High penetration of distributed solar generation creates operational challenges for electric utilities, including voltage fluctuations, power quality issues, and the need to balance economic efficiency with grid stability. A research team has developed a comprehensive optimization framework designed to manage these competing demands through coordinated, multi-timescale control.
The proposed system operates in two distinct phases. During the day-ahead planning stage, discrete devices such as on-load tap changers and capacitor banks are optimized to minimize daily power losses, voltage deviations, and equipment wear costs based on solar forecasts. This layer handles slower, strategic adjustments. In the intraday operational stage, faster-responding devices—PV inverters, static VAR compensators, and battery storage systems—actively mitigate real-time solar fluctuations and maintain voltage within acceptable ranges.
To solve this complex optimization problem efficiently, the researchers developed an Improved Crocodile Ambush Optimization Algorithm (ICAOA). This enhanced metaheuristic incorporates several innovations: a Sobol sequence initializes the population more effectively, adaptive parameters adjust dynamically during the search process, and a hybrid perturbation strategy improves convergence speed and solution quality.
Validation testing on the IEEE 33-bus distribution system demonstrated strong results. The day-ahead stage achieved a daily power loss of just 1.02 MWh with average voltage deviation of 0.014 per unit. Intraday rolling-horizon optimization further reduced losses to 0.032 MWh while maintaining zero voltage violations throughout the simulation period.
This framework addresses a critical need as distributed solar capacity continues expanding globally. By automating multi-timescale coordination of both discrete and continuous control devices, utilities can accommodate higher renewable penetration without compromising reliability or economic performance. The dual-layer approach efficiently divides computational effort between planning and real-time execution, making it practical for implementation in modern distribution management systems.
