Flexible Inverse Design of Carnot-Batteries with Fluid Mixtures: A combined theoretical-experimental approach

卡诺电池(CBS)将电能存储为热(火用)。在放电过程中，其目的是恢复电能。为了获得高效率，系统的每个部分必须接近热力学可逆性。除了效率，在未来的能源市场中，成本和进一步的标准也将是重要的。在这个项目中，我们将研究使用多组分混合物的CBS的逆向设计，并使用机器、热交换器、存储和流体的详细模型进行数学优化。选定的点将进行实验研究，旨在证明模型及其预测的有效性。该项目在很大程度上依赖于优先计划内的合作。逆向设计的标准将来自能源系统分析项目，部件的详细特征和相关性将从热力学、传热学和Termo-Fluid机械项目中获得。主要的假设是，相对简单的循环和共同优化的工作流体混合物和工作条件，使反向设计方法具有足够高的灵活性，并满足能源系统分析制定的标准，如每投资成本的往返效率和不同时间应用情况下的给定存储功率比，以满足市场需求和评估卡诺电池的限制。第二个主要假设是，实际的CBS热力学模型忽略了太多的细节，如局部性质、流体依赖效率、时间依赖和耦合效应，因此它们的预测存在很大的不确定性，特别是由于与实验缺乏比较。在这里，预计这个项目的结果将允许评估模型中所需的详细程度，以实现良好的准确预测和可靠的逆向设计。在这一资助期结束时，预计它将拥有一个可用于逆向工程的CB模型，并在选定的运行点进行实验验证。

Carnot batteries (CBs) store electrical energy as thermal exergy. Along discharging it is aimed to restore the electrical energy. For high efficiencies each part of the system must approach thermodynamic reversibility. Beside efficiency, also costs and further criteria will be important in future energy markets. In this project an inverse design of CBs using multi-component mixtures will be investigated and mathematically optimized, using detailed models for machines, heat exchangers, storages, and fluids. Selected points will be investigated experimentally, aiming to prove the validity of the models and their predictions. The project heavily relies on co-operations within the priority program. Criteria for the inverse design will come from projects from energy systems analysis, and detailed features and correlations of the parts will be obtained from thermodynamics, heat transfer and termo-fluid machine projects. The main hypothesis is that relatively simple cycles with co-optimized working fluid mixtures, and working conditions lead to a high enough degree in flexibility for an inverse design approach and meet the criteria formulated from energy systems analysis, like round trip efficiency per investment costs and given storage to power ratio for different temporal application-profiles, to meet the market needs and to evaluate the limits of Carnot batteries. The second main hypothesis is that actual thermodynamic models of CBs neglect too many details, like local properties, fluid dependent efficiencies, time dependencies, and the coupling effects so that their predictions suffer from large uncertainties, especially due to a lacking comparison with experiments. Here, it is expected that the results of this project will allow to assess the level of detail needed in models for good accuracy predictions and reliable inverse design. At the end of this funding period, it is expected to have a CB model, which can be used for inverse engineering, and is experimentally validated at selected operation points.