Demand response-oriented dynamic modeling and operational optimization of membrane-based chlor-alkali plants
Demand response-oriented dynamic modeling and operational optimization of membrane-based chlor-alkali plants
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DOI：
10.1016/j.compchemeng.2018.08.030
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发表时间：
2019-02
期刊：
影响因子：
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通讯作者：
Joannah I. Otashu;M. Baldea
中科院分区：
文献类型：
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作者：
Joannah I. Otashu;M. Baldea
电力密集型流程可能会提供重要的需求响应(DR)服务。对这样的需求响应过程进行建模并不容易，因为模型必须描述高度动态操作下的工厂瞬变特性，同时保持计算效率。我们为一个重要的电力密集型过程，即膜电池氯碱生产，开发了一个面向需求响应的模型，并通过一个工业规模的工厂提供了快速的需求响应。通过大量的仿真和优化案例研究，我们证明了在不影响电池浓度和温度的情况下，快速调制电池的功率需求是可能的。此外，电池温度动态被发现限制了工厂的需求响应能力，并且必须明确考虑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实现大幅度的负荷削减，并可以降低电解厂的能源成本。
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.