My PhD-project is motivated by the observation that current state of the art global NLP-solvers fail at small sized polynomial optimization instances. From a semi-algebraic point of view polynomial optimization problems (POP) can be reformulated to the taks of optimizing a linear function over a complicated convex set. Using this view we are trying to find good relaxations of this complicated convex set by easier sets and utilizing these in a new algorithm and solver.