[HTML][HTML] Artificial intelligence and machine learning approaches to energy demand-side response: A systematic review
Recent years have seen an increasing interest in Demand Response (DR) as a means to
provide flexibility, and hence improve the reliability of energy systems in a cost-effective way …
provide flexibility, and hence improve the reliability of energy systems in a cost-effective way …
From demand response to integrated demand response: Review and prospect of research and application
In the traditional power system demand response, customers respond to electricity price or
incentive and change their original power consumption pattern accordingly to gain …
incentive and change their original power consumption pattern accordingly to gain …
Review of smart meter data analytics: Applications, methodologies, and challenges
The widespread popularity of smart meters enables an immense amount of fine-grained
electricity consumption data to be collected. Meanwhile, the deregulation of the power …
electricity consumption data to be collected. Meanwhile, the deregulation of the power …
[HTML][HTML] Glucotypes reveal new patterns of glucose dysregulation
H Hall, D Perelman, A Breschi, P Limcaoco… - PLoS …, 2018 - journals.plos.org
Diabetes is an increasing problem worldwide; almost 30 million people, nearly 10% of the
population, in the United States are diagnosed with diabetes. Another 84 million are …
population, in the United States are diagnosed with diabetes. Another 84 million are …
Clustering of electricity consumption behavior dynamics toward big data applications
In a competitive retail market, large volumes of smart meter data provide opportunities for
load serving entities to enhance their knowledge of customers' electricity consumption …
load serving entities to enhance their knowledge of customers' electricity consumption …
Analysis and clustering of residential customers energy behavioral demand using smart meter data
S Haben, C Singleton… - IEEE transactions on smart …, 2015 - ieeexplore.ieee.org
Clustering methods are increasingly being applied to residential smart meter data, which
provides a number of important opportunities for distribution network operators (DNOs) to …
provides a number of important opportunities for distribution network operators (DNOs) to …
A comparative study of clustering techniques for electrical load pattern segmentation
Smart meters have been widely deployed in power networks since the last decade. This
trend has resulted in an enormous volume of data being collected from the electricity …
trend has resulted in an enormous volume of data being collected from the electricity …
Machine learning at central banks
C Chakraborty, A Joseph - 2017 - papers.ssrn.com
We introduce machine learning in the context of central banking and policy analyses. Our
aim is to give an overview broad enough to allow the reader to place machine learning …
aim is to give an overview broad enough to allow the reader to place machine learning …
Load profiling and its application to demand response: A review
The smart grid has been revolutionizing electrical generation and consumption through a
two-way flow of power and information. As an important information source from the demand …
two-way flow of power and information. As an important information source from the demand …
Revealing household characteristics from smart meter data
Utilities are currently deploying smart electricity meters in millions of households worldwide
to collect fine-grained electricity consumption data. We present an approach to automatically …
to collect fine-grained electricity consumption data. We present an approach to automatically …