Optimizing smart home energy management for sustainability
HEMS allows customers to track, manage, and regulate their home energy consumption, providing real-time alerts and reports on their usage patterns. The rise of energy
IntelliGrid AI: A Blockchain and Deep-Learning Framework for
IntelliGrid AI revolutionizes smart home energy management by integrating blockchain, deep learning, and vehicle-to-home (V2H) technology, enabling optimized energy
Design and Implementation of a Smart Home Energy
The paper “Design and Implementation of a Smart Home Energy Management System Using IoT and Machine Learning” proposes a system that aims to optimize energy
Optimization of Home Energy Management
Given these challenges, this paper proposes using the BFMO algorithm combined with DRL to develop a more adaptive and efficient
Home and Building Energy Management Systems
NLR researchers are developing tools to understand the impact of changes in home and building energy use and how building assets and energy management systems can
Adaptive home energy management based on PI-DRA-PPO for integrated
The seasonal hydrogen energy storage strategy is integrated into this framework to achieve low-carbon power self-sufficiency on a long timescale. Moreover, advancements in deep learning
Smart building energy management with renewables and storage
To address this challenge, a novel modified Weighted Mean of Vectors algorithm (MINFO) is proposed. This algorithm aims to enhance the performance of smart building EM
Multi-Objective Improved Differential Evolution Algorithm-Based
Abstract: Home energy management systems (HEMSs) are becoming increasingly popular as smart homes become more prevalent, along with their ability to reduce peak
Integrated Home Energy Management with Hybrid Backup Storage
This study presents an innovative home energy management system (HEMS) that incorporates PV, WTs, and hybrid backup storage systems, including a hydrogen storage
Optimization of Home Energy Management Systems in Smart
Given these challenges, this paper proposes using the BFMO algorithm combined with DRL to develop a more adaptive and efficient HEMS optimization framework.
A robust optimization framework for smart home energy
This paper presents a novel two-stage robust optimization framework for smart home energy management, integrating PV-BS, EV charging, and demand response strategies.