Deep learning in smart grid technology: A review of recent advancements and future prospects
The current electric power system witnesses a significant transition into Smart Grids (SG) as
a promising landscape for high grid reliability and efficient energy management. This …
a promising landscape for high grid reliability and efficient energy management. This …
A comprehensive review on deep learning approaches for short-term load forecasting
Y Eren, İ Küçükdemiral - Renewable and Sustainable Energy Reviews, 2024 - Elsevier
The balance between supplied and demanded power is a crucial issue in the economic
dispatching of electricity energy. With the emergence of renewable sources and data-driven …
dispatching of electricity energy. With the emergence of renewable sources and data-driven …
Cooperative dispatch of distributed energy storage in distribution network with PV generation systems
X Li, L Wang, N Yan, R Ma - IEEE Transactions on Applied …, 2021 - ieeexplore.ieee.org
Battery energy storage system (BESS) plays an important role in solving problems in which
the intermittency has to be considered while operating distribution network (DN) penetrated …
the intermittency has to be considered while operating distribution network (DN) penetrated …
基于人工智能技术的新型电力系统负荷预测研究综述
韩富佳, 王晓辉, 乔骥, 史梦洁, 蒲天骄 - 中国电机工程学报, 2023 - epjournal.csee.org.cn
在“双碳” 目标的驱动下, 构建以新能源为主体的新型电力系统是促进现代电力系统低碳转型发展
的重要前提与必然趋势. 由于复杂易变的多元负荷是新型电力系统的重要组成部分 …
的重要前提与必然趋势. 由于复杂易变的多元负荷是新型电力系统的重要组成部分 …
[HTML][HTML] A taxonomy of machine learning applications for virtual power plants and home/building energy management systems
A Virtual power plant is defined as an information and communications technology system
with the following primary functionalities: enhancing renewable power generation …
with the following primary functionalities: enhancing renewable power generation …
Building energy performance prediction: A reliability analysis and evaluation of feature selection methods
The advancement of smart meters using evolving technologies such as the Internet of
Things (IoT) is producing more data for the training of energy prediction models. Since many …
Things (IoT) is producing more data for the training of energy prediction models. Since many …
[PDF][PDF] 人工智能赋能源网荷储协同互动的应用及展望
王继业 - 中国电机工程学报, 2022 - epjournal.csee.org.cn
构建新型电力系统是能源电力行业推动国家碳达峰, 碳中和战略目标的关键举措.
新型电力系统的主要特征之一是源网荷储高效协同, 人工智能是实现源网荷储高效协同的重要赋 …
新型电力系统的主要特征之一是源网荷储高效协同, 人工智能是实现源网荷储高效协同的重要赋 …
An energy consumption prediction method for HVAC systems using energy storage based on time series shifting and deep learning
H Liu, Y Liu, X Guo, H Wu, H Wang, Y Liu - Energy and Buildings, 2023 - Elsevier
The prediction of building energy consumption plays a crucial role in responding to energy
demands and achieving low-carbon control through energy saving. In this study, we focused …
demands and achieving low-carbon control through energy saving. In this study, we focused …
Application of the hybrid neural network model for energy consumption prediction of office buildings
L Wang, D Xie, L Zhou, Z Zhang - Journal of Building Engineering, 2023 - Elsevier
Accurate building energy consumption prediction is crucial to the rational planning of
building energy systems. The energy consumption of buildings is influenced by various …
building energy systems. The energy consumption of buildings is influenced by various …
Internet of Behavior and Explainable AI Systems for Influencing IoT Behavior
Pandemics and natural disasters over the years have changed the behavior of people,
which has had a tremendous impact on all life aspects. With the technologies available in …
which has had a tremendous impact on all life aspects. With the technologies available in …