A facultatively oligotrophic ultramicrobacterium (strain RB2256) isolated from an Alaskan fjord by extinction dilution in seawater, was grown in batch culture and under single-and dual-substrate-limitation of alanine and glucose in a chemostat. The nature of the uptake systems, and the uptake kinetics and utilization patterns of alanine and glucose were investigated. Glucose uptake was inducible, the system exhibited a narrow substrate specificity, and part of the uptake system was osmotic-shock-sensitive. Half-saturation constants for glucose were between 7 and 74 pM during glucose limitation. The initial step in glucose metabolism was the synthesis of sugar polymers, even during glucose-limited growth. The alanine uptake system was constitutively expressed and was binding-protein-dependent. In addition to L-alanine, nine other amino acids inhibited accumulation of [14C]~-alanine, indicating broad substrate specificity of the alanine transporter. Half-saturation constants between 1.3 and 1-8 pM were determined for alanine uptake during alanine limitation. Simultaneous utilization of glucose and alanine occurred during substrate-limited growth in the chemostat, and during growth in batch culture a t relatively high (mM) substrate concentrations. However, the half-saturation constant for alanine transport during dual-substrate-limitation, i.e. in the presence of glucose, increased almost fivefold. We conclude that mixed substrate utilization is an inherent property of this organism.
In this work, a numerical model is developed in order to investigate the adaptability of the multi-pump multi-piston power take-off (MP 2 PTO) system of a novel wave energy converter (WEC). This model is realized in the MATLAB/SIMULINK environment, using the multi-body dynamics solver Multibody TM , which is based on the open-source tool WEC-Sim. Furthermore, the hydrodynamic coefficients are calculated using the open-source code NEMOH. After providing the description of the model, it is validated against experimental results and an analytical model, showing good agreement with both. Subsequently, simulations for a single floater device with a multi-piston pump (MPP) unit using our numerical model are carried out to demonstrate the adaptability of the WEC. In addition, the results demonstrate that the MPP with a simple control strategy can extract more energy than any non-adaptable piston pump under various sea states. Finally, a floater blanket (an array of interconnected floaters) model is developed to shed some light on the hydrodynamic response and the performance of MPPs. The developed numerical model will be used in the future to optimize the MP 2 PTO configuration, and to develop an energy maximization control strategy for the MP 2 PTO system.
Wave energy has great potential as a renewable energy source, and can therefore contribute significantly to the proportion of renewable energy in the global energy mix. This is especially important since energy mixes with high renewable penetration have become a worldwide priority. One solution to facilitate such goals is to harvest the latent untapped energy of the ocean waves and convert it into electrical energy. A device performing such a task is known as a wave energy converter (WEC). In the present work, we focus on a specific type of WEC, which has the advantages of both significant energy storage capabilities, and adaptability to extract energy from the whole spectrum of ocean waves. This WEC consists of an array of point absorber devices, comprising adaptable piston-type hydraulic pumps powered by interconnected floaters, whose target is to extract optimally the energy from waves of varying heights and periods. Two different cases are considered in this paper; namely, the analysis of the energy extraction in a simplified floater blanket, and a model predictive control strategy to maximize the extracted energy of the WEC.
Increased penetration of renewable energy generation motivates a change of paradigm in the way power systems are structured and operated, as advocated by the smart grid concept. Accordingly, in this paper we investigate the lossless storage capabilities of the Ocean Grazer wave energy converter (WEC), which could facilitate the aforementioned paradigm shift. This specific WEC exhibits both adaptability with respect to the incoming waves and significant lossless storage capabilities. We propose a model predictive control (MPC) strategy based on a lumped dynamical model in order to mitigate power imbalances in the power grid and maximize the revenue of the WEC. Furthermore, we illustrate that the proposed strategy exploits the WEC energy storage capabilities and we show the economic benefits it brings. Lastly, the proposed strategy is compared with a heuristic approach and a setting without storage.
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