CN110968953B - Electric power system transient stability simulation parallel computing method based on nested diagonal edge adding form - Google Patents
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Abstract
The invention discloses a power system transient stability simulation parallel computing method based on a nested diagonal edge adding form. In the fully parallel BBDF method, along with the increase of the concurrency number, the scale of the contact system is further increased, and when the scale of the contact system is larger than the maximum subsystem calculation amount, the acceleration ratio of the fully parallel BBDF method is saturated. On the basis of the full-parallel BBDF method, the invention further decomposes the contact system which is increased along with the increase of the concurrency number in the full-parallel BBDF method, solves the decomposed contact system by using the traditional BBDF method, and simultaneously introduces the mixed programming of subsystem-core mapping and MPI-OpenMP, thereby improving the acceleration ratio and the efficiency of the parallel transient stability simulation.
Description
Technical Field
The invention belongs to the field of power system automation, and particularly relates to a power system transient stability simulation parallel computing method based on a nested diagonal edge adding form.
Background
The transient stability time domain simulation of the power system is an important tool for analyzing the power system, and is widely applied to the research and engineering fields of the power industry. With the continuous increase of the network scale, the internal elements become more and more complex, the calculation amount thereof grows obviously, and the calculation is very time-consuming. The parallel computation can obviously improve the computation speed of transient stability simulation. For many years, researchers have made many efforts in parallel transient stability simulation of power systems.
The transient stability simulation of the power system needs to solve a group of high-dimensional nonlinear differential-algebraic equations, and the parallel method can be mainly divided into three types, namely a space parallel method, a time parallel method and a time-space parallel method. The space parallel method transforms or divides the differential algebra equation set and solves the differential algebra equation set in parallel. The spatially parallel method can be classified into coarse grain and fine grain. The coarse grain space parallel method aims at the block parallel solution of an equation set. The fine-grain spatial parallel method focuses on the element operation of the matrix. The time parallel method solves a plurality of simulation product steps at the same time. The time-space parallel method integrates the characteristics of space parallel and time parallel.
The BBDF method is a space parallel method and is widely applied to the field of parallel transient stability simulation of power systems. The power network is highly sparse, the power network can be divided into subsystems and contact systems based on road trees, and the network equation can be constructed in a diagonal edge adding form (BBDF). The BBDF method has a problem that, when the number of concurrences increases, the scale and the amount of calculation of the root system increase, resulting in rapid saturation of the acceleration ratio of the BBDF method.
In order to solve the problem, the leaf system and the root system are solved in parallel by the fully parallel BBDF method, and the limit of 50% of theoretical efficiency of the BBDF method is broken. However, when the root system calculation amount is larger than the maximum leaf system calculation amount, the acceleration ratio of the full-parallel BBDF method is still saturated.
Disclosure of Invention
The invention aims to provide a power system transient stability simulation parallel computing method based on a nested diagonal edge-adding form aiming at the defects of a full-parallel BBDF method.
The invention is realized by the following technical scheme: a power system transient stability simulation parallel computing method based on a nested diagonal edge adding form divides a power network into n leaf systems and 1 contact system based on a factor table road tree. After segmentation, the power network equation will form the following BBDF form:
wherein, diagonal block Y'iiAnd Y'rrRespectively representing node admittance matrixes of a leaf system and a contact system; boundary block Y'irAnd Y'riRepresenting a contact part between the leaf system i and the contact system r; viAnd VrNode voltage vectors of a leaf system and a contact system respectively; i'iAnd l'rThe virtual injection current vectors of the leaf system and the tie system, respectively.
The BBDF structure can be solved by a fully parallel BBDF method, and a flow chart of performing parallel transient stability simulation by the fully parallel BBDF method is shown in fig. 1. The leaf system and the root system are solved in parallel by the fully parallel BBDF method, and the limit of 50% of theoretical efficiency of the BBDF method is broken. However, when the root system calculation amount is larger than the maximum leaf system calculation amount, the acceleration ratio of the full-parallel BBDF method is still saturated.
If the contact system is further decomposed into m branch systems and 1 root system based on the factor table road tree at the moment, the decomposed power network integrally presents a nested BBDF structure of 'leaf-branch-root'. The network equation at this time is as follows:
wherein, diagonal block Y'ii、Y′jj、Y′ccRespectively representing node admittance matrixes of a leaf system, a branch system and a root system; boundary block Y'ijAnd Y'jiRepresenting the link part between the leaf system i and the branch system j; boundary block Y'icAnd Y'ciRepresenting the connection part between the leaf system i and the root system c; boundary block Y'jcAnd Y'cjRepresenting the part of the link between the branch system j and the root system c; vi、Vj、VcRespectively are node voltage vectors of a leaf system, a branch system and a root system; i'i、I′j、I′cRespectively a leaf system, a branch system,Virtual injection current vector of the root system.
After the connection system is decomposed, a branch-root BBDF structural unit formed by the branch system and the root system can be solved by adopting a traditional BBDF method.
The efficient realization of the parallel computation of transient stability simulation requires the establishment of a reasonable subsystem-core mapping and parallel communication topology. The leaf system and the branch system form a leaf-branch BBDF structural unit, the calculation amount of the leaf system and the branch system is generally larger, and the data exchange amount required to be completed is also larger. Therefore, subsystems within a leaf-branch BBDF fabric unit need to be allocated to the CPU cores of the same CPU chip, making full use of the high-speed storage of the third level cache of the CPU chip. When the CPU cores on the same CPU chip are synchronized by OpenMP, the parallel overhead is small. When the CPU cores on different CPU chips are synchronized by MPI, the parallel overhead is small, and the change is not large along with the increase of the number of the CPU chips. Therefore, parallel communication is performed between the CPU cores of the same CPU chip based on OpenMP, and parallel communication is performed between the CPU cores of different CPU chips based on MPI, so that parallel overhead can be reduced.
The new nested BBDF method provided by the invention is different from the full-parallel BBDF method, and the solving process of the transient stability simulation single product step by step is shown in FIG. 2 and corresponds to the step 2 of the invention. The invention specifically comprises the following steps:
step 1: dividing the power network into a plurality of subsystems and completing subsystem-core mapping, comprising the sub-steps of:
step 1.1: dividing the power network into n leaf systems and 1 contact system based on the factor table road tree, further decomposing the contact system into m branch systems and 1 root system, wherein the m branch systems and the 1 root system form a branch-root BBDF structural unit;
step 1.2: binding the calculation tasks of the leaf system, the branch system and the root system to a CPU core to complete subsystem-core mapping;
step 2: the step-by-step parallel computation of the single simulation product comprises the following sub-steps:
step 2.1: solving differential equations of a leaf system, a branch system and a root system in parallel;
step 2.2: executing fast forward operation of a leaf system and fast backward operation of a branch-root BBDF structural unit in parallel;
step 2.3: performing fast back-generation operation of a leaf system and fast forward-generation operation of a branch-root BBDF structural unit in parallel;
step 2.4: judging whether all the subsystem network equations are converged in parallel, if so, turning to the step 2.5, otherwise, turning to the step 2.2;
step 2.5: calculating the electromagnetic power of dynamic elements in a leaf system, a branch system and a root system in parallel;
step 2.6: and judging whether all the subsystem state variables are converged in parallel, if so, finishing the calculation of the current simulation product step by step, and starting the calculation of the next simulation product step by step, otherwise, turning to the step 2.1.
Further, in step 1.2, subsystem-core mapping is performed according to the following principle: each leaf system is independently distributed with a CPU core, and each branch system is independently distributed with a CPU core; a branch system and all leaf systems connected with the branch system form a leaf-branch BBDF structural unit, and subsystems contained in each leaf-branch BBDF structural unit are distributed to the CPU cores of the same CPU chip; if the CPU core on the same CPU chip is enough, a plurality of leaf-branch BBDF structural units can be distributed, otherwise, different leaf-branch BBDF structural units are distributed to different CPU chips; and fourthly, after the subsystem-core mapping of the leaf system and the branch system is completed, distributing the root system to a certain CPU core bearing the calculation task of the branch system.
Furthermore, parallel communication is performed between the CPU cores of the same CPU chip where the leaf system and the branch system are located based on OpenMP, and parallel communication is performed between the CPU cores of different CPU chips where the branch system and the root system are located based on MPI.
Further, in step 2.2, the fast forward operation of the leaf system and the fast backward operation of the branch-root BBDF structure unit are executed in parallel. The fast predecessor operation of each leaf system includes the following operations: calculating virtual injection current; ② fast calculation of the previous generation. The fast back-substitution operation of the branch-root BBDF structural unit comprises the following operations: calculating virtual injection current by a root system, reading the injection current of all branch systems to the root system, completing fast forward and fast backward operation to obtain the node voltage of the root system, and judging the network equation convergence of the root system; secondly, after the root system statistical calculation is finished, each branch system reads the node voltage of the root system, the fast back substitution calculation is finished to obtain the node voltage of the branch system, and the network equation convergence of the branch system is judged.
Further, step 2.2 to step 2.4 are parallel solving flows of network equations. In step 2.2, if the first iteration of the network equation solution is performed, the fast forward operation of the leaf system and the fast forward operation of the branch system are not performed, and the fast backward operation of the branch-root BBDF structural unit cannot be performed. Therefore, no fast back-substitution operation of the branch-root BBDF fabric unit is performed. All the calculations in step 2.2 can be performed normally, starting with the second iteration of the network equations.
Further, in step 2.3, the fast back-generation operation of the leaf system and the fast forward-generation operation of the branch-root BBDF structural unit are executed in parallel. The fast back-substitution operation of each leaf system comprises the following operations: reading the node voltage of a branch system connected with the leaf system, and finishing quick back substitution operation to obtain the node voltage of the leaf system; and secondly, judging the network equation convergence of the leaf system. The fast predecessor operation of the branch-root BBDF fabric unit comprises the following operations: calculating virtual injection current by each branch system, reading the injection current of all leaf systems connected with the branch system to the branch system, and completing rapid antecedent operation.
The invention has the beneficial effects that: the invention realizes the further decomposition of the contact system in the full parallel BBDF method, solves the decomposed contact system by the traditional BBDF method, reduces the calculation amount of the part needing serial calculation in parallel calculation, essentially enhances the concurrency of the parallel method, introduces the mixed programming of subsystem-core mapping and MPI-OpenMP in parallel, realizes the high-efficiency mapping among network topology, parallel communication topology and CPU chip structure, reduces the parallel overhead, and can obviously improve the acceleration ratio and the efficiency of parallel transient stable simulation.
Drawings
FIG. 1 is a schematic flow diagram of a fully parallel BBDF method;
FIG. 2 is a schematic flow chart of step 2 of the method of the present invention, i.e., solving for one integration step;
FIG. 3 is a graph comparing IEEE-2383 total parallel computing acceleration ratio;
FIG. 4 is a SYS1 graph comparing acceleration ratios for overall parallel computing;
FIG. 5 is a SYS2 graph comparing acceleration ratios for overall parallel computation.
Detailed Description
The invention is described in further detail below with reference to the figures and specific examples.
The invention provides a power system transient stability simulation parallel computing method based on a nested diagonal edge-adding form. The method comprises the following specific steps:
step 1: dividing the power network into a plurality of subsystems and completing subsystem-core mapping, comprising the sub-steps of:
step 1.1: dividing the power network into n leaf systems and 1 contact system based on the factor table road tree, further decomposing the contact system into m branch systems and 1 root system, wherein the m branch systems and the 1 root system form a branch-root BBDF structural unit;
step 1.2: binding the calculation tasks of the leaf system, the branch system and the root system to a CPU core to complete subsystem-core mapping;
step 2: the step-by-step parallel computation of the single simulation product comprises the following sub-steps:
step 2.1: solving differential equations of a leaf system, a branch system and a root system in parallel;
step 2.2: executing fast forward operation of a leaf system and fast backward operation of a branch-root BBDF structural unit in parallel;
step 2.3: performing fast back-generation operation of a leaf system and fast forward-generation operation of a branch-root BBDF structural unit in parallel;
step 2.4: judging whether all the subsystem network equations are converged in parallel, if so, turning to the step 2.5, otherwise, turning to the step 2.2;
step 2.5: calculating the electromagnetic power of dynamic elements in a leaf system, a branch system and a root system in parallel;
step 2.6: and judging whether all the subsystem state variables are converged in parallel, if so, finishing the calculation of the current simulation product step by step, and starting the calculation of the next simulation product step by step, otherwise, turning to the step 2.1.
In step 1.2, subsystem-core mapping is performed according to the following principle: each leaf system is independently distributed with a CPU core, and each branch system is independently distributed with a CPU core; a branch system and all leaf systems connected with the branch system form a leaf-branch BBDF structural unit, and subsystems contained in each leaf-branch BBDF structural unit are distributed to the CPU cores of the same CPU chip; if the CPU core on the same CPU chip is enough, a plurality of leaf-branch BBDF structural units can be distributed, otherwise, different leaf-branch BBDF structural units are distributed to different CPU chips; and fourthly, after the subsystem-core mapping of the leaf system and the branch system is completed, distributing the root system to a certain CPU core bearing the calculation task of the branch system.
The parallel communication between the CPU cores of the same CPU chip where the leaf system and the branch system are located is performed based on OpenMP, and the parallel communication between the CPU cores of different CPU chips where the branch system and the root system are located is performed based on MPI.
In step 2.2, the fast forward operation of the leaf system and the fast backward operation of the branch-root BBDF structural unit are executed in parallel. The fast predecessor operation of each leaf system includes the following operations: calculating virtual injection current; ② fast calculation of the previous generation. The fast back-substitution operation of the branch-root BBDF structural unit comprises the following operations: calculating virtual injection current by a root system, reading the injection current of all branch systems to the root system, completing fast forward and fast backward operation to obtain the node voltage of the root system, and judging the network equation convergence of the root system; secondly, after the root system statistical calculation is finished, each branch system reads the node voltage of the root system, the fast back substitution calculation is finished to obtain the node voltage of the branch system, and the network equation convergence of the branch system is judged.
Step 2.2 to step 2.4 are parallel solving flows of the network equation. In step 2.2, if the first iteration of the network equation solution is performed, the fast forward operation of the leaf system and the fast forward operation of the branch system are not performed, and the fast backward operation of the branch-root BBDF structural unit cannot be performed. Therefore, no fast back-substitution operation of the branch-root BBDF fabric unit is performed. All the calculations in step 2.2 can be performed normally, starting with the second iteration of the network equations.
In step 2.3, the fast back-generation operation of the leaf system and the fast forward-generation operation of the branch-root BBDF structural unit are executed in parallel. The fast back-substitution operation of each leaf system comprises the following operations: reading the node voltage of a branch system connected with the leaf system, and finishing quick back substitution operation to obtain the node voltage of the leaf system; and secondly, judging the network equation convergence of the leaf system. The fast predecessor operation of the branch-root BBDF fabric unit comprises the following operations: calculating virtual injection current by each branch system, reading the injection current of all leaf systems connected with the branch system to the branch system, and completing rapid antecedent operation.
The parallel program is applied in the arithmetic examples with different scales. The example includes a 2383wp system and two actual power systems of different sizes. SYS 1: middle region of china, 13490 nodes; SYS 2: 24886 nodes in a certain region of China. The simulation time is 10s, the simulation step size is 10ms, and the allowable iteration error is 1.0 e-4.
TABLE 1 optimal results obtained by the method of the invention, nested BBDF method and fully parallel BBDF method
2383 the actual acceleration ratio test effects of the system, SYS1 and SYS2 are shown in FIGS. 3, 4 and 5, respectively. Acceleration ratio curves obtained by the method, the nested BBDF method (NBBDF), the full-parallel BBDF method (FBBDF _ OpenMP) written by OpenMP and the full-parallel BBDF method (FBBDF _ MPI) written by MPI are respectively shown in the figure. Table 1 shows the optimal acceleration ratio results obtained for the three test systems. In the diagram, the parallel topology is represented by "number of participating computing chips × number of participating computing cores per chip", for example, 2 × 8 represents that there are 2 CPU chips in total, and 8 CPU cores on each chip participate in parallel computing. In the three test systems, the method disclosed by the invention achieves higher parallel acceleration ratio. 2383 in wp system, when the parallel topology is 2x8, the highest acceleration ratio 6.648 is obtained by the method, which is 25.24% higher than that of the existing method. In the SYS1 system, when the parallel topology is 6x8, the highest acceleration ratio 15.911 is obtained by the method, and the method is improved by 16.39% compared with the existing method. In the SYS2 system, when the parallel topology is 8x8, the highest acceleration ratio 20.781 is obtained by the method, and the improvement is 19.52% compared with the existing method.
Therefore, the method improves the full parallel BBDF method and further improves the acceleration ratio of parallel computation.
One skilled in the art can, using the teachings of the present invention, readily make various changes and modifications to the invention without departing from the spirit and scope of the invention as defined by the appended claims. Any modifications and equivalent variations of the above-described embodiments, which are made in accordance with the technical spirit and substance of the present invention, fall within the scope of protection of the present invention as defined in the claims.
Claims (6)
1. A power system transient stability simulation parallel computing method based on a nested diagonal edge adding form is characterized by comprising the following steps:
step 1: dividing the power network into a plurality of subsystems and completing subsystem-core mapping, comprising the sub-steps of:
step 1.1: dividing the power network into n leaf systems and 1 contact system based on the factor table road tree, further decomposing the contact system into m branch systems and 1 root system, wherein the m branch systems and the 1 root system form a branch-root BBDF structural unit;
step 1.2: binding the calculation tasks of the leaf system, the branch system and the root system to a CPU core to complete subsystem-core mapping;
step 2: the step-by-step parallel computation of single simulation product comprises the following substeps;
step 2.1: solving differential equations of a leaf system, a branch system and a root system in parallel;
step 2.2: executing fast forward operation of a leaf system and fast backward operation of a branch-root BBDF structural unit in parallel;
step 2.3: performing fast back-generation operation of a leaf system and fast forward-generation operation of a branch-root BBDF structural unit in parallel;
step 2.4: judging whether all the subsystem network equations are converged in parallel, if so, turning to the step 2.5, otherwise, turning to the step 2.2;
step 2.5: calculating the electromagnetic power of dynamic elements in a leaf system, a branch system and a root system in parallel;
step 2.6: and judging whether all the subsystem state variables are converged in parallel, if so, finishing the calculation of the current simulation product step by step, and starting the calculation of the next simulation product step by step, otherwise, turning to the step 2.1.
2. The method for parallel computation of transient stability simulation of power system based on nested diagonal edge-adding form of claim 1, wherein in step 1.2, subsystem-core mapping is performed according to the following principle: each leaf system is independently distributed with a CPU core, and each branch system is independently distributed with a CPU core; a branch system and all leaf systems connected with the branch system form a leaf-branch BBDF structural unit, and subsystems contained in each leaf-branch BBDF structural unit are distributed to the CPU cores of the same CPU chip; if the CPU core on the same CPU chip is enough, a plurality of leaf-branch BBDF structural units can be distributed, otherwise, different leaf-branch BBDF structural units are distributed to different CPU chips; and fourthly, after the subsystem-core mapping of the leaf system and the branch system is completed, distributing the root system to a certain CPU core bearing the calculation task of the branch system.
3. The electric power system transient stability simulation parallel computing method based on the nested diagonal edge-adding form of claim 1, characterized in that the parallel communication between the CPU cores of the same CPU chip where the leaf system and the branch system are located is performed based on OpenMP, and the parallel communication between the CPU cores of different CPU chips where the branch system and the root system are located is performed based on MPI.
4. The electric power system transient stability simulation parallel computing method based on the nested diagonal edge-adding form of claim 1, characterized in that in the step 2.2, fast forward operation of a leaf system and fast backward operation of a branch-root BBDF structural unit are executed in parallel; the fast predecessor operation of each leaf system includes the following operations: calculating virtual injection current; fast arithmetic of the first generation; the fast back-substitution operation of the branch-root BBDF structural unit comprises the following operations: calculating virtual injection current by a root system, reading the injection current of all branch systems to the root system, completing fast forward and fast backward operation to obtain the node voltage of the root system, and judging the network equation convergence of the root system; secondly, after the root system statistical calculation is finished, each branch system reads the node voltage of the root system, the fast back substitution calculation is finished to obtain the node voltage of the branch system, and the network equation convergence of the branch system is judged.
5. The electric power system transient stability simulation parallel computing method based on the nested diagonal edge-added form according to claim 1, wherein the steps 2.2 to 2.4 are parallel solving flows of network equations; in the step 2.2, if the iteration is the first iteration of the network equation solution, the fast back-substitution operation of the branch-root BBDF structural unit is not executed.
6. The electric power system transient stability simulation parallel computing method based on the nested diagonal edge-adding form of claim 1, characterized in that in the step 2.3, fast back-generation operation of a leaf system and fast forward-generation operation of a branch-root BBDF structural unit are executed in parallel; the fast back-substitution operation of each leaf system comprises the following operations: reading the node voltage of a branch system connected with the leaf system, and finishing quick back substitution operation to obtain the node voltage of the leaf system; judging the network equation convergence of the leaf system; the fast predecessor operation of the branch-root BBDF fabric unit comprises the following operations: calculating virtual injection current by each branch system, reading the injection current of all leaf systems connected with the branch system to the branch system, and completing rapid antecedent operation.
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Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101169743A (en) * | 2007-11-27 | 2008-04-30 | 南京大学 | Method for implementing parallel power flow calculation based on multi-core computer in electric grid |
| US8010572B1 (en) * | 2003-09-19 | 2011-08-30 | Unisys Corporation | Kstore scenario simulator processor and XML file |
| CN105448154A (en) * | 2015-09-21 | 2016-03-30 | 中国南方电网有限责任公司 | Integrated-platform-based substation operation training cabin |
| CN107069696A (en) * | 2016-09-23 | 2017-08-18 | 四川大学 | A kind of parallel calculating method of Power system state estimation |
| US10235341B2 (en) * | 2014-06-12 | 2019-03-19 | Tianjin University | Method for solving the decomposition-coordination calculation based on block bordered diagonal form (BBDF) model using data center |
| CN109522630A (en) * | 2018-11-05 | 2019-03-26 | 浙江大学 | A kind of electric power system transient stability emulation parallel calculating method based on diagonal edged form |
| CN110489798A (en) * | 2019-07-18 | 2019-11-22 | 天津大学 | Solver fine granularity efficient design method towards active power distribution network real-time simulation |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US10169571B1 (en) * | 2012-07-18 | 2019-01-01 | Sequitur Labs, Inc. | System and method for secure, policy-based access control for mobile computing devices |
-
2019
- 2019-11-29 CN CN201911201938.9A patent/CN110968953B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US8010572B1 (en) * | 2003-09-19 | 2011-08-30 | Unisys Corporation | Kstore scenario simulator processor and XML file |
| CN101169743A (en) * | 2007-11-27 | 2008-04-30 | 南京大学 | Method for implementing parallel power flow calculation based on multi-core computer in electric grid |
| US10235341B2 (en) * | 2014-06-12 | 2019-03-19 | Tianjin University | Method for solving the decomposition-coordination calculation based on block bordered diagonal form (BBDF) model using data center |
| CN105448154A (en) * | 2015-09-21 | 2016-03-30 | 中国南方电网有限责任公司 | Integrated-platform-based substation operation training cabin |
| CN107069696A (en) * | 2016-09-23 | 2017-08-18 | 四川大学 | A kind of parallel calculating method of Power system state estimation |
| CN109522630A (en) * | 2018-11-05 | 2019-03-26 | 浙江大学 | A kind of electric power system transient stability emulation parallel calculating method based on diagonal edged form |
| CN110489798A (en) * | 2019-07-18 | 2019-11-22 | 天津大学 | Solver fine granularity efficient design method towards active power distribution network real-time simulation |
Non-Patent Citations (3)
| Title |
|---|
| A New Fully Parallel BBDF Method in Transient Stability Simulations;Tannan Xiao等;《IEEE Journals & Magazine》;20190814;全文 * |
| Study on Reducing the Parallel Overhead of the BBDF Method for Power System Transient Stability Simulations;Xiao Tannan等;《IEEE Transactions on Power Systems》;20190718;第1-11页 * |
| 大规模交直流电网暂态稳定混合仿真与并行计算;童伟林;《中国优秀硕士学位论文全文数据库 工程科技Ⅱ辑》;20190815;第24-27页 * |
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