Chlor-alkali electrolysis indicates significant demand response potential, accounting for over 2% of Germany’s total elec-tricity demand. To fully analyze this potential, digital models or digital twins are necessary. In this study, we use the IRPopt modeling framework to develop a digital model of an electrolysis process and examine the cost-optimal load shifting application in the day-ahead spot and balancing reserve market for various price scenarios (2019, 2030, 2040). We also investigate the associated CO2 emissions. Combined optimization at both markets results in greater and more robust cost savings of 16.1% but cannibalizes the savings that are possible through optimization separately at each market. In future scenarios, the shares of savings from spot and reserve market could potentially reverse. CO2 savings between 2.5% and 9.2% appear only through optimization at the spot market and could even turn negative if optimized solely at the reserve market.