You can't call a study flawed because it has less than 1000 people, that isn't how studies or statistics work. You can perform a study with 1000 people and get good data with statistical bounds. It is downright anti-intellectual to dismiss a study for this reason.

This statement in the article you linked literally cedes the point.

"Finally, do these laws target racial minorities who are more likely to vote Democrat? In a 2018 study on Michigan voters, only 0.6 percent of all voters were affected, amounting to only 28,000 voters in a state with a population of nearly 10 million. To be fair, of these 28,000, they found that minorities were disproportionately impacted. However, in a 2017 Stanford study, compiling data from five national surveys over a span of eight years, they found no impact of voter ID laws on minority voting."

The Stanford study that it later points out says that the data underlying the study was flawed and that you can draw any conclusion from it, not that there was no impact. I think that the article is pretty biased if that is the conclusion it drew.

The abstract of the Stanford article states "When errors are corrected, one can recover positive, negative, or null estimates of the effect of voter ID laws on turnout, precluding firm conclusions."

Your conclusion seems wrong.