<p>In recent years, cryptocurrency mining has become a profitable and secure activity especially in countries with low energy prices. However, this activity leads to various concerns about excessive energy consumption, harmonic propagation and power quality degradation, and different tariffs paid for used energy. In this regard, a new methodology has been proposed in this paper using harmonic measurements for identification of cryptocurrency mining farms via harmonic state estimation (HSE) concept. The proposed method employs harmonic pollutant behavior of cryptocurrency miners for their identification. It employs various harmonic measurements to determine the harmonic power injected into the network using the HSE algorithm, allowing for the detection of different types of illegal mining farms. The methodology has been validated using DIgSILENT PowerFactory software across various test networks. The results demonstrate the ability of the proposed method to identify the location of illegal cryptocurrency mining farms and unauthorized energy consumption using HSE. Detection of changing the application type of consumers to partly/fully incorporate illegal miners is also available using the proposed method. The above will lead to improved conditions of sustainable energy supply and maintenance of power quality at the distribution network level.</p>