This work analyses the link between the aspect ratio of a vertical-axis straight-bladed (H-Rotor) wind turbine and its performance (power coefficient). The aspect ratio of this particular wind turbine is defined as the ratio between blade length and rotor radius. Since the aspect ratio variations of a vertical-axis wind turbine cause Reynolds number variations, any changes in the power coefficient can also be studied to derive how aspect ratio variations affect turbine performance. Using a calculation code based on the Multiple Stream Tube Model, symmetrical straight-bladed wind turbine performance was evaluated as aspect ratio varied. This numerical analysis highlighted how turbine performance is strongly influenced by the Reynolds number of the rotor blade. From a geometrical point of view, as aspect ratio falls, the Reynolds number rises which improves wind turbine performance.

Abstract:The contribution of renewable energies to the reduction of the impact of fossil fuels sources and especially energy supply in remote areas has occupied a role more and more important during last decades. The estimation of renewable power plants performances by means of deterministic models is usually limited by the innate variability of the energy resources. The accuracy of energy production forecasting results may be inadequate. An accurate feasibility analysis requires taking into account the randomness of the primary resource operations and the effect of component failures in the energy production process. This paper treats a novel approach to the estimation of energy production in a real photovoltaic power plant by means of dynamic reliability analysis based on Stochastic Hybrid Fault Tree Automaton (SHyFTA). The comparison between real data, deterministic model and SHyFTA model confirm how the latter better estimate energy production than deterministic model.

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In this paper, a spiking neural network–based architecture for the prediction of wind farm energy production is proposed. The model is also able to evaluate the wake effects due to interactions between the elements of a wind farm on the energy production of the whole farm. This method has been applied to a large wind power plant, composed of 28 turbines and 3 anemometric towers, located in the rural area of Vizzini's municipality in province of Catania, Italy, that is characterised by a complex orography and an extension of 30 km2. For the implementation of this architecture it was used the “NeuCube” simulator. The results show that the presented method can be successfully applied for predictions of wind energy generation in real wind farm also in presence of faults.

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The present study deals with a comparative evaluation of a single-zone (SZ) thermodynamic model and a 3D computational fluid dynamics (CFD) model for heat release calculation in internal combustion engines. The first law, SZ, model is based on the first law of thermodynamics. This model is characterized by a very simplified modeling of the combustion phenomenon allowing for a great simplicity in the mathematical formulation and very low computational time. The CFD 3D models, instead, are able to solve the chemistry of the combustion process, the interaction between turbulence and flame propagation, the heat exchange with walls and the dissociation and re-association of chemical species. They provide a high spatial resolution of the combustion chamber as well. Nevertheless, the computation requirements of CFD models are enormously larger than the SZ techniques. However, the SZ model needs accurate experimental in-cylinder pressure data for initializing the heat release calculation. Therefore, the main objective of an SZ model is to evaluate the heat release, which is very difficult to measure in experiments, starting from the knowledge of the in-cylinder pressure data. Nevertheless, the great simplicity of the SZ numerical formulation has a margin of uncertainty which cannot be known a priori. The objective of this paper was, therefore, to evaluate the level of accuracy and reliability of the SZ model comparing the results with those obtained with a CFD 3D model. The CFD model was developed and validated using cooperative fuel research (CFR) engine experimental in-cylinder pressure data. The CFR engine was fueled with 2,2,4-trimethylpentane, at a rotational speed of 600 r/ min, an equivalence ratio equal to 1 and a volumetric compression ratio of 5.8. The analysis demonstrates that, considering the simplicity and speed of the SZ model, the heat release calculation is sufficiently accurate and thus can be used for a first investigation of the combustion process.