论文标题
基于非线性模型的大规模区域加热网络拓扑设计的伴随优化方法
An adjoint optimization approach for the topological design of large-scale district heating networks based on nonlinear models
论文作者
论文摘要
本文讨论了为现实区域供暖网络找到最佳拓扑，管道直径选择和操作参数的问题。目前采用非线性流量和热传输模型进行拓扑设计的工具仅限于具有多达20个潜在消费者的小型加热网络。我们引入了一种基于伴随的数值优化策略，以实现大规模的非线性热网络优化。为了避免使用网络大小进行强大的计算成本缩放，我们将消费者限制与约束聚合策略进行汇总。此外，为了使这种连续的优化策略与拓扑优化和管道尺寸选择的离散性质保持一致，我们提出了一种数值延续策略，该策略逐渐迫使设计变量朝着离散的设计选择迫使。因此，同时确定最佳网络拓扑和管道尺寸。最后，我们通过设计一个具有160个消费者的虚拟地区供暖网络来证明该算法的可扩展性。作为概念验证，该网络已通过最低的投资成本和抽水功率进行了优化，同时将热量提供给消费者的热舒适度范围为5％。从整个网络中的15厘米宽管道分布开始，新型算法发现网络布局将管道投资降低23％，与泵相关的成本在标准笔记本电脑上不到一个小时的时间内将14倍降低了14倍。此外，嵌入非线性传输模型的重要性是从温度引起的72％的温度引起的变化中可以明显的。
This article deals with the problem of finding the best topology, pipe diameter choices, and operation parameters for realistic district heating networks. Present design tools that employ non-linear flow and heat transport models for topological design are limited to small heating networks with up to 20 potential consumers. We introduce an alternative adjoint-based numerical optimization strategy to enable large-scale nonlinear thermal network optimization. In order to avoid a strong computational cost scaling with the network size, we aggregate consumer constraints with a constraint aggregation strategy. Moreover, to align this continuous optimization strategy with the discrete nature of topology optimization and pipe size choices, we present a numerical continuation strategy that gradually forces the design variables towards discrete design choices. As such, optimal network topology and pipe sizes are determined simultaneously. Finally, we demonstrate the scalability of the algorithm by designing a fictitious district heating network with 160 consumers. As a proof-of-concept, the network is optimized for minimal investment cost and pumping power, while keeping the heat supplied to the consumers within a thermal comfort range of 5 %. Starting from a uniform distribution of 15 cm wide piping throughout the network, the novel algorithm finds a network lay-out that reduces piping investment by 23 % and pump-related costs by a factor of 14 in less than an hour on a standard laptop. Moreover, the importance of embedding the non-linear transport model is clear from a temperature-induced variation in the consumer flow rates of 72 %.
