Can X-LSTM-EO predict solar power generation?

In conclusion, the proposed X-LSTM-EO model, along with the use of the XAI-based LIME algorithm, offers a more accurate and transparent method for predicting solar power generation in solar plant systems. These findings have important implications for developing and deploying renewable energy sources, such as solar power.

Can a PSO optimizer accurately estimate PV power generation?

Additionally, the PSO optimizer was employed instead of the EO optimizer to validate the outcomes, which further demonstrated the efficacy of the EO optimizer. The experimental results and simulations demonstrate that the proposed model can accurately estimate PV power generation in response to abrupt changes in power generation patterns.

Why is PV power generation unstable?

Due to of the nature of these variables, PV power generation may become unstable with causing a reduction in PV output power or a sudden surplus. Moreover, this might lead to an imbalance between generating power and load demand, affecting the power grid’s ability to operate and control .

Can a TensorFlow model improve photovoltaic power units?

Moreover, the proposed model might assist in optimizing the operations of photovoltaic power units. The proposed model is implemented utilizing TensorFlow and Keras within the Google Collab environment.

Can deep learning predict solar power generation?

The prevalent deep learning models utilized for predicting solar power generation comprise the deep neural network (DNN), Boltzmann machines, recurrent neural network (RNN), and deep belief network (DBN). RNN has emerged as the favored alternative for performing predictions in smart grids .