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Fault detection and efficiency assessment for hvac systems using non-intrusive load monitoring: A review
Heat, ventilation, and air conditioning (HVAC) systems are some of the most energy-
intensive equipment in buildings and their faulty or inefficient operation can significantly …
intensive equipment in buildings and their faulty or inefficient operation can significantly …
Energy management in smart buildings and homes: current approaches, a hypothetical solution, and open issues and challenges
Energy plays a pivotal role for economic development of a country. A reliable energy source
is needed to improve the living standards of people. To achieve such a goal, governments …
is needed to improve the living standards of people. To achieve such a goal, governments …
Deep learning-based short-term load forecasting approach in smart grid with clustering and consumption pattern recognition
Different aggregation levels of the electric grid's big data can be helpful to develop highly
accurate deep learning models for Short-term Load Forecasting (STLF) in electrical …
accurate deep learning models for Short-term Load Forecasting (STLF) in electrical …
Impact of battery storage on residential energy consumption: An Australian case study based on smart meter data
Advanced metering infrastructure has been widely recognized as a key enabling factor for
delivering a range of benefits to the electricity industry as well as to energy consumers. The …
delivering a range of benefits to the electricity industry as well as to energy consumers. The …
Exploring the role of deep neural networks for post-disaster decision support
N Chaudhuri, I Bose - Decision Support Systems, 2020 - Elsevier
Disaster management operations are information intensive activities due to high uncertainty
and complex information needs. Emergency response planners need to effectively plan …
and complex information needs. Emergency response planners need to effectively plan …
Mobile apps meet the smart energy grid: A survey on consumer engagement and machine learning applications
Consumers lie at the epicenter of smart grids, since their activities account for a large portion
of the total energy demand. Therefore, utility companies, governmental agencies, and …
of the total energy demand. Therefore, utility companies, governmental agencies, and …
Beyond privacy and security: Exploring ethical issues of smart metering and non-intrusive load monitoring
Artificial intelligence is believed to facilitate cost-effective and clean energy by optimizing
consumption, reducing emissions, and enhancing grid reliability. Approaches such as non …
consumption, reducing emissions, and enhancing grid reliability. Approaches such as non …
The design of citizen-centric green IS in sustainable smart districts
Green information systems are often praised for their potential to foster sustainability in
citizens' daily lives and meet their needs. With this focus on citizens, districts that use smart …
citizens' daily lives and meet their needs. With this focus on citizens, districts that use smart …
A data-driven approach for targeting residential customers for energy efficiency programs
H Liang, J Ma, R Sun, Y Du - IEEE Transactions on Smart Grid, 2019 - ieeexplore.ieee.org
Targeting the right customers for energy efficiency (EE) programs is crucial for the power
distribution or retail companies to enhance the efficiency of marketing budget allocation and …
distribution or retail companies to enhance the efficiency of marketing budget allocation and …
Big data to the rescue? Challenges in analysing granular household electricity consumption in the United Kingdom
Rapid growth in smart meter installations has given rise to vast collections of data at a high
time-resolution and down to an individual level. However, to enable efficient policy …
time-resolution and down to an individual level. However, to enable efficient policy …