Correlations and Clustering in Wholesale Electricity Markets

TL;DR

This paper analyzes the structure of wholesale electricity market prices, using correlation and clustering methods to reveal the underlying locational grid structure from price data.

Contribution

It introduces novel correlation functions based on event synchronization and string analysis to uncover grid structure from market prices.

Findings

Price correlations reveal locational information.

New clustering methods effectively reconstruct grid structure.

Event synchronization captures spike-based price relationships.

Abstract

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.