Optimal Forecasting and Control of Mining as a Flexible System for Power Grid Balancing Based on the FCR Method

Abstract

The paper considers the concept of using cryptocurrency mining farms as a flexible load for balancing modern power systems through the Frequency Containment Reserve (FCR) mechanism. The combination of solar generation forecasting and optimal load control algorithms makes it possible to integrate mining into frequency regulation, thereby reducing risks associated with fluctuations in electricity and cryptocurrency prices. A model of dynamic power distribution is proposed, which allocates capacities between selling electricity to the market, using it for mining, or curtailment, depending on frequency deviations in the grid, forecasted generation, and market conditions.

The economic feasibility of this approach is substantiated: during hours of low or negative electricity prices, selling under the “green tariff” often results in losses, while redirecting excess energy to mining ensures more stable revenues. At the same time, mining profitability itself depends on market factors, which makes the application of an intelligent control system particularly relevant. The model includes both day-ahead planning and real-time adjustments, which allows minimizing curtailment, stabilizing cash flows, and improving the efficiency of renewable energy utilization.

The scientific novelty lies in combining renewable energy forecasting, optimal power allocation, and FCR support methods. This approach forms a new business model where mining farms act as active participants in energy markets, providing economic returns while enhancing system stability. The study also highlights the importance of regulatory aspects and the need to account for technical constraints, which determine the conditions for practical implementation. Further research should focus on real-data testing of the model, refinement of control parameters, and possible integration with energy storage systems.