An Incentive-based Online Optimization Framework for Distribution Grids

Journal Article · 09 October 2017 · IEEE Transactions on Automatic Control

DOI: https://doi.org/10.1109/TAC.2017.2760284 · OSTI ID:1409162

Zhou, Xinyang ^[1]; Dall'Anese, Emiliano ^[2]; Chen, Lijun ^[3]; Simonetto, Andrea ^[4]

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1. Univ. of Colorado, Boulder, CO (United States). Interdisciplinary Telecommunication Program
2. National Renewable Energy Lab. (NREL), Golden, CO (United States). Power Systems Engineering Center
3. Univ. of Colorado, Boulder, CO (United States). Computer Science and Telecommunications
4. IBM Research Ireland, Mulhuddart (Ireland)

This article formulates a time-varying social-welfare maximization problem for distribution grids with distributed energy resources (DERs) and develops online distributed algorithms to identify (and track) its solutions. In the considered setting, network operator and DER-owners pursue given operational and economic objectives, while concurrently ensuring that voltages are within prescribed limits. The proposed algorithm affords an online implementation to enable tracking of the solutions in the presence of time-varying operational conditions and changing optimization objectives. It involves a strategy where the network operator collects voltage measurements throughout the feeder to build incentive signals for the DER-owners in real time; DERs then adjust the generated/consumed powers in order to avoid the violation of the voltage constraints while maximizing given objectives. Stability of the proposed schemes is analytically established and numerically corroborated.

• Research Organization: National Renewable Energy Laboratory (NREL), Golden, CO (United States)
• Sponsoring Organization: USDOE Office of Electricity Delivery and Energy Reliability (OE)
• Grant/Contract Number: AC36-08GO28308
• OSTI ID: 1409162
• Report Number(s): NREL/JA--5D00-68133
• Journal Information: IEEE Transactions on Automatic Control, Journal Name: IEEE Transactions on Automatic Control Journal Issue: 7 Vol. 63; ISSN 0018-9286
• Publisher: IEEECopyright Statement
• Country of Publication: United States
• Language: English