Constructing Convex Inner Approximations of Steady-State Security Regions

Nguyen, Hung D.; Dvijotham, Krishnamurthy; Turitsyn, Konstantin

doi:10.1109/tpwrs.2018.2868752

Cited by 53 publications

(28 citation statements)

References 20 publications

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“…The problem ( 7) is widely used in literature [29]. One challenge associated with this optimization is the nonlinear and non-convex power flow constraints that makes solving this control problem inefficient.…”

Section: A Centralized Voltage Controlmentioning

confidence: 99%

Optimal Steady-State Voltage Control Using Gaussian Process Learning

Pareek

Weng

Nguyen

2021

IEEE Trans. Ind. Inf.

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Section: A Centralized Voltage Controlmentioning

confidence: 99%

Optimal Steady-State Voltage Control Using Gaussian Process Learning

Pareek

Weng

Nguyen

2021

IEEE Trans. Ind. Inf.

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“…We propose Algorithm 1 to approximate U defined in (7). It starts with a region U poly that is chosen based on experience and large enough to contain U .…”

Section: B Approximating Socp-relaxed Feasible Regionmentioning

confidence: 99%

“…For instance, reference [5] solved nonlinear programs to get a set of boundary points that each make a different safety limit binding, and then built a feasible region heuristically as the convex hull of those boundary points. Certified inner approximations of feasible regions were solved from convex programs based on a tightened-relaxed second-order cone approximation [6] or refined linear approximations [7], [8] to AC power flow. In particular, the refined linearizations [7], [8] may be more accurate than the DC models [1]- [3], by replacing the nonlinear terms with their improved constant estimates rather than zero.…”

Section: Introductionmentioning

confidence: 99%

“…Certified inner approximations of feasible regions were solved from convex programs based on a tightened-relaxed second-order cone approximation [6] or refined linear approximations [7], [8] to AC power flow. In particular, the refined linearizations [7], [8] may be more accurate than the DC models [1]- [3], by replacing the nonlinear terms with their improved constant estimates rather than zero. However, such estimation typically only works for a specific objective function that merely explores the feasible region towards a single direction or with a specific shape of the power injection vector.…”

Section: Introductionmentioning

confidence: 99%

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Improved Approximation of Dispatchable Region in Radial Distribution Networks via Dual SOCP

Chen¹,

Zhao²

2021

Preprint

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We develop an optimization method to approximate the region of feasible power injections in distribution networks. Based on the nonlinear Dist-Flow model of an alternatingcurrent (AC) network with a radial structure, we first formulate a power-injection feasibility problem considering voltage and current limits. The feasibility problem is then relaxed to a convex second-order cone program (SOCP). We utilize the strong dual problem of the SOCP to construct a convex polytopic approximation of the SOCP-relaxed feasible power injection region. We further develop a heuristic method to approximately remove the power injections that make the SOCP relaxation inexact, thus establishing an approximate polytope of solvable and safe power injections. Numerical results demonstrate a satisfactory balance reached by the proposed method between the accuracy of approximation and the simplicity of computation.

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“…The research on "SSSR" proposed in the literature study [20] could improve the shortcomings of static security analysis of multi-energy systems to a certain extent. An algorithm to construct inner approximations of static security was developed [21]. Furthermore, the maximal static security region was also proposed [22].…”

Section: Introductionmentioning

confidence: 99%