Planning for new generation infrastructure in hydrothermal power systems requires consideration of a series of nonlinearities that are often ignored in planning models for policy analysis. In this article, three different capacity-planning models are used, one nonlinear and two linear ones, with different degrees of complexity, to quantify the impact of simplifying the head dependency of hydropower generation on investments in both conventional and renewable generators and system operations. It was found that simplified investment models can bias the optimal generation portfolios by, for example, understating the need for coal and combined-cycle gas units and overstating investments in wind capacity with respect to a more accurate nonlinear formulation, which could affect policy recommendations. It was also found that the economic cost of employing a simplified model can be below 10% of total system cost for most of the scenarios and system configurations analyzed, but as high as nearly 70% of total system cost for specific applications. Although these results are not general, they suggest that for certain system configurations both linear models can provide reasonable approximations to more complex nonlinear formulations. Uncertain water inflows were also considered using stochastic variants of all three planning models. Interestingly, if due to time or computational limitations only one of these two features could be accounted for, these results indicate that explicit modeling of the nonlinear-head effect in a deterministic model could yield better results (up to 0.6% of economic regret) than a stochastic linear model (up to 9.6% of economic regret) that considers the uncertainty of water inflows.
To date, the micro-scale wind resource assessment for complex terrain has always been a challenging mission, due to the flow field complexity caused by the local topography. In this paper, a novel method, combining on-site measurement from multiple masts and computational fluid dynamics (CFD) simulations, is proposed for complex terrain site assessment. It is designed to accomplish the spatial variability reproduction of wind energy distribution, as well as the dynamic wind velocity estimation of any desired positions within the concerned region. CFD simulations are carried out to provide detailed wind fields, which implicitly carry the correlations of physical properties with the concerned space. The on-site measurement data from multiple masts are integrated into the assessment process, to provide dynamical corrections based on the reference solutions obtained from the CFD simulations. A high-resolutional wind resource distribution and accurate wind velocity estimations are achieved. A detailed case study on micro-scale wind resource assessment for a wind farm with complex terrain, located in China is presented for validation.
As a complement to the mandatory structural full‐scale test for wind turbine blades, the method of subcomponent testing has recently been proposed by international standards and guidelines for the experimental investigation of design‐critical full‐scale parts. This work investigated different subcomponent test (SCT) concepts for a trailing edge of an outboard segment from a 34‐m blade. Detailed analytical models to design the SCT concepts with regard to the boundary conditions were derived. Finite element analyses of the SCT's linear response were benchmarked against each other and against the full blade model in terms of displacements, rotations, in‐plane strains, and energy consumption. All SCT concepts were in good agreement with the full‐scale test with respect to the longitudinal strain response but showed deviations in the transverse and shear strain, as well as in the rotational and displacement response.