A review on renewable energy and electricity requirement forecasting models for smart grid and buildings
The benefits of renewable energy are that it is sustainable and is low in environmental
pollution. Growing load requirement, global warming, and energy crisis need energy …
pollution. Growing load requirement, global warming, and energy crisis need energy …
Forecasting holiday daily tourist flow based on seasonal support vector regression with adaptive genetic algorithm
Accurate holiday daily tourist flow forecasting is always the most important issue in tourism
industry. However, it is found that holiday daily tourist flow demonstrates a complex …
industry. However, it is found that holiday daily tourist flow demonstrates a complex …
Big data analytics for dynamic energy management in smart grids
The smart electricity grid enables a two-way flow of power and data between suppliers and
consumers in order to facilitate the power flow optimization in terms of economic efficiency …
consumers in order to facilitate the power flow optimization in terms of economic efficiency …
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 of electricity demand forecasting in low and middle income countries: The demand determinants and horizons
With the globally increasing electricity demand, its related uncertainties are on the rise as
well. Therefore, a deeper insight of load forecasting techniques for projecting future …
well. Therefore, a deeper insight of load forecasting techniques for projecting future …
Relationships between meteorological variables and monthly electricity demand
F Apadula, A Bassini, A Elli, S Scapin - Applied Energy, 2012 - Elsevier
Electricity demand depends on climatic condition and the influence of weather has been
widely reported in the past. The main purpose of this study is to analyse the effect of the …
widely reported in the past. The main purpose of this study is to analyse the effect of the …
A prediction model based on neural networks for the energy consumption of a bioclimatic building
Energy in buildings is a topic that is being widely studied due to its high impact on global
energy demand. This problem involves the performance of an adequate management of the …
energy demand. This problem involves the performance of an adequate management of the …
Long term load projection in high resolution for all countries globally
Electricity demand modelling is the central and integral issue for the planning and operation
of power systems. Load projection provides important information for electricity network …
of power systems. Load projection provides important information for electricity network …
Machine learning algorithms for short-term load forecast in residential buildings using smart meters, sensors and big data solutions
In this paper, we propose a scalable Big Data framework that collects the data from smart
meters and weather sensors, pre-processes and loads it into a NoSQL database that is …
meters and weather sensors, pre-processes and loads it into a NoSQL database that is …
[HTML][HTML] DA-LSTM: A dynamic drift-adaptive learning framework for interval load forecasting with LSTM networks
Load forecasting is a crucial topic in energy management systems (EMS) due to its vital role
in optimizing energy scheduling and enabling more flexible and intelligent power grid …
in optimizing energy scheduling and enabling more flexible and intelligent power grid …