Networks for Maximum Energy Recovery

Example 16.1 The process stream data for a heat recovery network problem are given in Table 16.1. A problem table analysis on these data reveals that the minimum hot utility requirement for the process is 15 MW and the minimum cold utility requirement is 26 MW for a minimum allowable temperature diflFerence of 20°C. The analysis also reveals that the pinch is located at a temperature of 120°C for hot streams and 100°C for cold streams. Design a heat exchanger network for maximum energy recovery in the minimum number of units. 

The proposed network for maximum energy recovery is shown in Figure 3.27. 

To design the network for maximum energy recovery start at the pinch and match streams following the rules on stream heat capacities for matches adjacent to the pinch. Where a match is made transfer the maximum amount of heat. 

Determine the pinch temperatures and the minimum utility requirements for the streams set out in the table below, for a minimum temperature difference between the streams of 20°C. Devise a heat exchanger network to achieve the maximum energy recovery. 

The Heat Exchanger Network assembling the subsystems is given in Fig. 10.30. This HEN corresponds to the maximum energy recovery thermodynamically possible for a given However, this is not the most economical network, if the costs of both energy and heat exchangers are taken into account. The network can be further reduced. 

The maximum energy recovery network found in the Example 10.3 has seven heat exchangers. First law analysis indicates a minimum number of five units because of four streams and two utilities. Two units could be removed. Identify the loops and redesign the network for =10 °C. 

Synthesis of heat exchanger network (HEN) for minimum energy requirements and maximum heat recovery. Determine matches in subsystems and generate alternatives. Network optimisation. Reduce redundant elements, as small heat exchangers, or small split streams. Find the trade-off between utility consumption, heat exchange area and number of units. Consider constraints. 

It is not trivial to determine the best modification options that could feature minimal capital cost and the smallest effect on existing infrastructure and thus achieve maximum energy savings. The search for such options could be very time consuming for a complex heat recovery system. The incentives to find practical yet optimal modifications have been discussed by many other researchers and practitioners. The network pinch method developed by Zhu and Asante (1999) has been proven successful for practical applications, which will be discussed in detail in this chapter. 

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