High Efficiency is key to profitable large-scale electrolysis production. Being able to determine how each of your cells are performing in terms of Specific Power Consumption (SPC) gives you the edge needed to get ahead in this competitive field.
We provide the ability to gain this edge by giving you a window into your asset data in order to effectively predict and characterizeeach component of an electrolyser (anode, cathode and membrane).
Make the best replacement decisions
We recommend that you base your decision to replace or to keep a component on the individual economic performance of each component and the cost of replacing it. If a component costs more to operate than to replace, it should be part of your next maintenance program. If not, it should be kept in place. This means:
Get rid of underperformers = Higher Current Efficiency = Energy Savings and/or More Output
Keep your over-performers = Extended Component Life Time = Lower Maintenance Costs
The EMOS® Cell Performance Analyzer (CPA) is a service which determines the precise performance and economics related to the operation of electrodes (U0, k-values) and membranes (k-value, C.E.) of single electrolysis cells.
CPA Case Study
The following case study used a new plant with 8 electrolysers over a 10 year period. Each electrolyser has 175 cells, for a plant total of 1400 cells.
The first graph shows the savings in Specific Power Consumption (SPC), with and without R2’s EMOS® Cell Performance Analyzer. The second graph displays the annual financial savings for different energy prices, over a 4 year period. The last diagram shows the reduction in replaced components from a total of 2880 components replaced after 8 years without R2, down to 1630 components replaced after 8 years with EMOS® Cell Performance Analyzer.
At the core of the EMOS® Predictive Maintenance Package, the EMOS ® Cell Performance Analyzer consists of the monthly determination of highly precise KPI’s for each cell: Current Efficiency (CE), Uo, k Value and the Specific Power Consumption. This provides the precise performance and operating costs of each single element which is key to be able to switch to a performance-base predictive maintenance strategy.