Enhancing Solar Power Projects Viability Through AI-Optimized Ramp Rate Control for Voltage Management in Distribution Networks

PV system under various operational scenarios, with a focus on optimizing voltage performance through intelligent ramp rate management.

This study was collected over the entire month of April 2023, comprising one-minute interval measurements of PV output, load demand, and step voltage. The simulation framework explores a broad set of scenarios, including two system capacities (3 MW and 6 MW), two weather conditions

(sunny and cloudy days), and three ramp rate control strategies: (1) No Ramp Rate Control, (2)

Fixed Ramp Rate Limit, and (3) AI-Optimized Ramp Rate Control.

Each configuration was analyzed to evaluate its impact on compliance to step voltage max allowable limit, and overall energy output. The no-control scenario resulted in frequent and unpredictable voltage disturbances, especially under high-capacity output during sunny periods. The fixed ramp rate strategy using the limit in voltage energy output, it introduced a degree of improvement but remained insufficient to handle more demanding load and weather variability conditions, particularly in larger systems.

In contrast, the proposed AI-based ramp control model dynamically adapted the solar output based on real-time voltage readings, historical generation, and load profile. It consistently maintained the voltage drop within acceptable operational boundaries and contributed to smoother transitions during fluctuating weather conditions.