Generation of Power Network Operating Scenarios for an AI-friendly Digital Environment

With the growing need for AI-driven solutions in power grid management, this work addresses the challenge of creating realistic synthetic operating scenarios essential for developing, testing, and validating AI-based decision-making systems. It uses spatial-temporal noise functions, predefined patterns, and optimal power flow to model renewable energy and conventional power plant generation, load, and losses. Quantitative and visual key performance indicators are proposed to evaluate the quality of the generated operating scenarios, and the validation highlights the framework’s ability to emulate diverse and practical operating scenarios, bridging gaps in AI-driven power system research and real-world applications.