Retrofitting of industrial heat recovery systems can contribute significantly to meeting energy efficiency targets for industrial plants. One issue to consider when screening retrofit design proposals is that industrial heat recovery systems must be able to handle variations, e.g., in inlet temperatures or heat capacity flow rates, in such a way that operational targets are reached. Consequently, there is a need for systematic retrofitting methodologies that are applicable to multi-period heat exchanger networks (HENs). In this study, a framework was developed to achieve flexible and cost-efficient retrofit measures of (industrial) HENs. The main idea is to split the retrofitting processes into several sub-steps. This splitting allows well-proven (single period) retrofit methodologies to be used to generate different design proposals, which are collected in a superstructure. By means of structural feasibility assessment, structurally infeasible design proposals can be discarded from further analysis, yielding a reduced superstructure. Additionally, critical point analysis is applied to identify those operating points within the uncertainty span that determine necessary overdesign of heat exchangers. In the final step, the most cost-efficient design proposal within the reduced superstructure is identified. The proposed framework was applied to a HEN retrofit case study to illustrate the proposed framework.

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In this study the performance of the American Meteorological Society and U.S. Environmental Protection Agency Regulatory Model (AERMOD), a Gaussian plume model, is compared in five test cases with the German Dispersion Model according to the Technical Instructions on Air Quality Control (Ausbreitungsmodell gemäbeta der Technischen Anleitung zur Reinhaltung der Luft) (AUSTAL2000), a Lagrangian model. The test cases include different source types, rural and urban conditions, flat and complex terrain. The predicted concentrations are analyzed and compared with field data. For evaluation, quantile-quantile plots were used. Further, a performance measure is applied that refers to the upper end of concentration levels because this is the concentration range of utmost importance and interest for regulatory purposes. AERMOD generally predicted concentrations closer to the field observations. AERMOD and AUSTAL2000 performed considerably better when they included the emitting power plant building, indicating that the downwash effect near a source is an important factor. Although AERMOD handled mountainous terrain well, AUSTAL2000 significantly underestimated the concentrations under these conditions. In the urban test case AUSTAL2000 did not perform satisfactorily. This may be because AUSTAL2000, in contrast to AERMOD, does not use any algorithm for nightly turbulence as caused by the urban heat island effect. Both models performed acceptable for a nonbuoyant volume source. AUSTAL2000 had difficulties in stable conditions, resulting in severe underpredictions. This analysis indicates that AERMOD is the stronger model compared with AUSTAL2000 in cases with complex and urban terrain. The reasons for that seem to be AUSTAL2000's simplification of the meteorological input parameters and imprecision because of rounding errors.

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To significantly decrease fossil carbon emissions from oil refineries, a combination of climate mitigation options will be necessary, with potential options including energy efficiency, carbon capture and storage/utilization, biomass integration and electrification. Since existing refinery processes as well as many of the potential new processes are characterized by large heating demands, but also offer large opportunities for process excess heat recovery, heat integration plays a major role for energy efficient refinery operation after the implementation of such measures. Consequently, the process heat recovery systems should not only be able to handle current operating conditions, but also allow for flexibility towards possible future developments. Evaluation of the flexibility of process heat recovery measures with both these perspectives enables a more accurate screening and selection of alternative process design options. This paper proposes a new approach for assessing the trade-off between total annual cost and potential operating flexibility for the heat exchanger network in short-as well as in long-term perspectives. The flexibility assessment is based on the evaluation of a flexibility ratio (similar to the conventional flexibility index) to determine the range in which operating conditions may vary while at the same time achieving feasible operation. The method is further based on identification of critical operating points to achieve pre-defined flexibility targets. This is followed by optimization of design properties (i.e., heat exchanger areas) such that feasible operation is ensured in the critical operating points and costs are minimized for representative operating conditions. The procedure is repeated for a range of different flexibility targets, resulting in a curve that shows the costs as a function of desired flexibility ratio. The approach is illustrated by an example representing a heat exchanger network retrofit at a large oil refinery. Finally, the paper illustrates a way to evaluate the cost penalty if the retrofit is optimized for one operating point but then operated under changed conditions. Consequently, the presented approach provides knowledge about cost and flexibility towards short-term variations considering also changes in operating conditions due to long-term development.