Grid-Aware versus Grid-Agnostic Distribution System Control: A Method for Certifying Engineering Constraint Satisfaction

Molzahn, Daniel K.; Roald, Line

doi:10.24251/hicss.2019.417

Cited by 25 publications

(15 citation statements)

References 34 publications

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“…In these systems, constraint screening can be used to distinguish between constraints which are not important to observe in real time (redundant constraints), and constraints which should be monitored as they will be violated before other constraints (non-redundant constraints). This type of application, which is further discussed in [23], may enable online control applications such as [24], [25] by reducing the measurement requirements.…”

Section: Applications Enabled By Implied Constraint Satisfactionmentioning

confidence: 99%

Implied Constraint Satisfaction in Power System optimization: The Impacts of Load Variations

Roald

Molzahn

2019

2019 57th Annual Allerton Conference on Communication, Control, and Computing (Allerton)

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In many power system optimization problems, we observe that only a small fraction of the line flow constraints ever become active at the optimal solution, despite variations in the load profile and generation costs. This observation has farreaching implications not only for power system optimization, but also for the practical long-term planning, operation, and control of the system. We formalize this empirical observation for problems involving the DC power flow equations. We use a two-step constraint screening approach to identify constraints whose satisfaction is implied by other constraints in the problem, and can therefore be removed from the problem. For the first screening step, we derive analytical bounds that quickly identify redundancies in the flow limits on parallel lines. The second screening step uses optimization-based constraint screening, where we solve a (relaxed) optimization problem for each constraint to identify redundancies. Different from existing methods, we specifically focus our approach on large ranges of load variation such that the results are valid for long periods of time, thus justifying the computational overhead required for the screening method. Numerical results for a wide variety of standard test cases show that even with load variations up to ±100% of nominal loading, we are able to eliminate a significant fraction of the flow constraints. This large reduction in constraints may enable a range of possible applications. As one illustrative example, we demonstrate the computational improvements for the unit commitment problem obtained as a result of the reduced number of constraints.

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Section: Applications Enabled By Implied Constraint Satisfactionmentioning

confidence: 99%

Implied Constraint Satisfaction in Power System optimization: The Impacts of Load Variations

Roald

Molzahn

2019

2019 57th Annual Allerton Conference on Communication, Control, and Computing (Allerton)

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“…Further, for the specific case of power systems, we believe that combining tailored model uncertainty descriptions and pre-processing to identify (and remove) redundant constraints from the problem formulation (see e.g. [23]) will certainly lead to less conservative robust stability guarantees.…”

Section: Discussionmentioning

confidence: 99%

“…By Proposition 3, the OAG algorithm is robustly stable with respect to the uncertainty and reaches the unique online approximate solution (which is, of course, different for every w). Figure 5 shows a simulation of the OAG algorithm for problem (23) applied to the IEEE37 bus system. The algorithm uses feedback on voltage measurements, which are computed by solving the AC power flow equations with 0 2,000 4,000 6,000 8,000 10,000 0.…”

Section: B Robust Feedback Optimization Of a Distribution Feedermentioning

confidence: 99%

Towards robustness guarantees for feedback-based optimization

Colombino

Simpson-Porco

Bernstein

2019

2019 IEEE 58th Conference on Decision and Control (CDC)

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Feedback-based online optimization algorithms have gained traction in recent years because of their simple implementation, their ability to reject disturbances in real time, and their increased robustness to model mismatch. While the robustness properties have been observed both in simulation and experimental results, the theoretical analysis in the literature is mostly limited to nominal conditions. In this work, we propose a framework to systematically assess the robust stability of feedback-based online optimization algorithms. We leverage tools from monotone operator theory, variational inequalities and classical robust control to obtain tractable numerical tests that guarantee robust convergence properties of online algorithms in feedback with a physical system, even in the presence of disturbances and model uncertainty. The results are illustrated via an academic example and a case study of a power distribution system.

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“…Thus, DER coordination under the Market DSO model should effectively account for AC network constraints, which has recently been termed "grid-aware" coordination (as opposed to grid-agnostic coordination) [16]. Grid-aware coordination of DERs has often employed optimization-based methods, such as [17], where the aggregator's DER control signals track a Karush-Kuhn-Tucker (KKT) point that satisfies the KKT optimality conditions.…”

Section: Related Literaturementioning

confidence: 99%

Hierarchical, Grid-Aware, and Economically Optimal Coordination of Distributed Energy Resources in Realistic Distribution Systems

et al. 2020

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Renewable portfolio standards are targeting high levels of variable solar photovoltaics (PV) in electric distribution systems, which makes reliability more challenging to maintain for distribution system operators (DSOs). Distributed energy resources (DERs), including smart, connected appliances and PV inverters, represent responsive grid resources that can provide flexibility to support the DSO in actively managing their networks to facilitate reliability under extreme levels of solar PV. This flexibility can also be used to optimize system operations with respect to economic signals from wholesale energy and ancillary service markets. Here, we present a novel hierarchical scheme that actively controls behind-the-meter DERs to reliably manage each unbalanced distribution feeder and exploits the available flexibility to ensure reliable operation and economically optimizes the entire distribution network. Each layer of the scheme employs advanced optimization methods at different timescales to ensure that the system operates within both grid and device limits. The hierarchy is validated in a large-scale realistic simulation based on data from the industry. Simulation results show that coordination of flexibility improves both system reliability and economics, and enables greater penetration of solar PV. Discussion is also provided on the practical viability of the required communications and controls to implement the presented scheme within a large DSO.

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Grid-Aware versus Grid-Agnostic Distribution System Control: A Method for Certifying Engineering Constraint Satisfaction

Cited by 25 publications

References 34 publications

Implied Constraint Satisfaction in Power System optimization: The Impacts of Load Variations

Implied Constraint Satisfaction in Power System optimization: The Impacts of Load Variations

Towards robustness guarantees for feedback-based optimization

Hierarchical, Grid-Aware, and Economically Optimal Coordination of Distributed Energy Resources in Realistic Distribution Systems

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