DER Information Unaware Coordination via Day-ahead Dynamic Power Bounds

TL;DR

This paper introduces a day-ahead DER coordination method that uses forecasted power ranges to set dynamic transformer bounds, improving reliability and reducing violations without requiring detailed DER owner data.

Contribution

It proposes a novel day-ahead coordination scheme that relies only on past data and forecasted ranges, avoiding the need for DER owner objectives and detailed communication.

Findings

Significantly reduces transformer rating violations compared to uncoordinated methods.

Maintains voltage deviations at levels similar to pre-renewable scenarios.

Effective in scenarios with high solar, EV, and storage penetration.

Abstract

Reliability and voltage quality in distribution networks have been achieved via a combination of transformer power rating satisfaction and voltage management asset control. To maintain reliable operation under this paradigm, however, future grids with deep DER penetrations would require costly equipment upgrades. These upgrades can be mitigated via judicious coordination of DER operation. Earlier work has assumed a hierarchical control architecture in which a global controller (GC) uses detailed power injection and DER data and knowledge of DER owners' objectives to determine setpoints that local controllers should follow in order to achieve reliable and cost effective grid operation. Having such data and assuming knowledge of DER owners' objectives, however, are often not desirable or possible. In an earlier work, a 2-layer DER coordination architecture was shown to achieve close to optimal performance despite infrequent communication to a global controller. Motivated by this work, this paper proposes a day-ahead coordination scheme that uses forecasted power profile ranges to generate day-ahead dynamic power rating bounds at each transformer. Novel features of this scheme include: (i) the GC knows only past node power injection data and does not impose or know DER owner objectives, (ii) we use bounds that ensure reliable operation to guide the local controllers rather than setpoint tracking, and (iii) we consider electric vehicle (EV) charging in addition to storage. Simulations using the IEEE 123-bus network show that with 50% solar, 50% EVs and 10% storage penetrations, the uncoordinated approach incurs rating violations at nearly all 86 transformers and results in 10 times higher voltage deviation, while our approach incurs only 12 rating violations and maintains almost the same voltage deviations as before the addition of solar and EVs.