Enhancing the Efficiency of AC/DC Hybrid Microgrids through Meteorological Data Forecasting Using Time Series Analysis (Case Study: Sistan Region)

This paper investigates the optimization of control strategies in AC/DC hybrid microgrids, emphasizing the integration of renewable energy sources such as wind and solar power. As the demand for reliable and sustainable energy solutions grows, hybrid microgrids have emerged as a viable option for balancing energy supply and demand in local grids. The study presents a comprehensive analysis of existing control mechanisms, highlighting their effectiveness in maintaining system stability amid fluctuating environmental conditions. Utilizing advanced data analytics tools, including WEKA, the research showcases innovative methods for forecasting energy generation and consumption patterns, thereby enhancing the operational efficiency of hybrid systems. Furthermore, the paper addresses the challenges posed by energy uncertainties and proposes solutions to minimize their impact on grid reliability. Notably, the study achieved a Mean Absolute Error (MAE) of ۰.۱۷۴۵ in the forecasting models. The findings underscore the importance of coordinated control strategies in achieving robust and resilient microgrid operations, ultimately contributing to the transition towards a more sustainable energy future.

Keywords:

Microgrid , Time Series , Sistan , Meteorological Data , WEKA , hybrid AC / DC Microgrid