Load forecasting benchmark for smart meter data

J Viana, RJ Bessa, J Sousa - 2019 IEEE Milan PowerTech, 2019 - ieeexplore.ieee.org
Actual integration of high-tech devices brings opportunities for better monitoring,
management and control of low voltage networks. In this new paradigm, efficient tools …

Forecasting of smart meter time series based on neural networks

T Zufferey, A Ulbig, S Koch, G Hug - … , DARE 2016, Riva del Garda, Italy …, 2017 - Springer
In traditional power networks, Distribution System Operators (DSOs) used to monitor energy
flows on a medium-or high-voltage level for an ensemble of consumers and the low-voltage …

Integrating the industrial consumer into smart grid by load curve forecasting using machine learning

S Ungureanu, V Ţopa, A Cziker - 2019 8th International …, 2019 - ieeexplore.ieee.org
Integration of industrial consumers into the smart grid concept can be facilitated by
optimizing short and very short-term forecasts of load curves for industrial consumers …

Inadequacy of standard algorithms and metrics for short-term load forecasts in low-voltage grids

T Zufferey, A Lepouze, G Hug - 2019 IEEE Milan PowerTech, 2019 - ieeexplore.ieee.org
Short-term load forecasting is becoming popular in low-voltage grids due to the availability
of Smart Meter (SM) measurements. At the individual customer level, load profiles are …

Load forecasting in different scale and horizon-a review

E Iskandarnia, H Al-Amal… - 3rd Smart Cities …, 2020 - ieeexplore.ieee.org
A review of the latest load forecasting techniques will be presented in this paper, in the
context of different scale and horizons. Today, the competitive energy market demands more …

Experimental analysis of the input variables' relevance to forecast next day's aggregated electric demand using neural networks

L Hernández, C Baladrón, JM Aguiar, L Calavia… - Energies, 2013 - mdpi.com
Thanks to the built in intelligence (deployment of new intelligent devices and sensors in
places where historically they were not present), the Smart Grid and Microgrid paradigms …

Smart meter forecasting from one minute to one year horizons

L Massidda, M Marrocu - Energies, 2018 - mdpi.com
The ability to predict consumption is an essential tool for the management of a power
distribution network. The availability of an advanced metering infrastructure through smart …

A comparative analysis of machine learning methods for short-term load forecasting systems

A Parrado-Duque, S Kelouwani… - … for Smart Grids …, 2021 - ieeexplore.ieee.org
End-users' electricity consumption is highly affected by weather conditions. The uncertain
nature of these circumstances can highly challenge energy supply and demand balancing …

Consumption based-only load forecasting for individual households in nanogrids: A case study

M Caliano, A Buonanno, G Graditi… - 2020 AEIT …, 2020 - ieeexplore.ieee.org
Electricity load forecasting plays an important role in planning and a vital role in the
operational management of an electric power system based on smart grids. In this work …

Short term load forecasting for individual consumers based on markov chains

H Früh, D Groß, K Rudion - 2019 Modern Electric Power …, 2019 - ieeexplore.ieee.org
Emerging smart-grid applications in low-voltage systems generate a need to forecast not
only aggregated load profiles, b ut i ndividual, c onsumer s pecific pr ofiles in a high …