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Microalgae growth optimization in open ponds with uncertain weather data

机译:天气数据不确定的开放池塘中微藻的生长优化

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Although microalgae-based processes are currently one of the most promising new technologies for the substitution of fossil fuels and chemicals, the theoretical potential of these technologies is currently limited by their low profitability, hence hindering the development of large scale plants in an economically feasible way. One of the process bottlenecks is the cultivation phase, whose operation is complicated by both the involved biological mechanisms complexity and the highly fluctuating weather conditions affecting the system. Available mathematical models describing microalgae growth and pond temperature dynamics through weather data implementation assume perfect knowledge of weather conditions, hence neglecting the inaccuracy of meteorological predictions that is expected even considering short-term forecasts. In this study a sensitivity study is first carried out to evaluate the weather variables that most impact on productivity. Then, two optimization approaches are proposed to prevent potential critical conditions (such as cell death due to too high temperatures) that may arise by using inaccurate weather forecast. The study demonstrates the reliability of the proposed methodologies and compares them in terms of productivity loss and water demand. (C) 2018 Elsevier Ltd. All rights reserved.
机译:尽管基于微藻的工艺目前是替代化石燃料和化学药品的最有前途的新技术之一,但这些技术的理论潜力目前受到其低利润率的限制,因此阻碍了以经济上可行的方式开发大型工厂。过程的瓶颈之一是栽培阶段,由于涉及的生物机制复杂性和影响系统的高度波动的天气条件,其操作过程变得复杂。通过天气数据的实现描述微藻生长和池塘温度动态的可用数学模型假设了对天气状况的完全了解,因此忽略了即使考虑短期预报也可以预期的气象预报的不准确性。在这项研究中,首先进行了敏感性研究,以评估对生产力影响最大的天气变量。然后,提出了两种优化方法来防止由于使用不准确的天气预报而可能出现的潜在关键条件(例如,由于温度过高导致的细胞死亡)。该研究证明了所提出方法的可靠性,并在生产率损失和需水量方面进行了比较。 (C)2018 Elsevier Ltd.保留所有权利。

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