Model-based optimization of water resource recovery facilities

基于模型的水资源回收设施优化

• 批准号: RGPIN-2016-06522
• 负责人: Vanrolleghem, Peter
• 金额: $ 3.64万
• 依托单位: Université Laval
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=709889
• 关键词: Model; based; optimization; water; resource

An important change is happening to the wastewater industry: a paradigm shift is occurring from an industry that treats wastewater to an industry that brings a more positive message: it produces clean water, and recovers fertilizers and energy contained in used' water. The fact that WRRFs aim at delivering valued products that can partially replace those produced by other means (typically in the chemical industry) leads to a big change in specifications of the outputs of the facility: no longer treated wastewater and biosolids, but products that have to compete with what is already on the market. These tighter specifications will impose a challenge on the process control systems that will be required to guarantee the quality of the products of the WRRFs. Given the difficulties in collecting high quality data on which the control systems rely to act upon the system (recent practical studies using partially automated data validation report data losses of 5 to 60%), important research efforts have to be deployed to create the process monitoring and control systems that maintain these tight product specifications at all time. Over the next 5 years the research program of this Discovery grant will develop control systems that benefit from the ability of new algorithms to not only reliably detect faults in the measurement equipment but can also find out what is wrong with the sensors (fault diagnosis). With this knowledge the problem can of course be handled through proper maintenance or replacement of the sensor, but until that happens, the control system must be able to still perform adequately. Fault-accommodation is the methodology that is then put in place and methods will be developed to replace the faulty data by using either historical information or simple models. In case the fault is too disruptive, a different control strategy will have to be adopted that does not rely on these data. A so-called control reconfiguration based on a fall-back strategy has to occur. Finally, because the requirements imposed on resource recovery facilities are becoming so much more stringent, a control approach that seems particularly suited for this type of situations with multiple objectives and complex behavior, will be evaluated: Extermum seeking control. Its intuitive nature will make sure that the results of this research have a good chance to make it to practice and generate the anticipated advances in performance. The project will train 8 graduate students (4 PhD and 4 MSc), at least 3 undergraduates, a postdoctoral fellow and a technician responsible for the industry standard pilot plant on which the different methods will be developed and tested. These HQP will acquire a wide range of skills thanks to the involvement in the different aspects of the research project, the exposure to national and international research and to practice through the work on an industry standard pilot facility.

废水行业正在发生重大变化：从处理废水的行业正在发生范式转变，转变为带来更积极信息的行业：它生产清洁水，并回收废水中所含的肥料和能源。 WRRF 旨在提供可部分替代其他方式（通常在化学工业）生产的产品的有价值产品，这一事实导致设施输出规格发生重大变化：不再处理废水和生物固体，而是经过处理的产品与市场上已有的产品竞争。这些更严格的规范将对保证 WRRF 产品质量所需的过程控制系统提出挑战。鉴于收集控制系统所依赖的高质量数据存在困难（最近使用部分自动化数据验证的实际研究报告数据丢失为 5% 至 60%），必须部署重要的研究工作来创建过程监控和控制系统始终保持这些严格的产品规格。 在接下来的 5 年里，这项发现资助的研究计划将开发控制系统，该系统受益于新算法的能力，不仅可以可靠地检测测量设备中的故障，而且还可以找出传感器的问题（故障诊断）。有了这些知识，问题当然可以通过正确维护或更换传感器来解决，但在此之前，控制系统必须仍然能够充分运行。错误适应是随后采用的方法，并且将开发方法来通过使用历史信息或简单模型来替换错误数据。如果故障破坏性太大，则必须采用不依赖这些数据的不同控制策略。必须进行所谓的基于后备策略的控制重新配置。最后，由于对资源回收设施的要求变得越来越严格，因此将评估一种似乎特别适合这种具有多个目标和复杂行为的情况的控制方法：Exterum寻求控制。其直观性将确保这项研究的结果有很好的机会付诸实践并产生预期的性能进步。 该项目将培养 8 名研究生（4 名博士和 4 名硕士）、至少 3 名本科生、一名博士后研究员和一名负责行业标准试点工厂的技术人员，在该工厂上将开发和测试不同的方法。由于参与研究项目的不同方面、接触国内和国际研究以及通过在行业标准试点设施上进行实践，这些 HQP 将获得广泛的技能。