Adaptive real-time grid operation via Online Feedback Optimization with sensitivity estimation

Picallo, Miguel; Ortmann, Lukas; Bolognani, Saverio; Dörfler, Florian

doi:10.1016/j.epsr.2022.108405

Cited by 13 publications

(19 citation statements)

References 13 publications

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“…Note that in order to execute (13), we would need to compute ∂h k−1 (ϕ, ξ)/∂ϕ for ϕ = q k−1 and ξ = ξ k−1 . This computation can be done by manipulating the power flow Jacobian without necessarily solving the power flow equations; however, it requires knowing the value of ξ k−1 , which we have assumed it is not a priori known.…”

Section: Model-based Feedback Optimizationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…The framework proposed in this paper is closely related to that presented in [13], which proposes a model-free, real-time optimal power flow solver through feedback optimization. Similar to the approach we adopt here, [13] proposes a datadriven online approach to learn a model of input-output sensitivities. The objective function of the online feedback optimization formulated is the operational cost of the inputs, and the inequality constraints are the operational limitations on the inputs.…”

Section: Introductionmentioning

confidence: 99%

“…In addition, the sensitivity estimate in our work is computed using all previous measurements with less weights assigned to older measurements. Finally, while the proposed scheme in [13] does not account for the constraints on control inputs when attempting to generate persistently exciting inputs, our work does take this important issue into account.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

An Online Feedback Optimization Approach to Voltage Regulation in Inverter-Based Power Distribution Networks

Domínguez-García¹,

Zholbaryssov²,

Amuda³

et al. 2023

Preprint

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We address the problem of controlling the reactive power setpoints of a set of distributed energy resources (DERs) in a power distribution network so as to mitigate the impact of variability in uncontrolled power injections associated with, e.g., renewable-based generation. We formulate the control design problem as a stochastic optimization problem, which we solve online using a modified version of a projected stochastic gradient descent (PSGD) algorithm. The proposed PSGDbased algorithm utilizes sensitivities of changes in bus voltage magnitudes to changes in DER reactive power setpoints; such sensitivities are learned online via a recursive least squares estimator (rLSE). To ensure proper operation of the rLSE, the sequence of incremental changes in DER reactive power setpoints needs to be persistently exciting, which is guaranteed by a mechanism built into the controller. We analyze the stability of the closed-loop system and showcase controller performance via numerical simulations on the IEEE 123-bus distribution test feeder.

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Section: Model-based Feedback Optimizationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

An Online Feedback Optimization Approach to Voltage Regulation in Inverter-Based Power Distribution Networks

Domínguez-García¹,

Zholbaryssov²,

Amuda³

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

“…( 22) with sampled pairs {x u m , u m } M m=1 , where u m are random control inputs which can be zero-mean white noise signals, e.g. a truncated Gaussian distribution [30]. Define…”

Section: Koopman-operator-based Emergency Frequency Control Strategymentioning

confidence: 99%

Data-driven Emergency Frequency Control for Multi-Infeed Hybrid AC-DC System

Cao¹,

Liu²,

Chen³

2022

Preprint

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With the continuous development of large-scale complex hybrid AC-DC grids, the fast adjustability of HVDC systems is required by the grid to provide frequency regulation services. This paper develops a fully data-driven linear quadratic regulator (LQR) for the HVDC to provide temporal frequency support. The main technical challenge is the complexity and the nonlinearity of multi-infeed hybrid AC-DC (MIDC) systems dynamics that make the LQR intractable. Based on Koopman operator (KO) theory, a Koopman eigenpairs construction method is developed to fit a global linear dynamic model of MIDC systems. Once globally linear representation of uncontrolled system dynamics is obtained offline, the control term is constituted by the gradient of the identified eigenfunctions and the control matrix B. In case that B is unknown, we propose a method to identify it based on the verified Koopman eigenfunctions. The active power reference is optimized online for LCC-HVDC in a moving horizon fashion to provide frequency support, with only locally measurable frequency and transmission power. The robustness of the proposed control method against approximation errors of the linear representation in eigenfunction coordinates is analyzed. Simulation results show the effectiveness, robustness and adaptability of the proposed emergency control strategy.

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