On Broader Distributed Energy Resource Aggregations in Unit Commitment Problems

ABSTRACT

The increasing scale and geographical diversity of distributed energy resources (DERs) necessitate innovative management strategies to integrate these resources effectively into the wholesale market, which has catalyzed the research on multi-transmission-node DER aggregation (M-DERA) to enable broader geographic DERs integration. However, M-DERAs also pose new challenges in estimating the nodal power proportion in the aggregated power. Given that nodal shift factors are distinct, an undesired estimation could lead to inaccurate power flow calculations in market operation tools such as unit commitment (UC). To this end, we propose a novel chance-constrained UC (CCUC) model to determine system optimal operation plans with M-DERAs, in which the estimated nodal power proportions of M-DERAs are characterized by distribution factors (DFs) and considered as uncertainties, and power flow limits are modeled as bilinear chance constraints. To handle the unique distribution of DFs, a novel bounded hetero-dimensional mixture model is proposed, which can capture the complex distribution over multiple hetero-dimensional hyperplanes in a bounded space.

BIOGRAPHY

Weilun Wang is currently a Ph.D. candidate in the Department of Electrical and Computer Engineering at Stevens Institute of Technology. His research interests include power system operation and planning under complex DER aggregation and EV charging facility management.