Title
Analytics-Based Optimization For Smart Grid Operations
Keywords
analytics; data; modeling; optimization; reactive power; smart grid; statistics
Abstract
Considering near-real-time data available on the smart grid, analytics can be used to determine the best-case scenario for optimal and reliable distribution of power. However, the distributed integration of renewable sources and demand response adds complexity to the modeling, control and optimization of smart grid operations. Latest concepts aim for using new model-based computational intelligence; that requires a combination of capabilities for system optimization, stochastic power flow, system state prediction, and solution checking. The statistical model-based optimization for developing dynamic, stochastic, computationally efficient, and scalable platforms is intended in this paper. Furthermore, an analytics-based optimization is proposed to the optimal reactive power dispatch considering load variations. This illustration uses analytics obtained from empirical modeling of recorded load data.
Publication Date
11-13-2014
Publication Title
Proceedings - 2014 IEEE International Workshop on Intelligent Energy Systems, IWIES 2014
Number of Pages
58-63
Document Type
Article; Proceedings Paper
Personal Identifier
scopus
DOI Link
https://doi.org/10.1109/IWIES.2014.6957047
Copyright Status
Unknown
Socpus ID
84916624051 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/84916624051
STARS Citation
Haghi, H. Valizadeh; Qu, Zhihua; and Lotfifard, S., "Analytics-Based Optimization For Smart Grid Operations" (2014). Scopus Export 2010-2014. 8262.
https://stars.library.ucf.edu/scopus2010/8262