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Real-Time Estimation of Support Provision Capability for Poor-Observable Distribution Networks

Mohammad Jafarian, Alireza Nouri, Valentín Rigoni, Andrew Keane

2022IEEE Transactions on Power Systems13 citationsDOIOpen Access PDF

Abstract

An indispensable step towards coordinating the actions of distribution and transmission system operators ( <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">dso</small> s- <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">tso</small> ) is to estimate the range of flexibility that can be offered to the <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">tso</small> by <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">dso</small> s. Within this context, a data-driven probabilistic approach is proposed to evaluate the capability of a distribution network in providing active and reactive power support in real-time. To this end, in an offline phase, a linear discriminant analysis model, together with a piecewise linear model of the distribution network are trained to delineate the boundary of a region representing the adherence to distribution network operational constraints. In the implementation phase, this region comprises the feasible set of a series of optimization problems, formulated to determine the support provision capability. These optimization problems are of iterative linear programming type, which allows for real-time applicability. The evaluated support capability can be deemed as the available reserve in real-time transmission operation, which enables providing a coordinated response towards unexpected events, and facilitates the participation of distributed resources in the balancing market by granting an up-to-date estimation of available supports. This approach is tested on the IEEE 123-node system and verified through comparison with an AC optimal power flow technique.

Topics & Concepts

Computer scienceFlexibility (engineering)Probabilistic logicSet (abstract data type)Linear programmingRange (aeronautics)Context (archaeology)Mathematical optimizationData miningArtificial intelligenceAlgorithmMathematicsEngineeringProgramming languagePaleontologyStatisticsBiologyAerospace engineeringOptimal Power Flow DistributionSmart Grid Energy ManagementElectric Power System Optimization