In this talk we introduce a globally convergent numerical method for solving optimization problems with non-linear PDE constraints. Therefore we use projection-based reduced-order-models and accelerated with hyperreduction (empirical quadrature). We embed this algorithm in a trust-region framework. Furthermore we adapt the method to optimization problems with PDE constraints and constraints in the parameterspace.