[HTML][HTML] Data analytics in the electricity sector–A quantitative and qualitative literature review
The rapid transformation of the electricity sector increases both the opportunities and the
need for Data Analytics. In recent years, various new methods and fields of application have …
need for Data Analytics. In recent years, various new methods and fields of application have …
Big data for internet of things: a survey
With the rapid development of the Internet of Things (IoT), Big Data technologies have
emerged as a critical data analytics tool to bring the knowledge within IoT infrastructures to …
emerged as a critical data analytics tool to bring the knowledge within IoT infrastructures to …
A retrospective analysis of the impact of the COVID-19 restrictions on energy consumption at a disaggregated level
Since the emergence of the virus that causes COVID-19 (the SARS-CoV-2) in Wuhan in
December 2019, societies all around the world have had to change their normal life patterns …
December 2019, societies all around the world have had to change their normal life patterns …
A short review on data mining techniques for electricity customers characterization
An important tool to manage electrical systems is the knowledge of customers' consumption
patterns. Data Mining (DM) emerges as an important tool for extracting information about …
patterns. Data Mining (DM) emerges as an important tool for extracting information about …
Recognition and classification of typical load profiles in buildings with non-intrusive learning approach
The recent increasing spread of Advanced Metering Infrastructure (AMI) has enabled the
collection of a huge amount of building related-data which can be exploited by both energy …
collection of a huge amount of building related-data which can be exploited by both energy …
Cross-temporal aggregation: Improving the forecast accuracy of hierarchical electricity consumption
Achieving high accuracy in energy consumption forecasting is critical for improving energy
management and planning. However, this requires the selection of appropriate forecasting …
management and planning. However, this requires the selection of appropriate forecasting …
Extraction of statistical features for type-2 fuzzy NILM with IoT enabled control in a smart home
Identification and monitoring of residential appliances are important facets for home energy
management and essential for proper functioning of the connected devices. In this paper …
management and essential for proper functioning of the connected devices. In this paper …
Daily load forecasting based on a combination of classification and regression tree and deep belief network
PP Phyo, C Jeenanunta - IEEE Access, 2021 - ieeexplore.ieee.org
The next-day load forecasting is complex due to the load pattern variations driven by
external factors, such as weather and time. This study proposes a hybrid model that …
external factors, such as weather and time. This study proposes a hybrid model that …
A pattern recognition methodology for analyzing residential customers load data and targeting demand response applications
The availability of smart meter data allows defining innovative applications such as demand
response (DR) programs for households. However, the dimensionality of data imposes …
response (DR) programs for households. However, the dimensionality of data imposes …
A cluster-based intelligence ensemble learning method for classification problems
Classification is a vital task in machine learning. By learning patterns of samples of known
categories, the model can develop the ability to distinguish the categories of samples of …
categories, the model can develop the ability to distinguish the categories of samples of …