4.6 Article

Enabling DER Participation in Frequency Regulation Markets

Journal

IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY
Volume 30, Issue 6, Pages 2391-2405

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TCST.2022.3143711

Keywords

Frequency control; Microgrids; Regulation; Costs; Random variables; Power systems; Energy resources; Distributed energy resources (DERs); frequency regulation market; microgrid abstractions; network optimization

Funding

  1. NSF [ECCS-1947050]
  2. ARPA-e NODES Program [DEAR0000695]

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This article proposes a framework for aggregating distributed energy resources into microgrids and participating in frequency regulation markets. The framework consists of a top layer for communication and optimization of the regulation signal, and a bottom layer for adjusting power levels to match the aggregator's output.
Distributed energy resources (DERs) are playing an increasing role in ancillary services for the bulk grid, particularly in frequency regulation. In this article, we propose a framework for collections of DERs, combined to form microgrids and controlled by aggregators, to participate in frequency regulation markets. Our approach covers both the identification of bids for the market clearing stage and the mechanisms for the real-time allocation of the regulation signal. The proposed framework is hierarchical, consisting of a top layer and a bottom layer. The top layer consists of the aggregators communicating in a distributed fashion to optimally disaggregate the regulation signal requested by the system operator. The bottom layer consists of the DERs inside each microgrid whose power levels are adjusted so that the tie line power matches the output of the corresponding aggregator in the top layer. The coordination at the top layer requires the knowledge of cost functions, ramp rates, and capacity bounds of the aggregators. We develop meaningful abstractions for these quantities respecting the power flow constraints and taking into account the load uncertainties and propose a provably correct distributed algorithm for optimal disaggregation of regulation signals among the microgrids.

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