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New Concepts FOR Organic Rankine Cycle Power Systems

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New Concepts FOR Organic Rankine Cycle Power Systems ( new-concepts-for-organic-rankine-cycle-power-systems )

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Energy Systems Design Accounting for Dynamic Performance Table 5.3: Design variables involved in the multi-objective optimization, with relative upper (UB) and lower (LB) bounds. The bounds relative to the tubes inlet diameter Din, length l, and thickness t are assumed equal for the design of the once-through boiler and of the recuperator. Variable Turbine inlet pressure P6 [bar] Pinch point recuperator ∆Trec [oC] Temperature difference OTB ∆TOTB [oC] Exhaust gas temperature T11 [oC] Inlet diameter of the tubes Din [mm] Length of the tubes l [m] Thickness of the tubes t [mm] Tube pitch prec [-] Baffle spacing lrec,b [%] Gas velocity uexh [m s-1] LB UB 5 41.1 10 40 10 80 140 180 16 50 1.83 7.32 1.6 3.2 1.1 1.3 20 100 10 70 of the once-through boiler and of the recuperator (see §5.4.1) is started, obtaining as outputs both the pressure drops and the design parameters of the components, which are then stored. The model of the ORC system is thus run again, but in this case the pressure losses in the OTB and in the re- cuperator are included in the computation. The results are then checked with respect to the second principle of Thermodynamics. It is also verified that the velocity in the tubes and on the shell side of the recuperator lies within the ranges specified in [16]. The process is repeated until the average change in the spread of the Pareto front is lower than the specified tolerance, which is assumed here equal to 10−3. When the multi-objective optimization terminates, the inputs of the dynamic models are stored in a file that is then used by the dynamic simulator as previously explained. The dynamic models are parametrized using the data for the heat exchangers and the turbine corresponding to the optimal ORC modules, as determined by the multi-objective optimization pro- cedure. These models are then used to predict the dynamics of the complete system in a predefined transient scenario. Note that the number of dynamic simulations to be performed is equal to the number of points of the Pareto front. The dynamic test, conceived to assess the dynamics of the complete system, consists in the simulation of the failure of a gas turbine unit. This has been defined according to the specifications of the platform owner, and represents the worst scenario the power system can possibly undergo without compromising the platform functionality. The same dynamic test is thus applied to all the design candidates previously defined. It is assumed that the combined cycle (gas turbine A and ORC) and the gas turbine B are providing the normal load (13 and 6 MWE each) while at time t0 gas turbine B trips. Hence, the combined cycle undergoes a load increment of ≈ 1.2 MWE s−1 (e.g. 6 MWE in 5 s, see Figs. 5.8b and 5.10a) and must take over the entire power demand, until gas turbine C is ignited. The process ends by storing the desired outputs of the dynamic analysis (e.g., the maximum undershoot of the electrical network frequency) for each choice of system design. Finally, post-processing is performed within the software environment for scientific computing. 137

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