By applying the precise deep-learning-based methods, the VPP operator can efficiently participate in energy markets, which guarantees the VPP profit margin. •.

Jan 16, 2023 ¡¤ In this paper, a comprehensive study has been investigated for the optimal management of a VPP by modeling different resources—RESs, energy storages, EVs, and ...

This article presents a 3-tier taxonomy of such functionalities. The top tier categories are optimization, forecasting and classification.

The numerical results confirmed that the BLSTM network outperformed the other methods and can forecast the stochastic parameters with only 3.56% and 3.53% ...

Mar 19, 2024 ¡¤ Advanced optimization techniques empower VPPs to operate efficiently, adapt to changing conditions, and contribute to a more sustainable energy future.

The optimal VPP economic dispatch can then be expressed as a partially observable Markov decision process (POMDP) problem. A novel deep reinforcement learning ...

This study examines the cost of optimal operating of the SVPP and the amount of produced pollution in four different scenarios in the presence of a demand ...

Use MATLAB, Deep Learning Toolbox, and Optimization Toolbox to create applications for generating renewable energy forecasts and optimizing energy market trades.

Apr 20, 2023 ¡¤ This study intends to optimize the trading decision-making strategy of the new electricity market with virtual power plants and improve the transmission ...

Mar 10, 2022 ¡¤ Intelligent virtual power plants such as Karit's are transforming renewable energy forecasting, management and optimisation with machine learning.