The unprecedented convergence robustness of SUGAR™ makes it the ideal tool for the most challenging transmission planning problems.

Quickly build models of the future grid with high renewable penetration.

Replacing conventional generation with renewables at the transmission- and distribution-levels creates challenging planning problems that SUGAR™ is uniquely designed to solve. SUGAR™ identifies and quantifies real and reactive power shortages under future high renewable penetration scenarios, allowing utilities to optimally plan for a greener future.

Ex.: High renewable penetration scenario in a large-scale planning case, where generators were retired, distributed renewables added, and loads scaled. These massive changes led to a poorly-conditioned test case that could take days of effort to solve. SUGAR™ solved this problem in minutes with its feasibility-enabled solution engine.

Simulate cascading events to secure the grid against blackouts.

The ability of SUGAR™ to distinguish “hard-to-solve” cases from infeasible, collapsed grids makes it the ideal tool to analyze cascading outages. Given an initiating event, such as an extreme contingency, SUGAR™ simulates protection schemes, under-frequency and under-voltage load shedding, and grid islanding to evaluate whether a blackout will occur.

Ex.: N-2 branch contingency applied to an 8k+ node system triggered a sequence of events leading to islanding and collapsed areas of the grid.

Optimize the grid for reliability, energy-efficiency, and cost with a flexible optimization engine.

SUGAR™ solves a variety of grid expansion and planning problems using a state-of-the-art nonlinear optimization framework. Optimally place new infrastructure, minimize system losses, and calculate generator set-points for lowest cost while ensuring N-1 security.

Ex.: Volt/VAR optimization indicated the optimal placement of a capacitor bank to guarantee N-1 security in a 70k+ bus case representing the U.S. transmission system.

The foundational technology behind SUGAR™ was originally developed at Carnegie Mellon University and has been published extensively in peer-reviewed conferences and journals. These publications offer a deep dive into the formulation, models, and algorithms used in SUGAR™.