Review of Artificial Intelligence Applications in Accelerating Operational Simulation of Power Systems

ObjectivesWith the rising penetration of renewable energy, it is imperative to conduct power and energy balance analysis, design planning schemes, and evaluate market mechanisms through detailed time-series operational simulation. However, due to the randomness and volatility of renewable energy and the continuous expansion of power grid, operational simulation faces challenges in balancing computational speed and accuracy. Artificial intelligence (AI), with its exceptional abilities in representation, generalization, and self-learning, provides new solutions to the current challenges. Therefore, the current status and necessity of the application of AI in accelerating the operational simulation of power systems are systematically analyzed, and the future development is prospected.MethodsFirst, from a mathematical perspective, the concepts of acceleration methods are classified into scenario aggregation, unit aggregation, constraint reduction, and algorithm acceleration. Second, the necessity of applying AI across different aspects is thoroughly analyzed, addressing the crucial question of “why AI is needed”. Then, current AI applications in accelerating operational simulation and their advantages are systematically summarized. Finally, recommended AI application scenarios in power systems and future prospects are presented.ConclusionsAI can provide effective support for accelerating operational simulation from multiple aspects. It shows particular strengths in handling non-linear correlations, substituting expert experience, and characterizing fuzzy rules.