State-of-the-art review on energy and load forecasting in microgrids using artificial neural networks, machine learning, and deep learning techniques
Forecasting renewable energy efficiency significantly impacts system management and
operation because more precise forecasts mean reduced risk and improved stability and …
operation because more precise forecasts mean reduced risk and improved stability and …
Load forecasting techniques and their applications in smart grids
The growing success of smart grids (SGs) is driving increased interest in load forecasting
(LF) as accurate predictions of energy demand are crucial for ensuring the reliability …
(LF) as accurate predictions of energy demand are crucial for ensuring the reliability …
Data-driven next-generation smart grid towards sustainable energy evolution: techniques and technology review
Meteorological changes urge engineering communities to look for sustainable and clean
energy technologies to keep the environment safe by reducing CO 2 emissions. The …
energy technologies to keep the environment safe by reducing CO 2 emissions. The …
Efficient short-term electricity load forecasting for effective energy management
Short-term electrical energy load forecasting is one of the most significant problems
associated with energy management for smart grids, which aims to optimize the operational …
associated with energy management for smart grids, which aims to optimize the operational …
Designing the Optimal Configuration of a Small Power System for Autonomous Power Supply of Weather Station Equipment
BV Malozyomov, NV Martyushev, EV Voitovich… - Energies, 2023 - mdpi.com
Autonomous power systems serving remote areas with weather stations with small
settlements are characterized by a fairly high cost of generating electricity and the purchase …
settlements are characterized by a fairly high cost of generating electricity and the purchase …
基于大语言模型的电力系统通用人工智能展望: 理论与应用
赵俊华， 文福拴， 黄建伟， 刘嘉宁， 赵焕… - 电力系统 …, 2024 - epjournal.csee.org.cn
大语言模型(LLM) 是一种利用大规模文本语料库进行预训练和微调的深度学习语言模型. 目前,
在通识问答, 文本生成和科学推理等方面已展现出强大的能力. 在此背景下, 文中探索了基于LLM …
在通识问答, 文本生成和科学推理等方面已展现出强大的能力. 在此背景下, 文中探索了基于LLM …
[HTML][HTML] Deep learning methods utilization in electric power systems
The fast expansion of renewable energy sources, rising electricity demand, and the
requirement for improved grid dependability have made it necessary to create cutting-edge …
requirement for improved grid dependability have made it necessary to create cutting-edge …
Group method of data handling using Christiano–Fitzgerald random walk filter for insulator fault prediction
Disruptive failures threaten the reliability of electric supply in power branches, often
indicated by the rise of leakage current in distribution insulators. This paper presents a …
indicated by the rise of leakage current in distribution insulators. This paper presents a …
Intelligent based hybrid renewable energy resources forecasting and real time power demand management system for resilient energy systems
The rapid growth of hybrid renewable Distributed Energy Resources (DERs) generation
possess various challenges with inaccurate forecast models in stochastic power systems …
possess various challenges with inaccurate forecast models in stochastic power systems …
Optimal management of energy consumption in an autonomous power system considering alternative energy sources
V Manusov, S Beryozkina, M Nazarov, M Safaraliev… - Mathematics, 2022 - mdpi.com
This work aims to analyze and manage the optimal power consumption of the autonomous
power system within the Pamir region of Republic of Tajikistan, based on renewable energy …
power system within the Pamir region of Republic of Tajikistan, based on renewable energy …