Development of systematic technique for energy and property integration in batch processes
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The increasing consumption of energy, generation of waste as well as higher cost of fresh resources and waste treatment systems are the important driving forces for developing efficient, environmentally friendly and economic resource conservation techniques in the process industries. Process integration is being recognized as an useful systematic strategy for resource conservation and waste minimization. Up to date, less research works have been investigated on heat and property integration and these works are only focused on continuous processes.Since the application of batch processes is increasingly popular due to the development of technology-intensive industries such as pharmacy, fine chemistry and foods, it is necessary to consider both heat and property integration in batch processes simultaneously. In this thesis, a new mixed integer nonlinear programming (MINLP) mathematical model is introduced to synthesize a property-based heat integrated resource conservation networks (HIRCNs) for batch processes. A source-HEN-sink superstructure is constructed to embed all possible network configurations. Then, an MINLP model that consists of propertybased resource conservation network (RCN) and heat exchanger network (HEN) models is developed.In the proposed model, the property-based RCN model is formulated based on supertargeting approach while HEN model is formulated via automated targeting method (ATM). The optimization objective is to minimize total annualized cost (TAC) for a batch process system. This includes the operating cost of fresh resources, hot and cold utilities as well as the capital cost of storage tanks. To demonstrate the proposed approach, three case studies were solved. Based on the optimized results, the proposed simultaneous targeting approach for property-based HIRCNs is more effective in term of TAC for HIRCNs than the presented sequential targeting approach.
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