(76d) Demand Response-Oriented Modeling and Production Scheduling Optimization for Chlor-Aklali Processes

The recent years have witnessed a significant increase in the amount of electricity generated from renewable resources, such as wind and solar power plants. These resources have significant environmental benefits but present the challenge of significant variations in generation rate, both over the course of the day and from season to season. Energy storage can, in principle, be used to smooth these fluctuations, but remains prohibitively expensive at the grid level. Thus, incorporating renewable resources in the power grid calls for the development of new operating strategies. Demand-side management or demand-response (DR) is one of the most widespread approaches to balancing power generation with power demand. In the DR context, customers are encouraged (via time-varying price signals or other economic incentives) to curtail their consumption during peak grid demand times. Such strategies are particularly amenable for industrial implementation, given that industrial electricity use is not driven by human needs and behaviors as is the case for residential demand.

Chlor-alkali production is one of the most electricity-intensive chemical processes, historically absorbing about two percent of the electricity generated in the United States [1,2]. The end products of this process, chlorine and caustic soda, are highly valuable chemicals that support other major industries like alumina smelting, organic chemicals, building and manufacturing (through the production of plastics and polymers etc.). The North American chlor-alkali market was valued at USD 13.68 billion in 2015 [3].

The majority of chlor-alkali production relies on brine electrolysis [4, 5]. Given the high electricity demand on this process, important research efforts have been targeted at improving the process efficiency, including the development of energy efficient membranes [6] and sophisticated electrodes [7]. Incipient efforts aimed at the intensification of the process have also been reported [8]. Industrial demand response, as described above, remains an alternative solution approach to resolve the high energy cost/operating cost challenge [2, 4, 9].

Demand response by means of fluctuating production rates, overproducing products during off-peak demand hours when electricity is typically cheap and storing excess product to supplement reduced production rate when electricity demand peaks (and thus, prices) have been studied for electricity-intensive chemical processes including air-separation [10-12] and aluminum smelting [13]. However, our literature survey revealed a relative paucity of studies rigorously covering the DR operation of brine electrolysis processes, in spite of the fact that this strategy is currently applied in practice.

Motivated by the above, in the present paper, we investigate the provision of demand response services by brine electrolysis plants, focusing on engagement in in electricity markets with fast dynamics (markets where prices are only known a few minutes before the operating period and prices change every few minutes). Such engagements in short-term markets have been shown to be highly profitable [14, 15].

The dynamics of chemical processes are typically slow with dominant time constants in the order of hours. Consequently, scheduling plant operations for providing demand response in fast paced electricity markets must explicitly account for process dynamics [10, 11, 16]. In order to consider both longer process time constants and fast market dynamics, we present a demand response-oriented modeling framework for brine electrolysis, paying specific attention to the dynamics of relevant variables and phenomena such as the cell temperature and current-voltage relationship. Additionally, we develop a production scheduling formulation for the provision of demand response by the chlor-alkali industry in fast-paced electricity markets. We evaluate the financial benefits and discuss potential process limitations to the provision of fast demand response. Our work show that the chlor-alkali industry is capable of safely and profitably providing significant load reductions in fast-changing electricity markets.

References

1. Annual Energy Outlook, 2017. U.S. Energy Information Administration, pp. 122. Accessed online https://www.eia.gov/outlooks/aeo/pdf/0383(2017).pdf, on April 7, 2018.
2. A. Kent, Ed., Riegel's handbook of industrial chemistry, 10th ed. Springer, 2003.
3. North America Chlor-alkali Market Analysis, 2018 – 2024. Grand View Research Inc. Accessed online https://www.grandviewresearch.com/industry-analysis/north-america-chlor-alkali-market, on April 7, 2018.
4. F. O'Brien, T. V. Bommaraju, and F. Hine, Handbook of Chlor-Alkali Technology: Volume I: Fundamentals, Volume II: Brine Treatment and Cell Operation, Volume III: Facility Design and Product Handling, Volume IV: Operations, Volume V: Corrosion, Environmental Issues, and Future Developments. Springer Science & Business Media, 2007, vol. 1.
5. Chemical economics handbook. IHS market. Accessed online https://ihsmarkit.com/products/chlorine-sodium-chemical-economics-handbook.html on April 7, 2018.
6. Gelb, Process for generating chlorine and caustic soda using a membrane electrolysis cell coupled to a membrane alkaline fuel cell, Mar. 3 1987, U.S. Patent 4,647,351.
7. Morimoto, K. Suzuki, T. Matsubara, and N. Yoshida, Oxygen reduction electrode in brine electrolysis," Electrochimica acta, vol. 45, no. 25, pp. 4257-4262, 2000.
8. Granados Mendoza, Intensification of the chlor-alkali process using a rotor-stator spinning disc membrane electrochemical reactor, Eindhoven University of Technology, 2016.
9. Chlistuno, Advanced chlor-alkali technology, Los Alamos, NM, USA, 2005.
10. Pattison, R. C., Touretzky, C. R., Johansson, T., Harjunkoski, I., & Baldea, M. (2016). Optimal Process Operations in Fast-Changing Electricity Markets: Framework for Scheduling with Low-Order Dynamic Models and an Air Separation Application. Industrial & Engineering Chemistry Research, 55(16), 4562-4584.
11. Cao, Y., Swartz, C. L., Baldea, M., & Blouin, S. (2015). Optimization-based assessment of design limitations to air separation plant agility in demand response scenarios. Journal of Process Control, 33, 37-48.
12. T. Kelley, R. C. Pattison, R. Baldick, and M. Baldea, An efficient MILP modeling framework for demand response operation of air separation units, accepted
13. Todd, M. Caufield, B. Helms, A. P. Generating, I. M. Starke, B. Kirby, and J. Kueck, Providing reliability services through demand response: A preliminary evaluation of the demand response capabilities of alcoa inc, ORNL/TM, vol. 233, 2008.
14. I. Otashu and M. Baldea, Grid-level battery operation of chemical processes and demand-side participation in short-term electricity markets. Applied Energy, vol. 220, pp. 562-575, 2018
15. Dowling, A. W., Kumar, R., & Zavala, V. M. (2017). A multi-scale optimization framework for electricity market participation. Applied Energy, 190, 147-164.
16. Baldea, M., & Harjunkoski, I. (2014). Integrated production scheduling and process control: A systematic review. Computers & Chemical Engineering, 71, 377-390