scholarly journals Factorisation Path Based Refactorisation for High-Performance LU Decomposition in Real-Time Power System Simulation

Energies ◽  
2021 ◽  
Vol 14 (23) ◽  
pp. 7989
Author(s):  
Jan Dinkelbach ◽  
Lennart Schumacher ◽  
Lukas Razik ◽  
Andrea Benigni ◽  
Antonello Monti
Keyword(s):  
Power Systems ◽  
Real Time ◽  
Decomposition Method ◽  
High Performance ◽  
Computation Time ◽  
Lu Decomposition ◽  
Nonlinear Component ◽  
Time Requirements ◽  
Component Models ◽  
Real Time Simulations

The integration of renewable energy sources into modern power systems requires simulations with smaller step sizes, larger network models and the incorporation of complex nonlinear component models. These features make it more difficult to meet computation time requirements in real-time simulations and have motivated the development of high-performance LU decomposition methods. Since nonlinear component models cause numerical variations in the system matrix between simulation steps, this paper places a particular focus on the recomputation of LU decomposition, i.e., on the refactorisation step. The main contribution is the adoption of a factorisation path algorithm for partial refactorisation, which takes into account that only a subset of matrix entries change their values. The approach is integrated into the modern LU decomposition method NICSLU and benchmarked against the methods SuperLU and KLU. A performance analysis was carried out considering benchmark as well as real power systems. The results show the significant speedup of refactorisation computation times in use cases involving system matrices of different sizes, a variety of sparsity patterns and different ratios of numerically varying matrix entries. Consequently, the presented high-performance LU decomposition method can assist in meeting computation time requirements in real-time simulations of modern power systems.

scholarly journals HiBuffer: Buffer Analysis of 10-Million-Scale Spatial Data in Real Time

2018 ◽  
Vol 7 (12) ◽  
pp. 467 ◽  
Author(s):  
Mengyu Ma ◽  
Ye Wu ◽  
Wenze Luo ◽  
Luo Chen ◽  
Jun Li ◽  
...  
Keyword(s):  
Real Time ◽  
Spatial Data ◽  
High Performance ◽  
Large Scale ◽  
Computation Time ◽  
Buffer Analysis ◽  
Data Volume ◽  
Time Buffer ◽  
Real World Datasets ◽  
Spatial Indexes

Buffer analysis, a fundamental function in a geographic information system (GIS), identifies areas by the surrounding geographic features within a given distance. Real-time buffer analysis for large-scale spatial data remains a challenging problem since the computational scales of conventional data-oriented methods expand rapidly with increasing data volume. In this paper, we introduce HiBuffer, a visualization-oriented model for real-time buffer analysis. An efficient buffer generation method is proposed which introduces spatial indexes and a corresponding query strategy. Buffer results are organized into a tile-pyramid structure to enable stepless zooming. Moreover, a fully optimized hybrid parallel processing architecture is proposed for the real-time buffer analysis of large-scale spatial data. Experiments using real-world datasets show that our approach can reduce computation time by up to several orders of magnitude while preserving superior visualization effects. Additional experiments were conducted to analyze the influence of spatial data density, buffer radius, and request rate on HiBuffer performance, and the results demonstrate the adaptability and stability of HiBuffer. The parallel scalability of HiBuffer was also tested, showing that HiBuffer achieves high performance of parallel acceleration. Experimental results verify that HiBuffer is capable of handling 10-million-scale data.

scholarly journals A Parallel Implementation of Unscheduled Flow Control in Interconnected Power Systems

2012 ◽  
Vol 2012 ◽  
pp. 1-19
Author(s):  
G. Ozdemir Dag ◽  
Mustafa Bagriyanik
Keyword(s):  
Power Systems ◽  
Power System ◽  
Parallel Computation ◽  
High Performance ◽  
Power Flow ◽  
Parallel Implementation ◽  
Computation Time ◽  
Test System ◽  
Fuzzy Decision Making ◽  
Optimization Approach

The unscheduled power flow problem needs to be minimized or controlled as soon as possible in a deregulated power system since the transmission systems are mostly operated at their power-carrying limits or very close to it. The time spent for simulations to determine the current states of all the system and control variables of the interconnected power system is important. Taking necessary action in case of any failure of equipment or any other occurrence of an undesired situation could be critical. Using supercomputing facilities and parallel computing techniques together decreases the computation time greatly. In this study, a parallel implementation of a multiobjective optimization approach based on both genetic algorithms and fuzzy decision making to manage unscheduled flows is presented. Parallel computation techniques are applied using supercomputers (high-performance computers). The proposed method is applied to the IEEE 300 bus test system. Two different cases for some parameters of GA are considered to see the power of parallel computation technique. Then the simulation results are presented.

scholarly journals Review on Real Time Background Extraction: Models, Applications, Environments, Challenges and Evaluation Approaches

2021 ◽  
Vol 17 (02) ◽  
pp. 37
Author(s):  
Maryam A. Yasir ◽  
Yossra Hussain Ali
Keyword(s):  
Real Time ◽  
High Performance ◽  
Performance Metrics ◽  
Computation Time ◽  
Background Extraction ◽  
Accurate Performance ◽  
Real Time Applications ◽  
Conventional Models ◽  
Evaluation Approaches ◽  
Extraction Model

<p>In the computer vision, background extraction is a promising technique. It is characterized by being applied in many different real time applications in diverse environments and with variety of challenges. Background extraction is the most popular technique employed in the domain of detecting moving foreground objects taken by stationary surveillance cameras. Achieving high performance is required with many perspectives and demands. Choosing the suitable background extraction model plays the major role in affecting the performance matrices of time, memory, and accuracy.</p><p>In this article we present an extensive review on background extraction in which we attempt to cover all the related topics. We list the four process stages of background extraction and we consider several well-known models starting with the conventional models and ending up with the state-of-the art models. This review also focuses on the model environments whether it is human activities, Nature or sport environments and illuminates on some of the real time applications where background extraction method is adopted. Many challenges are addressed in respect to environment, camera, foreground objects, background, and computation time. </p><p>In addition, this article provides handy tables containing different common datasets and libraries used in the field of background extraction experiments. Eventually, we illustrate the performance evaluation with a table of the set performance metrics to measure the robustness of the background extraction model against other models in terms of time, accurate performance and required memory.</p>

scholarly journals Implementation of SoC Based Real-Time Electromagnetic Transient Simulator

2017 ◽  
Vol 2017 ◽  
pp. 1-14 ◽  
Author(s):  
I. Herrera-Leandro ◽  
P. Moreno-Villalobos ◽  
S. Ortega-Cisneros ◽  
Jorge Rivera ◽  
F. Sandoval-Ibarra
Keyword(s):  
Power Systems ◽  
Real Time ◽  
High Performance ◽  
Design Stage ◽  
Solution Flow ◽  
Embedded Processor ◽  
Electromagnetic Transient ◽  
Protection Systems ◽  
Balanced Distribution ◽  
Two Sides

Real-time electromagnetic transient simulators are important tools in the design stage of new control and protection systems for power systems. Real-time simulators are used to test and stress new devices under similar conditions that the device will deal with in a real network with the purpose of finding errors and bugs in the design. The computation of an electromagnetic transient is complex and computationally demanding, due to features such as the speed of the phenomenon, the size of the network, and the presence of time variant and nonlinear elements in the network. In this work, the development of a SoC based real-time and also offline electromagnetic transient simulator is presented. In the design, the required performance is met from two sides, (a) using a technique to split the power system into smaller subsystems, which allows parallelizing the algorithm, and (b) with specialized and parallel hardware designed to boost the solution flow. The results of this work have shown that for the proposed case studies, based on a balanced distribution of the node of subsystems, the proposed approach has decreased the total simulation time by up to 99 times compared with the classical approach running on a single high performance 32-bit embedded processor ARM-Cortex A9.

scholarly journals Mathematical Modeling of the Dynamics of Linear Electrical Systems with Parallel Calculations

Energies ◽  
2021 ◽  
Vol 14 (10) ◽  
pp. 2930
Author(s):  
Sławomir Cieślik
Keyword(s):  
Mathematical Modeling ◽  
Power Systems ◽  
Real Time ◽  
Integration Time ◽  
Integration Step ◽  
Time Step ◽  
Parallel Calculations ◽  
Electrical Systems ◽  
Backward Euler ◽  
Real Time Simulations

The dynamics of power systems is often analyzed using real-time simulators. The basic requirements of these simulators are the speed of obtaining the results and their accuracy. Known algorithms (backward Euler or trapezoidal rule) used in real-time simulations force the integration time step to be reduced to obtain the appropriate accuracy, which extends the time of obtaining the results. The acceleration of obtaining the results is achieved by using parallel calculations. The paper presents an algorithm for mathematical modeling of the dynamics of linear electrical systems, which works stably with a relatively large integration time step and with accuracy much better than other algorithms widely described in the literature. The algorithm takes into account the possibility of using parallel calculations. The proposed algorithm combines the advantages of known methods used in the analysis of electrical circuits, such as nodal analysis, multi-terminal electrical component theory, and transient states analysis methods. However, the main advantage over other algorithms is the use of the method based on average voltages in the integration step (AVIS method). The attention was focused on the presentation of the scientifically acceptable general principle offered to mathematical modeling of dynamics of linear electrical systems with parallel computations. However, the evidence of its effective application in the analysis of the dynamics of electric power and electromechanical systems was indicated in the works carried out by the team of authors from the Institute of Electrical Engineering UTP University of Science and Technology in Bydgoszcz (Poland).

The Weld Image Acquisition and Preprocessing Based on FPGA

2013 ◽  
Vol 401-403 ◽  
pp. 1507-1513 ◽  
Author(s):  
Zhong Hu Yuan ◽  
Wen Tao Liu ◽  
Xiao Wei Han
Keyword(s):  
Image Processing ◽  
Real Time ◽  
High Speed ◽  
High Performance ◽  
Image Acquisition ◽  
Processing System ◽  
Large Data ◽  
Seam Tracking ◽  
Image Processing System ◽  
Time Requirements

In the weld image acquisition system, real-time image processing has been a difficult design bottleneck to break through, especially for the occasion of large data processing capability and more demanding real-time requirements, in which the traditional MCU can not adapt, so using high-performance FPGA as the core of the high speed image acquisition and processing card, better meets the large amount of data in most of the image processing system and high demanding real-time requirements. At the same time, system data collection, storage and display were implemented by using Verilog, and in order to reducing the influence of edge detection noise, the combination of image enhancement and median filtering image preprocessing algorithm was used. Compared to the pre-processing algorithm of the software implementation, it has a great speed advantage, and simplifies the subsequent processing work load, improves the speed and efficiency of the entire image processing system greatly. So it proves that the system has strong ability of restraining the noise of image, and more accurate extracted edge positioning, it can be applied in the seam tracking field which need higher real-time requirements.

scholarly journals Parallel Multiphysics Simulation of Package Systems Using an Efficient Domain Decomposition Method

Electronics ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 158
Author(s):  
Weijie Wang ◽  
Yannan Liu ◽  
Zhenguo Zhao ◽  
Haijing Zhou
Keyword(s):  
Domain Decomposition ◽  
Antenna Arrays ◽  
Electromagnetic Interference ◽  
Decomposition Method ◽  
High Performance ◽  
Large Scale ◽  
Electromagnetic Compatibility ◽  
Domain Decomposition Method ◽  
Computation Time ◽  
Multiphysics Simulations

With the continuing downscaling in feature sizes, the thermal impact on material properties and geometrical deformations can no longer be ignored in the analysis of the electromagnetic compatibility or electromagnetic interference of package systems, including System-in-Package and antenna arrays. We present a high-performance numerical simulation program that is intended to perform large-scale multiphysics simulations using the finite element method. An efficient domain decomposition method was developed to accelerate the multiphysics loops of electromagnetic–thermal stress simulations by considering the fact that the electromagnetic field perturbations caused by geometrical deformation are small and constrained in one or a few subdomains. The multi-level parallelism of the algorithm was also obtained based on an in-house developed parallel infrastructure. Numerical examples showed that our algorithm is able to enable simulation with multiple processors in parallel and, more importantly, achieve a significant reduction in computation time compared with traditional methods.

scholarly journals Risk-Based and Hydrodynamic Pluvial Flood Forecasts in Real Time

Water ◽  
2020 ◽  
Vol 12 (7) ◽  
pp. 1895
Author(s):  
Julian Hofmann ◽  
Holger Schüttrumpf
Keyword(s):  
Real Time ◽  
Flood Risk ◽  
High Efficiency ◽  
Computation Time ◽  
Warning Systems ◽  
Hydrodynamic Models ◽  
Model Concept ◽  
Urban Flood ◽  
Real Time Simulations ◽  
The City

The effective forecast and warning of pluvial flooding in real time is one of the key elements and remaining challenges of an integrated urban flood risk management. This paper presents a new methodology for integrating risk-based solutions and 2D hydrodynamic models into the early warning process. Whereas existing hydrodynamic forecasting methods are based on rigid systems with extremely high computational demands, the proposed framework builds on a multi-model concept allowing the use of standard computer systems. As a key component, a pluvial flood alarm operator (PFA-Operator) is developed for selecting and controlling affected urban subcatchment models. By distributed computing of hydrologic independent models, the framework overcomes the issue of high computational times of hydrodynamic simulations. The PFA-Operator issues warnings and flood forecasts based on a two-step process: (1) impact-based rainfall thresholds for flood hotspots and (2) hydrodynamic real-time simulations of affected urban subcatchments models. Based on the open-source development software Qt, the system can be equipped with interchangeable modules and hydrodynamic software while building on the preliminary results of flood risk analysis. The framework was tested using a historic pluvial flood event in the city of Aachen, Germany. Results indicate the high efficiency and adaptability of the proposed system for operational warning systems in terms of both accuracy and computation time.

scholarly journals EOBAA: Enhanced Ontology Based Alignment Algorithm for Mining Frequent Patterns

2018 ◽  
Vol 7 (3.12) ◽  
pp. 157
Author(s):  
D Srinivasa Rao ◽  
V Sucharitha ◽  
K V.V Satyanarayana
Keyword(s):  
Real Time ◽  
High Performance ◽  
Computation Time ◽  
Search Space ◽  
Search Tree ◽  
Frequent Itemsets ◽  
Alignment Algorithm ◽  
Frequent Patterns ◽  
Pruning Strategy ◽  
Real Time Applications

Mining frequent patterns are most widely used in many applications such as supermarkets, diagnostics, and other real-time applications. Performance of the algorithm is calculated based on the computation of the algorithm. It is very tedious to compute the frequent patterns in mining. Many algorithms and techniques are implemented and studied to generate the high-performance algorithms such as Prepost+ which employees the N-list to represent itemsets and directly discovers frequent itemsets using a set-enumeration search tree. But due to its pruning strategy, it is known that the computation time is more for processing the search space. It enumerates all item sets from datasets by the principle of exhaustion and they don’t sort them based on utility, but only a statistical proof of most recurring itemset. In this paper, the proposed Enhanced Ontologies based Alignment Algorithm (EOBAA) to identify, extract, sort out the HUI's from FI's. To improve the similarity measure the proposed system adopted Cosine similarity. The experiments conducted on 1 real datasets and show the performance of the EOBAA based on the computation time and accuracy of the proposed EOBAA.  

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