[HTML][HTML] Artificial intelligence and machine learning approaches to energy demand-side response: A systematic review
Recent years have seen an increasing interest in Demand Response (DR) as a means to
provide flexibility, and hence improve the reliability of energy systems in a cost-effective way …
provide flexibility, and hence improve the reliability of energy systems in a cost-effective way …
[HTML][HTML] Demand response performance and uncertainty: A systematic literature review
The present review has been carried out, resorting to the PRISMA methodology, analyzing
218 published articles. A comprehensive analysis has been conducted regarding the …
218 published articles. A comprehensive analysis has been conducted regarding the …
Artificial intelligence enabled demand response: Prospects and challenges in smart grid environment
Demand Response (DR) has gained popularity in recent years as a practical strategy to
increase the sustainability of energy systems while reducing associated costs. Despite this …
increase the sustainability of energy systems while reducing associated costs. Despite this …
Artificial intelligence application in demand response: advantages, issues, status, and challenges
In recent years, there has been a significant growth in demand response (DR) as a cost-
effective technique of providing flexibility and, as a result, improving the dependability of …
effective technique of providing flexibility and, as a result, improving the dependability of …
K-means and alternative clustering methods in modern power systems
As power systems evolve by integrating renewable energy sources, distributed generation,
and electric vehicles, the complexity of managing these systems increases. With the …
and electric vehicles, the complexity of managing these systems increases. With the …
[HTML][HTML] Data-driven modelling of energy demand response behaviour based on a large-scale residential trial
Recent years have seen an increasing interest in Demand Response (DR), as a means to
satisfy the growing flexibility needs of modern power grids. This increased flexibility is …
satisfy the growing flexibility needs of modern power grids. This increased flexibility is …
Modeling and simulation of smart grid-aware edge computing federations
Abstract Compute-intensive Internet of Things (IoTs) applications have led to the edge
computing paradigm. Edge computing decentralizes the IT infrastructure in multiple edge …
computing paradigm. Edge computing decentralizes the IT infrastructure in multiple edge …
Clustering algorithm-based network planning for advanced metering infrastructure in smart grid
JL Gallardo, MA Ahmed, N Jara - IEEE Access, 2021 - ieeexplore.ieee.org
Nowadays, legacy electrical distribution systems are migrating to a new modern electric grid
with the capability of supporting different applications such as advanced metering …
with the capability of supporting different applications such as advanced metering …
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 …
[HTML][HTML] Impacts of digitalization on smart grids, renewable energy, and demand response: An updated review of current applications
M Mahmood, P Chowdhury, R Yeassin… - Energy Conversion and …, 2024 - Elsevier
Decarbonization, decentralization, and digitalization are essential for advanced energy
systems (AES), which encompass smart grids, renewable energy integration, and demand …
systems (AES), which encompass smart grids, renewable energy integration, and demand …