Abstract
Building energy consumption accounts for a large fraction of the total global energy usage, and considerable energy savings are expected to be achieved in this respect through residential electrical load monitoring. Due to the limitations on the practical implementation of in-depth and expensive monitoring systems, non-intrusive load monitoring (NILM) is becoming a hot topic. In this paper, an overview of the state of the art residential electrical load monitoring is presented. Different from previous reviews, the applications of load monitoring are particularly addressed, based on which, technical challenges of load monitoring techniques, including NILM, are identified and thoroughly discussed, together with possible developments and trends predicted from the authors’ perspective.
| Original language | English |
|---|---|
| Pages (from-to) | 1125-1143 |
| Number of pages | 19 |
| Journal | Electric Power Components and Systems |
| Volume | 48 |
| Issue number | 11 |
| DOIs | |
| State | Published - 2020 |
Bibliographical note
Publisher Copyright:© 2020 Taylor & Francis Group, LLC.
Keywords
- appliance scheduling
- artificial intelligence (AI)
- artificial neural networks (ANN)
- big data
- building energy
- cybersecurity
- deep learning
- demand response
- distributed renewable energy source
- edge computing
- heating, ventilation and air conditioning (HVAC)
- home energy management system (HEMS)
- internet of things (IoT)
- load forecast
- load modeling
- long short-term memory (LSTM)
- machine learning
- net-zero-energy home
- non-intrusive load monitoring (NILM)
- photo-voltaic (PV)
- prosumer
- residential energy data
- smart appliance
- smart community
- smart grid
- smart home
- smart plug
- time of use
- transactive energy
ASJC Scopus subject areas
- Energy Engineering and Power Technology
- Mechanical Engineering
- Electrical and Electronic Engineering
