Engineering design and operations have traditionally favored steady-state optimization, often overlooking the dynamic and intermittent nature of ecosystems. This has led to environmental degradation and unsustainable practices. Techno-Ecological Synergy (TES) offers an alternative framework that seeks to harmonize technological systems with ecological processes, but previous TES studies have relied on retrospective models that assume perfect foresight of ecosystem behavior. This work presents a novel framework called TES-IDC (Techno-Ecological Synergy - integrated design and control) that addresses the limitations of retrospective TES models by incorporating adaptive recourse decisions. The framework extends the IDC methodology to TES models, utilizing a simulation-optimization approach to separate design and operational problems. The operational problem is modeled as a closed-loop model predictive controller (MPC) simulation, while Bayesian optimization is employed to identify design conditions that minimize both capital and operational costs. A key innovation of TES-IDC is the use of an infinite-horizon MPC policy to account for both short- and long-term impacts at a reasonable computational cost. The effectiveness of the TES-IDC framework is demonstrated through an air quality regulation case study, where it determines the optimal size of a reforestation area and a policy for technological operations, considering the environment’s dynamic capacity. The derived operational policy successfully meets short-term air quality constraints while optimizing long-term economic and ecological objectives. This research highlights the potential of TES-IDC in designing sustainable systems that adapt to the dynamic nature of ecosystems, paving the way for a more harmonious coexistence between human activities and the environment.

中文翻译：

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通过多尺度 MPC 和贝叶斯优化实现稳态技术和顺势生态系统之间的实时协同作用


工程设计和运营传统上偏爱稳态优化，往往忽视了生态系统的动态和间歇性。这导致了环境退化和不可持续的做法。技术-生态协同 （TES） 提供了一个替代框架，旨在将技术系统与生态过程协调一致，但以前的 TES 研究依赖于回顾性模型，这些模型假设对生态系统行为有完美的预见。这项工作提出了一个称为 TES-IDC（技术-生态协同 - 集成设计和控制）的新框架，它通过结合适应性追索决策来解决回顾性 TES 模型的局限性。该框架将 IDC 方法扩展到 TES 模型，利用仿真优化方法将设计和运营问题分开。运营问题被建模为闭环模型预测控制器 （MPC） 仿真，同时采用贝叶斯优化来确定可最大限度地降低资本和运营成本的设计条件。TES-IDC 的一项关键创新是使用无限视野 MPC 策略，以合理的计算成本考虑短期和长期影响。TES-IDC 框架的有效性通过空气质量监管案例研究得到证明，其中它确定了重新造林区域的最佳规模和技术运营政策，同时考虑了环境的动态容量。衍生的运营政策成功地满足了短期空气质量限制，同时优化了长期经济和生态目标。 这项研究强调了 TES-IDC 在设计适应生态系统动态性质的可持续系统方面的潜力，为人类活动与环境之间更和谐的共存铺平了道路。