(687a) A Process Systems Integration Tool to Build Energy Efficiencies in Biorefineries: Selection of Processes to Save Energy and Boost Cogeneration
More often than not, biorefining is rather challenged by high energy cost, which in combination with the volatile economies of emerging markets of biochemicals, threaten large-scale production and long-term projects. One should test and investigate useful targets to screen less promising chemistries at early stages of development. Other than the implementation of individual chemistries, energy synergies among the different chemistries (by means of process-to-process integration) are justified rather hopeful for the reduction of production cost and could improve margins for profits. Synergies would increase energy cost savings by utilizing available energy of some processes for the entry of others with lower energy cost than working individually. This paper further advocates the investigation of synergetic chemistries (processes) to increase cogeneration potentials â also combined with energy targeting (steam savings) â as necessary to offset volatilities of biochemicals prices.
Given a value chain of candidate chemistries, the new version screens all possible emerging biorefinery sites based on criteria used for energy and cogeneration targeting, also holding options for site utility levels to select ad optimize. This work takes advantage of the linear Turbine Hardware Model (THM), proposed by Mavromatis and Kokossis2, to provide good approximations of shaft-work potentials using an equivalent linear expression of the Willans line. The analysis assumes the use of backpressure turbines capable to receive and extract steam at multiple levels. The methodology decomposes complex turbine configurations using (instead) single turbines at each expansion zone â namely, the span between utility levels â facing with non-linearities of turbine efficiencies with load. Though the Turbine Hardware Model has been effectively applied in integration schemes of fixed and known hot/cold streams and processes, its implementation in the case of upcoming biorefineries is challenged by the integration domain, which also involves variable processes/streams to select and integrate. In this sense, streams may offer energy for direct and indirect integration as well as for cogeneration increasing the size and complexity of the overall biorefinery synthesis problem. For this purpose, this work uses the Total Site Cascade to host all possible streams and utilities matches. The appropriate selection of processes â in other words, sources for generation of steam â and utility levels would maximize cogeneration and improve robustness of the biorefinery site.
The implementation of the THM for total site integration purposes is limited by the use of fixed options for streams to combine and integrate along the intervals. Mavromatis and Kokossis2 proposed a three-cascade representation each assigned to handle (i) heat sources, (ii) heat sinks and (iii) steam levels. Instead, this work addresses all hot/cold streams and steam utilities as degrees of freedom in integration, while integration takes place on a single site cascade (the TSC) that is formulated based on a modified transshipment model that combines integration of streams and cascading of steam. The TSC solves each debottleneck problem associated with each process (direct integration) and combines energy residuals from hot streams and utilities to implement process-to-process (indirect) integration. The optimally energy integrated biorefinery is also capable to deliver steam (i.e. generated from the boiler and the available heat of process streams) to produce shaft-work that is estimated with the use of the THM. The TSC configuration involves intervals associated with all candidate process streams, while steam can be imported-exported at inlet-outlet temperatures of the intervals. The entire temperature range is also enhanced by multiple candidate temperature levels that configure the expansion zones for steam cascading in order to select steam levels and optimize loads of the utility mains with respect to shaft-work production and energy savings due to process-to-process integration. The model also uses binary variables to reconstruct single turbines into complex configuration alternatives that may hold multiple options for steam induction, pass-out and exhaustion aiming to approximate actual capital cost of applied turbines.
Complex and large value chains are examined by means of a biomass graph that enables the formulation of mass balances to make decisions about biorefinery processes and to activate their contribution to the Total Site Cascade. The overall domain is formulated by the variable processes and hot/cold streams, the binary variables for the selection of utility levels and the turbines as well as the heat flows of the heat transshipment model; the latter refer (i) to direct heat transfer between hot-cold streams, (ii) to indirect heat transfer among streams by means of steam generation-reuse and (iii) to steam residuals that relate with cogeneration potentials at each expansion zone. Mass (from the biomass graph) and energy (from the TSC) balances are combined as an optimization model to select processes, products and utilities levels and can be used with alternative objective functions for the minimization of energy cost or the maximization of biorefinery profitability; the latter may include options for energy, operation and investment costs and profits from bioproducts and cogeneration.
The proposed updated model is illustrated through a real-life biorefinery problem that bears 11 candidate biochemicals to examine and select. The analysis highlighted top trends for processes and bioproducts along with high energy savings that count for 20% of the site energy consumption and strong potentials for power cogeneration that counts more than one third of the biorefinery profitability.
1 Pyrgakis KA, Kokossis AC. A Total Site Synthesis approach for the selection, integration and planning of multiple-feedstock biorefineries. Computers & Chemical Engineering. 2018; https://doi.org/10.1016/j.compchemeng.2018.09.003. In press.
2 Mavromatis SP, Kokossis AC. Conceptual optimisation of utility networks for operational variations-II. Network development and optimisation. Chemical Engineering Science. 1998; 53;8:1609-1630.