Privacy-preserving demand response of aggregated residential load
The randomness, dispersion, and small capacity of residential load make it difficult to
participate in incentive-based demand response. Meanwhile, the rapid development of …
participate in incentive-based demand response. Meanwhile, the rapid development of …
Hybrid load forecasting for mixed-use complex based on the characteristic load decomposition by pilot signals
K Park, S Yoon, E Hwang - IEEE Access, 2019 - ieeexplore.ieee.org
In this paper, a characteristic load decomposition (CLD)-based day-ahead load forecasting
scheme is proposed for a mixed-use complex. The aggregated load of the complex is …
scheme is proposed for a mixed-use complex. The aggregated load of the complex is …
A new layered architecture for future big data-driven smart homes
In this paper, a new layered architecture is proposed for big data-driven processing and
management of future smart homes. The proposed Representational State Transfer (REST) …
management of future smart homes. The proposed Representational State Transfer (REST) …
Load Forecasting Based on Genetic Algorithm–Artificial Neural Network-Adaptive Neuro-Fuzzy Inference Systems: A Case Study in Iraq
AMM AL-Qaysi, A Bozkurt, Y Ates - Energies, 2023 - mdpi.com
This study focuses on the important issue of predicting electricity load for efficient energy
management. To achieve this goal, different statistical methods were compared, and results …
management. To achieve this goal, different statistical methods were compared, and results …
Assessing quantum computing performance for energy optimization in a prosumer community
The efficient management of energy communities relies on the solution of the “prosumer
problem”, ie, the problem of scheduling the household loads on the basis of the user needs …
problem”, ie, the problem of scheduling the household loads on the basis of the user needs …
Prosumer flexibility: A comprehensive state-of-the-art review and scientometric analysis
There is a growing need for increased flexibility in modern power systems. Traditionally, this
flexibility has been provided by supply-side technologies. There has been an increase in the …
flexibility has been provided by supply-side technologies. There has been an increase in the …
Fuzzy based particle swarm optimization for modeling home appliances towards energy saving and cost reduction under demand response consideration
Recently, homes consume around 40% of world power and produce 21% of the total
greenhouse gas emissions. Thus, the proper management of energy in the domestic sector …
greenhouse gas emissions. Thus, the proper management of energy in the domestic sector …
Microgrid energy management system based on fuzzy logic and monitoring platform for data analysis
Energy management and monitoring systems are significant difficulties in applying
microgrids to smart homes. Thus, further research is required to address the modeling and …
microgrids to smart homes. Thus, further research is required to address the modeling and …
User preference-based demand response for smart home energy management using multiobjective reinforcement learning
SJ Chen, WY Chiu, WJ Liu - IEEE Access, 2021 - ieeexplore.ieee.org
A well-designed demand response (DR) program is essential in smart home to optimize
energy usage according to user preferences. In this study, we proposed a multiobjective …
energy usage according to user preferences. In this study, we proposed a multiobjective …
Reserve evaluation and energy management of micro-grids in joint electricity markets based on non-intrusive load monitoring
The heating, ventilation, and air-conditioning (HVAC) units are regarded as major demand
response (DR) resources in micro-grids. However, due to privacy concerns and technical …
response (DR) resources in micro-grids. However, due to privacy concerns and technical …