Combination of linear power flow tools for voltages and power estimation on MV networks

Buire, Jerome; Guillaud, Xavier; Colas, Frédéric; Dieulot, Jean-Yves; Alvaro, Leticia De

doi:10.1049/oap-cired.2017.0806

Cited by 5 publications

(9 citation statements)

References 7 publications

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“…This figure shows the feasible region created by this constraint is convex. This result can be extended to the feasible region created by all the constraints (25).…”

Section: Resultsmentioning

confidence: 95%

“…The results from the optimization problem that minimizes (24) s.t. (25) can be compared with classical control tuning methods. The first method assumed no reactive power control that is Q p = 0.…”

Section: Resultsmentioning

confidence: 99%

“…Simulations of real distribution networks have shown that the real error is lower than 0.001 pu for 86% of configurations of real networks. The theoretical error is below 0.01 pu [25]. A simple estimation of current lines is obtained by the admittance matrix and Ohm's law (6).…”

Section: Linear Stochastic Power Flow Model Under Linear Controlmentioning

confidence: 99%

“…Paper [24] proposes a more general model which considers networks with shunt elements, several slack buses, and displays a larger validity domain. The practical performances and validity domain of this model have been evaluated using an industrial distribution grid in [25].…”

Section: Linear Stochastic Power Flow Model Under Linear Controlmentioning

confidence: 99%

“…Moreover, the confidence levels η i , δ i that the constraints respectively on DG powers and line currents are respected should exceed a contractual value. All the mandatory constraints are summed up in equation (25).…”

Section: Convexity Of the Subproblemsmentioning

confidence: 99%

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Convex formulation of confidence level optimization of DG affine reactive power controllers in distribution grids

Buire

Dieulot

Colas

et al. 2020

Electric Power Systems Research

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is an open access repository that collects the work of Arts et Métiers ParisTech researchers and makes it freely available over the web where possible. This is an author-deposited version published in: https://sam.ensam.eu Handle ID AbstractVolatile productions and consumptions generate a stochastic behavior of distribution grids and make its supervision difficult to achieve. Usually, the Distributed Generators reactive powers are adjusted to perform decentralized voltage control. Industrial controllers are generally equipped with a local affine feedback law, which settings are tuned at early stage using local data. A centralized and more efficient tuning method should aim to maximize the probability that all the node voltages of distribution grids remain within prescribed bounds. When the characteristics of the stochastic power forecasts are known, the centralized algorithm allows to update the settings on a regular time basis. However, the method requires to solve stochastic optimization problem. Assuming that stochastic variables have Gaussian distributions, a procedure is given which guarantees the convergence of the stochastic optimization. Convex problems drastically reduce the difficulty and the computational time required to reach the global minimum, compared to nonconvex optimal power flow problems. The linear controllers with optimized parameters are compared to traditional control laws using simulations of a real distribution grid model. The results show that the algorithm is reliable and moreover fast enough. Hence, the proposed method can be used to update periodically the control parameters.

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“…This figure shows the feasible region created by this constraint is convex. This result can be extended to the feasible region created by all the constraints (25).…”

Section: Resultsmentioning

confidence: 95%

Section: Resultsmentioning

confidence: 99%