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The AquaCrop simulation model, originally designed for annual crops, is expanded here to simulate alfalfa, a perennial forage crop. A new routine was added to the model to mimic the assimilate partitioning between above and below-ground plant parts to account for the utilization of reserves in Spring and for their storage in the Fall. The simulation of the transfer of assimilates requires only three extra crop parameters which makes the model also easy to calibrate. To evaluate the model, yield data collected in Louvain-La-Neuve (Belgium), Isparta (Turkey), and Ottawa (Canada) for different alfalfa cultivars, various years and field and irrigation management strategies were used. To assess the accuracy and robustness of the simple assimilate remobilization process, simulations were run for the three different environments with a common set of crop parameters which were parameterized. The dispersion between the observed and simulated cumulative dry above-ground biomass during the growing cycle was small (r² = 0.97; nRMSE = 11%; Nash-Sutcliffe model EF = 0.97), and a systematic over- or underestimation by the model was not observed (Willmott's index of agreement, d = 0.99). When evaluating the goodness of fit of the 81 individual harvest events, the results were still very satisfactory although the nRMSE doubled. The simulations indicated that the AquaCrop model adapted to perennial crops and with a novel storage-remobilization routine, could predict well alfalfa yields in various climates and environments, with and without water and fertility stress, and for three different alfalfa cultivars. • The AquaCrop simulation model is expanded to simulate perennial forage crops. • A simple routine describes the transfer of assimilates between the above ground biomass and the below-ground storage organs. • Variations in partitioning along the season was simulated by increasing or reducing the crop water productivity. • Simulations were run with a common set of crop parameters for different years, alfalfa cultivars, climates, and environments. • The simulations indicated that AquaCrop can well predict the total yield of alfalfa that can be expected in various environments. [ABSTRACT FROM AUTHOR]

In recent years, numerous research works have been reported on the flexural response of aluminium alloy tubular cross-sections. However, studies on monosymmetric cross-sections and particularly channel (C-) sections are limited, albeit their increased usage in structural applications. This paper aims to address this knowledge gap providing an improved understanding about the minor axis bending behaviour of C-sections through an experimental and numerical investigation. In total 14 specimens made from 6082-T6 heat-treated aluminium alloy were subjected to four-point bending. Tensile coupon tests were also performed to determine the mechanical properties of the examined aluminium alloy. The obtained experimental results are analysed and discussed. A series of geometrically and materially nonlinear analyses were also carried out to study the flexural performance of C-sections in two aluminium alloys and two bending orientations over a range of cross-sectional aspect ratios and slendernesses. The experimental and numerical results are utilised to assess the European design standards. The applicability of the Continuous Strength Method and the Direct Strength Method is also evaluated. An alternative design method based on the plastic effective width concept is proposed for slender C-sections subjected to minor axis bending. This method accounts for the inelastic reserve capacity which is in accordance with the experimental and numerical observations. • Flexural response of aluminium alloy C-sections is investigated. • 14 four-point minor axis bending tests are reported. • A wide parametric study is carried out. • Current codified design provisions are assessed. • The plastic effective width method is proposed for slender C-sections under minor axis bending. [ABSTRACT FROM AUTHOR]

• Reserve capacity activation is explicitly modelled for hydropower plants. • A new hybrid stochastic-robust optimization model is formulated. • The column-and-constraint generation technique is used to create extreme scenarios. • The new hybrid model is compared to the standard stochastic and robust formulations. As the penetration of variable renewable power generation increases in power systems around the world, system security is challenged. It is crucial to coordinate the available flexible generating resources, such as hydropower, to meet the need for system balancing. However, reserved capacity on hydropower plants should only be activated if there is sufficient energy or storage capacity to either increase or decrease production. The potential change in production will also affect all reservoirs and plants connected by the cascaded topology. These issues are largely ignored or simplified in hydropower reserve scheduling models. To properly account for the possible activation of reserved capacity, several two-stage model formulations based on stochastic and robust optimization are presented and compared in this paper. The uncertainty in net load deviations due to forecasting errors in renewable power generation is considered the source of reserve capacity activation. The case study based on a real Norwegian watercourse clearly shows the benefit of using any of the two-stage model solutions over the standard deterministic reserve procurement. A novel hybrid stochastic-robust model formulation is presented and shown to efficiently increase the robustness of the solution without notably increasing the reserve procurement cost compared to the stochastic and robust models. [ABSTRACT FROM AUTHOR]

• A chance-constrained DCOPF with non-parametric correlated probabilistic forecasts of DLR and wind power. • The model co-optimizes energy and reserves with typical risk aversion levels of TSOs. • Assuming a normal distribution overestimates the probabilistic forecasts of DLR. • DLR reduces wind power curtailment and dispatch costs in highly congested networks. Compared to Seasonal Line Rating (SLR), Dynamic Line Rating (DLR) allows for higher power flows on overhead transmission lines, depending on the actual weather conditions. Nevertheless, the potential of DLR has to be traded off against the additional uncertainty associated with varying ratings. This paper proposes a DC-Optimal Power Flow (DCOPF) algorithm that accounts for DLR uncertainty by means of Chance-Constraints (CC). The goal is to determine the optimal day-ahead dispatch taking the cost of reserve procurement into account. The key contribution of this paper consists in considering both non-parametric predictive distributions of DLR and the combined wind power uncertainty in the optimization problem. Our results highlight the benefits of DLR in wind-dominated power systems, assuming typical risk aversion levels in the line rating estimation. [ABSTRACT FROM AUTHOR]