The energy sector plays a vital role in achieving a sustainable net-zero future, and the
adoption of advanced technologies such as AI, blockchain, quantum computing, digital twin …

The intermittent and stochastic nature of Renewable Energy Sources (RESs) necessitates
accurate power production prediction for effective scheduling and grid management. This …

Grid connected Photovoltaic (PV) plants with battery energy storage system, are being
increasingly utilised worldwide for grid stability and sustainable electricity supplies. In this …

Accurate and reliable PV power probabilistic-forecasting results can help grid operators and
market participants better understand and cope with PV energy volatility and uncertainty and …

Solar photovoltaic microgrids are reliable and efficient systems without the need for energy
storage. However, during power outages, the generated solar power cannot be used by …

This study evaluates the effectiveness of the long and short-term (LSTM) implementation
with a particular emphasis on assessing the impact of transfer learning techniques in …

This study presents a model for predicting photovoltaic power generation based on
meteorological, temporal and geographical variables, without using irradiance values, which …

Global energy demand is on the rise, driven by factors such as population growth and
economic development. Utilizing renewable energy is crucial to meeting this energy …

Rare or missing data pose significant challenges in the prediction of wind power (WP) and
photovoltaic power (PV). Many methods address the data scarcity issue solely through …

The stability and manageability of power systems with a growing share of renewable
energies depend on accurate forecasts and feed-in information. This study provides …