Point Estimate Schemes to Solve the Probabilistic Power Flow

By Juan M. Morales, Juan Pérez-Ruiz. IEEE Transactions on Power Systems, 2007

669 citations recorded by the source corpus.

Subfields: Electrical and Electronic Engineering, Safety, Risk, Reliability and Quality, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/be5bf2f970f176c831db02f1c0550b2b0b758ec7

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Citations in the corpus

Probabilistic Load Flow Modeling Comparing Maximum Entropy and Gram-Charlier Probability Density Function Reconstructions (2013, methodology): “FEPES will also include multi-linearization [5], recombining convolved solutions at significant points (mean, 1, 2 and ) and a modified point estimate method [12], [38] for determining nonlinear mean values in the AC case, thereby improving tail”
Basis-Adaptive Sparse Polynomial Chaos Expansion for Probabilistic Power Flow (2017, neutral): “tainty from the inputs to the outputs in the form of statistical moments [13], [14].”
Parzen Window Density Estimator-Based Probabilistic Power Flow With Correlated Uncertainties (2016, methodology): “The rest of the procedure for PEMs is as described in [18].”
A hybrid of ant colony optimization and artificial bee colony algorithm for probabilistic optimal placement and sizing of distributed energy resources (2015, methodology): “Different types of approximation methods are utilized in the field of engineering systems under uncertainty [22].”
A Multi-Objective Transmission Expansion Planning Framework in Deregulated Power Systems With Wind Generation (2014, methodology): “A NSGA II-based POPFwas used to determine trade-offs between reliability measures, absorption of private investments and installation costs for different solutions.”
Probabilistic Load Flow Evaluation With Hybrid Latin Hypercube Sampling and Cholesky Decomposition (2009, methodology): “The deterministic adopted data of IEEE 118-bus test system are introduced in [30] and probabilistic data assumptions are the same as [16].”
Interval Power Flow Analysis Using Linear Relaxation and Optimality-Based Bounds Tightening (OBBT) Methods (2015, methodology): “Probabilistic method was used in [6]–[8] where equations were linearized for further convolution.”
Probabilistic load flow in systems with wind generation (2009, methodology): “Another recent proposal is the Point Estimate method [9], [10], that approximates the moments of the system variables of interest.”