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Scheduling chemical processes for frequency regulation

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  • Otashu, Joannah I.
  • Baldea, Michael

Abstract

Fast-paced demand response programs like frequency regulation play an important role in real-time balancing of the demand and supply of electricity. Chemical plants are a desirable participant in demand response programs due to their localized, large electricity demand, and to their ability to modulate power demand by properly scheduling production and product storage. However, the dynamics of such loads are complex and nonlinear, and must be explicitly accounted for when engaging in demand response or frequency regulation. Considerations such as ramp rate and capacity limits, which are typically employed on the grid side in managing demand response activities, do not sufficiently characterize the transient properties of the operation of chemical processes. Thus, using exogenous demand response dispatch signals for marshaling frequency regulation may be economically suboptimal or impossible to follow by a chemical plant. Motivated by the above, a new approach to frequency regulation that guarantee feasible power modulation and is well-suited for chemical processes is developed in this work. New metrics for describing the flexibility of the process for frequency regulation are provided. The strategy is demonstrated for a relevant class of industrial process – chlor-alkali production. It is shown that frequency regulation service can be provided with minimum disruption to the operations of the chemical process.

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  • Otashu, Joannah I. & Baldea, Michael, 2020. "Scheduling chemical processes for frequency regulation," Applied Energy, Elsevier, vol. 260(C).
    • Handle: RePEc:eee:appene:v:260:y:2020:i:c:s0306261919318124
    DOI: 10.1016/j.apenergy.2019.114125
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    References listed on IDEAS

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    Cited by:

    1. Wu, Long & Yin, Xunyuan & Pan, Lei & Liu, Jinfeng, 2023. "Distributed economic predictive control of integrated energy systems for enhanced synergy and grid response: A decomposition and cooperation strategy," Applied Energy, Elsevier, vol. 349(C).
    2. Liu, Xin & Li, Yang & Lin, Xueshan & Guo, Jiqun & Shi, Yunpeng & Shen, Yunwei, 2022. "Dynamic bidding strategy for a demand response aggregator in the frequency regulation market," Applied Energy, Elsevier, vol. 314(C).
    3. Klaucke, Franziska & Hoffmann, Christian & Hofmann, Mathias & Tsatsaronis, George, 2020. "Impact of the chlorine value chain on the demand response potential of the chloralkali process," Applied Energy, Elsevier, vol. 276(C).
    4. Elmore, Clay T. & Dowling, Alexander W., 2021. "Learning spatiotemporal dynamics in wholesale energy markets with dynamic mode decomposition," Energy, Elsevier, vol. 232(C).
    5. Golmohamadi, Hessam, 2022. "Demand-side management in industrial sector: A review of heavy industries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 156(C).
    6. Jens Baetens & Jeroen D. M. De Kooning & Greet Van Eetvelde & Lieven Vandevelde, 2020. "A Two-Stage Stochastic Optimisation Methodology for the Operation of a Chlor-Alkali Electrolyser under Variable DAM and FCR Market Prices," Energies, MDPI, vol. 13(21), pages 1-19, October.
    7. Nina Strobel & Daniel Fuhrländer-Völker & Matthias Weigold & Eberhard Abele, 2020. "Quantifying the Demand Response Potential of Inherent Energy Storages in Production Systems," Energies, MDPI, vol. 13(16), pages 1-22, August.

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