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Title: Optimal Grid – Distributed Energy Resource Coordination: Distribution Locational Marginal Costs and Hierarchical Decomposition
We consider radial distribution networks hosting Distributed Energy Resources (DERs), including Solar Photo­voltaic (PV) and storage-like loads, such as Electric Vehicles (EVs). We employ short-run dynamic Distribution Locational Marginal Costs (DLMCs) of real and reactive power to co­optimize distribution network and DER schedules. Striking a balance between centralized control and distributed self­dispatch, we present a novel hierarchical decomposition ap­proach that is based on centralized AC Optimal Power Flow (OPF) interacting with DER self-dispatch that adapts to real and reactive power DLMCs. The proposed approach is designed to be highly scalable for massive DER Grid integration with high model fidelity incorporating rigorous network component dynamics and costs and reffecting them in DLMCs. We illustrate the use of an Enhanced AC OPF to discover spatiotemporally varying DLMCs enabling optimal Grid-DER coordination in­corporating congestion and asset (transformer) degradation. We employ an actual distribution feeder to exemplify the use of DLMCs as financial incentives conveying sufficient information to optimize Distribution Network and DER (PV and EV) operation, and we discuss the applicability and tractability of the proposed approach, while modeling the full complexity of spatiotemporal DER capabilities and preferences.
Authors:
;
Award ID(s):
1733827
Publication Date:
NSF-PAR ID:
10208113
Journal Name:
57th Allerton Conference on Communication, Control, and Computing. Allerton, September 24-27, 2019
Page Range or eLocation-ID:
318 to 325
Sponsoring Org:
National Science Foundation
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