Artificial intelligence techniques lead to data-driven energy services in distribution power
systems by extracting value from the data generated by the deployed metering and sensing …

The liberalization of electricity markets and the development of renewable energy sources
has led to new challenges for decision makers. These challenges are accompanied by an …

Estimating the financial viability of renewable energy investments requires the availability of
long-term, finely-resolved electricity prices over the investment lifespan. This entails …

The paper presents a way of creating three new, innovative variables based on air
temperature to be used in forecasts of electricity demand and prices. The forecasting …

Abstract The implementation of Carbon Capture and Storage-CCS has been projected to
deliver substantial reductions to achieve the Net Zero scenario by 2050 and it is regarded a …

The growing share of renewables, the retirement of coal generation, and the increasing
significance (and price) of carbon emissions continue to reshape electricity market …

This study uses fully modified ordinary least squares (FMOLS), dynamic ordinary least
squares (DOLS), canonical cointegrating regressions (CCR), and quantile regression to …

Electricity price changes can significantly affect expenses in energy intensive industries,
adjust profits or losses for electricity retailers and cause problems for country's national …

Abstract [eng] This article introduces a statistical approach that helps to evaluate different
power generation sources' influence on electricity market prices. The methodology involves …

(English) The rapid advancement of digitalization, combined with the integration of
renewable generation and the development of information and communication technologies …