Key Features

• Incorporation of industry-standard models for synchronous machines, automatic voltage regulators, governors, and inverters as well as novel models, including synchronous machines, machine learning surrogates and aggregate distribution systems
• Exchangeable solvers from the Scientific Machine Learning ecosystem
• Separation of models from the integration algorithms coupled with novel numerical techniques

Core Capabilities

• Runs quasi-static, electromagnetic time domain simulations and small signal stability analysis
• Models novel and advanced inverter control methodologies
• Integrates with the rest of Sienna to perform stability analyses of systems with high penetration of inverter-based resources
• Accelerates the electromagnetic analysis of large interconnected systems by over 10×, employing advanced modeling and algorithmic innovations
• Runs electromagnetic simulations of large interconnected systems employing averaging techniques and modern integration methods
• Provides flexibility when making trade-offs between precision and solution speed for distinct use cases and requirements
• Increases levels of control for modelers to arrive at conclusions about system stability within a required parameter of precision
• Allows researchers to implement new control techniques for modern inverter-based generation and assess the numerical requirements of the proposed controls