A Brief Review on Estimation and Forecasting of Grid System in Sustainable Micro Grid System Integration

Within a specific integration share, renewable resources have shown themselves to be beneficial and workable options. But as they become more pervasive, they begin to test the limitations of traditional generation, leading to a decentralized uncertainty characterized by bi-directional power flows. This calls for the creation of sophisticated systems that can precisely forecast renewable production, particularly in greater integration scenarios. The outcomes of several scenarios demonstrate the noteworthy influence of including temperature and humidity into the forecasting model. Accuracy measures like mean square error, root mean square error, and mean absolute range normalized error are significantly improved by its addition. It's interesting to note that renewable availability only makes a small contribution to these gains. As we move toward decarbonized power systems, the research highlights how crucial it is becoming for expert forecasting systems to account for less energy. For these kinds of systems to adapt to the changing dynamics of renewable energy production and consumption, the relationship between input and output has to be represented at a high resolution.