CN109412145B - Active power distribution network dynamic characteristic evaluation method based on synchronous measurement data - Google Patents

Active power distribution network dynamic characteristic evaluation method based on synchronous measurement data Download PDF

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CN109412145B
CN109412145B CN201811205387.9A CN201811205387A CN109412145B CN 109412145 B CN109412145 B CN 109412145B CN 201811205387 A CN201811205387 A CN 201811205387A CN 109412145 B CN109412145 B CN 109412145B
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value
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CN109412145A (en
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郑雪筠
谢伟
王少荣
凌平
李成靖
柳劲松
朱郁馨
方陈
周昀
李妍
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Huazhong University of Science and Technology
State Grid Shanghai Electric Power Co Ltd
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State Grid Shanghai Electric Power Co Ltd
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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
    • 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]
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E40/00—Technologies for an efficient electrical power generation, transmission or distribution
    • Y02E40/70—Smart grids as climate change mitigation technology in the energy generation sector
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E60/00—Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
    • Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
    • Y04S10/00—Systems supporting electrical power generation, transmission or distribution
    • Y04S10/22—Flexible AC transmission systems [FACTS] or power factor or reactive power compensating or correcting units

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Abstract

The invention belongs to the field of evaluation of dynamic characteristics of a power distribution network, and provides a dynamic characteristic evaluation method based on synchronous measurement data and suitable for an active power distribution network comprising a distributed power supply, an energy storage system, an electric vehicle charging facility and a flexible load.

Description

Active power distribution network dynamic characteristic evaluation method based on synchronous measurement data
Technical Field
The invention belongs to the field of power distribution network dynamic characteristic evaluation, and particularly relates to a dynamic characteristic evaluation method based on synchronous measurement data and suitable for an active power distribution network (ADN) containing a Distributed Generation (DG), an Energy Storage System (ESS), an Electric Vehicle (EV) charging facility and a Flexible Load (FL).
Background
According to the definition of an active power distribution network operation and development report published in 2008 by international large grid Conference (CIGRE), an active power distribution network is a power distribution system which manages the power flow through a flexible network topology and actively controls and actively manages Distributed Energy Resources (DER). Where, depending on the appropriate regulatory environment and access protocol, the DER may also assume responsibility for supporting the system to some extent. From the perspective of a power supply source, the active power distribution network is different from a traditional power distribution network in that the power distribution network internally contains distributed power sources and a system with two roles of power sources and loads. For this reason, the active distribution network is also called an active distribution network. The wide access of the distributed power supply enables the power distribution network to be developed into an active power distribution network from a traditional passive power distribution network and the power flow is changed from one direction to two directions; on the other hand, the renewable energy power generation system with intermittency and randomness in the distributed power source occupies a considerable proportion, so that the power flow change situation of the power distribution network is difficult to predict. Meanwhile, along with the application and popularization of electric vehicles, electric vehicle charging facilities (including electric vehicle charging piles and charging stations) are used as a type of novel loads of the power distribution network, and power flow changes of the power distribution network are also aggravated. In fact, because the power load is changed frequently, the power flow and the bus voltage of the power distribution network are not changed all the time, and only compared with the traditional power distribution network, the power flow change and the bus voltage change of the active power distribution network are more complicated. It should be noted that not only the results of the active distribution network power flow changes and bus voltage changes are to be noted, but also the dynamic process of their changes should be highly appreciated. Because various distributed power supplies, energy storage systems and the like in the active power distribution network have feedback control systems, the dynamic characteristics and the interaction of the feedback control systems can possibly deteriorate the dynamic process of the active power distribution network, and the active power distribution network has adverse effects of continuous power oscillation, frequent bus voltage out-of-limit, repeated switching of reactive compensation equipment and the like in the dynamic process. Similarly, the charging load of many electric vehicle charging facilities may also cause undesirable dynamic processes in the active power distribution grid. For example, when a large number of electric vehicle charging piles are charged in the same area and at the same time in a constant current charging mode, the charging load can be regarded as a constant power load, and voltage instability may be caused under certain conditions.
Disclosure of Invention
The invention aims to overcome the defects of the prior art, and provides a dynamic characteristic evaluation method based on synchronous measurement data and suitable for an active power distribution network comprising a distributed power supply, an energy storage system, an electric vehicle charging facility and a flexible load.
The object of the invention is achieved by the following technical measures.
A dynamic characteristic evaluation method of an active power distribution network based on synchronous measurement data comprises the following steps:
(1) selecting specific evaluation indexes according to the requirements of application units;
(1.1) node dynamic characteristic evaluation index
(A) Maximum fluctuation amount of node voltage
The maximum fluctuation amount of the node voltage is defined as follows: the maximum node voltage fluctuation quantity is the percentage of the difference between the maximum node voltage value and the minimum node voltage value relative to the average node voltage value in an observation time window;
the node voltage maximum fluctuation amount calculation method comprises the following steps: assuming a current observation time windowThe voltage measured values of the internal node j are N in total, and the ith voltage measured value is recorded as Uj(i) Noting the first voltage measurement value as Uj(l) The average value of the N voltage measurement values is recorded as
Figure GDA0003405424950000031
Namely have
Figure GDA0003405424950000032
The maximum fluctuation amount of the voltage of the node j in the current observation time window is:
Figure GDA0003405424950000033
in the formula, i and l are numbers of voltage measurement values of the node j in the current observation time window;
(B) node voltage dispersion
Node voltage dispersion definition: the node voltage dispersion degree refers to the variance of the node voltage measured value relative to the average value percentage in an observation time window;
the method for calculating the node voltage dispersion comprises the following steps: assuming that the number of voltage measurement values of the node j in the current observation time window is N, the ith voltage measurement value is recorded as Uj(i) The average value of the N voltage measurement values is recorded as
Figure GDA0003405424950000034
Namely have
Figure GDA0003405424950000035
The dispersion of the voltage at the node j in the observation time window is:
Figure GDA0003405424950000041
in the formula, UFj(i) Is the relative error of the ith voltage measurement at node j with respect to the average voltage over the current observed time window, i.e.
Figure GDA0003405424950000042
(C) Node voltage regulation time ratio
And (3) defining the regulation time ratio of the node voltage: the node voltage regulation time ratio is the percentage of data points of which the relative error of a voltage measurement value relative to a voltage average value is more than 2% in the total data points in the current observation time window;
the node voltage regulation time ratio calculation method comprises the following steps: assuming that the number of voltage measurement values of the node j in the current observation time window is N, the ith voltage measurement value is recorded as Uj(i) The average value of the N voltage measurement values is recorded as
Figure GDA0003405424950000043
Namely have
Figure GDA0003405424950000044
Setting the voltage measured value of the node j in the current observation time window
Figure GDA0003405424950000045
The number of data points within the range is recorded as NUThe regulation time ratio of the voltage of the node j in the observation time window is
Figure GDA0003405424950000046
(D) Percent frequency of node voltage fluctuation
The node voltage fluctuation frequency percentage is defined as follows: the average value of the measured values of the node voltage in the current observation time window is recorded as
Figure GDA0003405424950000047
The node voltage fluctuation frequency percentage refers to the node voltage measured value curve relative to the node voltage measured value in the observation time window
Figure GDA0003405424950000048
The percentage of the total crossing times of the interval relative to the maximum crossing times which can be theoretically reached, namely N-1 times;
the calculation method of the node voltage fluctuation frequency percentage comprises the following steps: assuming that the number of voltage measurement values of the node j in the current observation time window is N, the ith voltage measurement value is recorded as Uj(i) The average value of the N voltage measurement values is recorded as
Figure GDA0003405424950000051
Namely have
Figure GDA0003405424950000052
To be provided with
Figure GDA0003405424950000053
For reference, the voltage measurement of node j is classified and a classification function US is definedjIs composed of
Figure GDA0003405424950000054
And recording a one-dimensional vector formed by N voltage measurement values of the node j in the current observation time window as Uj(1),Uj(2),···,Uj(N)]TTo classify the function USjActing on each voltage measured value of the node j in the current observation time window one by one according to the time sequence to obtain a corresponding one-dimensional classification vector (US)j(1),USj(2),···,USj(N)]TWherein USj(i) Only one of three values of 1, 0 and-1 can be taken; then, the voltage fluctuation frequency of the node j is recorded as mjAnd the initial value is 0, then mjIs calculated as
Figure GDA0003405424950000055
Finally, the voltage fluctuation frequency percentage of the node j in the current observation time window is obtained as
Figure GDA0003405424950000056
(1.2) Branch dynamic characteristic evaluation index
(A) Maximum fluctuation amount of branch active power
The maximum fluctuation amount of the branch active power is defined as follows: the maximum fluctuation quantity of the active power of the branch refers to the percentage of the difference between the maximum value of the active power of the branch and the minimum value of the active power of the branch relative to the average value of the active power of the branch in the current observation time window;
the method for defining and calculating the maximum fluctuation quantity of the branch active power comprises the following steps: assuming that N active power measurement values of branch k in the current observation time window exist, and recording the ith active power measurement value as Pk(i) Note the first measured value of active power as Pk(l) The average value of the N active power measurement values is recorded as
Figure GDA0003405424950000061
Namely have
Figure GDA0003405424950000062
Then the maximum fluctuation amount of the active power of branch k in the observation time window is:
Figure GDA0003405424950000063
in the formula, i and l are numbers of active power measured values of the branch k in a current observation time window;
(B) branch active power dispersion
Branch active power dispersion definition: the branch active power dispersion degree refers to the variance of the percentage of the branch active power measured value relative to the average value in the current observation time window;
the method for calculating the branch active power dispersion comprises the following steps: assuming that N active power measurement values of branch k in the current observation time window exist, and recording the ith active power measurement value as Pk(i) The average value of the N active power measurement values is recorded as
Figure GDA0003405424950000064
Namely have
Figure GDA0003405424950000065
The dispersion of the active power of the branch k in the observation time window is:
Figure GDA0003405424950000066
wherein the content of the first and second substances,
Figure GDA0003405424950000067
the measured value of the ith active power of the branch k is the relative error of the average active power in the current observation time window;
(C) branch active power regulation time ratio
The branch active power regulation time is defined by the ratio: the branch active power regulation time ratio refers to the percentage of data points, in which the relative error of a branch active power measured value relative to an active power average value is more than 2%, in a current observation time window to the total data points;
the branch active power regulation time ratio calculation method comprises the following steps: assuming that N active power measurement values of branch k in the current observation time window exist, and recording the ith active power measurement value as Pk(i) The average value of the N active power measurement values is recorded as
Figure GDA0003405424950000071
Namely have
Figure GDA0003405424950000072
Belonging the measured value of the active power of the branch k in the current observation time window to
Figure GDA0003405424950000073
The number of points in the range is recorded as NPIf the active power of the branch k is within the observation time window, the adjustment time ratio is:
Figure GDA0003405424950000074
(D) branch active power fluctuation frequency percentage
The active power fluctuation frequency percentage of the branch is defined as follows: recording the average value of the active power measured values of the branch in the current observation time window as
Figure GDA0003405424950000075
The active power fluctuation frequency percentage of the branch refers to the relation between the curve of the measured value of the active power of the branch and the curve of the measured value of the active power of the branch in the observation time window
Figure GDA0003405424950000076
The percentage of the total crossing times of the interval relative to the maximum crossing times which can be theoretically reached, namely N-1 times;
the method for calculating the active power fluctuation frequency percentage of the branch comprises the following steps: assuming that N active power measurement values of branch k in the current observation time window exist, and recording the ith active power measurement value as Pk(i) The average value of the N active power measurement values is recorded as
Figure GDA0003405424950000077
Namely have
Figure GDA0003405424950000078
To be provided with
Figure GDA0003405424950000079
For reference, the active power measurement values of the branch k are classified and a classification function PS is definedkComprises the following steps:
Figure GDA0003405424950000081
and recording a one-dimensional vector formed by N active power measurement values of the branch k in the current observation time window as Pk(1),Pk(2),···,Pk(N)]TSorting function PSkActing one by one in time sequenceObtaining corresponding one-dimensional classification vector [ PS ] by each active power measured value of branch k in current observation time windowk(1),PSk(2),···,PSk(N)]TIn which PS isk(i) Only one of three values of 1, 0 and-1 can be taken; then recording the active power fluctuation frequency of the branch k as mPkAnd the initial value is 0, then mPkIs calculated as
Figure GDA0003405424950000082
And finally obtaining the percentage of the active power fluctuation frequency of the branch k in the current observation time window as follows:
Figure GDA0003405424950000083
(E) maximum fluctuation amount of branch reactive power
The maximum fluctuation amount of branch reactive power is defined as follows: the maximum fluctuation quantity of the branch reactive power refers to the percentage of the difference value between the maximum value and the minimum value of the branch reactive power relative to the average value of the branch reactive power in the current observation time window;
the method for calculating the maximum fluctuation amount of branch reactive power comprises the following steps: assuming that the number of the reactive power measured values of the branch k in the current observation time window is N, the ith reactive power measured value is recorded as Qk(i) Noting that the first reactive power measurement value is Qk(l) The average value of the N reactive power measurement values is recorded as
Figure GDA0003405424950000084
Namely have
Figure GDA0003405424950000085
The maximum fluctuation amount of the reactive power of the branch in the observation time window is:
Figure GDA0003405424950000091
in the formula, i and l are numbers of the reactive power measured value of the branch k in the current observation time window;
(F) branch reactive power dispersion
Branch reactive power dispersion definition: the branch reactive power dispersion refers to the variance of the percentage of the branch reactive power measured value relative to the average value in an observation time window;
the method for calculating the branch reactive power dispersion comprises the following steps: assuming that the number of the reactive power measured values of the branch k in the current observation time window is N, the ith reactive power measured value is recorded as Qk(i) The average value of the N reactive power measurement values is recorded as
Figure GDA0003405424950000092
Namely have
Figure GDA0003405424950000093
The dispersion of the reactive power of branch k in the observation time window is:
Figure GDA0003405424950000094
wherein the content of the first and second substances,
Figure GDA0003405424950000095
the relative error of the ith data point of the reactive power measured value of the branch k relative to the average reactive power in the current observation time window is obtained;
(G) branch reactive power regulation time ratio
And branch reactive power regulation time ratio definition: the branch reactive power regulation time ratio refers to the percentage of data points in which the relative error of a branch reactive power measured value relative to the reactive power average value is more than 2% in the total data points in the current observation time window;
the branch reactive power regulation time ratio calculation method comprises the following steps: assuming that the number of the reactive power measured values of the branch k in the current observation time window is N, the ith reactive power measured value is recorded as Qk(i) Remember that N is noneThe average of the work power measurements is
Figure GDA0003405424950000101
Namely have
Figure GDA0003405424950000102
The measured value of the reactive power of the branch in the current observation time window belongs to
Figure GDA0003405424950000103
The number of points in the range is recorded as NQIf the ratio of the adjusting time of the reactive power of the branch k in the observation time window is:
Figure GDA0003405424950000104
(H) branch reactive power fluctuation frequency percentage
The branch reactive power fluctuation frequency percentage is defined as follows: recording the average value of the branch reactive power measurement values in the current observation time window as
Figure GDA0003405424950000105
The percentage of the frequency of the branch reactive power fluctuation refers to the relation between the curve of the reactive power measured value and the curve of the branch reactive power measured value in the observation time window
Figure GDA0003405424950000106
The percentage of the total crossing times of the interval relative to the maximum crossing times which can be theoretically reached, namely N-1 times;
the method for calculating the branch reactive power fluctuation frequency percentage comprises the following steps: assuming that the number of the reactive power measured values of the branch k in the current observation time window is N, the ith reactive power measured value is recorded as Qk(i) The average value of the N reactive power measurement values is recorded as
Figure GDA0003405424950000107
Namely have
Figure GDA0003405424950000108
To be provided with
Figure GDA0003405424950000109
On the basis, the reactive power measured values of the branch k are classified and a classification function QS is definedkComprises the following steps:
Figure GDA00034054249500001010
recording a one-dimensional vector formed by N reactive power measurement values of the branch k in the current observation time window as [ Q ]k(1),Qk(2),···,Qk(N)]TClassification function QSkActing on each reactive power measured value of the branch k in the current observation time window one by one according to the time sequence to obtain a corresponding one-dimensional classification vector (QS)k(1),QSk(2),···,QSk(N)]TWherein QS isk(i) Only one of three values of 1, 0 and-1 can be taken; then recording the reactive power fluctuation frequency of the branch k as mQkAnd the initial value is 0, then mQkIs calculated as
Figure GDA0003405424950000111
Finally, the percentage of the reactive power fluctuation frequency of the branch k in the current observation time window is obtained as follows:
Figure GDA0003405424950000112
(I) maximum fluctuation amount of branch current
The maximum fluctuation amount of the branch current is defined as follows: the maximum fluctuation quantity of the branch current is the percentage of the difference between the maximum value of the branch current and the minimum value of the branch current relative to the average value of the branch current in the current observation time window;
the method for calculating the maximum fluctuation amount of the branch current comprises the following steps: assuming that the current measurement values of the branch k in the current observation time window are N in total, the ith current measurement value is recorded as Ik(i) Noting the first current measurement as Ik(l) The average value of the N current measurement values is recorded as
Figure GDA0003405424950000113
Namely have
Figure GDA0003405424950000114
The maximum fluctuation amount of the current of branch k in the observation time window is:
Figure GDA0003405424950000115
in the formula, i and l are serial numbers of current measurement values of the branch k in the current observation time window;
(J) branch current dispersion
Branch current dispersion definition: the branch current dispersion refers to the variance of the percentage of the measured value of the branch current relative to the average value in an observation time window;
the branch current dispersion calculation method comprises the following steps: assuming that the current measurement values of the branch k in the current observation time window are N in total, the ith current measurement value is recorded as Ik(i) The average value of the N current measurement values is recorded as
Figure GDA0003405424950000121
Namely have
Figure GDA0003405424950000122
The dispersion of the current of branch k in the observation time window is:
Figure GDA0003405424950000123
wherein the content of the first and second substances,
Figure GDA0003405424950000124
the relative error of the ith data point of the current measurement value of the branch k relative to the average current in the current observation time window is obtained;
(K) branch current regulation time ratio
And branch current regulation time ratio definition: the branch current regulation time ratio is the percentage of data points in which the relative error of a branch current measurement value relative to a current average value is more than 2% in the total data points in the current observation time window;
the branch current regulation time ratio calculation method comprises the following steps: assuming that the current measurement values of the branch k in the current observation time window are N in total, the ith current measurement value is recorded as Ik(i) The average value of the N current measurement values is recorded as
Figure GDA0003405424950000125
Namely have
Figure GDA0003405424950000126
The measured value of the branch current in the current observation time window belongs to
Figure GDA0003405424950000127
The number of points in the range is recorded as NIIf the current of the branch k is within the observation time window, the adjustment time ratio is:
Figure GDA0003405424950000128
(L) percent of branch current fluctuation frequency
The branch current fluctuation frequency percentage is defined as follows: the average value of the branch current measurement values in the current observation time window is recorded as
Figure GDA0003405424950000129
The fluctuation frequency percentage of the branch current means that the branch current measured value curve is related to the branch current measured value in the observation time window
Figure GDA0003405424950000131
The percentage of the total crossing times of the interval relative to the maximum crossing times which can be theoretically reached, namely N-1 times;
calculation of branch current fluctuation frequency percentageThe method comprises the following steps: assuming that the current measurement values of the branch k in the current observation time window are N in total, the ith current measurement value is recorded as Ik(i) The average value of the N current measurement values is recorded as
Figure GDA0003405424950000132
Namely have
Figure GDA0003405424950000133
To be provided with
Figure GDA0003405424950000134
For reference, the current measured values of the branch k are classified and a classification function IS IS definedkComprises the following steps:
Figure GDA0003405424950000135
recording a one-dimensional vector formed by N current measurement values of the branch k in the current observation time window as [ Ik(1),Ik(2),···,Ik(N)]TTo classify the function ISkActing on each current measured value of the branch k in the current observation time window one by one according to the time sequence to obtain a corresponding one-dimensional classification vector [ ISk(1),ISk(2),···,ISk(N)]TWherein ISk(i) Only one of three values of 1, 0 and-1 can be taken; then, the current fluctuation frequency of the branch k is recorded as mIkAnd the initial value is 0, then mIkIs calculated by
Figure GDA0003405424950000136
And finally, the current fluctuation frequency percentage of the branch k in the current observation time window is obtained as follows:
Figure GDA0003405424950000137
maximum fluctuation amount of (M) branch power factor
The maximum fluctuation amount of the branch power factor is defined as follows: the percentage of the difference between the maximum value of the branch power factor and the minimum value of the branch power factor relative to the average value of the branch power factor in an observation time window is shown;
the method for calculating the maximum fluctuation amount of the branch power factor comprises the following steps: assuming that the number of the power factor measurement values of the branch k in the current observation time window is N, the ith power factor measurement value is recorded as Fk(i) Noting that the first power factor measurement value is Fk(l) The average value of the N power factor measurement values is recorded as
Figure GDA0003405424950000141
Namely have
Figure GDA0003405424950000142
The maximum fluctuation amount of the power factor of branch k within the observation time window is:
Figure GDA0003405424950000143
in the formula, i and l are numbers of power factor measured values of the branch k in a current observation time window;
(N) branch power factor dispersion
Branch power factor dispersion definition: the branch power factor dispersion refers to the variance of the percentage of the branch power factor measured value relative to the average value in an observation time window;
the branch power factor dispersion calculation method comprises the following steps: assuming that the number of the power factor measurement values of the branch k in the current observation time window is N, the ith power factor measurement value is recorded as Fk(i) The average value of the N power factor measurement values is recorded as
Figure GDA0003405424950000144
Namely have
Figure GDA0003405424950000145
The dispersion of the power factor of branch k within the observation time window is:
Figure GDA0003405424950000146
wherein the content of the first and second substances,
Figure GDA0003405424950000147
the relative error of the ith data point of the power factor measured value of the branch k relative to the average power factor in the current observation time window is obtained;
(O) branch power factor adjustment time ratio
The branch power factor regulation time is defined by the ratio: the branch power factor adjustment time ratio refers to the percentage of data points in which the relative error of a branch power factor measured value relative to the power factor average value is greater than 2% in the total data points in the current observation time window;
the branch power factor adjusting time ratio calculating method comprises the following steps: assuming that the number of the power factor measurement values of the branch k in the current observation time window is N, the ith power factor measurement value is recorded as Fk(i) The average value of the N power factor measurement values is recorded as
Figure GDA0003405424950000151
Namely have
Figure GDA0003405424950000152
The measured value of the branch power factor in the current observation time window belongs to
Figure GDA0003405424950000153
The number of points in the range is recorded as NFThen, the ratio of the adjustment time of the power factor of branch k in the observation time window is:
Figure GDA0003405424950000154
(P) branch power factor fluctuation frequency percentage
The branch power factor fluctuation frequency percentage is defined as follows: the current observation timeThe average value of the measured values of the power factors of the branch circuits in the window is recorded as
Figure GDA0003405424950000155
The percentage of the branch power factor fluctuation frequency refers to the power factor measurement curve relative to the observation time window
Figure GDA0003405424950000156
The percentage of the total crossing times of the interval relative to the maximum crossing times which can be theoretically reached, namely N-1 times;
the method for calculating the branch power factor fluctuation frequency percentage comprises the following steps: assuming that the number of the power factor measurement values of the branch k in the current observation time window is N, the ith power factor measurement value is recorded as Fk(i) The average value of the N power factor measurement values is recorded as
Figure GDA0003405424950000157
Namely have
Figure GDA0003405424950000158
To be provided with
Figure GDA0003405424950000159
For reference, the power factor measured values of the branch k are classified and a classification function FS is definedkComprises the following steps:
Figure GDA0003405424950000161
and recording a one-dimensional vector formed by N power factor measurement values of the branch k in the current observation time window as Fk(1),Fk(2),···,Fk(N)]TA classification function FSkActing on each power factor measured value of the branch k in the current observation time window one by one according to the time sequence to obtain a corresponding one-dimensional classification vector [ FSk(1),FSk(2),···,FSk(N)]TIn which FSk(i) Only one of three values of 1, 0 and-1 can be taken; then, the power factor fluctuation frequency of the branch k is recorded as mFkAnd the initial value is 0, then mFkIs calculated as
Figure GDA0003405424950000162
Finally, the power factor fluctuation frequency percentage of the branch k in the current observation time window is obtained as follows:
Figure GDA0003405424950000163
(1.3) comprehensive evaluation index of dynamic characteristics of whole network
(A) Evaluation index for dynamic characteristics of nodes of whole network
Assuming that the whole network has J nodes, taking each node as an element, forming a node set and marking the node set as psinodeThe evaluation index of the dynamic characteristics of the nodes in the whole network and the calculation method thereof are as follows
UMF (unified modeling framework) with maximum fluctuation quantity of node voltage of whole networkmax
Figure GDA0003405424950000164
Average maximum fluctuation amount of node voltage of whole network
Figure GDA0003405424950000165
Figure GDA0003405424950000166
Node voltage maximum dispersion UD of whole networkmax
Figure GDA0003405424950000171
Average dispersion of node voltage of whole network
Figure GDA0003405424950000172
Figure GDA0003405424950000173
UAT (Universal asynchronous receiver) based on maximum regulation time ratio of node voltage of whole networkmax
Figure GDA0003405424950000174
Average regulation time ratio of node voltage of whole network
Figure GDA0003405424950000175
Figure GDA0003405424950000176
UFF (unidirectional flux) with maximum fluctuation frequency percentage of node voltage of whole networkmax
Figure GDA0003405424950000177
Average fluctuation frequency percentage of node voltage of whole network
Figure GDA0003405424950000178
Figure GDA0003405424950000179
(B) Evaluation index of dynamic characteristics of branches of whole network
Assuming that the whole network has K branches, taking each branch as an element to form a branch set and marking the branch set as psilineThe evaluation index of the dynamic characteristics of the branches of the whole network and the calculation method thereof are as follows
Active power maximum fluctuation PMF of whole network branchmax
Figure GDA00034054249500001710
Average maximum fluctuation quantity of active power of all network branches
Figure GDA00034054249500001711
Figure GDA00034054249500001712
Full-network branch active power maximum dispersion PDmax
Figure GDA0003405424950000181
Average dispersion of active power of all network branches
Figure GDA0003405424950000182
Figure GDA0003405424950000183
PAT (active power maximum regulation time ratio) of all network branchesmax
Figure GDA0003405424950000184
Ratio of active power average regulation time of whole network branch
Figure GDA0003405424950000185
Figure GDA0003405424950000186
Percentage PFF of maximum fluctuation frequency of active power of all network branchesmax
Figure GDA0003405424950000187
Percentage of average fluctuation frequency of active power of branches of whole network
Figure GDA0003405424950000188
Figure GDA0003405424950000189
Full-network branch reactive power maximum fluctuation quantity QMFmax
Figure GDA00034054249500001810
Average maximum fluctuation amount of reactive power of all network branches
Figure GDA00034054249500001811
Figure GDA00034054249500001812
Full-network branch reactive power maximum dispersion QDmax
Figure GDA00034054249500001813
Average dispersion of reactive power of all network branches
Figure GDA00034054249500001814
Figure GDA00034054249500001815
QAT (QAT) for maximum regulation time ratio of reactive power of all network branchesmax
Figure GDA0003405424950000191
Ratio of reactive power average regulation time of whole network branch
Figure GDA0003405424950000192
Figure GDA0003405424950000193
QFF (quad flat no-lead) with maximum fluctuation frequency percentage of reactive power of all network branchesmax
Figure GDA0003405424950000194
Percentage of average fluctuation frequency of reactive power of all network branches
Figure GDA0003405424950000195
Figure GDA0003405424950000196
Full-network branch current maximum fluctuation IMFmax
Figure GDA0003405424950000197
Average maximum fluctuation amount of current of all network branches
Figure GDA0003405424950000198
Figure GDA0003405424950000199
Maximum dispersion ID of branch current of whole networkmax
Figure GDA00034054249500001910
Average dispersion of current of all-network branch
Figure GDA00034054249500001911
Figure GDA00034054249500001912
IAT (integrated circuit) for maximum regulation time ratio of current of whole network branchmax
Figure GDA00034054249500001913
Average regulation time ratio of current of whole network branch
Figure GDA00034054249500001914
Figure GDA00034054249500001915
Percentage IFF of maximum fluctuation frequency of current of whole network branchmax
Figure GDA0003405424950000201
Average fluctuation frequency percentage of current of whole network branch
Figure GDA0003405424950000202
Figure GDA0003405424950000203
Full-network power factor maximum fluctuation FMFmax
Figure GDA0003405424950000204
Average maximum fluctuation of power factor of whole network
Figure GDA0003405424950000205
Figure GDA0003405424950000206
Full-network power factor maximum dispersion FDmax
Figure GDA0003405424950000207
Average dispersion of power factor of whole network
Figure GDA0003405424950000208
Figure GDA0003405424950000209
Full-network power factor maximum regulation time ratio FATmax
Figure GDA00034054249500002010
Average regulation time ratio of power factor of whole network
Figure GDA00034054249500002011
Figure GDA00034054249500002012
FFF (percent of maximum fluctuation frequency) of full-network power factormax
Figure GDA00034054249500002013
Average fluctuation frequency percentage of power factor of whole network
Figure GDA00034054249500002014
Figure GDA00034054249500002015
(C) Comprehensive evaluation index for dynamic characteristics of whole network
The total network node dynamic characteristic evaluation indexes and the total network branch dynamic characteristic evaluation indexes are 40, and in practical application, partial indexes are selected to evaluate the dynamic characteristics of the active power distribution network according to specific requirements with emphasis; assuming that only M indexes are used in a certain actual evaluation, the comprehensive evaluation index of the dynamic characteristics of the whole network is
Figure GDA0003405424950000211
s.t.0≤wi≤1
Figure GDA0003405424950000212
In the formula, wiWeight representing the ith index, INiA value representing the ith index;
(2) setting the weight corresponding to each evaluation index;
(3) selecting the size of a current observation time window according to the actual frequency of PMU synchronous measurement data, so that not less than 10 data points are in the current observation time window;
(4) reading data points in the current observation time window, wherein the data points comprise a node voltage measured value, a branch active power measured value, a branch reactive power measured value, a branch current measured value and a branch power factor measured value;
(5) calculating the dynamic characteristic indexes of each node according to the selection result of the node dynamic characteristic evaluation indexes in the step (1);
(6) calculating the dynamic characteristic index of each branch according to the selection result of the branch dynamic characteristic evaluation index in the step (1);
(7) calculating the node dynamic characteristic evaluation index of the whole network on the basis of the node dynamic characteristic evaluation index obtained in the step (5);
(8) calculating the dynamic characteristic evaluation index of the whole network branch on the basis of the dynamic characteristic evaluation index of the branch obtained in the step (6);
(9) and solving a comprehensive evaluation index CI of the dynamic characteristics of the whole network.
The active power distribution network dynamic characteristic evaluation method based on the synchronous measurement data has the advantages that:
1. the evaluation method provided by the invention does not need to know the topological structure and specific parameters of the corresponding active power distribution network, only evaluates based on synchronous data acquired by PMU, can evaluate power distribution networks with different voltage levels or multiple voltage levels and power distribution networks with any structures, and has strong universality and practicability;
2. the evaluation method provided by the invention designs evaluation indexes of five state quantities, namely node voltage, branch active power, branch reactive power, branch current and power factor in the dynamic process of the active power distribution network, comprehensively covers all aspects of the dynamic process of the active power distribution network, and has scientific evaluation result;
3. the evaluation method provided by the invention not only reflects the dynamic characteristic index of the whole network, but also reflects the corresponding nodes and branches in the bad dynamic process of the active power distribution network, and has good application value.
Detailed Description
The present invention will be further described below in order to make the technical means, the creation features and the objects of the present invention easy to understand.
The embodiment of the invention provides an active power distribution network dynamic characteristic evaluation method based on synchronous measurement data, which comprises the following steps:
(1) and selecting specific evaluation indexes according to the requirements of application units.
(1.1) node dynamic characteristic evaluation index
(A) Maximum fluctuation amount of node voltage
The maximum fluctuation amount of the node voltage is defined as follows: the maximum fluctuation amount of the node voltage refers to the percentage of the difference between the maximum value of the node voltage and the minimum value of the node voltage relative to the average value of the node voltage in an observation time window.
The node voltage maximum fluctuation amount calculation method comprises the following steps: assuming that the number of voltage measurement values of the node j in the current observation time window is N, the ith voltage measurement value is recorded as Uj(i) Noting the first voltage measurement value as Uj(l) The average value of the N voltage measurement values is recorded as
Figure GDA0003405424950000231
Namely have
Figure GDA0003405424950000232
The maximum fluctuation amount of the voltage of the node j in the current observation time window is:
Figure GDA0003405424950000233
in the formula, i and l are numbers of voltage measured values of the node j in the current observation time window.
(B) Node voltage dispersion
Node voltage dispersion definition: node voltage dispersion refers to the variance of the node voltage measurements in percent of the mean over an observation time window.
The method for calculating the node voltage dispersion comprises the following steps: assuming that the number of voltage measurement values of the node j in the current observation time window is N, the ith voltage measurement value is recorded as Uj(i) The average value of the N voltage measurement values is recorded as
Figure GDA0003405424950000234
Namely have
Figure GDA0003405424950000235
The dispersion of the voltage at the node j in the observation time window is:
Figure GDA0003405424950000236
in the formula, UFj(i) Is the relative error of the ith voltage measurement at node j with respect to the average voltage over the current observed time window, i.e.
Figure GDA0003405424950000241
(C) Node voltage regulation time ratio
And (3) defining the regulation time ratio of the node voltage: the node voltage regulation time ratio is the percentage of data points in which the relative error of a voltage measurement value relative to a voltage average value is greater than 2% in a current observation time window to the total data points.
The node voltage regulation time ratio calculation method comprises the following steps: assuming that the number of voltage measurement values of the node j in the current observation time window is N, the ith voltage measurement value is recorded as Uj(i) The average value of the N voltage measurement values is recorded as
Figure GDA0003405424950000242
Namely have
Figure GDA0003405424950000243
Setting the voltage measured value of the node j in the current observation time window
Figure GDA0003405424950000244
The number of data points within the range is recorded as NUThe regulation time ratio of the voltage of the node j in the observation time window is
Figure GDA0003405424950000245
(D) Percent frequency of node voltage fluctuation
The node voltage fluctuation frequency percentage is defined as follows: the average value of the measured values of the node voltage in the current observation time window is recorded as
Figure GDA0003405424950000246
The node voltage fluctuation frequency percentage refers to the node voltage measured value curve relative to the node voltage measured value in the observation time window
Figure GDA0003405424950000247
The percentage of total number of crossings in the interval relative to the maximum number of crossings that can theoretically be reached (i.e.N-1).
The calculation method of the node voltage fluctuation frequency percentage comprises the following steps: assuming that the number of voltage measurement values of the node j in the current observation time window is N, the ith voltage measurement value is recorded as Uj(i) The average value of the N voltage measurement values is recorded as
Figure GDA0003405424950000248
Namely have
Figure GDA0003405424950000249
To be provided with
Figure GDA00034054249500002410
For reference, the voltage measurement of node j is classified and a classification function US is definedjIs composed of
Figure GDA0003405424950000251
And recording a one-dimensional vector formed by N voltage measurement values of the node j in the current observation time window as Uj(1),Uj(2),···,Uj(N)]TTo classify the function USjActing on each voltage measured value of the node j in the current observation time window one by one according to the time sequence to obtain a corresponding one-dimensional classification vector (US)j(1),USj(2),···,USj(N)]TWherein USj(i) It is only possible to take one of the three values 1, 0, -1. Then, the voltage fluctuation frequency of the node j is recorded as mjAnd the initial value is 0, then mjIs calculated as
Figure GDA0003405424950000252
Finally, the voltage fluctuation frequency percentage of the node j in the current observation time window is obtained as
Figure GDA0003405424950000253
(1.2) Branch dynamic characteristic evaluation index
(A) Maximum fluctuation amount of branch active power
The maximum fluctuation amount of the branch active power is defined as follows: the maximum fluctuation quantity of the active power of the branch refers to the percentage of the difference between the maximum value of the active power of the branch and the minimum value of the active power of the branch relative to the average value of the active power of the branch in the current observation time window.
The method for defining and calculating the maximum fluctuation quantity of the branch active power comprises the following steps: assuming that N active power measurement values of branch k in the current observation time window exist, and recording the ith active power measurement value as Pk(i) Note the first measured value of active power as Pk(l) The average value of the N active power measurement values is recorded as
Figure GDA0003405424950000254
Namely have
Figure GDA0003405424950000255
Then the maximum fluctuation amount of the active power of branch k in the observation time window is:
Figure GDA0003405424950000261
in the formula, i and l are numbers of active power measured values of the branch k in the current observation time window.
(B) Branch active power dispersion
Branch active power dispersion definition: the branch active power dispersion refers to the variance of the percentage of the branch active power measured value relative to the average value in the current observation time window.
The method for calculating the branch active power dispersion comprises the following steps: assuming that N active power measurement values of branch k in the current observation time window exist, and recording the ith active power measurement value as Pk(i) The average value of the N active power measurement values is recorded as
Figure GDA0003405424950000262
Namely have
Figure GDA0003405424950000263
The dispersion of the active power of the branch k in the observation time window is:
Figure GDA0003405424950000264
wherein the content of the first and second substances,
Figure GDA0003405424950000265
is the relative error of the ith active power measurement value of branch k with respect to the average active power within the current observation time window.
(C) Branch active power regulation time ratio
The branch active power regulation time is defined by the ratio: the branch active power regulation time ratio refers to the percentage of data points in which the relative error of a branch active power measured value relative to an active power average value is greater than 2% in the total data points in the current observation time window.
The branch active power regulation time ratio calculation method comprises the following steps: assuming that N active power measurement values of branch k in the current observation time window exist, and recording the ith active power measurement value as Pk(i) The average value of the N active power measurement values is recorded as
Figure GDA0003405424950000271
Namely have
Figure GDA0003405424950000272
Belonging the measured value of the active power of the branch k in the current observation time window to
Figure GDA0003405424950000273
The number of points in the range is recorded as NPIf the active power of the branch k is within the observation time window, the adjustment time ratio is:
Figure GDA0003405424950000274
(D) branch active power fluctuation frequency percentage
The active power fluctuation frequency percentage of the branch is defined as follows: recording the average value of the active power measured values of the branch in the current observation time window as
Figure GDA0003405424950000275
The active power fluctuation frequency percentage of the branch refers to the relation between the curve of the measured value of the active power of the branch and the curve of the measured value of the active power of the branch in the observation time window
Figure GDA0003405424950000276
The percentage of total number of crossings in the interval relative to the maximum number of crossings that can theoretically be reached (i.e.N-1).
The method for calculating the active power fluctuation frequency percentage of the branch comprises the following steps: assuming that N active power measurement values of branch k in the current observation time window exist, and recording the ith active power measurement value as Pk(i) The average value of the N active power measurement values is recorded as
Figure GDA0003405424950000277
Namely have
Figure GDA0003405424950000278
To be provided with
Figure GDA0003405424950000279
For reference, the active power measurement values of the branch k are classified and a classification function PS is definedkComprises the following steps:
Figure GDA00034054249500002710
and recording a one-dimensional vector formed by N active power measurement values of the branch k in the current observation time window as Pk(1),Pk(2),···,Pk(N)]TSorting function PSkActing on each active power measured value of the branch k in the current observation time window one by one according to the time sequence to obtain a corresponding one-dimensional classification vector [ PSk(1),PSk(2),···,PSk(N)]TIn which PS isk(i) It is only possible to take one of the three values 1, 0, -1. Then recording the active power fluctuation frequency of the branch k as mPkAnd the initial value is 0, then mPkIs calculated as
Figure GDA0003405424950000281
And finally obtaining the percentage of the active power fluctuation frequency of the branch k in the current observation time window as follows:
Figure GDA0003405424950000282
(E) maximum fluctuation amount of branch reactive power
The maximum fluctuation amount of branch reactive power is defined as follows: the maximum fluctuation amount of the branch reactive power refers to the percentage of the difference value between the maximum value and the minimum value of the branch reactive power relative to the average value of the branch reactive power in the current observation time window.
The method for calculating the maximum fluctuation amount of branch reactive power comprises the following steps: assuming that the number of the reactive power measured values of the branch k in the current observation time window is N, the ith reactive power measured value is recorded as Qk(i) Noting that the first reactive power measurement value is Qk(l) Remember the N idle workThe average of the rate measurements is
Figure GDA0003405424950000283
Namely have
Figure GDA0003405424950000284
The maximum fluctuation amount of the reactive power of the branch in the observation time window is:
Figure GDA0003405424950000285
in the formula, i and l are numbers of the reactive power measured value of the branch k in the current observation time window.
(F) Branch reactive power dispersion
Branch reactive power dispersion definition: the branch reactive power dispersion degree refers to the variance of the percentage of the branch reactive power measured value relative to the average value in the observation time window.
The method for calculating the branch reactive power dispersion comprises the following steps: assuming that the number of the reactive power measured values of the branch k in the current observation time window is N, the ith reactive power measured value is recorded as Qk(i) The average value of the N reactive power measurement values is recorded as
Figure GDA0003405424950000291
Namely have
Figure GDA0003405424950000292
The dispersion of the reactive power of branch k in the observation time window is:
Figure GDA0003405424950000293
wherein the content of the first and second substances,
Figure GDA0003405424950000294
the relative error of the ith data point of the reactive power measured value of the branch k relative to the average reactive power in the current observation time window.
(G) Branch reactive power regulation time ratio
And branch reactive power regulation time ratio definition: the branch reactive power regulation time ratio refers to the percentage of data points in which the relative error of a branch reactive power measured value relative to the reactive power average value is greater than 2% in the total data points in the current observation time window.
The branch reactive power regulation time ratio calculation method comprises the following steps: assuming that the number of the reactive power measured values of the branch k in the current observation time window is N, the ith reactive power measured value is recorded as Qk(i) The average value of the N reactive power measurement values is recorded as
Figure GDA0003405424950000295
Namely have
Figure GDA0003405424950000296
The measured value of the reactive power of the branch in the current observation time window belongs to
Figure GDA0003405424950000297
The number of points in the range is recorded as NQIf the ratio of the adjusting time of the reactive power of the branch k in the observation time window is:
Figure GDA0003405424950000301
(H) branch reactive power fluctuation frequency percentage
The branch reactive power fluctuation frequency percentage is defined as follows: recording the average value of the branch reactive power measurement values in the current observation time window as
Figure GDA0003405424950000302
The percentage of the frequency of the branch reactive power fluctuation refers to the relation between the curve of the reactive power measured value and the curve of the branch reactive power measured value in the observation time window
Figure GDA0003405424950000303
The total crossing number of the interval is relative to the maximum crossing number (N-1 time).
The method for calculating the branch reactive power fluctuation frequency percentage comprises the following steps: assuming that the number of the reactive power measured values of the branch k in the current observation time window is N, the ith reactive power measured value is recorded as Qk(i) The average value of the N reactive power measurement values is recorded as
Figure GDA0003405424950000304
Namely have
Figure GDA0003405424950000305
To be provided with
Figure GDA0003405424950000306
On the basis, the reactive power measured values of the branch k are classified and a classification function QS is definedkComprises the following steps:
Figure GDA0003405424950000307
recording a one-dimensional vector formed by N reactive power measurement values of the branch k in the current observation time window as [ Q ]k(1),Qk(2),···,Qk(N)]TClassification function QSkActing on each reactive power measured value of the branch k in the current observation time window one by one according to the time sequence to obtain a corresponding one-dimensional classification vector (QS)k(1),QSk(2),···,QSk(N)]TWherein QS isk(i) It is only possible to take one of the three values 1, 0, -1. Then recording the reactive power fluctuation frequency of the branch k as mQkAnd the initial value is 0, then mQkIs calculated as
Figure GDA0003405424950000308
Finally, the percentage of the reactive power fluctuation frequency of the branch k in the current observation time window is obtained as follows:
Figure GDA0003405424950000311
(I) maximum fluctuation amount of branch current
The maximum fluctuation amount of the branch current is defined as follows: the maximum fluctuation amount of the branch current refers to the percentage of the difference between the maximum value of the branch current and the minimum value of the branch current relative to the average value of the branch current in the current observation time window.
The method for calculating the maximum fluctuation amount of the branch current comprises the following steps: assuming that the current measurement values of the branch k in the current observation time window are N in total, the ith current measurement value is recorded as Ik(i) Noting the first current measurement as Ik(l) The average value of the N current measurement values is recorded as
Figure GDA0003405424950000312
Namely have
Figure GDA0003405424950000313
The maximum fluctuation amount of the current of branch k in the observation time window is:
Figure GDA0003405424950000314
in the formula, i and l are numbers of current measured values of the branch k in the current observation time window.
(J) Branch current dispersion
Branch current dispersion definition: the branch current dispersion refers to the variance of the branch current measurement value in percentage relative to the average value within the observation time window.
The branch current dispersion calculation method comprises the following steps: assuming that the current measurement values of the branch k in the current observation time window are N in total, the ith current measurement value is recorded as Ik(i) The average value of the N current measurement values is recorded as
Figure GDA0003405424950000315
Namely have
Figure GDA0003405424950000316
The dispersion of the current of branch k in the observation time window is:
Figure GDA0003405424950000321
wherein the content of the first and second substances,
Figure GDA0003405424950000322
is the relative error of the ith data point of the current measurement value of branch k relative to the average current in the current observation time window.
(K) Branch current regulation time ratio
And branch current regulation time ratio definition: the branch current regulation time ratio is the percentage of data points in which the relative error of a branch current measurement value relative to a current average value is greater than 2% in the total data points in the current observation time window.
The branch current regulation time ratio calculation method comprises the following steps: assuming that the current measurement values of the branch k in the current observation time window are N in total, the ith current measurement value is recorded as Ik(i) The average value of the N current measurement values is recorded as
Figure GDA0003405424950000323
Namely have
Figure GDA0003405424950000324
The measured value of the branch current in the current observation time window belongs to
Figure GDA0003405424950000325
The number of points in the range is recorded as NIIf the current of the branch k is within the observation time window, the adjustment time ratio is:
Figure GDA0003405424950000326
(L) percent of branch current fluctuation frequency
The branch current fluctuation frequency percentage is defined as follows: measuring the branch current in the current observation time windowThe average of the values is recorded as
Figure GDA0003405424950000327
The fluctuation frequency percentage of the branch current means that the branch current measured value curve is related to the branch current measured value in the observation time window
Figure GDA0003405424950000328
The percentage of total number of crossings in the interval relative to the maximum number of crossings that can theoretically be reached (i.e.N-1).
The method for calculating the fluctuation frequency percentage of the branch current comprises the following steps: assuming that the current measurement values of the branch k in the current observation time window are N in total, the ith current measurement value is recorded as Ik(i) The average value of the N current measurement values is recorded as
Figure GDA0003405424950000331
Namely have
Figure GDA0003405424950000332
To be provided with
Figure GDA0003405424950000333
For reference, the current measured values of the branch k are classified and a classification function IS IS definedkComprises the following steps:
Figure GDA0003405424950000334
recording a one-dimensional vector formed by N current measurement values of the branch k in the current observation time window as [ Ik(1),Ik(2),···,Ik(N)]TTo classify the function ISkActing on each current measured value of the branch k in the current observation time window one by one according to the time sequence to obtain a corresponding one-dimensional classification vector [ ISk(1),ISk(2),···,ISk(N)]TWherein ISk(i) It is only possible to take one of the three values 1, 0, -1. Then, the current fluctuation frequency of the branch k is recorded as mIkAnd the initial value is 0, then mIkIs calculated by
Figure GDA0003405424950000335
And finally, the current fluctuation frequency percentage of the branch k in the current observation time window is obtained as follows:
Figure GDA0003405424950000336
maximum fluctuation amount of (M) branch power factor
The maximum fluctuation amount of the branch power factor is defined as follows: the percentage of the difference between the maximum branch power factor and the minimum branch power factor relative to the average branch power factor in the observation time window is referred to.
The method for calculating the maximum fluctuation amount of the branch power factor comprises the following steps: assuming that the number of the power factor measurement values of the branch k in the current observation time window is N, the ith power factor measurement value is recorded as Fk(i) Noting that the first power factor measurement value is Fk(l) The average value of the N power factor measurement values is recorded as FkThat is to say have
Figure GDA0003405424950000341
The maximum fluctuation amount of the power factor of branch k within the observation time window is:
Figure GDA0003405424950000342
in the formula, i and l are numbers of the power factor measured value of the branch k in the current observation time window.
(N) branch power factor dispersion
Branch power factor dispersion definition: the branch power factor dispersion refers to the variance of the branch power factor measurement value relative to the average percentage in the observation time window.
The branch power factor dispersion calculation method comprises the following steps: assuming that the total number of the power factor measured values of the branch k in the current observation time window is N, recording the power factor measured valuesThe ith power factor measurement value in (1) is Fk(i) The average value of the N power factor measurement values is recorded as
Figure GDA0003405424950000343
Namely have
Figure GDA0003405424950000344
The dispersion of the power factor of branch k within the observation time window is:
Figure GDA0003405424950000345
wherein the content of the first and second substances,
Figure GDA0003405424950000346
is the relative error of the ith data point of the power factor measurement for branch k with respect to the average power factor over the current observed time window.
(O) branch power factor adjustment time ratio
The branch power factor regulation time is defined by the ratio: the branch power factor adjustment time ratio refers to the percentage of data points in which the relative error of a branch power factor measured value relative to the power factor average value is greater than 2% in the total data points in the current observation time window.
The branch power factor adjusting time ratio calculating method comprises the following steps: assuming that the number of the power factor measurement values of the branch k in the current observation time window is N, the ith power factor measurement value is recorded as Fk(i) The average value of the N power factor measurement values is recorded as
Figure GDA0003405424950000351
Namely have
Figure GDA0003405424950000352
The measured value of the branch power factor in the current observation time window belongs to
Figure GDA0003405424950000353
The number of points in the range is recorded as NFThen, the ratio of the adjustment time of the power factor of branch k in the observation time window is:
Figure GDA0003405424950000354
(P) branch power factor fluctuation frequency percentage
The branch power factor fluctuation frequency percentage is defined as follows: the average value of the branch power factor measured values in the current observation time window is recorded as
Figure GDA0003405424950000355
The percentage of the branch power factor fluctuation frequency refers to the power factor measurement curve relative to the observation time window
Figure GDA0003405424950000356
The percentage of total number of crossings in the interval relative to the maximum number of crossings that can theoretically be reached (i.e.N-1).
The method for calculating the branch power factor fluctuation frequency percentage comprises the following steps: assuming that the number of the power factor measurement values of the branch k in the current observation time window is N, the ith power factor measurement value is recorded as Fk(i) The average value of the N power factor measurement values is recorded as
Figure GDA0003405424950000357
Namely have
Figure GDA0003405424950000358
To be provided with
Figure GDA0003405424950000359
For reference, the power factor measured values of the branch k are classified and a classification function FS is definedkComprises the following steps:
Figure GDA00034054249500003510
and recording N power factor measured values of branch k in current observation time windowOne-dimensional vector is [ F ]k(1),Fk(2),···,Fk(N)]TA classification function FSkActing on each power factor measured value of the branch k in the current observation time window one by one according to the time sequence to obtain a corresponding one-dimensional classification vector [ FSk(1),FSk(2),···,FSk(N)]TIn which FSk(i) It is only possible to take one of the three values 1, 0, -1. Then, the power factor fluctuation frequency of the branch k is recorded as mFkAnd the initial value is 0, then mFkIs calculated as
Figure GDA0003405424950000361
Finally, the power factor fluctuation frequency percentage of the branch k in the current observation time window is obtained as follows:
Figure GDA0003405424950000362
(1.3) comprehensive evaluation index of dynamic characteristics of whole network
(A) Evaluation index for dynamic characteristics of nodes of whole network
Assuming that the whole network has J nodes, taking each node as an element, forming a node set and marking the node set as psinodeThe evaluation index of the dynamic characteristics of the nodes of the whole network defined by the present invention and the calculation method thereof are shown in table 1 below.
TABLE 1 evaluation index of node dynamic characteristics of the whole network
Figure GDA0003405424950000363
Figure GDA0003405424950000371
(B) Evaluation index of dynamic characteristics of branches of whole network
The method for defining and calculating the dynamic characteristic evaluation indexes of the whole network branches is completely similar to the method for defining and calculating the dynamic characteristic evaluation indexes of the whole network nodes, and the dynamic characteristic evaluation indexes of the whole network branches are listed in table 2 in consideration of the fact that the specific method is clearly described in the step (A) of evaluating the dynamic characteristic indexes of the whole network nodes and the fact that the number of the dynamic characteristic evaluation indexes of the whole network branches is large.
TABLE 2 evaluation index of dynamic characteristics of branches of the whole network
Figure GDA0003405424950000372
(C) Comprehensive evaluation index for dynamic characteristics of whole network
In the embodiment, the total network node dynamic characteristic evaluation indexes and the total network branch dynamic characteristic evaluation indexes are 40, and in practical application, partial indexes can be selected to evaluate the dynamic characteristics of the active power distribution network with a certain emphasis according to specific requirements. Assuming that only M indexes are used in a certain actual evaluation, the comprehensive evaluation index of the dynamic characteristics of the whole network is
Figure GDA0003405424950000381
s.t.0≤wi≤1
Figure GDA0003405424950000382
In the formula, wiWeight representing the ith index, INiIndicating the value of the ith index.
(2) The weight corresponding to each evaluation index is set by a method (such as an expert scoring method) well known to those skilled in the art.
(3) And selecting the size of the current observation time window according to the actual frequency of PMU synchronous measurement data, so that not less than 10 data points are obtained in the current observation time window.
(4) And reading data points in the current observation time window, wherein the data points comprise a node voltage measured value, a branch active power measured value, a branch reactive power measured value, a branch current measured value and a branch power factor measured value.
(5) And (4) selecting a corresponding formula to calculate the dynamic characteristic index of each node according to the selection result of the node dynamic characteristic evaluation index in the step (1).
(6) And (4) selecting a corresponding formula to calculate the dynamic characteristic index of each branch according to the selection result of the branch dynamic characteristic evaluation index in the step (1).
(7) According to table 1, the evaluation index of the dynamic characteristics of the nodes in the whole network is calculated on the basis of the evaluation index of the dynamic characteristics of the nodes obtained in the step (5).
(8) And (4) according to the table 2, calculating the dynamic characteristic evaluation index of the whole network branch on the basis of the branch dynamic characteristic evaluation index obtained in the step (6).
(9) And (5) on the basis of the step (7) and the step (8), obtaining a comprehensive evaluation index CI of the dynamic characteristics of the whole network.
Practice proves that the important beneficial effects of the embodiment are embodied in two aspects:
firstly, the provided technical method is scientific. Specifically, the evaluation indexes of the provided technical method fully consider the causes of the bad dynamic process of the active power distribution network comprising the distributed power supply, the energy storage system, the electric automobile charging facility and the flexible load: the method comprises the following inducements of distributed power supply output change, energy storage system charge and discharge, large-scale electric vehicle charge, load change, control system coupling effect, forced oscillation, series resonance and the like. Obviously, when the power distribution network is disturbed, the larger the fluctuation amplitude, the longer the fluctuation time and the higher the fluctuation frequency of the state quantity of the power distribution network, the worse the dynamic performance of the power distribution network. The evaluation indexes in the embodiment include evaluation indexes for evaluating fluctuation conditions of local state quantities in the dynamic process of the active power distribution network and evaluation indexes for evaluating dynamic characteristics of the whole network.
Secondly, the dynamic characteristics of the corresponding active power distribution network can be evaluated only based on the synchronous data of the nodes and the branches collected by the PMU, the network structure and specific parameters of the corresponding active power distribution network do not need to be known, and evaluation results of different active power distribution networks are comparable. This makes the technical solution provided very practical.
Details not described in the present specification belong to the prior art known to those skilled in the art.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.

Claims (2)

1. A dynamic characteristic evaluation method of an active power distribution network based on synchronous measurement data is characterized by comprising the following steps:
(1) selecting specific evaluation indexes according to the requirements of application units;
(1.1) node dynamic characteristic evaluation index
(A) Maximum fluctuation amount of node voltage
The maximum fluctuation amount of the node voltage is defined as follows: the maximum node voltage fluctuation quantity is the percentage of the difference between the maximum node voltage value and the minimum node voltage value relative to the average node voltage value in an observation time window;
the node voltage maximum fluctuation amount calculation method comprises the following steps: assuming that the number of voltage measurement values of the node j in the current observation time window is N, the ith voltage measurement value is recorded as Uj(i) Noting the first voltage measurement value as Uj(l) The average value of the N voltage measurement values is recorded as
Figure FDA0003405424940000011
Namely have
Figure FDA0003405424940000012
The maximum fluctuation amount of the voltage of the node j in the current observation time window is:
Figure FDA0003405424940000013
in the formula, i and l are numbers of voltage measurement values of the node j in the current observation time window;
(B) node voltage dispersion
Node voltage dispersion definition: the node voltage dispersion degree refers to the variance of the node voltage measured value relative to the average value percentage in an observation time window;
the method for calculating the node voltage dispersion comprises the following steps: assuming that the number of voltage measurement values of the node j in the current observation time window is N, the ith voltage measurement value is recorded as Uj(i) The average value of the N voltage measurement values is recorded as
Figure FDA0003405424940000014
Namely have
Figure FDA0003405424940000015
The dispersion of the voltage at the node j in the observation time window is:
Figure FDA0003405424940000021
in the formula, UFj(i) Is the relative error of the ith voltage measurement at node j with respect to the average voltage over the current observed time window, i.e.
Figure FDA0003405424940000022
(C) Node voltage regulation time ratio
And (3) defining the regulation time ratio of the node voltage: the node voltage regulation time ratio is the percentage of data points of which the relative error of a voltage measurement value relative to a voltage average value is more than 2% in the total data points in the current observation time window;
the node voltage regulation time ratio calculation method comprises the following steps: assuming that the number of voltage measurement values of the node j in the current observation time window is N, the ith voltage measurement value is recorded as Uj(i) The average value of the N voltage measurement values is recorded as
Figure FDA0003405424940000023
Namely have
Figure FDA0003405424940000024
Setting the voltage measured value of the node j in the current observation time window
Figure FDA0003405424940000025
The number of data points within the range is recorded as NUThe regulation time ratio of the voltage of the node j in the observation time window is
Figure FDA0003405424940000026
(D) Percent frequency of node voltage fluctuation
The node voltage fluctuation frequency percentage is defined as follows: the average value of the measured values of the node voltage in the current observation time window is recorded as
Figure FDA0003405424940000027
The node voltage fluctuation frequency percentage refers to the node voltage measured value curve relative to the node voltage measured value in the observation time window
Figure FDA0003405424940000028
The percentage of the total crossing times of the interval relative to the maximum crossing times which can be theoretically reached, namely N-1 times;
the calculation method of the node voltage fluctuation frequency percentage comprises the following steps: assuming that the number of voltage measurement values of the node j in the current observation time window is N, the ith voltage measurement value is recorded as Uj(i) The average value of the N voltage measurement values is recorded as
Figure FDA0003405424940000031
Namely have
Figure FDA0003405424940000032
To be provided with
Figure FDA0003405424940000033
For reference, the voltage measurement of node j is classified and a classification function US is definedjIs composed of
Figure FDA0003405424940000034
And recording a one-dimensional vector formed by N voltage measurement values of the node j in the current observation time window as Uj(1),Uj(2),···,Uj(N)]TTo classify the function USjActing on each voltage measured value of the node j in the current observation time window one by one according to the time sequence to obtain a corresponding one-dimensional classification vector (US)j(1),USj(2),···,USj(N)]TWherein USj(i) Only one of three values of 1, 0 and-1 can be taken; then, the voltage fluctuation frequency of the node j is recorded as mjAnd the initial value is 0, then mjIs calculated as
Figure FDA0003405424940000035
Finally, the voltage fluctuation frequency percentage of the node j in the current observation time window is obtained as
Figure FDA0003405424940000036
(1.2) Branch dynamic characteristic evaluation index
(A) Maximum fluctuation amount of branch active power
The maximum fluctuation amount of the branch active power is defined as follows: the maximum fluctuation quantity of the active power of the branch refers to the percentage of the difference between the maximum value of the active power of the branch and the minimum value of the active power of the branch relative to the average value of the active power of the branch in the current observation time window;
the method for defining and calculating the maximum fluctuation quantity of the branch active power comprises the following steps: supposing that the current observation time window is withinN active power measured values of the path k are recorded, wherein the ith active power measured value is Pk(i) Note the first measured value of active power as Pk(l) The average value of the N active power measurement values is recorded as
Figure FDA0003405424940000041
Namely have
Figure FDA0003405424940000042
Then the maximum fluctuation amount of the active power of branch k in the observation time window is:
Figure FDA0003405424940000043
in the formula, i and l are numbers of active power measured values of the branch k in a current observation time window;
(B) branch active power dispersion
Branch active power dispersion definition: the branch active power dispersion degree refers to the variance of the percentage of the branch active power measured value relative to the average value in the current observation time window;
the method for calculating the branch active power dispersion comprises the following steps: assuming that N active power measurement values of branch k in the current observation time window exist, and recording the ith active power measurement value as Pk(i) The average value of the N active power measurement values is recorded as
Figure FDA0003405424940000044
Namely have
Figure FDA0003405424940000045
The dispersion of the active power of the branch k in the observation time window is:
Figure FDA0003405424940000046
wherein the content of the first and second substances,
Figure FDA0003405424940000047
the measured value of the ith active power of the branch k is the relative error of the average active power in the current observation time window;
(C) branch active power regulation time ratio
The branch active power regulation time is defined by the ratio: the branch active power regulation time ratio refers to the percentage of data points, in which the relative error of a branch active power measured value relative to an active power average value is more than 2%, in a current observation time window to the total data points;
the branch active power regulation time ratio calculation method comprises the following steps: assuming that N active power measurement values of branch k in the current observation time window exist, and recording the ith active power measurement value as Pk(i) The average value of the N active power measurement values is recorded as
Figure FDA0003405424940000051
Namely have
Figure FDA0003405424940000052
Belonging the measured value of the active power of the branch k in the current observation time window to
Figure FDA0003405424940000053
The number of points in the range is recorded as NPIf the active power of the branch k is within the observation time window, the adjustment time ratio is:
Figure FDA0003405424940000054
(D) branch active power fluctuation frequency percentage
The active power fluctuation frequency percentage of the branch is defined as follows: recording the average value of the active power measured values of the branch in the current observation time window as
Figure FDA0003405424940000055
The active power fluctuation frequency percentage of the branch refers to the relation between the curve of the measured value of the active power of the branch and the curve of the measured value of the active power of the branch in the observation time window
Figure FDA0003405424940000056
The percentage of the total crossing times of the interval relative to the maximum crossing times which can be theoretically reached, namely N-1 times;
the method for calculating the active power fluctuation frequency percentage of the branch comprises the following steps: assuming that N active power measurement values of branch k in the current observation time window exist, and recording the ith active power measurement value as Pk(i) The average value of the N active power measurement values is recorded as
Figure FDA0003405424940000057
Namely have
Figure FDA0003405424940000058
To be provided with
Figure FDA0003405424940000059
For reference, the active power measurement values of the branch k are classified and a classification function PS is definedkComprises the following steps:
Figure FDA0003405424940000061
and recording a one-dimensional vector formed by N active power measurement values of the branch k in the current observation time window as Pk(1),Pk(2),···,Pk(N)]TSorting function PSkActing on each active power measured value of the branch k in the current observation time window one by one according to the time sequence to obtain a corresponding one-dimensional classification vector [ PSk(1),PSk(2),···,PSk(N)]TIn which PS isk(i) Only one of three values of 1, 0 and-1 can be taken; then recording the active power fluctuation frequency of the branch k as mPkAnd the initial value is 0, then mPkIs calculated as
Figure FDA0003405424940000062
And finally obtaining the percentage of the active power fluctuation frequency of the branch k in the current observation time window as follows:
Figure FDA0003405424940000063
(E) maximum fluctuation amount of branch reactive power
The maximum fluctuation amount of branch reactive power is defined as follows: the maximum fluctuation quantity of the branch reactive power refers to the percentage of the difference value between the maximum value and the minimum value of the branch reactive power relative to the average value of the branch reactive power in the current observation time window;
the method for calculating the maximum fluctuation amount of branch reactive power comprises the following steps: assuming that the number of the reactive power measured values of the branch k in the current observation time window is N, the ith reactive power measured value is recorded as Qk(i) Noting that the first reactive power measurement value is Qk(l) The average value of the N reactive power measurement values is recorded as
Figure FDA0003405424940000064
Namely have
Figure FDA0003405424940000065
The maximum fluctuation amount of the reactive power of the branch in the observation time window is:
Figure FDA0003405424940000071
in the formula, i and l are numbers of the reactive power measured value of the branch k in the current observation time window;
(F) branch reactive power dispersion
Branch reactive power dispersion definition: the branch reactive power dispersion refers to the variance of the percentage of the branch reactive power measured value relative to the average value in an observation time window;
the method for calculating the branch reactive power dispersion comprises the following steps: assuming that the number of the reactive power measured values of the branch k in the current observation time window is N, the ith reactive power measured value is recorded as Qk(i) The average value of the N reactive power measurement values is recorded as
Figure FDA0003405424940000072
Namely have
Figure FDA0003405424940000073
The dispersion of the reactive power of branch k in the observation time window is:
Figure FDA0003405424940000074
wherein the content of the first and second substances,
Figure FDA0003405424940000075
the relative error of the ith data point of the reactive power measured value of the branch k relative to the average reactive power in the current observation time window is obtained;
(G) branch reactive power regulation time ratio
And branch reactive power regulation time ratio definition: the branch reactive power regulation time ratio refers to the percentage of data points in which the relative error of a branch reactive power measured value relative to the reactive power average value is more than 2% in the total data points in the current observation time window;
the branch reactive power regulation time ratio calculation method comprises the following steps: assuming that the number of the reactive power measured values of the branch k in the current observation time window is N, the ith reactive power measured value is recorded as Qk(i) The average value of the N reactive power measurement values is recorded as
Figure FDA0003405424940000081
Namely have
Figure FDA0003405424940000082
The measured value of the reactive power of the branch in the current observation time window belongs to
Figure FDA0003405424940000083
The number of points in the range is recorded as NQIf the ratio of the adjusting time of the reactive power of the branch k in the observation time window is:
Figure FDA0003405424940000084
(H) branch reactive power fluctuation frequency percentage
The branch reactive power fluctuation frequency percentage is defined as follows: recording the average value of the branch reactive power measurement values in the current observation time window as
Figure FDA0003405424940000085
The percentage of the frequency of the branch reactive power fluctuation refers to the relation between the curve of the reactive power measured value and the curve of the branch reactive power measured value in the observation time window
Figure FDA0003405424940000086
The percentage of the total crossing times of the interval relative to the maximum crossing times which can be theoretically reached, namely N-1 times;
the method for calculating the branch reactive power fluctuation frequency percentage comprises the following steps: assuming that the number of the reactive power measured values of the branch k in the current observation time window is N, the ith reactive power measured value is recorded as Qk(i) The average value of the N reactive power measurement values is recorded as
Figure FDA0003405424940000087
Namely have
Figure FDA0003405424940000088
To be provided with
Figure FDA0003405424940000089
Reactive power measurement of branch k as referenceThe values are classified and a classification function QS is definedkComprises the following steps:
Figure FDA00034054249400000810
recording a one-dimensional vector formed by N reactive power measurement values of the branch k in the current observation time window as [ Q ]k(1),Qk(2),···,Qk(N)]TClassification function QSkActing on each reactive power measured value of the branch k in the current observation time window one by one according to the time sequence to obtain a corresponding one-dimensional classification vector (QS)k(1),QSk(2),···,QSk(N)]TWherein QS isk(i) Only one of three values of 1, 0 and-1 can be taken; then recording the reactive power fluctuation frequency of the branch k as mQkAnd the initial value is 0, then mQkIs calculated as
Figure FDA0003405424940000091
Finally, the percentage of the reactive power fluctuation frequency of the branch k in the current observation time window is obtained as follows:
Figure FDA0003405424940000092
(I) maximum fluctuation amount of branch current
The maximum fluctuation amount of the branch current is defined as follows: the maximum fluctuation quantity of the branch current is the percentage of the difference between the maximum value of the branch current and the minimum value of the branch current relative to the average value of the branch current in the current observation time window;
the method for calculating the maximum fluctuation amount of the branch current comprises the following steps: assuming that the current measurement values of the branch k in the current observation time window are N in total, the ith current measurement value is recorded as Ik(i) Noting the first current measurement as Ik(l) The average value of the N current measurement values is recorded as
Figure FDA0003405424940000093
Namely have
Figure FDA0003405424940000094
The maximum fluctuation amount of the current of branch k in the observation time window is:
Figure FDA0003405424940000095
in the formula, i and l are serial numbers of current measurement values of the branch k in the current observation time window;
(J) branch current dispersion
Branch current dispersion definition: the branch current dispersion refers to the variance of the percentage of the measured value of the branch current relative to the average value in an observation time window;
the branch current dispersion calculation method comprises the following steps: assuming that the current measurement values of the branch k in the current observation time window are N in total, the ith current measurement value is recorded as Ik(i) The average value of the N current measurement values is recorded as
Figure FDA0003405424940000101
Namely have
Figure FDA0003405424940000102
The dispersion of the current of branch k in the observation time window is:
Figure FDA0003405424940000103
wherein the content of the first and second substances,
Figure FDA0003405424940000104
the relative error of the ith data point of the current measurement value of the branch k relative to the average current in the current observation time window is obtained;
(K) branch current regulation time ratio
And branch current regulation time ratio definition: the branch current regulation time ratio is the percentage of data points in which the relative error of a branch current measurement value relative to a current average value is more than 2% in the total data points in the current observation time window;
the branch current regulation time ratio calculation method comprises the following steps: assuming that the current measurement values of the branch k in the current observation time window are N in total, the ith current measurement value is recorded as Ik(i) The average value of the N current measurement values is recorded as
Figure FDA0003405424940000105
Namely have
Figure FDA0003405424940000106
The measured value of the branch current in the current observation time window belongs to
Figure FDA0003405424940000107
The number of points in the range is recorded as NIIf the current of the branch k is within the observation time window, the adjustment time ratio is:
Figure FDA0003405424940000108
(L) percent of branch current fluctuation frequency
The branch current fluctuation frequency percentage is defined as follows: the average value of the branch current measurement values in the current observation time window is recorded as
Figure FDA0003405424940000109
The fluctuation frequency percentage of the branch current means that the branch current measured value curve is related to the branch current measured value in the observation time window
Figure FDA0003405424940000111
The percentage of the total crossing times of the interval relative to the maximum crossing times which can be theoretically reached, namely N-1 times;
branch current ripple frequencyThe calculation method of the sub-percentage is as follows: assuming that the current measurement values of the branch k in the current observation time window are N in total, the ith current measurement value is recorded as Ik(i) The average value of the N current measurement values is recorded as
Figure FDA0003405424940000112
Namely have
Figure FDA0003405424940000113
To be provided with
Figure FDA0003405424940000114
For reference, the current measured values of the branch k are classified and a classification function IS IS definedkComprises the following steps:
Figure FDA0003405424940000115
recording a one-dimensional vector formed by N current measurement values of the branch k in the current observation time window as [ Ik(1),Ik(2),···,Ik(N)]TTo classify the function ISkActing on each current measured value of the branch k in the current observation time window one by one according to the time sequence to obtain a corresponding one-dimensional classification vector [ ISk(1),ISk(2),···,ISk(N)]TWherein ISk(i) Only one of three values of 1, 0 and-1 can be taken; then, the current fluctuation frequency of the branch k is recorded as mIkAnd the initial value is 0, then mIkIs calculated by
Figure FDA0003405424940000116
And finally, the current fluctuation frequency percentage of the branch k in the current observation time window is obtained as follows:
Figure FDA0003405424940000117
maximum fluctuation amount of (M) branch power factor
The maximum fluctuation amount of the branch power factor is defined as follows: the percentage of the difference between the maximum value of the branch power factor and the minimum value of the branch power factor relative to the average value of the branch power factor in an observation time window is shown;
the method for calculating the maximum fluctuation amount of the branch power factor comprises the following steps: assuming that the number of the power factor measurement values of the branch k in the current observation time window is N, the ith power factor measurement value is recorded as Fk(i) Noting that the first power factor measurement value is Fk(l) The average value of the N power factor measurement values is recorded as
Figure FDA0003405424940000121
Namely have
Figure FDA0003405424940000122
The maximum fluctuation amount of the power factor of branch k within the observation time window is:
Figure FDA0003405424940000123
in the formula, i and l are numbers of power factor measured values of the branch k in a current observation time window;
(N) branch power factor dispersion
Branch power factor dispersion definition: the branch power factor dispersion refers to the variance of the percentage of the branch power factor measured value relative to the average value in an observation time window;
the branch power factor dispersion calculation method comprises the following steps: assuming that the number of the power factor measurement values of the branch k in the current observation time window is N, the ith power factor measurement value is recorded as Fk(i) The average value of the N power factor measurement values is recorded as
Figure FDA0003405424940000124
Namely have
Figure FDA0003405424940000125
The dispersion of the power factor of branch k within the observation time window is:
Figure FDA0003405424940000126
wherein the content of the first and second substances,
Figure FDA0003405424940000127
the relative error of the ith data point of the power factor measured value of the branch k relative to the average power factor in the current observation time window is obtained;
(O) branch power factor adjustment time ratio
The branch power factor regulation time is defined by the ratio: the branch power factor adjustment time ratio refers to the percentage of data points in which the relative error of a branch power factor measured value relative to the power factor average value is greater than 2% in the total data points in the current observation time window;
the branch power factor adjusting time ratio calculating method comprises the following steps: assuming that the number of the power factor measurement values of the branch k in the current observation time window is N, the ith power factor measurement value is recorded as Fk(i) The average value of the N power factor measurement values is recorded as
Figure FDA0003405424940000131
Namely have
Figure FDA0003405424940000132
The measured value of the branch power factor in the current observation time window belongs to
Figure FDA0003405424940000133
The number of points in the range is recorded as NFThen, the ratio of the adjustment time of the power factor of branch k in the observation time window is:
Figure FDA0003405424940000134
(P) branch power factor fluctuation frequency percentage
The branch power factor fluctuation frequency percentage is defined as follows: the average value of the branch power factor measured values in the current observation time window is recorded as
Figure FDA0003405424940000135
The percentage of the branch power factor fluctuation frequency refers to the power factor measurement curve relative to the observation time window
Figure FDA0003405424940000136
The percentage of the total crossing times of the interval relative to the maximum crossing times which can be theoretically reached, namely N-1 times;
the method for calculating the branch power factor fluctuation frequency percentage comprises the following steps: assuming that the number of the power factor measurement values of the branch k in the current observation time window is N, the ith power factor measurement value is recorded as Fk(i) The average value of the N power factor measurement values is recorded as
Figure FDA0003405424940000137
Namely have
Figure FDA0003405424940000138
To be provided with
Figure FDA0003405424940000139
For reference, the power factor measured values of the branch k are classified and a classification function FS is definedkComprises the following steps:
Figure FDA0003405424940000141
and recording a one-dimensional vector formed by N power factor measurement values of the branch k in the current observation time window as Fk(1),Fk(2),···,Fk(N)]TA classification function FSkAccording to the time sequenceSequentially acting on each power factor measured value of the branch k in the current observation time window to obtain a corresponding one-dimensional classification vector [ FS ]k(1),FSk(2),···,FSk(N)]TIn which FSk(i) Only one of three values of 1, 0 and-1 can be taken; then, the power factor fluctuation frequency of the branch k is recorded as mFkAnd the initial value is 0, then mFkIs calculated as
Figure FDA0003405424940000142
Finally, the power factor fluctuation frequency percentage of the branch k in the current observation time window is obtained as follows:
Figure FDA0003405424940000143
(1.3) comprehensive evaluation index of dynamic characteristics of whole network
(A) Evaluation index for dynamic characteristics of nodes of whole network
Assuming that the whole network has J nodes, taking each node as an element, forming a node set and marking the node set as psinodeThe evaluation index of the dynamic characteristics of the nodes in the whole network and the calculation method thereof are as follows
UMF (unified modeling framework) with maximum fluctuation quantity of node voltage of whole networkmax
Figure FDA0003405424940000144
Average maximum fluctuation amount of node voltage of whole network
Figure FDA0003405424940000145
Figure FDA0003405424940000146
Node voltage maximum dispersion UD of whole networkmax
Figure FDA0003405424940000151
Average dispersion of node voltage of whole network
Figure FDA0003405424940000152
Figure FDA0003405424940000153
UAT (Universal asynchronous receiver) based on maximum regulation time ratio of node voltage of whole networkmax
Figure FDA0003405424940000154
Average regulation time ratio of node voltage of whole network
Figure FDA0003405424940000155
Figure FDA0003405424940000156
UFF (unidirectional flux) with maximum fluctuation frequency percentage of node voltage of whole networkmax
Figure FDA0003405424940000157
Average fluctuation frequency percentage of node voltage of whole network
Figure FDA0003405424940000158
Figure FDA0003405424940000159
(B) Evaluation index of dynamic characteristics of branches of whole network
Assuming that the whole network has K branches, taking each branch as an element to form a branch set and marking the branch set as psilineThe evaluation index of the dynamic characteristics of the branches of the whole network and the calculation method thereof are as follows
Active power maximum fluctuation PMF of whole network branchmax
Figure FDA00034054249400001510
Average maximum fluctuation quantity of active power of all network branches
Figure FDA00034054249400001511
Figure FDA00034054249400001512
Full-network branch active power maximum dispersion PDmax
Figure FDA0003405424940000161
Average dispersion of active power of all network branches
Figure FDA0003405424940000162
Figure FDA0003405424940000163
PAT (active power maximum regulation time ratio) of all network branchesmax
Figure FDA0003405424940000164
Ratio of active power average regulation time of whole network branch
Figure FDA0003405424940000165
Figure FDA0003405424940000166
Percentage PFF of maximum fluctuation frequency of active power of all network branchesmax
Figure FDA0003405424940000167
Percentage of average fluctuation frequency of active power of branches of whole network
Figure FDA0003405424940000168
Figure FDA0003405424940000169
Full-network branch reactive power maximum fluctuation quantity QMFmax
Figure FDA00034054249400001610
Average maximum fluctuation amount of reactive power of all network branches
Figure FDA00034054249400001611
Figure FDA00034054249400001612
Full-network branch reactive power maximum dispersion QDmax
Figure FDA00034054249400001613
Average dispersion of reactive power of all network branches
Figure FDA00034054249400001614
Figure FDA00034054249400001615
QAT (QAT) for maximum regulation time ratio of reactive power of all network branchesmax
Figure FDA0003405424940000171
Ratio of reactive power average regulation time of whole network branch
Figure FDA0003405424940000172
Figure FDA0003405424940000173
QFF (quad flat no-lead) with maximum fluctuation frequency percentage of reactive power of all network branchesmax
Figure FDA0003405424940000174
Percentage of average fluctuation frequency of reactive power of all network branches
Figure FDA0003405424940000175
Figure FDA0003405424940000176
Full-network branch current maximum fluctuation IMFmax
Figure FDA0003405424940000177
Average maximum fluctuation amount of current of all network branches
Figure FDA0003405424940000178
Figure FDA0003405424940000179
Maximum dispersion ID of branch current of whole networkmax
Figure FDA00034054249400001710
Average dispersion of current of all-network branch
Figure FDA00034054249400001711
Figure FDA00034054249400001712
IAT (integrated circuit) for maximum regulation time ratio of current of whole network branchmax
Figure FDA00034054249400001713
Average regulation time ratio of current of whole network branch
Figure FDA00034054249400001714
Figure FDA00034054249400001715
Percentage IFF of maximum fluctuation frequency of current of whole network branchmax
Figure FDA0003405424940000181
Average fluctuation frequency percentage of current of whole network branch
Figure FDA0003405424940000182
Figure FDA0003405424940000183
Full-network power factor maximum fluctuation FMFmax
Figure FDA0003405424940000184
Average maximum fluctuation of power factor of whole network
Figure FDA0003405424940000185
Figure FDA0003405424940000186
Full-network power factor maximum dispersion FDmax
Figure FDA0003405424940000187
Average dispersion of power factor of whole network
Figure FDA0003405424940000188
Figure FDA0003405424940000189
Full-network power factor maximum regulation time ratio FATmax
Figure FDA00034054249400001810
Average regulation time ratio of power factor of whole network
Figure FDA00034054249400001811
Figure FDA00034054249400001812
FFF (percent of maximum fluctuation frequency) of full-network power factormax
Figure FDA00034054249400001813
Average fluctuation frequency percentage of power factor of whole network
Figure FDA00034054249400001814
Figure FDA00034054249400001815
(C) Comprehensive evaluation index for dynamic characteristics of whole network
The total network node dynamic characteristic evaluation indexes and the total network branch dynamic characteristic evaluation indexes are 40, and in practical application, partial indexes are selected to evaluate the dynamic characteristics of the active power distribution network according to specific requirements with emphasis; assuming that only M indexes are used in a certain actual evaluation, the comprehensive evaluation index of the dynamic characteristics of the whole network is
Figure FDA0003405424940000191
s.t.0≤wi≤1
Figure FDA0003405424940000192
In the formula, wiWeight representing the ith index, INiA value representing the ith index;
(2) setting the weight corresponding to each evaluation index;
(3) selecting the size of a current observation time window according to the actual frequency of PMU synchronous measurement data, so that not less than 10 data points are in the current observation time window;
(4) reading data points in the current observation time window, wherein the data points comprise a node voltage measured value, a branch active power measured value, a branch reactive power measured value, a branch current measured value and a branch power factor measured value;
(5) calculating the dynamic characteristic indexes of each node according to the selection result of the node dynamic characteristic evaluation indexes in the step (1);
(6) calculating the dynamic characteristic index of each branch according to the selection result of the branch dynamic characteristic evaluation index in the step (1);
(7) calculating the node dynamic characteristic evaluation index of the whole network on the basis of the node dynamic characteristic evaluation index obtained in the step (5);
(8) calculating the dynamic characteristic evaluation index of the whole network branch on the basis of the dynamic characteristic evaluation index of the branch obtained in the step (6);
(9) and solving a comprehensive evaluation index CI of the dynamic characteristics of the whole network.
2. The active power distribution network dynamic characteristic evaluation method based on the synchronous measurement data as claimed in claim 1, wherein: in the step (2), weights corresponding to the evaluation indexes are set by adopting an expert scoring method.
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