Comparative study of clustering techniques for real‐time dynamic model reduction

Purvine, Emilie; Cotilla‐Sanchez, Eduardo; Halappanavar, Mahantesh; Huang, Zhenyu; Lin, Guang; Lu, Shuai; Wang, Shaobu

doi:10.1002/sam.11352

Cited by 7 publications

(5 citation statements)

References 33 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Clustering and model reduction techniques will continue to allow the application of these advanced analyses with computationally tractable grid equivalents. At the same time, the breadth of objectives on planning, operational, and environmental procedures will be thoughtfully applied to a unique system with the use of multi-scale, multi-objective methodologies [175][176][177].…”

Section: Probabilistic Planning and Operation Methodsmentioning

confidence: 99%

Resilience in an Evolving Electrical Grid

et al. 2021

View full text Add to dashboard Cite

Fundamental shifts in the structure and generation profile of electrical grids are occurring amidst increased demand for resilience. These two simultaneous trends create the need for new planning and operational practices for modern grids that account for the compounding uncertainties inherent in both resilience assessment and increasing contribution of variable inverter-based renewable energy sources. This work reviews the research work addressing the changing generation profile, state-of-the-art practices to address resilience, and research works at the intersection of these two topics in regards to electrical grids. The contribution of this work is to highlight the ongoing research in power system resilience and integration of variable inverter-based renewable energy sources in electrical grids, and to identify areas of current and further study at this intersection. Areas of research identified at this intersection include cyber-physical analysis of solar, wind, and distributed energy resources, microgrids, network evolution and observability, substation automation and self-healing, and probabilistic planning and operation methods.

show abstract

Section: Probabilistic Planning and Operation Methodsmentioning

confidence: 99%

Resilience in an Evolving Electrical Grid

et al. 2021

View full text Add to dashboard Cite

show abstract

“…The ExaGraph team has also worked on the application of community detection for model reduction in the context of electric power grid domain (Purvine et al, 2017), and more recently for the purpose of fast and efficient ordering of vertices in graphs for efficient execution on hierarchical memory systems (Barik et al, 2020).…”

Section: Combinatorial Approaches For Graph Algorithmsmentioning

confidence: 99%

EXAGRAPH: Graph and combinatorial methods for enabling exascale applications

Acer

Azad

Boman

et al. 2021

The International Journal of High Performance Computing Applica

Self Cite

View full text Add to dashboard Cite

Combinatorial algorithms in general and graph algorithms in particular play a critical enabling role in numerous scientific applications. However, the irregular memory access nature of these algorithms makes them one of the hardest algorithmic kernels to implement on parallel systems. With tens of billions of hardware threads and deep memory hierarchies, the exascale computing systems in particular pose extreme challenges in scaling graph algorithms. The codesign center on combinatorial algorithms, ExaGraph, was established to design and develop methods and techniques for efficient implementation of key combinatorial (graph) algorithms chosen from a diverse set of exascale applications. Algebraic and combinatorial methods have a complementary role in the advancement of computational science and engineering, including playing an enabling role on each other. In this paper, we survey the algorithmic and software development activities performed under the auspices of ExaGraph from both a combinatorial and an algebraic perspective. In particular, we detail our recent efforts in porting the algorithms to manycore accelerator (GPU) architectures. We also provide a brief survey of the applications that have benefited from the scalable implementations of different combinatorial algorithms to enable scientific discovery at scale. We believe that several applications will benefit from the algorithmic and software tools developed by the ExaGraph team.

show abstract

“…The separation from the negative ideal solution: Association Rules: Various data mining techniques have been proposed to identify interesting patterns in large transactional databases [4,6,15,28,30,[38][39][40]. In this study, we applied the Apriori Algorithm data mining technique to extract association rules among attributes from our vision examination database.…”

Section: Ideal Solutionmentioning

confidence: 99%

Association Analysis of Scoliosis Based on Backpack Carrying Methods and Head Positions of Elementary School Students

Hsu

Lai

Huang

et al. 2019

BJSTR

View full text Add to dashboard Cite

To prevent scoliosis development at early stage of growth in elementary school students, we assessed how body posture-namely the school bag carrying method and head position-can affect the morphology of the spinal column. We applied various data mining techniques and multicriteria decision-making to compare the important attributes of scoliosis, in addition to using entropy and principal component analysis to identify the relationship between scoliosis and the various examined attributes. Decision trees were constructed to classify the scoliosis condition of students based on their school bag carrying method, visual acuity, and head position. Association rules were then discovered to represent the associations among different attributes in the database. In this paper, we present several findings, including that the apex of the scoliosis curve in elementary school students is highly dependent on the side on which they carry their backpack, head position, ocular height, and pupil distance. Our analysis results indicate that scoliosis also affects students' visions. The findings of this study provide a new perspective on the treatment of scoliosis in elementary school students at an early stage and preventing the condition from worsening later on in their development.

show abstract

Comparative study of clustering techniques for real‐time dynamic model reduction

Cited by 7 publications

References 33 publications

Resilience in an Evolving Electrical Grid

Resilience in an Evolving Electrical Grid

EXAGRAPH: Graph and combinatorial methods for enabling exascale applications

Association Analysis of Scoliosis Based on Backpack Carrying Methods and Head Positions of Elementary School Students

Contact Info

Product

Resources

About