The expansion of renewable energies and the concomitant compensatory measures, such as the expansion of the electricity grid, the installation of energy storage facilities, or the flexibilization of demand, lead to a more elaborated energy supply system. Furthermore, the technological development of small power plants has further progressed, and many novel technologies have achieved grid parity. For manufacturing companies, the integration of renewable generation plants at their own site therefore represents a promising strategy for being both technically independent of the electricity grid and autonomous of price policy decisions and volatile market prices. This paper outlines the existing decentralized, renewable power generation technologies, their energetic modeling, and a hybrid optimization methodology for their dimensioning that uses mixed integer linear programming (MILP) and linear programming (LP) problem formulation. Finally, the introduced dimensioning method is applied to an exemplary manufacturing company that is assumed to be in the central part of Germany and located in the metalworking sector. The company has an electricity demand of approximately 20,000 MWh/a. The optimization results in a maximum expansion of PV and the use of CHP to cover the base load leading to a promising energy cost reduction of almost 20%.