On the Statistical Settings of Generation and Load in a Synthetic Grid Modeling
For power system researchers, this provides a more realistic synthetic grid modeling method, though it is an incremental improvement over existing approaches.
The paper develops a method to generate statistically correct random generation capacities and load settings for synthetic power grid models, using exponential distributions and correlations with nodal degree. The approach improves realism over random assignment.
This paper investigates the problem of generation and load settings in a synthetic power grid modeling of high-voltage transmission network, considering both electrical parameters and topology measures. Our previous study indicated that the relative location of generation and load buses in a realistic grid are not random but correlated. And an entropy based optimization approach has been proposed to determine a set of correlated siting for generation and load buses in a synthetic grid modeling. Using the exponential distribution of individual generation capacity or load settings in a grid, and the non-trivial correlation between the generation capacity or load setting and the nodal degree of a generation or load bus we develop an approach to generate a statistically correct random set of generation capacities and load settings, and then assign them to each generation or load bus in a grid.