[HTML][HTML] Data analytics in the electricity sector–A quantitative and qualitative literature review
The rapid transformation of the electricity sector increases both the opportunities and the
need for Data Analytics. In recent years, various new methods and fields of application have …
need for Data Analytics. In recent years, various new methods and fields of application have …
Data driven prediction models of energy use of appliances in a low-energy house
LM Candanedo, V Feldheim, D Deramaix - Energy and buildings, 2017 - Elsevier
This paper presents and discusses data-driven predictive models for the energy use of
appliances. Data used include measurements of temperature and humidity sensors from a …
appliances. Data used include measurements of temperature and humidity sensors from a …
N-BEATS neural network for mid-term electricity load forecasting
This paper addresses the mid-term electricity load forecasting problem. Solving this problem
is necessary for power system operation and planning as well as for negotiating forward …
is necessary for power system operation and planning as well as for negotiating forward …
Forecasting mid-long term electric energy consumption through bagging ARIMA and exponential smoothing methods
EM de Oliveira, FLC Oliveira - Energy, 2018 - Elsevier
In the last decades, the world's energy consumption has increased rapidly due to
fundamental changes in the industry and economy. In such terms, accurate demand …
fundamental changes in the industry and economy. In such terms, accurate demand …
A hybrid short-term load forecasting model based on variational mode decomposition and long short-term memory networks considering relevant factors with …
F He, J Zhou, Z Feng, G Liu, Y Yang - Applied energy, 2019 - Elsevier
Short-term load forecasting plays an essential role in the safe and stable operation of power
systems and has always been a vital research issue of energy management. In this …
systems and has always been a vital research issue of energy management. In this …
Short-term electricity demand forecasting with MARS, SVR and ARIMA models using aggregated demand data in Queensland, Australia
Accurate and reliable forecasting models for electricity demand (G) are critical in
engineering applications. They assist renewable and conventional energy engineers …
engineering applications. They assist renewable and conventional energy engineers …
Electric load forecasting methods: Tools for decision making
For decision makers in the electricity sector, the decision process is complex with several
different levels that have to be taken into consideration. These comprise for instance the …
different levels that have to be taken into consideration. These comprise for instance the …
A review on active customers participation in smart grids
Industrial., commercial, and residential facilities are progressively adopting automation and
generation capabilities. By having flexible demand and renewable energy generation …
generation capabilities. By having flexible demand and renewable energy generation …
Triple seasonal methods for short-term electricity demand forecasting
JW Taylor - European Journal of Operational Research, 2010 - Elsevier
Online short-term load forecasting is needed for the real-time scheduling of electricity
generation. Univariate methods have been developed that model the intraweek and intraday …
generation. Univariate methods have been developed that model the intraweek and intraday …
A variance inflation factor and backward elimination based robust regression model for forecasting monthly electricity demand using climatic variables
Selection of appropriate climatic variables for prediction of electricity demand is critical as it
affects the accuracy of the prediction. Different climatic variables may have different impacts …
affects the accuracy of the prediction. Different climatic variables may have different impacts …