The impact of the COVID-19 on households' hourly electricity consumption in Canada
The spread of the COVID-19 pandemic caused a tremendous impact on our societies,
including changes in household energy consumption. Using measured electricity use data …
including changes in household energy consumption. Using measured electricity use data …
Sequential learning-based energy consumption prediction model for residential and commercial sectors
The use of electrical energy is directly proportional to the increase in global population, both
concerning growing industrialization and rising residential demand. The need to achieve a …
concerning growing industrialization and rising residential demand. The need to achieve a …
Unlocking emerging impacts of carbon tax on integrated energy systems through supply and demand co-optimization
Integrated energy systems (IES) can help achieve greater energy efficiency, and then
ultimately promote a climate-neutral economy by utilizing local renewable resources …
ultimately promote a climate-neutral economy by utilizing local renewable resources …
A novel forecasting strategy for improving the performance of deep learning models
IE Livieris - Expert Systems with Applications, 2023 - Elsevier
In this research, a new strategy is introduced for the development of robust, efficient and
reliable deep learning time-series models, which is based on a sophisticated algorithmic …
reliable deep learning time-series models, which is based on a sophisticated algorithmic …
Knowledge Extraction from PV Power Generation with Deep Learning Autoencoder and Clustering-Based Algorithms
The unpredictable nature of photovoltaic solar power generation, caused by changing
weather conditions, creates challenges for grid operators as they work to balance supply …
weather conditions, creates challenges for grid operators as they work to balance supply …
K-PCD: A new clustering algorithm for building energy consumption time series analysis and predicting model accuracy improvement
Clustering algorithms are often applied to building energy consumption data analysis to
mine representative patterns of building energy usage. This paper proposes a new …
mine representative patterns of building energy usage. This paper proposes a new …
Phase change with inner ventilation for energy management: Roofs buildings in hot & dry climates case
Demand for cooling in hot and dry climactic regions of the world is expected to increase
rapidly, while the cost of cooling relative to household incomes and the associated …
rapidly, while the cost of cooling relative to household incomes and the associated …
[HTML][HTML] An unsupervised learning schema for seeking patterns in rms voltage variations at the sub-10-minute time scale
This paper proposes an unsupervised learning schema for seeking the patterns in rms
voltage variations at the time scale between 1 s and 10 min, a rarely considered time scale …
voltage variations at the time scale between 1 s and 10 min, a rarely considered time scale …
[HTML][HTML] A holistic time series-based energy benchmarking framework for applications in large stocks of buildings
With the proliferation of Internet of Things (IoT) sensors and metering infrastructures in
buildings, external energy benchmarking, driven by time series analytics, has assumed a …
buildings, external energy benchmarking, driven by time series analytics, has assumed a …
[HTML][HTML] Seeking patterns in rms voltage variations at the sub-10-minute scale from multiple locations via unsupervised learning and patterns' post-processing
This paper addresses the issue of seeking sub-10-min patterns in fast rms voltage variations
from time-limited measurement data at multiple locations worldwide. This is a rarely …
from time-limited measurement data at multiple locations worldwide. This is a rarely …