Long short term memory networks for short-term electric load forecasting

A Narayan, KW Hipel - 2017 IEEE International Conference on …, 2017 - ieeexplore.ieee.org
Short-term electricity demand forecasting is critical to utility companies. It plays a key role in
the operation of power industry. It becomes all the more important and critical with …

Two-stage artificial neural network model for short-term load forecasting

YY Hsu, TT Tung, HC Yeh, CN Lu - IFAC-PapersOnLine, 2018 - Elsevier
Short-term load forecast (STLF) is important to ensure stable, reliable and efficient power
system operations. In this paper, we propose a two-stage artificial neural network (ANN) …

Recurrent Neural Network Based Short-Term Load Forecast with Spline Bases and Real-Time Adaptation

TL Yuan, DS Jiang, SY Huang, YY Hsu, HC Yeh… - Applied Sciences, 2021 - mdpi.com
Short-term load forecast (STLF) plays an important role in power system operations. This
paper proposes a spline bases-assisted Recurrent Neural Network (RNN) for STLF with a …

Market value of differentially-private smart meter data

S Chhachhi, F Teng - 2021 IEEE Power & Energy Society …, 2021 - ieeexplore.ieee.org
This paper proposes a framework to investigate the value of sharing privacy-protected smart
meter data between domestic consumers and load serving entities. The framework consists …

Fast scenario reduction for power systems by deep learning

Q Li, DW Gao - arXiv preprint arXiv:1908.11486, 2019 - arxiv.org
Scenario reduction is an important topic in stochastic programming problems. Due to the
random behavior of load and renewable energy, stochastic programming becomes a useful …

Adaptive Supervisory Framework for Cyber-Physical Systems-Optimal Scheduling of Smart Home Appliances

JPBGP Leitão - 2021 - search.proquest.com
Throughout the 21 st century, technology has advanced at exponential speed, spreading
into our daily routines and becoming critical in almost any everyday life domain. The …