CN110380409B - Active power distribution network distributed robust state estimation method and system considering communication failure - Google Patents
Active power distribution network distributed robust state estimation method and system considering communication failure Download PDFInfo
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Abstract
The invention discloses a distributed robust state estimation method and a distributed robust state estimation system for an active power distribution network considering communication failure, wherein the method comprises the following steps: dividing the power distribution network into Ns sub-regions, and establishing a distributed state estimation model; the three-layer distributed communication architecture is formed by intra-subregion communication, inter-subregion communication and communication between subregions and a control center; the local state estimation of each sub-area is realized by adopting an improved weighted least square method for each sub-area; coordinating the state quantity of the overlapped nodes between the adjacent subregions and the estimation value of the standard deviation thereof by adopting a consistency algorithm, and using the state quantity and the estimation value of the standard deviation as the newly added virtual measurement and the error thereof for the next iterative calculation of the local state estimation; and judging whether the distributed state estimation meets the convergence condition or not, and recording the distributed state estimation result. Compared with the traditional distributed state estimation method, the distributed robust state estimation method effectively improves the calculation efficiency.
Description
Technical Field
The invention relates to the technical field of power distribution network state estimation, in particular to an active power distribution network distributed robust state estimation method and system considering communication failure.
Background
The statements in this section merely provide background information related to the present disclosure and may not necessarily constitute prior art.
The power distribution network state estimation is one of high-level applications of a power distribution management system, and means that a proper filtering method is adopted to estimate a complete, accurate and reliable power distribution network running state according to measurement information obtained by measurement equipment installed in a power distribution network and pseudo measurement data obtained according to load prediction or non-telemetering data, so that accurate state information is provided for real-time and effective control and management of the power distribution network, and accurate data support is provided for other high-level applications in the power distribution management system. The active power distribution network has the characteristics of large system scale, unbalanced three phases, high requirements on data real-time performance and accuracy and the like, so that the traditional centralized state estimation faces great challenges in calculation accuracy and calculation time, particularly in the aspect of calculation efficiency; the distributed state estimation can divide a large-scale system into a plurality of small-scale subsystems, and a parallel or serial computing architecture is adopted, so that the computing scale can be effectively reduced, and the computing efficiency is improved, therefore, the development of the distributed state estimation becomes necessary.
A reliable communication system is a basic guarantee for distributed state estimation of an active power distribution network. When the communication system normally operates, the distributed state estimation can acquire complete and accurate measurement data and coordinate interaction information, and efficient and accurate calculation of the distributed state estimation is facilitated. However, communication failure may occur occasionally in the communication system, which may cause problems such as data missing or bad data, and these problems may have a large adverse effect on the performance of the distributed state estimation calculation. Therefore, how to improve the robustness of the distributed state estimation algorithm to the communication failure problem has important value.
The inventor finds that the distributed state estimation method of the active power distribution network mainly has the following problems:
(1) the influence of the communication failure problem (represented by bad data) occurring inside the sub-region on the distributed state estimation is not considered;
(2) the influence of the problem of communication failure among sub-regions in the distributed communication architecture on the distributed state estimation is not considered;
(3) distributed state estimation is computationally inefficient.
Disclosure of Invention
In order to solve the problems, the invention provides a distributed robust state estimation method and a distributed robust state estimation system for an active power distribution network, which take communication failure into consideration, can effectively weaken the negative influence of the communication failure in a distributed communication architecture on the distributed state estimation calculation performance while improving the calculation efficiency.
In some embodiments, the following technical scheme is adopted:
a distributed robust state estimation method for an active power distribution network considering communication failure comprises the following steps:
(1) dividing the power distribution network into Ns sub-regions, and establishing a distributed state estimation model; the three-layer distributed communication architecture is formed by intra-subregion communication, inter-subregion communication and communication between subregions and a control center;
(2) the local state estimation of each sub-area is realized by adopting an improved weighted least square method for each sub-area;
(3) coordinating the state quantity of the overlapped nodes between the adjacent subregions and the estimation value of the standard deviation thereof by adopting a consistency algorithm, and using the state quantity and the estimation value of the standard deviation as the newly added virtual measurement and the error thereof for the next iterative calculation of the local state estimation;
(4) judging whether the distributed state estimation meets the convergence condition, if not, returning to the step (2); and if so, finishing iteration and recording the distributed state estimation result.
In other embodiments, the following technical solutions are adopted:
an active power distribution network distributed robust state estimation system considering communication failure, comprising:
the device is used for dividing the power distribution network into Ns sub-regions and establishing a distributed state estimation model;
means for constructing a three-tier distributed communications architecture; the three-layer distributed communication architecture is composed of intra-sub-area communication, inter-sub-area communication and communication between the sub-areas and the control center;
means for performing local state estimation for each sub-region using modified weighted least squares for each sub-region;
means for coordinating state quantities of overlapping nodes between adjacent sub-regions and estimates of their standard deviations using a consistency algorithm; the obtained state quantity and the estimated value of the standard deviation thereof are used as newly added virtual measurement and the error thereof for the next iterative calculation of the local state estimation;
means for determining whether the distributed state estimate satisfies a convergence condition;
means for recording the distributed state estimation results.
In other embodiments, the following technical solutions are adopted:
a terminal device comprising a processor and a computer-readable storage medium, the processor being configured to implement instructions; the computer readable storage medium is used for storing a plurality of instructions, and the instructions are suitable for being loaded by a processor and executing the active power distribution network distributed robust state estimation method considering communication failure.
In other embodiments, the following technical solutions are adopted:
a computer readable storage medium, wherein a plurality of instructions are stored, said instructions being adapted to be loaded by a processor of a terminal device and to execute the above method for estimating distributed robust state of an active distribution network considering communication failure.
Compared with the prior art, the invention has the beneficial effects that:
(1) on the basis of analyzing the adverse effect of the communication failure problem on the distributed state estimation of the active power distribution network, the distributed robust state estimation method is provided, and compared with the traditional distributed state estimation method, the method effectively improves the calculation efficiency;
(2) according to the method, the local state estimation is carried out by utilizing the weight adaptive improved weighted least square method, so that the negative influence of bad data on the state estimation caused by internal communication failure in a factor area is weakened;
(3) according to the invention, the consistency algorithm coordination interaction process is embedded into the weighted least square method iteration process, so that the problem of communication failure between sub-regions can be well solved, and the robustness of the algorithm is improved.
Drawings
FIG. 1 is a diagram of a distributed communication architecture in accordance with one embodiment;
FIG. 2 is a flowchart of a distributed robust state estimation algorithm according to a first embodiment;
FIG. 3 is a communication topology under normal conditions and communication failure conditions according to the first embodiment;
fig. 4 is a wiring diagram of an IEEE123 node distribution network and a partitioning condition thereof according to the first embodiment;
fig. 5 is a simulation time chart of the IEEE123 node power distribution network in the first embodiment;
fig. 6 is a simulation accuracy diagram of the IEEE123 node power distribution network in the first embodiment.
Detailed Description
It should be noted that the following detailed description is exemplary and is intended to provide further explanation of the disclosure. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of example embodiments according to the present application. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, and it should be understood that when the terms "comprises" and/or "comprising" are used in this specification, they specify the presence of stated features, steps, operations, devices, components, and/or combinations thereof, unless the context clearly indicates otherwise.
Example one
In one or more embodiments, an active distribution network distributed robust state estimation method considering communication failure is disclosed, and with reference to fig. 2, the method includes the following steps:
(1) giving a communication framework of the distributed state estimation, and analyzing the negative influence of communication failure in the distributed communication framework on the distributed state estimation;
as shown in fig. 1, the distributed communication architecture is divided into three layers, and each layer of communication is composed of intra-sub-area communication, inter-sub-area communication, and communication between a sub-area and a control center, each layer of communication corresponds to different communication tasks and functions, and under the background of distributed state estimation of the power distribution network, intra-sub-area communication is mainly used for collecting measurement information collected by a terminal, uploading the measurement information to the sub-area control center, and providing measurement data for local state estimation; communication among the sub-areas is mainly used for exchanging relevant information after local state estimation and is used for 1) judging whether the distributed state estimation of the power distribution network is converged or not and 2) information interaction, so that the estimation precision is improved, and the convergence characteristic of the distributed state estimation of the power distribution network is improved; the communication between the sub-areas and the control center mainly plays a role in uploading the converged estimation result to the control center.
In this embodiment, the influence of communication on the performance of distributed state estimation calculation is mainly focused on, and therefore, communication of a part of the converged estimation result uploaded to the control center is not considered, and only communication inside and between sub-regions is considered. In a distributed communication architecture of a power distribution network, in order to guarantee reliability and effectiveness of communication, an IEC61850 standard and a TCP protocol are mainly adopted. Generally, the transmission interval of data is 20ms, and the requirement for information transmission in the distributed state estimation calculation process of the power distribution network can be met.
When the communication system works normally, the distributed state estimation of the power distribution network can be carried out quickly and effectively; however, communication failure problems occurring occasionally during communication can have a great adverse effect on the distributed state estimation calculation performance of the power distribution network. The problem of communication failure in a distributed communication architecture is mainly addressed by the following two aspects:
1) the consequences of a communication failure within a sub-area are mainly data loss and bad data.
2) Communication failure between sub-regions can cause communication data loss or bad data to appear between sub-regions, which will have bad influence on information interaction and coordination between sub-regions in distributed state estimation.
(2) On the premise of known measurement configuration and partition, completing the partition of sub-areas of the power distribution network containing overlapped nodes, and establishing a distributed state estimation model;
the nodes configured with PMUs (power management units) are used as overlapping nodes, so that the partitioning and decoupling of the active power distribution network are realized. A distributed state estimation model is established as shown in the following formula:
s.t. g(x)＝0
wherein subscript i represents the ith sub-region; j. the design is a squarei(xi) An objective function representing a subregion i; z isiFor measuring the amount of sub-area i, hi(x) Is a measurement function; w'iIs the amount of sub-region iMeasuring a weight matrix, wherein an adaptive variable is related to the size of the residual error; the equation is constrained to make the state quantity estimated values of the overlapped nodes in different sub-regions equal, as follows:
in the formula (I), the compound is shown in the specification,
respectively representing the estimated values of three-phase voltage amplitude and phase angle of the overlapped node in the sub-region i and the sub-region j, i, j E (1, N)s)。
(3) Each sub-area adopts an improved weighted least square method to realize local state estimation;
the local state estimation based on the improved weighted least square method is realized in parallel by each subarea, and the target function of the subarea i is as follows
min Ji(xi)＝(zi-hi(xi))TW'i(zi-hi(xi))
For the weighted least squares method, the magnitude of the measured weight should depend on the precision of the measuring device; in the simulation of the power distribution network state estimation, it is generally assumed that the measurement data conform to normal distribution, and the measurement weight is calculated according to the reciprocal of the square of the standard deviation of the corresponding measurement data, that is to say
Wherein sigmalFor the standard deviation of the metrology data, 1/3 is usually taken as the maximum error. The maximum error is typically given by taking a certain percentage as the error coverage of 99.7% according to the measurement type, for example, the conventional SCADA measurement is typically 1% to 3% of the actual value, the PMU measurement is typically 0.5% to 0.7% of the actual value, and the pseudo measurement is typically 20% to 50% of the maximum error of the corresponding measurement. In the weighted least squares method, the residual is defined as the difference between the measured and estimated values, as shown in the following equation:
rl＝zl-hl(x)
in the formula, rlThe residual error of measurement l.
When bad data exists, the residual error is very large, so in the iteration process of the weighted least square method, whether the data is the bad data or not can be judged according to the size of the residual error, and the size of the weight is adjusted according to the size of the residual error, so that the bad influence of the bad data on the state estimation is weakened, and the specific operation is as follows:
in the formula, kl＝rl/σlTo measure the normalized residual of l, ksA threshold set according to the 3 sigma principle is used to determine whether the measurement is bad data. For a determined measurement, σlIs definite, therefore klProportional to the residual error. When k is a certain measured datalThe value is greater than a set value ksAnd reducing the corresponding weight, wherein the larger the damage degree of the measured data is, the smaller the weight is, thereby achieving the purpose of weakening the negative influence of the measured data on the state estimation.
Then, Δ x at the k-th iteration is calculated using the following equationiObtaining the state quantity estimation result x of the iterationi。
Wherein H is a Jacobian matrix.
(4) Performing information interaction between the sub-regions, and performing coordination calculation on the interacted data by adopting a consistency algorithm;
a coherence algorithm based on a finite time-averaged coherence protocol is used to coordinate the state quantities of overlapping nodes between adjacent sub-regions. After the partition decoupling of the power distribution network is realized, the data exchange condition among the sub-areas can be described by a communication network, each sub-area corresponds to one communication node, and the communication interaction relationship among the sub-areas can be represented by a graph G (D, E), wherein a set D represents the communication node corresponding to the sub-area, and a set E represents the communication relationship among the adjacent sub-areas. The set of adjacent sub-regions of sub-region i is represented by:
Mi＝{j∈D|(i,j)∈E}
in the formula, j represents the jth sub-region.
The laplacian matrix corresponding to the graph G may be represented by L ═ Lij]Expressing that the elements in the Laplace matrix of the interaction relation based on the communication topology can be defined as
In the formula IijWith-1 is meant that sub-region i is adjacent to sub-region j and the diagonal element l of the laplace matrix isiiRepresenting the total number of all sub-regions adjacent to sub-region i.
The consistency calculation formula of the overlapped node data in the sub-area i is as follows:
where KC is 1,2, …, KC is the number of non-zero eigenvalues of the laplace matrix L; lambda [ alpha ]kcIs the kc-th non-zero eigenvalue of the laplacian matrix L; according to the finite time average consistency protocol, when KC ═ KC, the calculation of the interaction data can result in an average consistency result.
And processing the data interacted between the sub-regions by using the formula to obtain consistent overlapped node state quantities and estimated values of standard deviations thereof, wherein the quantities are used as newly added virtual measurement and errors thereof to be used for recalculation of local state estimation.
In fig. 3, assuming that the communication topology of the three sub-regions has communication failure between the regions 2 and 3, the laplacian matrix corresponding to the communication topology is
In the formula, LaRepresenting the corresponding laplacian matrix under normal conditions; l isbIndicating a laplacian matrix in the presence of a communication failure.
In the consensus algorithm, the formula is used
Performing data consistency operation by using LaAnd its eigenvalue calculation and adoption of LbAnd the results obtained by calculating the characteristic values are the same, and the influence of communication failure between adjacent sub-regions on distributed state estimation can be effectively weakened in the iterative process of the weighted least square method by utilizing the consistency algorithm to coordinate and calculate.
(5) And (4) judging whether the distributed state estimation is converged, if not, turning to the step (2), and if so, recording the distributed state estimation result. And obtaining the running state of the power distribution network according to the distributed state estimation result, and providing accurate state information for real-time and effective control and management of the power distribution network.
Since the coordination interaction between adjacent sub-regions is embedded in the local state estimation, the convergence of the distributed robust state estimation needs to satisfy two conditions simultaneously, 1) the local state estimation converges; 2) the overall convergence between adjacent sub-regions. As shown in the following formula
Δxi<
Δxij<
In the formula,. DELTA.xi<For characterizing the convergence of the local state estimate, Δ xij<For characterizing convergence between adjacent sub-regions.
FIG. 4 shows a system structure diagram of an IEEE123 node power distribution network and a partition condition thereof, which are used for a simulation verification method.
Fig. 5 and 6 are comparisons of conventional distributed state estimation with the distributed robust state estimation of the present invention in different scenarios. When a scene is set, the communication failure in the subareas mainly focuses on the influence caused by bad data, and the bad data is set as a negative value of actual measurement and is given in a probability form. The communication failure between the sub-regions mainly focuses on the influence caused by bad data and data loss, and the information interacted between the adjacent sub-regions is relatively less and is also given in a probability form. As shown in table 1:
TABLE 1 distributed robust State estimation simulation scenario setup
As can be seen from fig. 5 and 6, in scenario 1, the calculation accuracy of the conventional distributed state estimation algorithm is better than that of the distributed robust state estimation algorithm, but the simulation time is longer. The main reason is that the distributed robust state estimation algorithm embeds information interaction and coordination between the sub-regions into the local state estimation iteration process, each iteration of the local state estimation is latest interactive data, the convergence speed is high, the local state estimation can output an estimation result only through one iteration convergence, and although part of calculation precision is sacrificed, the calculation efficiency is greatly improved. In an IEEE123 node power distribution network, under the condition of communication failure, the distributed robust state estimation algorithm can still effectively weaken the negative effects of the distributed robust state estimation algorithm, and the effectiveness and the expandability of the algorithm are verified.
Example two
In one or more embodiments, an active distribution network distributed robust state estimation system considering communication failure is disclosed, comprising:
the device is used for dividing the power distribution network into Ns sub-regions and establishing a distributed state estimation model;
means for constructing a three-tier distributed communications architecture; the three-layer distributed communication architecture is composed of intra-sub-area communication, inter-sub-area communication and communication between the sub-areas and the control center;
means for performing local state estimation for each sub-region using modified weighted least squares for each sub-region;
means for coordinating state quantities of overlapping nodes between adjacent sub-regions and estimates of their standard deviations using a consistency algorithm; the obtained state quantity and the estimated value of the standard deviation thereof are used as newly added virtual measurement and the error thereof for the next iterative calculation of the local state estimation;
means for determining whether the distributed state estimate satisfies a convergence condition;
means for recording the distributed state estimation results.
EXAMPLE III
In one or more embodiments, a terminal device is disclosed, which includes a server including a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor executes the computer program to implement the method for distributed robust state estimation of an active distribution network in consideration of communication failure in the first embodiment. For brevity, no further description is provided herein.
It should be understood that in this embodiment, the processor may be a central processing unit CPU, and the processor may also be other general purpose processors, digital signal processors DSP, application specific integrated circuits ASIC, off-the-shelf programmable gate arrays FPGA or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, and so on. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The memory may include both read-only memory and random access memory, and may provide instructions and data to the processor, and a portion of the memory may also include non-volatile random access memory. For example, the memory may also store device type information.
In implementation, the steps of the above method may be performed by integrated logic circuits of hardware in a processor or instructions in the form of software.
The method for estimating the distributed robust state of the active power distribution network in consideration of the communication failure in the first embodiment may be directly implemented by a hardware processor, or implemented by a combination of hardware and software modules in the processor. The software modules may be located in ram, flash, rom, prom, or eprom, registers, among other storage media as is well known in the art. The storage medium is located in a memory, and a processor reads information in the memory and completes the steps of the method in combination with hardware of the processor. To avoid repetition, it is not described in detail here.
Those of ordinary skill in the art will appreciate that the various illustrative elements, i.e., algorithm steps, described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
Although the embodiments of the present invention have been described with reference to the accompanying drawings, it is not intended to limit the scope of the present invention, and it should be understood by those skilled in the art that various modifications and variations can be made without inventive efforts by those skilled in the art based on the technical solution of the present invention.
Claims (10)
1. A distributed robust state estimation method for an active power distribution network considering communication failure is characterized by comprising the following steps:
(1) dividing the power distribution network into Ns sub-regions, and establishing a distributed state estimation model; the three-layer distributed communication architecture is formed by intra-subregion communication, inter-subregion communication and communication between subregions and a control center;
(2) the local state estimation of each sub-area is realized by adopting an improved weighted least square method for each sub-area;
(3) coordinating the state quantity of the overlapped nodes between the adjacent subregions and the estimation value of the standard deviation thereof by adopting a consistency algorithm, and using the state quantity and the estimation value of the standard deviation as the newly added virtual measurement and the error thereof for the next iterative calculation of the local state estimation;
(4) judging whether the distributed state estimation meets the convergence condition, if not, returning to the step (2); if so, finishing iteration and recording a distributed state estimation result;
and coordinating data interacted between the adjacent subregions by adopting a consistency algorithm, wherein the data comprises state quantities of overlapped nodes between the adjacent subregions and estimation values of standard deviations of the state quantities of the overlapped nodes, and the estimation values of the state quantities of the overlapped nodes and the estimation values of the standard deviations of the state quantities of the overlapped nodes are obtained by estimating local states of the adjacent subregions.
2. The method for distributed robust state estimation of the active power distribution network in consideration of the communication failure as claimed in claim 1, wherein the nodes configured with the PMU are used as overlapped nodes, state quantity estimation values of the overlapped nodes in different sub-areas are equal to each other and used as constraint conditions, and a distributed state estimation model is established with a target of minimum weighted least square objective function of each sub-area.
3. The method for estimating the distributed robust state of the active power distribution network in consideration of the communication failure as recited in claim 1, wherein the established distributed state estimation model specifically comprises:
s.t.g(x)＝0
wherein subscript i represents the ith sub-region; j. the design is a squarei(xi) An objective function representing a subregion i; z is a radical ofiFor measuring the amount of sub-area i, hi(x) A measurement function for sub-region i; wi'is a metrology weight matrix for sub-region i, where the l-th diagonal element is w'lRepresenting the weight of the first measurement; and g (x) 0 is an equality constraint, wherein the equality constraint and the basic power flow equation constraint are contained in the estimation values of the overlapped nodes in different subregions.
4. The method for estimating the distributed robust state of the active power distribution network in consideration of the communication failure as claimed in claim 1, wherein in the three-layer distributed communication architecture, the intra-sub-area communication is used for collecting the measurement information collected by the terminal, uploading the measurement information to a sub-area control center, and providing the measurement data for local state estimation; communication among the sub-areas is used for exchanging relevant information after local state estimation, judging whether the distributed state estimation of the power distribution network is converged or not, and improving the distributed state estimation precision of the power distribution network through information interaction; the communication of the sub-areas with the control center is used to upload the converged estimation results to the control center.
5. The method for estimating the distributed robust state of the active power distribution network in consideration of the communication failure as claimed in claim 1, wherein the local state estimation of each sub-region is realized by adopting an improved weighted least square method for each sub-region, specifically:
in the weighted least squares method, the residual is defined as the difference between the measured value and the estimated value;
in the iteration process of the weighted least square method, when the residual error is greater than or equal to a set threshold value, judging that the measured value is bad data, and reducing the corresponding weight of the measured value; and the larger the damage degree of the measured value is, the smaller the weight is;
w 'of'l,newFor updated weights, klTo measure the normalized residual of l, ksA threshold set according to the 3 sigma principle is used to determine whether the measurement is bad data;
then calculate Δ x at the k iterationiObtaining the state quantity estimation result x of the iterationi；
Wherein HiThe matrix is a Jacobian matrix obtained by calculating the partial derivative of the state quantity by a measuring function.
6. The method for estimating the distributed robust state of the active power distribution network in consideration of the communication failure as claimed in claim 1, wherein the consistency calculation formula of the overlapped node data in the sub-region i is as follows:
wherein KC is 1,2, L, KC is the number of non-zero eigenvalues of the laplace matrix L; lambda [ alpha ]kcIs the kc-th non-zero eigenvalue of the laplacian matrix L; when KC is KC, calculating the interactive data to obtain an average consistency result; x is the number ofi,kc、xi,kc-1Respectively, the state quantities during the iteration of the consistency formula.
7. The method for distributed robust state estimation of the active power distribution network considering communication failure as claimed in claim 6, wherein the communication interaction relationship between the sub-areas is represented by a graph G ═ (D, E), where a set D represents a communication node corresponding to a sub-area, and a set E represents a communication relationship between adjacent sub-areas; the set of adjacent sub-regions of sub-region i is denoted Mi{ j ∈ D | (i, j) ∈ E }; lapuThe Lass matrix L ═ Lij]；
Wherein lijWith-1 is meant that sub-region i is adjacent to sub-region j, diagonal element liiRepresenting the total number of all sub-regions adjacent to sub-region i.
8. An active power distribution network distributed robust state estimation system considering communication failure, comprising:
the device is used for dividing the power distribution network into Ns sub-regions and establishing a distributed state estimation model;
means for constructing a three-tier distributed communications architecture; the three-layer distributed communication architecture is composed of intra-sub-area communication, inter-sub-area communication and communication between the sub-areas and the control center;
means for performing local state estimation for each sub-region using modified weighted least squares for each sub-region;
means for coordinating state quantities of overlapping nodes between adjacent sub-regions and estimates of their standard deviations using a consistency algorithm; the obtained state quantity and the estimated value of the standard deviation thereof are used as newly added virtual measurement and the error thereof for the next iterative calculation of the local state estimation;
means for determining whether the distributed state estimate satisfies a convergence condition;
means for recording distributed state estimation results;
and coordinating data interacted between the adjacent subregions by adopting a consistency algorithm, wherein the data comprises state quantities of overlapped nodes between the adjacent subregions and estimation values of standard deviations of the state quantities of the overlapped nodes, and the estimation values of the state quantities of the overlapped nodes and the estimation values of the standard deviations of the state quantities of the overlapped nodes are obtained by estimating local states of the adjacent subregions.
9. A terminal device comprising a processor and a computer-readable storage medium, the processor being configured to implement instructions; the computer-readable storage medium is used for storing a plurality of instructions, wherein the instructions are adapted to be loaded by a processor and to perform the method for distributed robust state estimation of an active power distribution network considering communication failure according to any of claims 1 to 7.
10. A computer-readable storage medium having stored thereon a plurality of instructions, wherein the instructions are adapted to be loaded by a processor of a terminal device and to perform the method for distributed robust state estimation of an active distribution network considering communication failure according to any of claims 1 to 7.
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