[HTML][HTML] Optimization with constraint learning: A framework and survey

AO Fajemisin, D Maragno, D den Hertog - European Journal of Operational …, 2024 - Elsevier
Many real-life optimization problems frequently contain one or more constraints or objectives
for which there are no explicit formulae. If however data on feasible and/or infeasible states …

Novel exertion of intelligent static compensator based smart inverters for ancillary services in a distribution utility network-review

S Srinivasarangan Rangarajan, J Sharma… - Electronics, 2020 - mdpi.com
Integration of distributed energy resources (DER) has always posed a challenge. Smart
inverters have started playing a crucial role in efficient integration of DERs. With the basic …

Data-driven local control design for active distribution grids using off-line optimal power flow and machine learning techniques

S Karagiannopoulos, P Aristidou… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
The optimal control of distribution networks often requires monitoring and communication
infrastructure, either centralized or distributed. However, most of the current distribution …

A survey on applications of machine learning for optimal power flow

F Hasan, A Kargarian… - 2020 IEEE Texas Power …, 2020 - ieeexplore.ieee.org
Optimal power flow (OPF) is at the heart of many power system operation tools and market
clearing processes. Several mathematical and heuristic approaches have been presented in …

Designing reactive power control rules for smart inverters using support vector machines

M Jalali, V Kekatos, N Gatsis… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
Smart inverters have been advocated as a fast-responding mechanism for voltage
regulation in distribution grids. Nevertheless, optimal inverter coordination can be …

[HTML][HTML] Reactive power control in photovoltaic systems through (explainable) artificial intelligence

C Utama, C Meske, J Schneider, C Ulbrich - Applied Energy, 2022 - Elsevier
Across the world, efforts to support the energy transition and halt climate change have
resulted in significant growth of the number of renewable distributed generators (DGs) …

Hybrid learning aided inactive constraints filtering algorithm to enhance AC OPF solution time

F Hasan, A Kargarian… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
The optimal power flow (OPF) problem contains many constraints. However, equality
constraints and a limited set of inequality constraints encompass sufficient information to …

[HTML][HTML] Decentralized control in active distribution grids via supervised and reinforcement learning

S Karagiannopoulos, P Aristidou, G Hug, A Botterud - Energy and AI, 2024 - Elsevier
While moving towards a low-carbon, sustainable electricity system, distribution networks are
expected to host a large share of distributed generators, such as photovoltaic units and wind …

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 …

An overview of grid-edge control with the digital transformation

TT Mai, PH Nguyen, QT Tran, A Cagnano… - Electrical …, 2021 - Springer
Distribution networks are evolving to become more responsive with increasing integration of
distributed energy resources (DERs) and digital transformation at the grid edges. This …