Robust Partitioning and Operation of Networked Microgrids to Maximize Uncertain Load Delivery in Distribution Grids
A two-stage robust optimization approach that configures and operates networked microgrids to maximize the delivery of uncertain loads in unbalanced distribution grids, while minimizing generation costs.
Distributionally Robust Multiperiod Dispatch Optimization with Uncertainty Modeling for Renewable Generation and Distributed Energy Resources
The core message of this article is to propose a novel approximation method for multiple joint chance constraints (JCCs) to model the uncertainty in power system dispatch problems, which solves the conservativeness and potential infeasibility concerns of the conventional Conditional Value at Risk (CVaR) method. The proposed method is then extended to handle multiple data-driven distributionally robust joint chance constraints (DRJCCs) that fit the practical scenario of power system dispatch problems where the distribution of uncertain variables is often inaccessible.
Efficient Algorithms for Solving Large-Scale AC Unit Commitment Problems in Power Systems
This work develops efficient decomposition algorithms capable of obtaining high-quality solutions to large-scale AC unit commitment problems within realistic time limits required by power system operations.