Because of the expected growing implementation of large scale water electrolysis, an apparent opportunity arises to implement systems in which the by-product oxygen is harnessed by using it as a raw material in another process. This is also known as an oxygen synergy, an example of industrial symbiosis.
A procedure to design and evaluate the performance of this kind of systems was devised by following guidelines of chemical process design and systems thinking. The method starts by defining the system’s spatial and temporal boundaries as well as a design goal. Then, it is further described by determining the systems’ elements, inputs and outputs, as well as its operation mode. All this information comprises the initial design space and, is organized in
a graphical representation also known as a superstructure of options.
Taking into account the socioeconomic environment of the energy transition in the Netherlands between 2020 and 2030, this methodology was used to design an industrial cluster with two oxygen producers and four oxygen users. This consist of an Air Separation unit (ASU), a Polymer Electrolyte Membrane (PEM) electrolyzer, an Auto-Thermal Reformer (ATR), an Oxy-fuel combustion power plant (OXFC), as well as two gasification processes: one for H2 production (referred to as B-to-H2), and the other for methanol synthesis (referred as
B-to-MeOH). Additionally, the option of importing or exporting O2 to another location is added. Then, this initial set of options is translated into a Multi Integer Linear Programming (MILP) problem with the help of Linny-R, a graphical specification language to solve optimization problems. The MILP includes both capital and operational costs (also referred to as CAPEX and OPEX), and aims to select a configuration that yields the highest benefits.
Furthermore, three different scenarios were devised to evaluate different techno-economic conditions. The scenario PEM 2020 includes current CAPEX and OPEX for the electrolyzer, while PEM 2030 examines the effects of lower costs expected for this technology. Furthermore, the scenario Small ASU, analyses the effects of having a smaller O2 production capacity in
the cluster. Because of the input and output prices selected, the selection the fist scenario just includes the ASU. However, for the PEM 2030, the electrolyzer is also selected, and the final configuration includes both O2 producers. For the final scenario, no process is selected.
Then, when the output prices are varied, the topology selection changes. As when a product reaches a certain price, which is high enough to cover both the capital and operational expenses, the technology is present in the final configuration. These minimum selling prices are compared with reference values found in literature, to validate them. It was determined
that model is able to roughly evaluate the operation and profitability of all the presented options, and thus can be used as a first evaluation method to discard options that are not economically attractive. However, the greatest limitation lies in the concept design phase, because the most optimal solution might not be included in the initial set of options.
This process turned out to also be useful when comparing the effects of operating with and without synergies. For the cases evaluated, the benefits are higher when the main O2 provider is the PEM electrolyzer. In most of the business cases the obtained benefits are two times
higher, than when the ASU is used. Furthermore, because of expected lower electricity prices and capital expenses for electrolysis’s, the business cases with O2 synergies are likely to be more beneficial in the future. As the only economically attractive option for current techno-economic data is a synergy to produce H2 via ATR.
Finally, a relationship between the O2 price and the minimum H2 required price to invest in an electrolyzer was found for techno-economic specifications, one for the year 2020 and one for 2030. At low H2 market prices, the benefit from selling O2 improves the business case for the electrolyzer. This correlations can be useful for further oxygen synergies research, or industrial gas suppliers and electrolyzer suppliers, who want to render appeal to their business cases by finding synergy opportunities. If the devised methodology is further developed it can be used to model the oxygen demand and supply between various clusters, or find other opportunities in which an industrial symbiosis might be economically attractive. Furthermore, the effects of other external effects can be also modeled. For example, the variation in raw material prices or a policy to
reduce CO2 emissions. Though it still needs to be further tested, it has been proven that the superstructure model can be used as a first evaluation method to discard options that are not economically attractive, and to evaluate different configurations with and without operating
under industrial symbiosis.