Energy, economic, environmental and engineering quantity optimization of industrial energy recovery network

Abstract

The industrial energy recovery network has a large energy-saving potential. The retrofit of the original heat exchanger network (HEN) plays an important role in reducing energy consumption in existing process industries. However, a single economic or energy target is no longer sufficient to meet the retrofit needs of existing process industries. Therefore, an improved retrofit method that comprehensively considers many-objective is worthy of exploration. In this study, a many-objective optimization model with energy, economic, environmental and engineering quantity (4E) indexes for heat exchanger network retrofit is proposed, which avoids the one-sided analysis brought by single-objective optimization. The non-dominated sorting genetic algorithm based on reference point (NSGA-III) is applied to solve the proposed retrofit model. Three typical cases are used to verify and analyze the effectiveness and superiority of the proposed method. The case results show that the many-objective optimization method provides diverse retrofit options and flexibility to decision makers. Retrofit schemes with comparative energy, economic or environmental performance may take on notable difference in engineering quantity. Compared with the original networks, the retrofitted networks in the case studies can achieve a decrease in energy consumption up to 49.6%, a decrease in the total annual cost up to 22.2%, and a decrease in environmental impact up to 32.8%. Compared with the literature, the proposed method obtains optimization solutions with less energy consumption, capital cost, environmental impact and payback period.