Yufei Wang

Heat Integration Across Plants Considering Distance Factor

Heat integration across plants is an extension of conventional heat integration in a single plant for further improving energy efficiency. This chapter addresses the application of both Pinch Analysis and Mathematical Programming on solving heat integration problems across plants. For heat integration across plants, the required pipelines between plants is much longer than heat integration within a single plant, so more attentions must be paid on distance factor as it incurs more expense. A number of factors can affect the final design of pipelines between plants, for example, direct and indirect heat integration, the connection patterns between plants, the selection of intermediate fluid, etc. In this chapter, three connection patterns (series, split, parallel) for interconnectivity of individual plants in an area are presented. Each connection pattern has different performance on energy saving and pipeline length. To determine the energy target for the three connection patterns, a graphical methodology is presented. In addition, Mathematical Programming is used to determine the optimal design considering both direct and indirect heat integration. Parameters of intermediate fluid can be also optimized if indirect heat integration is applied. Some case studies are illustrated to demonstrate the capabilities of the presented models and graphic tool.

Simultaneous synthesis of multi-plant heat exchanger networks using process streams across plants

Abstract Interplant heat integration using process streams is an alternative way to synthesize multi-plant heat exchanger networks (HENs). Compared with conventional way using steam, directly using process stream can recover more heat but with more pipelines. Due to the geographically separated locations of individual plants, distance related factors should be fully considered. In addition, the interaction between interplant heat integration and intra-plant heat integration is not fully addressed in traditional design methods. To counter these limitations, we present a new methodology for multi-plant HENs synthesis directly using process streams. The methodology makes use of a generalized disjunctive programming (GDP) formulation which gives rise to a mixed-integer nonlinear programming (MINLP) problem. For illustration purpose, two literature problems are conducted to verify the applicability of the proposed methodology. Our results can automatically offer the optimal design for multi-plant HENs, which are both more cost-optimal than the ones reported in the cited literatures.

Simultaneous Optimization of Cooler Network, Pump Network, and Cooling Tower

This paper presents a model for optimizing the cooler network, pump network, and cooling tower simultaneously. Each part of cooling water system interacts with each other. However, most of previous works focus on the optimization of stand-alone components. In order to find the optimal structure, all of three parts are supposed to be optimized simultaneously. The series-parallel configuration of cooler network is presented in this paper. The pressure drop of cooler is treated as optimization variable. The coolers’ heights are considered and auxiliary pump network is employed to reduce pumping cost. Besides, the cooling tower capital and operational costs are taken into account. The most important variables include water inlet and outlet temperature, water flowrate and air flowrate. The MINLP (mixed-integer nonlinear programming) problem is formulated so as to minimize the total annual cost of overall cooling water system. A case from refinery is employed to verify the effectiveness of proposed model.

Comparison of Energy Performance of Organic Rankine and Kalina Cycles Considering Combined Heat Sources at Different Temperature

Abstract An organic Rankine cycle (ORC) and Kalina cycle are both promising ways for low-temperature waste heat utilization, and these two technologies have their own applicable occasions. It is significant to choose a proper cycle considering waste heat features for efficient utilization of energy. For combined heat source, the ratio of latent heat to sensible heat, R, is a very important parameter to choose a suitable cycle. When R is small, it is proper to choose a Kalina cycle; while when R is large, it is better to choose an ORC. There is a turning point of R, which is related to the heat source temperature, working fluids and cycle parameters. In this paper, based on the simulation models developed for ORC and Kalina cycles in Aspen HYSYS, the optimum working fluids of ORC are selected, and cycle parameters of both cycles are optimized. Then the turning point of R is found at different waste heat temperatures. Results show that the turning point of R fluctuates with increase of waste heat temperature at range of 150-200°C, and it peaks at 150°C and 180°C. When waste heat temperature is higher than 190°C, ORC is better than Kalina cycle whatever R is. The paper can provide a reference to choose a suitable power generation system for combined heat source at different waste heat temperatures.

Mitigation of Fouling in Crude Preheat Trains by Simultaneous Dynamic Optimization of Flow Rate and Velocity Distribution

Abstract Crude oil fouling has been researched for decades, whereas optimization methods proposed to mitigate the effect of fouling on heat exchanger network performance are not many. For preheat trains with multi parallel branches, flow rate redistribution (change split ratios) is a valid mean for fouling mitigation, but related works ignored the consideration of significant power and pump cost associated with pressure drop caused by fouling. Crude velocity is correlated with fouling, so that detailed modification of heat exchanger can be considered to change velocity to further correlate heat transfer, pressure drop, and fouling. A time discretization method is proposed in this paper for fouling mitigation of heat exchanger network by dynamic optimization of velocity distribution through two ways. Simulated annealing algorithm is used to solve the model. Fouling rate in heat exchanger affected by wall temperature and velocity can in turn decrease wall temperature and increase velocity, which corresponds to a dynamic process. To describe the dynamic behaviour of optimization problem, the whole operational time horizon is divided into several time intervals and adjacent intervals are linked by fouling resistance. The flow split ratios both for cold and hot streams are changed with time. The objective function is represented by minimum annual total cost for preheat train. The main optimization constraints are composed of mass and energy balances and bounds for fluid velocity. A simple preheat train is used to illustrate the utilization of the optimization method. The optimization results present better heat exchanger network performance compared to the base case.