Timothy D. Mount

h-index3
2papers

2 Papers

92.2SYApr 14
Wholesale Market Participation via Competitive DER Aggregation

Cong Chen, Ahmed S. Alahmed, Timothy D. Mount et al.

We consider the aggregation of distributed energy resources (DERs), such as solar PV, energy storage, and flexible loads, by a profit-seeking aggregator participating directly in the wholesale market under distribution network access constraints. We propose a competitive DER aggregator (DERA) model that directly controls local DERs to maximize its profits, while ensuring each aggregated customer gains a surplus higher than their surplus under the regulated retail tariff. The DERA participates in the wholesale electricity market as virtual storage with optimized generation offers and consumption bids derived from the propoed competitive aggregation model. Also derived are DERA's bid curves for the distribution network access and DERA's profitability when competing with the regulated retail tariff. We show that, with the same distribution network access, the proposed DERA's wholesale market participation achieves the same welfare-maximizing outcome as when its customers participate directly in the wholesale market. Extensive numerical studies compare the proposed DERA with existing methods in terms of customer surplus and DERA profit. We empirically evaluate how many DERAs can survive in the competition at long-run equilibrium, and assess the impacts of DER adoption levels and distribution network access on short-run operations.

OCJul 4, 2025
Energy Management for Renewable-Colocated Artificial Intelligence Data Centers

Siying Li, Lang Tong, Timothy D. Mount

We develop an energy management system (EMS) for artificial intelligence (AI) data centers with colocated renewable generation. Under a cost-minimizing framework, the EMS of renewable-colocated data center (RCDC) co-optimizes AI workload scheduling, on-site renewable utilization, and electricity market participation. Within both wholesale and retail market participation models, the economic benefit of the RCDC operation is maximized. Empirical evaluations using real-world traces of electricity prices, data center power consumption, and renewable generation demonstrate significant electricity cost reduction from renewable and AI data center colocations.