Model-Driven Quantitative Assessment Method for Flexible Load Adjustability

With the large-scale integration of renewable energy generation and flexible loads, the source-load matching in power grids has become increasingly challenging, necessitating the full exploration of flexible load regulation potential. To conduct quantitative assessment of adjustability capacity for multiple types of flexible loads, this paper first defines six standard indicators for evaluating flexible load adjustability: maximum adjustable capacity, adjustable duration, response time, regulation rate, regulation gradient, and regulation quality. Subsequently, response models are established for various types of flexible loads based on their characteristics, including thermostatically controlled loads, distributed energy storage, electric vehicles, adjustable industrial loads, data centers, and 5G base stations, with detailed descriptions of power constraints, dynamic constraints, and other characteristic constraints for each load type. The models are then established based on standard indicators to quantitatively assess the adjustability of different flexible loads. Finally, a distribution network optimization scheduling model with objectives of maximizing renewable energy accommodation and minimizing system operation cost is constructed and tested in the IEEE 33-bus test system. Results demonstrate that the proposed method can effectively quantify and assess the regulation capacity of flexible loads, and verify the important role of diversified flexible loads in distribution network.