Abstract
In the process industry, a large amount of low-grade waste heat is discharged into the environment. Furthermore, district heating and cooling systems require considerable low-grade energy. The integration of the two systems has great significance for energy saving. Because the energy demand of consumers varies in periods, the design and operation of an industrial waste heat recovery system need to match with the fluctuations of district energy demand. However, the impact of the periodic changes on the integration schemes are not considered enough in existing research. In this study, a framework method for solving above problem is proposed. Industrial waste heat was integrated with a district heating and cooling system through a heat recovery loop. A three-step mathematical programming method was used in design and operation optimization for multiperiod integration. A case study was conducted, and the results show that the multiperiod optimization method can bring significant benefits to the system. By solving the mixed integer nonlinear programming model, the optimal operation plans of the integration in different periods can be obtained.
Highlights
In the process industry, a large amount of waste heat usually exists
In multiperiod heat exchanger network (HEN), the design area of exchanger (Ai,k needed in all periods [30], which is expressed by Equation (34)
By integrating waste heat with the district heating and cooling (DHC) system, this number drops to 1.854 × 105 USD with a decrease of 55.9%
Summary
A large amount of waste heat usually exists. According to the different temperature levels, industrial waste heat can be divided into high-grade waste heat, medium-grade waste heat, and low-grade waste heat. As an effective method to reduce energy consumption, Heat Integration (HI) has been studied in depth in the past 40 years [2]. Such methods led to significant energy saving in the process industry around the world. There are two mainstream methods for the design of HENs: pinch analysis (PA) and mathematical programming (MP). The former is based on thermodynamic principles and a graphical method [3], and the core of the latter is superstructure formulation, whereby the generalized superstructure [4] and the stage-wise superstructure are widely used [5]. High-grade and medium-grade waste heat can be effectively utilized by HENs
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