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Demand response-oriented dynamic modeling and operational optimization of membrane-based chlor-alkali plants

机译:基于需求响应的膜式氯碱厂动态建模和运行优化

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摘要

Power-intensive processes can potentially provide significant demand response (DR) services. Modeling such processes for demand response is not trivial as models must depict plant transient properties under highly dynamic operation while remaining computationally efficient. We develop a demand response-oriented model for an important power-intensive process i.e., chlor-alkali production using membrane cells, and demonstrate the provision of fast demand response by an industrial-size plant. Through an extensive simulation and optimization case study, we show that the fast modulation of the cell power demand is possible without adverse impact on cell concentration and temperature. Additionally, the cell temperature dynamics are found to restrict the demand response capacity of the plant and must to be explicitly accounted for to support dynamic cell operation in DR scenarios. Substantial load curtailment during peak electricity price periods can be achieved and the energy cost to the electrolysis plant can be reduced. (C) 2018 Elsevier Ltd. All rights reserved.
机译:耗电量很大的过程可能会提供重要的需求响应(DR)服务。对此类过程进行需求响应建模并非易事,因为模型必须描述高度动态操作下的工厂暂态特性,同时保持计算效率。我们针对重要的电力密集型流程(即使用膜式电池生产氯碱)开发了面向需求响应的模型,并演示了工业规模工厂提供的快速需求响应。通过广泛的仿真和优化案例研究,我们表明可以快速调节电池功率需求,而不会对电池浓度和温度产生不利影响。此外,发现电池温度动态限制了工厂的需求响应能力,必须明确考虑电池温度动态以支持灾难恢复场景中的动态电池运行。可以在高峰电价期间大幅削减负荷,并可以降低电解厂的能源成本。 (C)2018 Elsevier Ltd.保留所有权利。

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