4.7 Article

Coordinating Demand Response Aggregation With LV Network Operational Constraints

Journal

IEEE TRANSACTIONS ON POWER SYSTEMS
Volume 36, Issue 2, Pages 979-990

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TPWRS.2020.3014144

Keywords

Real-time systems; Schedules; Power demand; Reactive power; Mathematical model; Load management; Demand aggregator; demand response; distributed energy resources; optimization; system flexibility

Funding

  1. Science Foundation Ireland under the SFI Strategic Partnership Programme [SFI/15/SPP/E3125]

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The increasing use of renewable energy resources is driving the growing importance of demand response mechanisms to improve the resilience and efficiency of power system operation, with residential demand response expected to become a key asset. To effectively utilize this resource, demand response aggregators must leverage the capabilities of a large group of households and participate in the electricity market, while also considering the operational constraints of the local network to avoid compromising the quality of electricity service and overestimating the true demand response potential.
High shares of renewable energy resources are increasing the value of using demand response (DR) mechanisms to enhance the resiliency and efficiency of power system operation. In this context, residential DR is expected to become an increasingly important asset. In order to exploit this resource, DR aggregators are expected to combine the capabilities of a large group of householders and participate, as a single provider, in the electricity market. In doing so, it is imperative for aggregators to consider the operational constraints of the local network. Otherwise, the quality of the electricity service can be jeopardized and the true DR potential overestimated. This paper presents a novel methodology that integrates DR aggregators with distribution network operators for a secure and efficient scheduling and real-time operation of DR in residential radial feeders. The method is evaluated on a real unbalanced feeder where DR provision (from a mix of technologies) is coordinated with the network steady-state thermal and voltage limits. In this study, with the corresponding data seasonality and controllable devices, it is shown that complying with network operational constraints can impose, at certain times, a significant limit to the allocation of DR.

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