Predictability and Fairness in Load Aggregation and Operations of Virtual Power Plants
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Abstract (arXiv)
In power systems, one wishes to regulate the aggregate demand of an ensemble of distributed energy resources (DERs), such as controllable loads and battery energy storage systems. We suggest a notion of predictability and fairness, which suggests that the long-term averages of prices or incentives offered should be independent of the initial states of the operators of the DER, the aggregator, and the power grid. We show that this notion cannot be guaranteed with many traditional controllers used by the load aggregator, including the usual proportional-integral (PI) controller. We show that even considering the non-linearity of the alternating-current model, this notion of predictability and fairness can be guaranteed for incrementally input-to-state stable (iISS) controllers, under mild assumptions.
Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). Builds on 11 of its 88 references that are in the map. First posted on arXiv 6 Oct 2021.
Builds on
11 of 88 references.
References · 11
- 2019Solutions of DC OPF are Never AC Feasiblecited by 16
- 2016Convergence Properties for Discrete-time Nonlinear Systemscited by 10
- 2020Adaptive Charging Networks: A Framework for Smart Electric Vehicle Chargingcited by 8
- 2013Design and Stability of Load-Side Primary Frequency Control in Power Systemscited by 5
- 2018On the Ergodic Control of Ensemblescited by 5
- 2014Optimal load-side control for frequency regulation in smart gridscited by 3
- 2016An SQP Method Combined with Gradient Sampling for Small-Signal Stability Constrained OPFcited by 3
- 2020Real-time Flexibility Feedback for Closed-loop Aggregator and System Operator Coordinationcited by 2
- 2020Predictability and Fairness in Social Sensingcited by 2
- 2016Gather-and-broadcast frequency control in power systemscited by 1
- 2021Unique Ergodicity in the Interconnections of Ensembles with Applications to Two-Sided Marketscited by 1
Built on by
Citing papers per year: 2022: 1; 2023: 1; 2024: 0; 2025: 2.
4 papers.
- 2022Closed-Loop View of the Regulation of AI: Equal Impact across Repeated Interactionscited by 3
- 2025humancompatible.interconnect: Testing Properties of Repeated Uses of Interconnections of AI Systemscited by 1
- 2025Stochastic Sample Approximations of (Local) Moduli of Continuitycited by 1
- 2023Predictability and Fairness in Load Aggregation with Deadbandcited by 0
- 2025Stochastic Sample Approximations of (Local) Moduli of Continuity18 Sep 2025
- 2025humancompatible.interconnect: Testing Properties of Repeated Uses of Interconnections of AI Systems13 Jul 2025
- 2023Predictability and Fairness in Load Aggregation with Deadband28 May 2023
- 2022Closed-Loop View of the Regulation of AI: Equal Impact across Repeated Interactions3 Sep 2022