Integrating Artificial Intelligence in Power System Simulations for Biotechnological Manufacturing Optimization

Abstract

In the landscape of public infrastructure development, the enhancement of power systems is a pivotal indicator. Economic growth and societal demands have led to increasingly complex power infrastructures, incorporating numerous distributed renewable energy sources. This expansion generates vast amounts of data with typical big data characteristics—volume, variety, and velocity. Addressing the unique challenges presented by power system data necessitates advanced analytical methods. The burgeoning field of Artificial Intelligence (AI) in computer science offers promising solutions, making substantial impacts across various sectors. AI is recognized as a cornerstone of technological and intellectual advancement, and its integration within power systems is a strategic component of national development agendas. This paper explores the integration of AI technologies in power system operations, highlighting two principal AI advancements currently influencing the field. It provides a detailed analysis of AI applications in power system management, including planning, integrated control, simulation, forecasting, and diagnostics. By evaluating the effectiveness of AI technologies in enhancing the functionality and efficiency of electrical systems, this study underscores the transformative potential of AI in redefining power infrastructure within the biotechnological industry.