Electrical model-free voltage calculations using neural networks and smart meter data

V Bassi, LF Ochoa, T Alpcan… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
The proliferation of residential technologies such as photovoltaic (PV) systems and electric
vehicles can cause voltage issues in low voltage (LV) networks. During operation, voltage …

A data-driven global sensitivity analysis framework for three-phase distribution system with PVs

K Ye, J Zhao, C Huang, N Duan… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Global sensitivity analysis (GSA) of distribution system with respect to stochastic PV and
load variations plays an important role in designing optimal voltage control schemes. This …

Predicting Voltage Changes in Low-Voltage Secondary Networks using Deep Neural Networks

J Yusuf, JA Azzolini, MJ Reno - 2023 IEEE Power and Energy …, 2023 - ieeexplore.ieee.org
High penetrations of residential solar PV can cause voltage issues on low-voltage (LV)
secondary networks. Distribution utility planners often utilize model-based power flow …

Voltage Calculations in Secondary Distribution Networks via Physics-Inspired Neural Network Using Smart Meter Data

L Liu, N Shi, D Wang, Z Ma, Z Wang… - … on Smart Grid, 2024 - ieeexplore.ieee.org
The increasing penetration of distributed energy resources (DERs) leads to voltage issues
across distribution networks, necessitating voltage calculations by utilities. Electric model …

Co-Simulation of a cellular energy system

M Venzke, Y Shudrenko, A Youssfi, T Steffen, V Turau… - Energies, 2023 - mdpi.com
The concept of cellular energy systems of the German Association for Electrical, Electronic &
Information Technologies (VDE) proposes sector coupled energy networks for energy …

Towards a universally applicable neural state estimation through transfer learning

S Balduin, EMSP Veith, A Berezin… - 2021 IEEE PES …, 2021 - ieeexplore.ieee.org
With the expansion of renewable energies, more grid transparency is necessary in order to
continue to guarantee a stable grid operation. In transmission grids, state estimation has …

Accelerating energy-economic simulation models via machine learning-based emulation and time series aggregation

AJ Bogensperger, Y Fabel, J Ferstl - Energies, 2022 - mdpi.com
Energy-economic simulation models with high levels of detail, high time resolutions, or large
populations (eg, distribution networks, households, electric vehicles, energy communities) …

Sampling strategies for static powergrid models

S Balduin, E Veith, S Lehnhoff - arxiv preprint arxiv:2204.09053, 2022 - arxiv.org
Machine learning and computational intelligence technologies gain more and more
popularity as possible solution for issues related to the power grid. One of these issues, the …

Sample-Efficient Learning for a Surrogate Model of Three-Phase Distribution System

HT Nguyen, YJ Kim, DH Choi - IEEE Transactions on Power …, 2023 - ieeexplore.ieee.org
A surrogate model that accurately predicts distribution system voltages is crucial for reliable
smart grid planning and operation. This letter proposes a fixed-point data-driven surrogate …

[PDF][PDF] Deliverable 0: Concept, Smart Meter Data, and Initial Findings

V Bassi, LN Ochoa - 2022 - researchgate.net
This report provides the foundations of the electrical model-free approach to calculate
voltages proposed by the University of Melbourne within the context of the Project “Model …