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                     School of Chemical Engineering,   software tools (Cont.):
                         Purdue University, 311      HI tools, 195–201
                     Scilab computational package, 24  integrating renewable energy into
                     Scottish Environment Protection     other energy systems, 216–218
                         Agency (SEPA), 300          mathematical modeling suites,
                     screening and scoping audits, 5–6   210–211
                     search algorithms, for nonlinear   Modelica, 24, 211–212
                         unconstrained problems, 30  other, 211–218
                     second law of thermodynamics, 14–15  overview of available, 191
                     segmentation, 286–287           WATER, mass integration software,
                     SEMPRA ENERGY, 3                    201–202, 266
                     SEPA. See Scottish Environment   Solution Structures Generation
                         Protection Agency             algorithm (SSG), 38, 157–158
                     service providers:            specifications, 25
                       combined analysis, 307–308  spreadsheet-based tools, 200, 201
                       general information sources,   SPRINT:
                           297–300                   HI tools and, 195, 286
                       HI, 301–303                   software interface, 196
                       mass integration, 305–306   SSG algorithm. See Solution
                       optimization for sustainable    Structures Generation algorithm
                           industry, 311           STAR, 286
                     S-Graph Studio, 193–194         graphical user interface, 196
                     S-graphs:                       HI tools and, 195–198
                       batch processes and, 159–163  steady-state models, 23–24
                       example recipe, 162         steam:
                       framework for scheduling, 161–163  heating with, 50–51
                       HI and recipe for case study with,   system and heat recovery, 99–100
                           181, 182                stochastic methods:
                       recipe for two batches, 162   error minimization tools and, 43
                       scheduling frameworks, suitability   optimization problems and, 32–33
                           and limitations, 159–161  streams:
                       solution for recipe under NIS   aqueous, 23
                           policy, 162               CCs and heat recovery for
                     Shifted Composite Curves (SCCs), 63  multiple, 51–54
                       relation between GCCs and, 64  data extraction and, 284–285, 289–290
                     simple heat integration, 176–177  emissions/effluents, materials
                     simplex method algorithm for LPR    and, 185
                         problems, 29                heat exchangers and multi, 4
                     simulated annealing (SA) stochastic   heat recovery between hot and
                         search method, 32, 33           cold, 51
                     simulation tools, 39          structural process optimization:
                       for process industry, 24      mathematical programming and,
                     SITE-int, 198                       153–158
                     SMILP. See successive mixed integer   MSG, SSG, ABB and, 157–158
                         linear program              P-graph symbols of process
                     SOFCs, 4                            elements and, 154
                     software tools:                 P-graphs and process structure of
                       balancing/flowsheeting simulation   operating units, 155
                           for energy-saving analysis,   P-graphs and process structures
                           215                           violating axioms, 157
                       emerging trends, 212–215      P-graph’s mathematical engine and,
                       flowsheeting simulation packages,   157–158
                           202–206                   P-graph’s significance for, 155–157
                       general-purpose optimization   process representation via
                           packages, 206–210             P-graphs, 154–155
                       graph-based process optimization   reduction in search space,
                           tools, 191–195                combinatorial axioms and, 157
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