annual users on adaptability
Figure FDA0002666366360000012
Comprises the following steps:
Figure FDA0002666366360000013
wherein N isuc_nThe total number of complaints of the annual users, N is a positive integer, Nuc_minFor the minimum value of the total number of reliability-related annual user complaints in the last N years of the evaluation subject, Nuc_maxTo evaluate the objectThe maximum of the total number of user complaints per year related to reliability in the last n years,
Figure FDA0002666366360000021
is the sum of complaints of the past years.
3. The power grid extension planning adaptability analysis method considering customer appeal as claimed in claim 1, wherein: influence factor A of the average power supply reliability on adaptabilityASAIComprises the following steps:
Figure FDA0002666366360000022
wherein, tq、mqThe power failure time and the number of power failure users in the power failure of the qth time, M is the total number of users, and T is the statistical time.
4. The power grid extension planning adaptability analysis method considering customer appeal as claimed in claim 1, wherein: influence factor A of the user load level on adaptabilitylComprises the following steps:
Figure FDA0002666366360000023
wherein, D is the user load grade, and the user load grade is divided into a first grade, a second grade and a third grade, namely D is 1, 2 and 3; y is the number of users, YmaxThe number of users of all load grades.
5. The power grid extension planning adaptability analysis method considering customer appeal as claimed in claim 1, wherein: influence factor A of average power failure frequency of the system on adaptabilityfComprises the following steps:
Af＝lg(|100SAIFI-25|*10)
SAIFI is the average number of power failures a user of the system is subjected to per unit time.
6. The power grid extension planning adaptability analysis method considering customer appeal as claimed in claim 1, wherein: factor of influence of the voltage level on the adaptability
Figure FDA0002666366360000024
Comprises the following steps:
Figure FDA0002666366360000025
wherein, UkFor the current voltage class, UiIs the node voltage.
7. The power grid extension planning adaptability analysis method considering customer appeal as claimed in claim 1, wherein: factor A of influence of the node capacity on the adaptabilityQiComprises the following steps:
Figure FDA0002666366360000031
wherein i is a node at a certain position, UkFor the current voltage class, UiIs the node voltage, QiInstalled capacity, P, after planning for grid expansioniIs the rated power.
8. The power grid extension planning adaptability analysis method considering customer appeal as claimed in claim 6, wherein: the voltage class UkMay be any one of 220kV, 110kV, 35kV, 10kV, 6kV, 380V and 220V.
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