Non-intrusive Monitoring of Edge-level Cryptocurrency Mining in Power Distribution Grids

Abstract

With increasing activities in cryptocurrencies and their fast-growing global mining demand comes new opportunities and challenges facing the electric energy systems. From the electric grid perspective, the key challenges are how to properly monitor and predict cryptocurrency mining demand at wholesale and retail levels. While large-scale mining companies connected to the transmission level can use directly instrument sensors to monitor their mining demand, how to monitor behind-the-meter cryptocurrency mining demand is still an open question. In this paper, we propose an edge-level distribution level Bitcoin mining detection scheme that utilizes smart meter data to detect the on/off status of the mining machines and estimates the power consumption magnitude of the mining load in each house. We investigate the performance of our algorithm with different Bitcoin load variations representing a wide range of possible mining devices and behaviors. Numerical results suggest that the proposed algorithm can detect both the on/off status of these loads with above 94% accuracy and calculate its load magnitude with less than 16% error for common ASIC miners. Building upon this method, aggregators could coordinate individual household mining loads for participation in demand response programs that help reduce peak demand and increase social welfare.