Data Mining in Smart Grids

Effective smart grid operation requires rapid decisions in a data-rich, but information-limited, environment. In this context, grid sensor data-streaming cannot provide the system operators with the necessary information to act on in the time frames necessary to minimize the impact of the disturbanc...

Full description

Saved in:

Bibliographic Details
Other Authors:	Vaccaro, Alfredo (Editor)
Format:	Book Chapter
Published:	Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute 2020
Subjects:	Information technology industries voltage regulation smart grid decentralized control architecture multi-agent systems t-SNE algorithm numerical weather prediction data preprocessing data visualization wind power generation partial discharge gas insulated switchgear case-based reasoning data matching variational autoencoder DSHW TBATS NN-AR time-series clustering decentral smart grid control (DSGC) interpretable and accurate DSGC-stability prediction data mining computational intelligence fuzzy rule-based classifiers multi-objective evolutionary optimization power systems resilience dynamic Bayesian network Markov model probabilistic modeling resilience models
Online Access:	Get Fullteks DOAB: description of the publication
Tags:	Add Tag No Tags, Be the first to tag this record!

Be the first to leave a comment!

Data Mining in Smart Grids

Similar Items