Improving the energy efficiency of process plants is central to minimising operatingcosts and increasing profitability. Growing concerns on climate change is also anissue due to the increasing level of carbon dioxide emissions. Process industriesremain one of the largest consumers of energy. Maximising energy recovery in heatexchanger networks (HENs) reduce the total energy consumption in processindustries. However, cost effective retrofit of HENs remains a great challenge. Anideal retrofit design is one that has the right balance between efficient use of existingequipment and limited amount of modifications and downtime, while maximisingenergy recovery. The key objective of this thesis is to present novel methodologiesfor cost effective retrofit of HENs, while ensuring industrial applicability.The cost associated with the application of structural modifications and additionalheat transfer area, has led to an increased interest into the use of heat transferenhancement for retrofit. Heat transfer enhancement is beneficial, as it usuallyrequires low capital investment for fixed network topology, and no additional heattransfer area in existing heat exchangers. However, the challenges of heat transferenhancement for industrial applications are: (1) identifying the best heat exchangerto enhance; (2) dealing with downstream effects on the HEN after applyingenhancement; and (3) dealing with its effect on pressure drop. This thesis presentssequential based methodologies consisting of a combination of heuristics and a profitbased non-linear optimisation model for tackling these three issues. The robustnessof the new approach lies in its ability to provide useful insights into the interaction ofvarious units in a HEN whilst being pertinent for automation.Notwithstanding the drawbacks of structural modifications in retrofit, the degree ofenergy savings that can be obtained cannot be ignored. A robust retrofit strategy forthe application of structural modifications in retrofit is required. This thesis presentsa methodology that provides new fundamental insights into the application ofstructural modifications that ultimately leads to a faster retrofit procedure, withoutcompromising the performance and feasibility of the retrofitted HEN. The newapproach: (1) identifies the best location to apply a series of modifications; and (2)presents an algorithm that can be automated for the identification of the best singleand multiple modifications that provides maximum energy recovery for a givenHEN. The robustness of the new approach is tested by a comparison with the wellestablishedstochastic optimisation approach for structural modifications i.e.simulated annealing. To improve the retrofit result, this work also considerscombining the use of structural modifications and heat transfer enhancement. Theaim is to harnesses the benefits of both methods to obtain a cost effective retrofitdesign. The analysis carried out in this work is subject to minimising the energyconsumption and maximising the retrofit profit. A decision on the best retrofitstrategy to apply to a given HEN depends on the given retrofit objective. However,this work provides an adequate basis on which the decision can be made based onindustrial applicability, profit and energy saving.
|Date of Award||31 Dec 2016|
- The University of Manchester
|Supervisor||Robin Smith (Supervisor) & Megan Jobson (Supervisor)|