Data Centers and Electricity Prices in PJM: An Analysis of Load Growth and Trading Opportunities

Abstract

Northern Virginia is home to the world’s largest concentration of data centers, with over 900 facilities and more than 89,000 megawatts of capacity all in a twenty mile radius in Loudoun County. These buildings operate at an almost constant load around the clock, creating persistent and concentrated demand on a system not designed to accommodate it. Despite the huge growth of data centers recently, no prior empirical work has quantified their causal effect on local electricity congestion prices or if it opens trading opportunities. This thesis asks two questions. First, does the concentration of data center load in Northern Virginia drive up electricity congestion prices systematically, and in what way? Second, does that create a pricing pattern that market participants can exploit? This thesis uses seven years of hourly day-ahead and real-time locational marginal price data from PJM Interconnection, covering January 2019 through March 2026, along with operational data for 932 data center facilities, and a graph of the PJM transmission network. This thesis uses a difference-in-differences design, a network- based proximity measure, and a walk-forward trading model to answer both questions. The results show that data center load accumulation caused a significant and persistent congestion premium at grid nodes close by. It increased overall congestion prices, as well as the frequency of price spikes. This thesis creates theoretical models that estimate the congestion effect of any proposed data center based on its size and electrical proximity to a pricing node. While directional trading models were fairly accurate, adding in data center data did not substantially improve the models. The constant load and public nature of data centers makes it so that their information is reasonably priced in. These findings show that data center growth drastically changes price dynamics in affected areas. While no short-term trading edge is found from public DC data directly, the persistent congestion premium and elevated volatility off