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Chapter 6: Case studies Figure 87: Heat source mass flow rate and temperature In a real system, heat sink conditions are likely to vary as well, but in a more limited scale. This is simulated by assuming a heat sink with a constant flow rate, but variable temperature: Tcf ,su=15−5⋅cos(4⋅π⋅t) [°C] ttot where ttot is the total simulation time, in this case 1469 seconds. (93) To maximize the amount of energy recovered from this heat source, the working conditions of the ORC should constantly be adapted to the heat source temperature and flow rate. A proper control strategy must therefore be developed. The following methodology is proposed: 1. Static and dynamic models of the cycle are developed (cfr. Chapter 4). The static model analogous to the dynamic model, but with all the time derivatives set to zero. 2. The static model is used to optimize the working conditions of the cycle for a wide range of heat source and heat sink conditions. 3. The optimized working points are used to define a model-based control strategy. 4. The control strategy is implemented in the dynamic model and simulated with the random variable heat source. Its performance is finally compared to alternative control strategies. In addition to the objective of maximizing the recovered energy, the formation of droplets at the evaporator outlet must be avoided, since it can damage certain types of expanders. A positive superheating must therefore always be maintained by the control strategy. 19PDF Image | Organic Rankine Cycles for Waste Heat Recovery and Solar Uses
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