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Low-head microhydro systems for energy production are becoming accepted because of oil crises and new advances in their design and efficiencies. As this is still a new area for development and experimentation, it is important to test and validate the optimal conditions and the hydrodynamic behaviour of such systems under different conditions. The aim of this paper is to present a turbine design validation practise, which researchers and equipment manufactures can use for the hydrodynamic behaviour analysis of new low-head turbines prior to production and application. Laboratory experimental tests and advanced CFD numerical analysis are described for the flow behaviour analysis of a new prototype microtubular propeller. Laboratory experimental results are presented and used for the evaluation of the turbine performance curves. Comparisons between experimental and CFD results are also presented. Finally, an assessment of the hydrodynamic behaviour is made for a scaled model application, using the theory of turbomachine similarity.

The purpose of this paper is to analyze different storage pond configurations used to manage the water inflow from storm events and to establish a methodology to optimize the energy production using this water. The case study area is a catchment based on the Alcântara zone, in Lisbon, Portugal. This is an urban area, which faces severe occurrences of storm events. These events are caused by a non-efficient drainage system, and the proximity of the river and the sea, which cannot handle large storm event inflows. Due to climate change effects, the storm rainfall hyetographs are modified and runoff in this urban area has increased for the last decades causing major inundations.The Danish Hydraulic Institute (DHI) MIKE BASIN (MB) and Bentley PondPack software are used to define solutions for this case study by embodying some of the Alcântara's catchment characteristics. Different relevant components used to create the models are presented. In order to model completely the studied area, several physical elements such as reservoirs or hydropower plants are included. The Nedbør-Afstrømnings-Model (NAM model) is also presented. It is a rainfall-runoff simulator, included in DHI MB, which can create runoff time series from rainfall time series. The methodologies used to optimize energy production in each of case studies developed are detailed. Results are presented showing that some ponds configurations permit to produce more energy than others and the production of energy can be maximized by optimizing the hydropower production target demand.