… Table 2 summarizes the closely related surveys/reviews on smart microgrids and reveals
our survey's novelty. The aforementioned surveys and review works either focus on a specific …

… In this paper, we have presented a review on solar energy prediction and its impact on
smart microgrids. Energy generation from solar panels is intermittent in nature because of its …

… power generation forecasting using deep learning methods in the smart microgrid, but does
… of the deep learning method for predicting electricity use and renewable energy generation. …

… -model forecasting technique with ensemble deep learning. Initial layer constructed with …
Paper 116 proposed an adaptive and intelligent power control approach in microgrid under grid-…

… Considering that solar irradiance is hard to anticipate, this paper develops a deep learning
… the suggested deep model outperforms other well-known algorithms in smart microgrids. …

… smart grids. Accordingly, in this article, a precise forecasting method based on a deep learning
… Lu, “Optimal load dispatch of community microgrid with deep learning based solar power …

… and modelling of microgrids that can … microgrids. Finally, a future vision for designing
hierarchical and architectural control techniques for the optimal operation of intelligent microgrids is …

… of the microgrid. The results of this study can also serve as a benchmark dataset for future
research, providing a basis for evaluating other machine learning models and techniques that …

… the use of learning techniques. Chengdong et al. [2] propose advanced techniques to solve
the problem of energy forecasting. Authors adapted a deep learning-based method to the …

… (DRL) are representative methods and relatively mature methods … three methods, summarizes
their potential for application in smart … , and operational control in micro grids. In the future, …