Correlations and Clustering in Wholesale Electricity Markets

We study the structure of locational marginal prices in day-ahead and real-time wholesale electricity markets. In particular, we consider the case of two North American markets and show that the price correlations contain information on the locational structure of the grid. We study various clustering methods and introduce a type of correlation function based on event synchronization for spiky time series, and another based on string correlations of location names provided by the markets. This allows us to reconstruct aspects of the locational structure of the grid.

[1]  Leonhard Held,et al.  Gaussian Markov Random Fields: Theory and Applications , 2005 .

[2]  L. Tesfatsion,et al.  Locational marginal pricing basics for restructured wholesale power markets , 2009, 2009 IEEE Power & Energy Society General Meeting.

[3]  R. Tibshirani,et al.  Sparse inverse covariance estimation with the graphical lasso. , 2008, Biostatistics.

[4]  Rosario N. Mantegna,et al.  Correlation filtering in financial time series , 2005 .

[5]  Hawoong Jeong,et al.  Systematic analysis of group identification in stock markets. , 2005, Physical review. E, Statistical, nonlinear, and soft matter physics.

[6]  Giulio Cimini,et al.  Stock markets reconstruction via entropy maximization driven by fitness and density , 2016 .

[7]  Steffen Rebennack,et al.  An introduction to optimal power flow: Theory, formulation, and examples , 2016 .

[8]  Vito Latora,et al.  The multiplex dependency structure of financial markets , 2016, Complex..

[9]  Silke Wagner,et al.  Comparing Clusterings - An Overview , 2007 .

[10]  T. Aste,et al.  Correlation filtering in financial time series (Invited Paper) , 2005, SPIE International Symposium on Fluctuations and Noise.

[11]  Francesco Pozzi,et al.  Exponential smoothing weighted correlations , 2012 .

[12]  T. Aste,et al.  Multi-scaling of wholesale electricity prices , 2015, 1507.06219.

[13]  R Quian Quiroga,et al.  Event synchronization: a simple and fast method to measure synchronicity and time delay patterns. , 2002, Physical review. E, Statistical, nonlinear, and soft matter physics.

[14]  Jean-Philippe Bouchaud,et al.  Financial Applications of Random Matrix Theory: Old Laces and New Pieces , 2005 .

[15]  M Tumminello,et al.  A tool for filtering information in complex systems. , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[16]  Jean-Loup Guillaume,et al.  Fast unfolding of community hierarchies in large networks , 2008, ArXiv.

[17]  Ulrike von Luxburg,et al.  A tutorial on spectral clustering , 2007, Stat. Comput..

[18]  Nello Cristianini,et al.  Kernel Methods for Pattern Analysis , 2004 .

[19]  Kenji Fukumizu,et al.  Statistical Convergence of Kernel CCA , 2005, NIPS.

[20]  F. Schweppe,et al.  Optimal Pricing in Electrical Networks over Space and Time , 1984 .

[21]  M E J Newman,et al.  Finding and evaluating community structure in networks. , 2003, Physical review. E, Statistical, nonlinear, and soft matter physics.

[22]  Hans-Peter Kriegel,et al.  Integrating structured biological data by Kernel Maximum Mean Discrepancy , 2006, ISMB.

[23]  M E J Newman,et al.  Community structure in social and biological networks , 2001, Proceedings of the National Academy of Sciences of the United States of America.

[24]  Pablo Jensen,et al.  Analysis of community structure in networks of correlated data. , 2008, Physical review. E, Statistical, nonlinear, and soft matter physics.

[25]  Fabrizio Lillo,et al.  Correlation, Hierarchies, and Networks in Financial Markets , 2008, 0809.4615.

[26]  Guido Caldarelli,et al.  Enhanced capital-asset pricing model for the reconstruction of bipartite financial networks. , 2016, Physical review. E.

[27]  Tomaso Aste,et al.  Correction: Relation between Financial Market Structure and the Real Economy: Comparison between Clustering Methods , 2014, PloS one.

[28]  R. F. Bishop,et al.  Magnetic order in spin-1 and spin-$$\frac{3} {2}$$ interpolating square-triangle Heisenberg antiferromagnets , 2011, 1111.7237.

[29]  D. Garlaschelli,et al.  Community detection for correlation matrices , 2013, 1311.1924.

[30]  J. Bouchaud,et al.  Noise Dressing of Financial Correlation Matrices , 1998, cond-mat/9810255.

[31]  Ying Cui,et al.  Sparse estimation of high-dimensional correlation matrices , 2016, Comput. Stat. Data Anal..

[32]  Bernhard Schölkopf,et al.  Hilbert Space Embeddings and Metrics on Probability Measures , 2009, J. Mach. Learn. Res..