A Wind-Solar-Energy Storage system integrates electricity generation from wind turbines and solar panels with energy storage technologies, such as batteries. This combination addresses the variable nature of renewable energy sources, ensuring a consistent and reliable energy supply. The integration of wind, solar, and energy storage, commonly known as a Wind-Solar-Energy Storage system, is emerging as the optimal solution to stabilise renewable energy output and enhance. . Ever wondered what happens when the wind stops blowing or the sun takes a coffee break behind the clouds? Enter energy storage – the unsung hero keeping your lights on during nature's downtime. The global renewable energy landscape is undergoing a seismic shift, with wind power and photovoltaic. .
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This paper presents a variety of ML approaches combined with XAI to predict solar power generation, aiming to optimize energy management in smart grids. . Machine learning (ML) algorithms can provide highly accurate predictions, but their complexity often makes them difficult to interpret due to their black-box nature. Combining ML and Explainable Artificial Intelligence (XAI) makes these models more transparent and enables users to understand the. . This paper proposes a model called X-LSTM-EO, which integrates explainable artificial intelligence (XAI), long short-term memory (LSTM), and equilibrium optimizer (EO) to reliably forecast solar power generation. The LSTM component forecasts power generation rates based on environmental conditions. .
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