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Optimal Power Flow Models With Probabilistic Guarantees: A Boolean Approach

Miguel A. Lejeune, Payman Dehghanian

2020IEEE Transactions on Power Systems17 citationsDOI

Abstract

The legacy Optimal Power Flow (OPF) dispatch in electric power grids with high proliferation of renewables can be at risk due to the lack of awareness on major uncertainties, and sudden changes in renewable outputs. This may, in turn, result in conditions where transmission line power flows are significantly exceeded, and subsequent automatic protective actions take place. This letter presents a new generalized joint chance-constrained model for the OPF problem that effectively captures the stochasticity in renewable power generation in the system. In dealing with the complexity, and non-convexity of the proposed optimization model with probabilistic guarantees, we propose a novel tractable Boolean method to transform the model into an equivalent deterministic mixed-integer linear problem, which can be solved quickly, and efficiently by off-the-shelf solvers. Numerical results verify the effectiveness of the proposed model, and the suggested Boolean methodology.

Topics & Concepts

Probabilistic logicMathematical optimizationConvexityComputer scienceElectric power systemRenewable energyEconomic dispatchPower flowComputational complexity theoryAC powerPower (physics)AlgorithmMathematicsEngineeringArtificial intelligenceEconomicsQuantum mechanicsFinancial economicsPhysicsElectrical engineeringOptimal Power Flow DistributionElectric Power System OptimizationPower System Reliability and Maintenance
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