The widespread use of optimization methods in the design phase of District Heating Networks is currently limited by the availability of scalable optimization approaches that accurately represent the network. In this paper, we compare and benchmark two different approaches to non-linear topology optimization of District Heating Networks in terms of computational cost and optimality gap. The first approach solves a mixed-integer non-linear optimization problem that resolves the binary constraints of pipe routing choices using a combinatorial optimization approach. The second approach solves a relaxed optimization problem using an adjoint optimization approach, and enforces a discrete network topology through penalization. Our benchmark shows that the relaxed penalized problem has a polynomial computational cost scaling, while the combinatorial solution scales exponentially, making it intractable for practical-sized networks. We also evaluate the optimality gap between the two approaches on two different District Heating Network optimization cases. We find that the mixed-integer approach outperforms the adjoint approach on a single-producer case, but the relaxed penalized problem is superior on a multi-producer case. Based on this study, we discuss the importance of initialization strategies for solving the optimal topology and design problem of District Heating Networks as a non-linear optimization problem.
翻译:在地区供热网络的设计阶段,广泛使用优化方法目前受到限制,因为有能够准确代表网络的可伸缩优化方法。在本文件中,我们比较并基准地标了两种不同办法,即从计算成本和最佳性差距的角度对地区供热网络的非线性地形优化进行非线性优化。第一种办法解决混合内联非线性非线性优化问题,用组合优化方法解决管道路由选择的二进制限制。第二种办法用一种联合优化方法解决宽松的优化问题,并通过惩罚性实施一种离散网络表层学。我们的基准表明,受轻度处罚的问题具有多元计算成本的缩放,而组合式解决办法则具有指数性,使实际规模网络难以使用。我们还评估了两种办法在两个不同的地区供热网络优化案例中的最佳性差距。我们发现,混合内联式方法在单一供热器案件中超越了双联性方法,但较宽松的受处罚问题在多制者案例中更为突出。基于这一研究,我们讨论了最佳区域最佳设计问题的重要性。</s>