Motivation
The increased proliferation of distributed energy resources (solar panels, electric vehicles) turns passive consumers in electric grids into prosumers (producers+consumers). Prosumers may utilize their production for self-consumption, or trade energy with each other in collectives known as local energy markets. An electric distribution grid may consist of multiple local energy markets. However, the scale and composition of local energy markets within large distribution grids remains unclear. To investigate this, one must solve a graph partitioning problem.
From the grid operator’s perspective, local energy markets may improve operation by decreasing risks of voltage violation congested grids. At the same time, local energy markets limit the efficiency of energy dispatch by prioritizing locally optimal resource operation over grid-wide optimal operation. Optimal partitioning will thus involve studying the risk-efficiency tradeoffs in local energy markets.
The goal of the project is to investigate computationally efficient algorithms for distribution grid partitioning ([1],[2] for examples in related topics). The project will extend existing models developed in our lab previously to make them scalable. The candidate will also get a chance to work on real-world distribution grid data.
This project can be adapted in scope to serve as either a Semester or a Master’s project.
Requirements
We are seeking candidates that have strong background in linear algebra and power systems. Knowledge of graph theory is a plus. The candidate must have good programming skills (python).
Contact
Interested candidates may send their transcripts and resume to [email protected] or [email protected].
References
[1] B. Zhao, Z. Xu, C. Xu, C. Wang and F. Lin, “Network Partition-Based Zonal Voltage Control for Distribution Networks With Distributed PV Systems,” in IEEE Transactions on Smart Grid, vol. 9, no. 5, pp. 4087-4098, Sept. 2018, doi: 10.1109/TSG.2017.2648779
[2] H.D. Chiang and R.Jean Jumeau, “Optimal network reconfigurations in distribution systems. I. A new formulation and a solution methodology,” IEEE Trans. Power Del., vol. 5, no. 4, pp. 1902–1909, Oct. 1990.