The paper addresses the need for alternative energy sources to supply decentralized regions of Kyrgyzstan—particularly farming communities and geological survey teams—with reliable electric and thermal power. Given that over 80% of the country's territory is mountainous, utilizing the energy of mountain rivers through the development of small or micro hydropower plants (HPPs) is a national priority. A central challenge in designing such systems is the selection of an appropriate hydroturbine, as this choice directly impacts the efficient use of the fluctuating water flow in mountainous terrain. Seasonal and climatic variations cause changes in water head and flow rate, making it difficult to maintain the turbine’s rated power output throughout the year. To explore effective ways of adapting turbine performance to these variable conditions, the study proposes a simulation-based laboratory setup. The experimental stand is built around a pair of AC machines: an asynchronous (induction) motor, which simulates the mechanical power generation from a hydroturbine, and a synchronous generator, which models the electrical load using a combination of active and reactive components. The turbine’s mechanical characteristics are derived through CFD modeling using FlowVision software, which solves the Navier–Stokes and continuity equations to determine turbine head as a function of power output. These data are then transformed into universal turbine performance curves used to replicate turbine behavior in the lab. Variations in river head or flow rate are simulated via a frequency converter and nonlinear control block, enabling the induction motor to imitate changes in turbine speed and output power. The system’s built-in PI controllers ensure stable operation across different operating conditions. This approach provides a practical framework for evaluating turbine designs under real-world variability in mountain water resources, supporting more efficient deployment of micro-HPPs in remote and energy-scarce regions.