Abstract
High renewable energy penetration fundamentally changes power system operation modes and security mechanisms. Such changes pose two challenges to power system operation and planning with traditional analytic methods: the diverse operation modes make it difficult to identify power system patterns, and the complex security mechanism of converter-based devices jeopardizes power system security and stability. Data-driven approaches provide a promising way to handle these challenges in power system operation and planning, especially for power system security and stability problems. This article summarizes a data-driven framework to extract power system security rules and embed the rules into power system optimization under high renewable energy penetration. First, we propose a data-driven method to identify power system operation patterns and explore how high penetrated renewable energy impacts power system security and stability. Then, we review various data-driven methods for modeling complex security and stability rules. Finally, we show how the data-driven rules are transformed into optimization constraints that can be embedded into the power system operation model. The framework is validated through case studies of real-world power systems.
Published Version
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