Big Data In Smart Grid - Wireless networking, Signal processing and文档.pptx

Case Study of Big Data Analysis for Smart Grid;Overview;Big Data;Big Data Business;However;Smart Grid;Overview;Smart Pricing for Maximizing Profit ;Load Profiling;Question: How to cluster smart meter big data;Bayesian rule Posterior Likelihood Prior μ contains information such as how many clusters, and which sample belongs to which cluster μ should be nonparametric and can be any value Sample the posterior distribution P(μ|Observations), and get values of the parameter μ. ;Generative model vs. Inference algorithm;Generative model: A general idea;Generative model: Stick breaking process:;Generative model; Finding the posterior of the multivariate distribution P(Z|X) Given observation X, what are the probability that it belongs to cluster Z Which cluster a sample belongs to? Painful due to the integrations needed to carry out. ;Nonparametric Bayesian Classification inference  ;Inference model: Posterior distributions;Inference model: Gibbs sampler;Two Gaussian distributed clusters with KL divergence (KLD) 4.5 ;Indian Buffet Process (IBP) ;Load Profiling Results; Sublinear Algorithm Basics; Application in Smart Grid; Smart Pricing Performance;Overview;Sparse Optimization;ADMM problem form (f and g are convex closed proper) Divide one problem into multiple subproblems Augmented Lagrangian function ADMM: Each iteration is not feasible, but converge O(1/k) speed ;Contingency Analysis in Power Grid;Security-constrained Optimal Power Flow;Security-constrained Optimal Power Flow;SCOPF Using ADMM;Results;Conclusion;Reason and Benefit;Funding Summary;Award Summary;Publication Summary; Overview of Wireless Amigo Lab;Research Lab Summary;Thanks