Title
Online Rolling Evolutionary Decoder-Dispatch Framework for the Secondary Frequency Regulation of Time-Varying Electrical-Grid-Electric-Vehicle System
Abstract
The widespread integration of electric vehicles (EVs) into the electrical grid creates a new opportunity for frequency regulation. In this article, to deal with the penetration of intermittent renewable energy and the time variance of system model, an online evolutionary mechanism is developed for the electrical-grid- electric-vehicle system. With a real-time decoder consisting of the long-short-term memory (LSTM) array, the dispatch center is upgraded from a passive executor to an intelligent analyst, which extracts the rolling features from multiple time scales. Based on the high-dimension decoding information from the LSTM array, a deep neural network (DNN) array is then embedded to provide strategic dispatch commands learning from the evolving memory. The whole decoder-dispatch framework is then upgraded with a unified online adaption technique to achieve gradient optimization and weight evolution. The proposed evolutionary structure is validated on a frequency management system to demonstrate its superior performance.
Year
DOI
Venue
2021
10.1109/TSG.2020.3020983
IEEE Transactions on Smart Grid
Keywords
DocType
Volume
Online dispatch algorithm,long-short-term memory-deep neural network (LSTM-DNN) array,electric vehicles,electrical grid
Journal
12
Issue
ISSN
Citations 
1
1949-3053
1
PageRank 
References 
Authors
0.35
0
5
Name
Order
Citations
PageRank
Chaoyu Dong110.35
Ronghe Chu210.35
Thomas Morstyn3122.28
M. D. McCulloch42310.72
Hongjie Jia572.86