Review of low voltage load forecasting: Methods, applications, and recommendations

S Haben, S Arora, G Giasemidis, M Voss, DV Greetham - Applied Energy, 2021 - Elsevier
The increased digitalisation and monitoring of the energy system opens up numerous
opportunities to decarbonise the energy system. Applications on low voltage, local networks …

Short term load forecasting

M Jacob, C Neves, D Vukadinović Greetham… - … and Assessing Risk of …, 2020 - Springer
Electrification of transport and heating, and the integration of low carbon technologies (LCT)
is driving the need to know when and how much electricity is being consumed and …

[PDF][PDF] A review of publicly available energy data sets

S Kapoor, B Sturmberg, M Shaw - Wattwatchers' My Energy …, 2020 - wattwatchers.com.au
With increasing levels of renewable energy powering our electricity system, data that tracks
energy generation, distribution and consumption has never been more important. For …

On the evaluation of dynamic selection parameters for time series forecasting

EG Silva, GDC Cavalcanti… - … Joint Conference on …, 2020 - ieeexplore.ieee.org
Dynamic predictor selection has been applied to time series context to improve the accuracy
to forecast. A crucial step in dynamic selection methods if the definition of the region of …

[PDF][PDF] Advancing methods for forecasting and analyzing low-voltage load data

M Voß - 2024 - depositonce.tu-berlin.de
As we move towards a low-carbon energy future, the role of low-voltage distribution
networks is increasing as they accommodate more distributed renewable energy resources …

Permutation-based residential short-term load forecasting in the context of energy management optimization objectives

M Voss - Proceedings of the Eleventh ACM International …, 2020 - dl.acm.org
What makes a household-level short-term load forecast" good"? Individual household load
profiles are intermittent, as distinct peaks correspond to specific activities in the household …

An Analysis of Short-Term Load Forecasting on Residential Buildings Using Deep Learning Models

S Suresh - 2020 - vtechworks.lib.vt.edu
Building energy load forecasting is becoming an increasingly important task with the rapid
deployment of smart homes, integration of renewables into the grid and the advent of …

[PDF][PDF] Dekarbonisierung des urbanen Verkehrs am Beispiel Berlin

D Göhlich - BAND 147 JAHRGANG 2021 - leibnizsozietaet.de
Dekarbonisierung des urbanen Verkehrs am Beispiel Berlin Page 116 Sitzungsberichte der
Leibniz-Sozietät 147 (2021), 117–131 der Wissenschaften zu Berlin Dietmar Göhlich …