0000000000369074

AUTHOR

Morten Kolbak

showing 1 related works from this author

Generalization Capacity Analysis of Non- Intrusive Load Monitoring using Deep Learning

2020

Appliance Load Monitoring is a technique used to monitor devices existing in homes, industry or naval vessels. Acquisition of device-level data can provide great benefits in many areas such as energy management, demand response, and load forecasting. However, the monitoring process is often provided with a costly installation, as it requires a large number of sensors and a data center. Non-Intrusive Load Monitoring (NILM) is an alternative and cost-efficient load monitoring solution. Simply put, NILM is the process of obtaining device-level data by analyzing the aggregated data read from the main meter that measures the electricity consumption of the whole house. Before NILM analysis is per…

energy managementComputer scienceEnergy managementbusiness.industryDeep learningReal-time computingenergy disaggregationProcess (computing)deep learningload monitoringDemand responsedemand responseMetreData centerMicrogridElectricityArtificial intelligencebusiness
researchProduct