Chemical Engineering Transactions (Aug 2018)

Algorithmic Process Synthesis and Optimisation for Multiple Time Periods Including Waste Treatment: Latest Developments in P-graph Studio Software

  • Botond Bertok,
  • Aniko Bartos

DOI
https://doi.org/10.3303/CET1870017
Journal volume & issue
Vol. 70

Abstract

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Food, water and domestic energy demands changes seasonally as well as the availability of renewable energy sources. One of the challenging questions of utilizing renewable resources is its synchronization with the periodically varying demands. Only those methods can estimate the economic feasibility, which can explicitly take into account the pairing of demands with potential resources in multiple time horizons as well as the potential storage options. Moreover, waste treatment cannot be neglected in any long-term technology planning procedure. The P-graph framework provides appropriate formal and algorithmic basis for process synthesis, including structural modelling and model validation (Friedler et al., 1992), generation of alternative network structures (Friedler et al., 1995), determination of the optimal and N-best design alternatives (Friedler et al., 1996). By the help of the P-graph framework and its software implementation, i.e., the P-graph Studio developed at the University of Pannonia, process-network synthesis problems can be modelled and solved in general (Bertok et al., 2013), and optimization of multiperiod operation (Heckl et al., 2014), as well as multiperiod system design (Aviso et al., 2016) and waste treatment optimization (Friedler et al., 1994) in particular. Thanks to the built-in algorithm RCABB (Bartos et al., 2015) not just the best, but the list of N-best structurally different alternative network configurations can be generated utilizing the computational power of the computers executing. In the present work, recent additions to the software is to be introduced for multiperiod process-network synthesis including the design of waste treatment system, and computer aid for answering questions about the sensitivity of a configuration to the actual economic environment are to be shown.