The article analyses effects of price signals on the consumption behavior of household electricity customers. It proposes a systematic analysis process consisting of data preprocessing, aggregation steps and clustering methods. This analysis process was applied to two smart meter datasets (Olympic Peninsula Project, RESIDENS). Large fluctuations in customers' response to the same price signal were detected
This paper introduces a new clustering approach for multi-customer intelligent demand response for c...
Grid modernization using advanced metering infrastructure (AMI) will continue to enhance timely comm...
Influencing households to adopt sustainable energy consumption behaviour is important to the transit...
Demand response (DR) is widely seen as an element bringing needed flexibility to the sustainable pow...
The roll out of smart meters introduces "Time of Use" tariffs to incentive demand response for house...
The availability of smart meter data allows defining innovative applications such as demand response...
Energy management plays a crucial role in providing necessary system flexibility to deal with the on...
Clustering methods are increasingly being applied to residential smart meter data, which provides a ...
Cluster analysis is increasingly applied to smart meter electricity demand data to identify patterns...
There is growing interest in discerning behaviors of electricity users in both the residential and c...
Based on a previous empirical study of the effect of a residential demand response program in Sala, ...
Researching the dynamics of energy consumption at finely resolved timescales is increasingly practic...
Based on a previous empirical study of the effect of a residential demand response program in Sala, ...
This thesis develops novel methods for econometric analysis of time series data, and applies these m...
The 2020 International Workshop on Advanced Analytics and Learning on Temporal Data (AALTD 2020),Ghe...
This paper introduces a new clustering approach for multi-customer intelligent demand response for c...
Grid modernization using advanced metering infrastructure (AMI) will continue to enhance timely comm...
Influencing households to adopt sustainable energy consumption behaviour is important to the transit...
Demand response (DR) is widely seen as an element bringing needed flexibility to the sustainable pow...
The roll out of smart meters introduces "Time of Use" tariffs to incentive demand response for house...
The availability of smart meter data allows defining innovative applications such as demand response...
Energy management plays a crucial role in providing necessary system flexibility to deal with the on...
Clustering methods are increasingly being applied to residential smart meter data, which provides a ...
Cluster analysis is increasingly applied to smart meter electricity demand data to identify patterns...
There is growing interest in discerning behaviors of electricity users in both the residential and c...
Based on a previous empirical study of the effect of a residential demand response program in Sala, ...
Researching the dynamics of energy consumption at finely resolved timescales is increasingly practic...
Based on a previous empirical study of the effect of a residential demand response program in Sala, ...
This thesis develops novel methods for econometric analysis of time series data, and applies these m...
The 2020 International Workshop on Advanced Analytics and Learning on Temporal Data (AALTD 2020),Ghe...
This paper introduces a new clustering approach for multi-customer intelligent demand response for c...
Grid modernization using advanced metering infrastructure (AMI) will continue to enhance timely comm...
Influencing households to adopt sustainable energy consumption behaviour is important to the transit...