Hello!
Statistical power indicates the probability that we will detect an effect if there is a real effect to be found (i.e., a true positive). Type II error indicates the probability that we will not detect an effect if there is a real effect to be found (i.e., a false negative).
For the first part of your question, that's answer A.
For the second part of your question, if we increase the significance level, we're less likely to capture a true positive. This means the statistical power decreases. We're more likely to get a false negative. This means the Type II error increases. That's answer D.
It might be helpful to look for a table summarizing Type I and Type II error (e.g., there's a nice one on Scribbr), which can be a helpful tool for these kinds of questions.
Best of luck!