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Energy optimization of a wastewater treatment plant based on energy audit data: small investment with high return

机译:基于能源审计数据的废水处理厂能量优化:高回报投资小投资

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Ambitious energy targets in the 2020 European climate and energy package have encouraged many stakeholders to explore and implement measures improving the energy efficiency of water and wastewater treatment facilities. Model-based process optimization can improve the energy efficiency of wastewater treatment plants (WWTP) with modest investment and a short payback period. However, such methods are not widely practiced due to the labor-intensive workload required for monitoring and data collection processes. This study offers a multi-step simulation-based methodology to evaluate and optimize the energy consumption of the largest Italian WWTP using limited, preliminary energy audit data. An integrated modeling platform linking wastewater treatment processes, energy demand, and production sub-models is developed. The model is calibrated using a stepwise procedure based on available data. Further, a scenario-based optimization approach is proposed to obtain the non-dominated and optimized performance of the WWTP. The results confirmed that up to 5000 MWh annual energy saving in addition to improved effluent quality could be achieved in the studied case through operational changes only.
机译:2020年欧洲气候和能源包的雄心勃勃的能源目标鼓励许多利益相关者探索和实施措施,提高水和废水处理设施的能源效率。基于模型的过程优化可以提高污水处理厂(WWTP)的能源效率,具有适度的投资和短期回收期。然而,由于监测和数据收集过程所需的劳动密集型工作负载,这些方法并未被广泛实行。本研究提供了一种基于多步模拟的方法,可以使用有限的初步能量审计数据来评估和优化最大的意大利WWTP的能耗。开发了一种与污水处理过程,能源需求和生产子模型的集成建模平台。使用基于可用数据的逐步过程进行校准该模型。此外,提出了一种基于场景的优化方法来获得WWTP的非主导和优化性能。结果证实,通过仅通过操作变化,可以在研究的情况下实现高达5000米的节能除了改善的污水质量。

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