On data-driven modeling and control in modern power grids stability: Survey and perspective

X Gong, X Wang, B Cao - Applied Energy, 2023 - Elsevier
Modern power grids are fast evolving with the increasing volatile renewable generation,
distributed energy resources (DERs) and time-varying operating conditions. The DERs …

[HTML][HTML] Advancements in data-driven voltage control in active distribution networks: A Comprehensive review

SM Abdelkader, S Kinga, E Ebinyu, J Amissah… - Results in …, 2024 - Elsevier
Distribution systems are integrating a growing number of distributed energy resources and
converter-interfaced generators to form active distribution networks (ADNs). Numerous …

Hierarchical control for microgrids: a survey on classical and machine learning-based methods

S Li, A Oshnoei, F Blaabjerg, A Anvari-Moghaddam - Sustainability, 2023 - mdpi.com
Microgrids create conditions for efficient use of integrated energy systems containing
renewable energy sources. One of the major challenges in the control and operation of …

Review of computational intelligence approaches for microgrid energy management

M Bilal, AA Algethami, S Hameed - IEEE Access, 2024 - ieeexplore.ieee.org
This research investigates implementing and optimizing microgrid energy management
systems (EMS) utilizing artificial intelligence (AI). Inspired by the need for efficient resource …

Control of a microgrid using robust data-driven-based controllers of distributed electric vehicles

P Khemmook, K Prompinit, T Surinkaew - Electric Power Systems Research, 2022 - Elsevier
Current advancements in power electronic converters have paved a way to shift the attention
from the traditional internal combustion engine to electric vehicles (EVs). In previous …

Challenges in smartizing operational management of functionally-smart inverters for distributed energy resources: A review on machine learning aspects

Y Fujimoto, A Kaneko, Y Iino, H Ishii, Y Hayashi - Energies, 2023 - mdpi.com
The widespread introduction of functionally-smart inverters will be an indispensable factor
for the large-scale penetration of distributed energy resources (DERs) via the power system …

Artificial intelligence-based methods for renewable power system operation

Y Li, Y Ding, S He, F Hu, J Duan, G Wen… - Nature Reviews …, 2024 - nature.com
Carbon neutrality goals are driving the increased use of renewable energy (RE). Large-
scale use of RE requires accurate energy generation forecasts; optimized power dispatch …

Multi-objective optimization for dc microgrid using combination of nsga-ii algorithm and linear search method

Z Ren, X Qu, M Wang, C Zou - IEEE Journal on Emerging and …, 2023 - ieeexplore.ieee.org
With the penetration of renewable sources, the DC microgrid is much more efficient and
flexible to link renewable power generators and DC loads. Due to the uncertainties in both …

Analytical overvoltage and power-sharing control method for photovoltaic-based low-voltage islanded microgrid

R Bakhshi-Jafarabadi, A Lekić, FD Marvasti… - IEEE …, 2023 - ieeexplore.ieee.org
Overvoltage instability is a growing concern in a standalone low-voltage (LV) microgrid (MG)
with non-dispatchable intermittent renewable energies such as residential and commercial …

[HTML][HTML] Energy Intelligence: A Systematic Review of Artificial Intelligence for Energy Management

A Safari, M Daneshvar, A Anvari-Moghaddam - Applied Sciences, 2024 - mdpi.com
Artificial intelligence (AI) and machine learning (ML) can assist in the effective development
of the power system by improving reliability and resilience. The rapid advancement of AI and …