Control systems for low-inertia power grids: A survey on virtual power plants

DE Ochoa, F Galarza-Jimenez, F Wilches-Bernal… - IEEE …, 2023 - ieeexplore.ieee.org
Virtual Power Plants (VPPs) have emerged as a modern real-time energy management
architecture that seeks to synergistically coordinate an aggregation of renewable and non …

Reinforcement learning for sustainable energy: A survey

K Ponse, F Kleuker, M Fejér, Á Serra-Gómez… - arXiv preprint arXiv …, 2024 - arxiv.org
The transition to sustainable energy is a key challenge of our time, requiring modifications in
the entire pipeline of energy production, storage, transmission, and consumption. At every …

A novel contingency-aware primary frequency control for power grids with high CIG-penetration

OO Khamisov, M Ali, T Sayfutdinov… - … on Power Systems, 2023 - ieeexplore.ieee.org
The ever-growing trend of Converter-Interfaced Generation (CIG) integration in electrical
power grids has led to a tremendous concern about systems' inertia, stability, and frequency …

The role of artificial intelligence in Latin Americas energy transition

VMM Jimenez, EP Gonzalez - IEEE Latin America Transactions, 2022 - ieeexplore.ieee.org
Latin Americas energy transition involves the massive integration of sustainable energy,
different than hydro, at large and small scale, consumer empowerment, and the adoption of …

Stability Constrained Optimization in High IBR-Penetrated Power Systems-Part I: Constraint Development and Unification

Z Chu, F Teng - arXiv preprint arXiv:2307.12151, 2023 - arxiv.org
Maintaining power system stability is becoming more and more challenging due to the ever-
increasing inverter-interfaced renewable penetration in power systems. To ensure system …

[HTML][HTML] Battery control with lookahead constraints in distribution grids using reinforcement learning

J da Silva André, E Stai, O Stanojev, G Hug - Electric Power Systems …, 2022 - Elsevier
In this paper, a computationally efficient real-time control of a battery with lookahead state-of-
energy constraints in active distribution grids with distributed energy sources is presented …

Safe Reinforcement Learning for Strategic Bidding of Virtual Power Plants in Day-Ahead Markets

O Stanojev, L Mitridati, RN Di Prata… - 2023 IEEE International …, 2023 - ieeexplore.ieee.org
This paper presents a novel safe reinforcement learning algorithm for strategic bidding of
Virtual Power Plants (VPPs) in day-ahead electricity markets. The proposed algorithm …

Improved fractional order control with virtual inertia provision methodology for electric vehicle batteries in modern multi-microgrid energy systems

WA Hafez, M Aly, EA Mohamed, NA Nagem - Journal of Energy Storage, 2025 - Elsevier
Providing inertia in modern electrical power grids has become a highly demanding task to
mitigate reduced power system inertia of renewable energy sources (RES) based power …

Data-driven demand-side flexibility quantification: Prediction and approximation of flexibility envelopes

N Hekmat, H Cai, T Zufferey, G Hug… - 2023 IEEE Belgrade …, 2023 - ieeexplore.ieee.org
Real-time quantification of residential building energy flexibility is needed to enable a cost-
efficient operation of active distribution grids. A promising means is to use the socalled …

[HTML][HTML] Demand response for frequency regulation with neural network load controller under high intermittency photovoltaic systems

XC Miow, YS Lim, LC Hau, J Wong, H Patsios - Energy Reports, 2023 - Elsevier
The rate of change of frequency (ROCOF) has become a key parameter to be monitored
under high penetration of renewable energy. Any significant ROCOF should be mitigated …