امكان‌سنجي كاهش ريسك برنامه‌ريزي روز بعد خرده‌فروش به كمك بهره‌برداري از ماينرهاي ارزهاي ديجيتال

In power systems, a fundamental requirement is the balance between generation an‎d consumption. However, due to inaccuracies in load an‎d generation forecasting, discrepancies between scheduled an‎d actual power often arise. Retailers are obligated to fulfill their supply commitments based on contracts with end-users. If actual consumption exceeds the forecasted amount, the retailer faces financial losses, as they are forced to procure the additional power from the high-price Real-Time Market (RTM) rather than the Day-Ahead Market (DAM). Conversely, lower-than-anticipated consumption leads to surplus energy, which, if not sold in the RTM, subjects the retailer to imbalance penalties. Consequently, inherent forecasting errors impose significant financial risks on retailers. Energy Storage Systems (ESS), specifically high-capacity batteries, serve as a viable mitigation strategy. These systems enable retailers to store surplus energy to avoid penalties during periods of overestimation an‎d inject stored power during supply deficits, thereby reducing reliance on the RTM. Nevertheless, high capital costs remain a primary barrier. eva‎luating the economic feasibility of battery investment requires a comprehensive study of parameters such as subscriber counts, consumption profiles, an‎d time-varying electricity prices to determine whether battery deployment effectively mitigates risk an‎d enhances profitability. Cryptocurrency mining rigs, acting as flexible loads, offer dual utility: they function as consumers an‎d can serve as supplementary revenue streams for retailers. The results of this study indicate that scheduled energy procurement an‎d sales vary across different scenarios, ranging between 1.6 MW an‎d 4.5 MW. In certain cases, such as Scenario 9, the power imbalance reaches -0.75 MW. Furthermore, battery performance analysis reveals that optimal battery capacity peaks at 1.75 MW, while in the worst-case scenario, it is non-existent. Concurrently, the profitability of Bitcoin mining—a function of Bitcoin price, network difficulty, miner power consumption, an‎d the number of active units—is integrated as a key metric for economic eva‎luation. Comparative analysis in Chapter 4 demonstrates that the integration of cryptocurrency miners an‎d energy storage systems significantly improves power management, reduces uncertainty, an‎d maximizes retailer profitability. The synergistic operation of batteries an‎d mining rigs is also investigated. In this configuration, profitability is contingent upon several factors, including Bitcoin market price, time-of-use (TOU) electricity prices, blockchain network difficulty, miner return on investment (ROI), the number of active miners, an‎d battery capacity.

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