In this paper, we perform a short-run Electricity Price Forecast (EPF) with a Recurrent Neural
Network (RNN), namely Long Short-Term Memory (LSTM), using an algorithm that selects …

In this paper, we report a study having as a main goal the obtaining of a method that can
provide an accurate forecast of the residential electricity consumption, refining it up to the …

The ultra-short-term forecasting of the wind speed in large-scale wind plants not only helps
to monitor system operation but also improves the acceptance rate for the power system …

An accurate forecast of the electricity consumption is particularly important to both
consumers and system operators. The purpose of this study is to develop a forecasting …

Accurate forecasting of the produced and consumed electricity from wind farms is an
essential aspect for wind power plant operators. In this context, our research addresses …

A problem of optimally projecting a wind farm is considered. The criteria are the energy
produced by the farm and its costs. The starting option is either financial investments into the …

In this chapter, we will underline the importance of the key performance indicators (KPIs)
computation for power plants' management. The main scope of the KPIs is to continuously …

Tourism represents a fundamental drive for economic growth, having the potential to aid in
poverty reduction through its capacity of generating jobs and incomes based on both tourism …

This paper presents conceptual design and architecture of an informatics solution that aims
to implement analytical models for optimization and forecasting the electricity demand and …

This paper is focused on analyzing a key aspect, the management of the Graphics
Processing Units'(GPUs) memory, which is of paramount importance when developing a …