Contact: Eleni Stai
Background:
Solving the AC OPF with stochastic resources (e.g., renewable energy) and storage devices (e.g., batteries) involves the non-linear power flow equations, thus it is, as well known, nonconvex and hard to solve. There exist approaches in literature for approximating the solution of the AC OPF with several of them providing an exact solution under stronger or milder conditions.
In this project we will study the performance of CoDistFlow [1] in large-scale evaluation settings. CoDistFlow is an iterative scheme for approximating the solution of the AC OPF in presence of stochastic resources and batteries, while accounting for grid and battery loses. Scenario-based optimization is applied for handling the uncertainty of loads and renewable energy. We aim at an implementation of CoDistFlow using Gurobi so that numerical evaluations over a large set of scenarios can be performed. Additionally, we will perform numerical evaluations in case of time-varying battery capacities such as the electric vehicles.
Project Goals:
- Implementation of CoDistFlow in Matlab using Gurobi.
- Comparative results via simulations and numerical evaluations in large-scale simulation settings, e.g., large number of scenarios for the scenario-based optimization.
Required Skills:
- MATLAB
- Load Flow
- Optimal Power Flow
References:
- [1] E. Stai, L. Reyes-Chamorro, F. Sossan, J. Y. Le Boudec and M. Paolone, Dispatching Stochastic Heterogeneous Resources Accounting for Grid and Battery Losses, to appear in IEEE Transactions on Smart Grid.
Supervisors: Eleni Stai, Cong Wang