Construction of Energy Storage Value Evaluation Model of Distribution Network Based on Stochastic Forest Algorithm

In the competitive free market environment for power supply, power grid companies strive to provide safe, reliable, and high-quality power services while minimizing the operational, maintenance, and upgrade costs of the power grid. This enables them to offer affordable electricity to users. Energy storage technology plays a crucial role in the development of smart grids. This paper presents research on the construction of an energy storage value evaluation model for distribution networks using the Random Forest (RF) algorithm. The research methodology involves establishing relevant index data to create a sample set. The RF model is then utilized to normalize the independent and dependent variables of the training samples. Subsequently, the RF function in the RF package is employed to train the model, and test samples are evaluated using the trained model to obtain a comprehensive evaluation value. The research findings indicate that the model developed in this study consistently achieves evaluation accuracy above 95%. The experimental results demonstrate that the proposed method exhibits high accuracy and strong robustness, meeting the requirements of real-time applications.