Recently, there has been increased interest in designing stand-alone Hybrid Renewable Energy Systems (HRES) for remote communities. Several methodologies have been proposed to tackle the design optimization problem, to develop strategies for optimal operation/dispatch, or to address both problems concurrently. So far, however, these methods have been developed only for specific communities or system configurations (e.g., wind-diesel; PV-diesel). In this study, we propose a multilevel design optimization method that considers both optimal component selection and dispatch strategy that can be applied to any community regardless of the available renewable resources, thus overcoming the limitations of previous studies. The new approach considers a wide range of renewable and non-renewable energy technologies, a database of commercially available components, and leverages state-of-the-art methods for solving each optimization subproblem. The novel algorithm was evaluated with a set of meteorological conditions that emulate different remote communities. In addition, two pricing scenarios for diesel are studied to explore how the HRES design is influenced by this parameter.
Developing Wind Power Simulations And Laboratory Experiments For Courses In Renewable Energy Systems