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In recent years, sites with low annual average wind speeds have begun to be considered for the development of new wind farms. The majority of design methods for a wind turbine operating at low wind speed is to increase the blade length or hub height compared to a wind turbine operating in high wind speed sites. The cost of the rotor and the tower is a considerable portion of the overall wind turbine cost. This study investigates a method to trade-off the blade length and hub height during the wind turbine optimization at low wind speeds. A cost and scaling model is implemented to evaluate the cost of energy. The procedure optimizes the blades’ aero-structural performance considering blade length and the hub height simultaneously. The blade element momentum (BEM) code is used to evaluate blade aerodynamic performance and classical laminate theory (CLT) is applied to estimate the stiffness and mass per unit length of each blade section. The particle swarm optimization (PSO) algorithm is applied to determine the optimal wind turbine with the minimum cost of energy (COE). The results show that increasing rotor diameter is less efficient than increasing the hub height for a low wind speed turbine and the COE reduces 16.14% and 17.54% under two design schemes through the optimization.

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A methodology whereby the digging performance of the hydraulic excavator can be determined is presented, with uncertainty during the digging operation being taken into consideration. Natural variability in medium properties and differences in operation styles are the significant sources of uncertainty. The most probable direction interval of the digging resistance obtained from the experimental data is given to quantify the contribution of uncertain medium properties to the variation of the digging resistance direction. A digging capability polygon, which is used to characterize excavator’s capability to apply forces to overcome the digging resistance, is defined by the driving capability constraints of hydraulic cylinders, the stability constraints of the excavator and the most probable direction interval of the digging resistance. A set of significant performance measures, which can be used to quantify the maximum digging capability of the excavator and the exerting extent of the driving capability of hydraulic cylinders, are given based on the digging capability polygon for a given manipulator configuration. The Cartesian workspace of the excavator is discretized into finite digging points to reduce the computational work for global digging performance analysis. Considering differences in operation styles, for each digging point the digging angle is discretized with a certain step and the inverse kinematics approach is taken to derive the manipulator configuration corresponding to each incremental step of the digging angle. Quantitative measures of the global digging performance are proposed according to the performance statistics for all manipulator configurations of all digging points in the entire workspace. These measures can be used to assess the mechanical capability of the working mechanism of a hydraulic excavator and to assess the operation styles used by different operators who have different level of experiences. Finally, the proposed methodology is illustrated using an application example of a 36-ton hydraulic excavator.