Simultaneous optimization of heat-integrated water networks involving process-to-process streams for heat integration

This paper presents an extension of our recent work, in which we addressed the simultaneous synthesis of heat-integrated water networks. The novelty and goal of this work is the development of an extended superstructure and simultaneous optimization model of heat-integrated water networks now involving process-to-process streams, and other streams within the overall network, for heat integration. Those heat-integration opportunities have not yet been fully taken into account in most existing models of heat-integrated water networks. In this study, we presented two strategies for heat integration of process-to-process streams. The first one includes the placement of heat exchangers on each hot and cold process-to-process stream. The second allows for the cooling and splitting of hot streams, and heating and splitting of cold streams. This extended model was formulated as a non-convex mixed-integer non-linear programming (MINLP) problem. The objective was to minimize the total annual network cost. Two examples with single and multiple contaminants are used in order to demonstrate that involving process-to-process streams for heat integration, novel and improved solutions can be obtained compared to those reported in the literature.     

Application of global optimization strategies to refinery hydrogen network

In this paper, a new method is presented in optimization of hydrogen network. The mixed integer non-linear programming (MINLP) and non-linear programming (NLP) problems have been solved with two methods, simultaneously. The linearization technique for non-linear programming models which proposed by McCormick (1976) and also a new method proposed by Faria and Bagajewicz (2011) have been used to solve these problems. Application of this new method is presented in global optimization of MINLP/NLP, and hydrogen network problem.     

Fair electricity transfer price and unit capacity selection for microgrids

Microgrids are defined as an area of electricity distribution network that can operate autonomously from the rest of the network. In order to achieve the best economic outcomes, the participants in a microgrid can benefit from cooperation in microgrid design and operation. In this paper, a mathematical programming formulation is presented for fair, optimised cost distribution amongst participants in a general microgrid. The proposed formulation is based on the Game-theory Nash bargaining solution approach for finding optimal multi-partner cost levels subject to given upper bounds on the equivalent annual costs. The microgrid planning problem concerning the fair electricity transfer price and unit capacity selection is first formulated as a mixed integer non-linear programming model. Then, a separable programming approach is applied to reform the resulting mixed integer non-linear programming model to a mixed integer linear programming form. The model is applied to a case study with a microgrid involving five participants.     

Optimal synthesis and design of Heat Recovery Steam Generation (HRSG) via mathematical programming

Thermal efficiency of Combined Cycle Power Plants (CCPPs) depends strongly on the Heat Recovery Steam Generation (HRSG) design which links the gas cycle with the steam cycle. Therefore, the HRSG must be carefully designed in order to maximize the heat exchanged and to improve the overall performance of the plant.In this paper, a mixed integer non-linear programming (MINLP) model to simultaneously optimize the equipment arrangement, geometric design and operating conditions of CCPPs is proposed. General Algebraic Modelling System (GAMS) is used to implement and to solve the mathematical model. The HRSG model involves discrete decisions connected with the geometric design and the selection of tube diameters as well as the length and width of each solid fin. Continuous variables are used to model the operating conditions of the HRSG and steam turbines (ST). The solution strategy for the resulting model comprises two phases: the first one focuses the process optimization but considering only global energy and mass balances and this phase provides initial-bounds values for the second phase where the complete and rigorous model involving discrete decisions is solved. Different case studies with increasing complexity have been successfully solved. Model validation and results obtained from the MINLP model by considering different objective functions are discussed.     

Ethanol and glycerin processor systems coupled to solid oxide fuel cells (SOFCs). Optimal operation and heat exchangers network synthesis

This paper is aimed at presenting a methodology for the simultaneous synthesis of solid oxide fuel cell (SOFC) based systems and their associated heat exchangers network (HEN). The optimization model is formulated as a mixed integer nonlinear mathematical programming (MINLP) problem. The optimization goal is to maximize the overall net efficiency of the integrated system.     

复杂公用工程系统最优综合的MINLP方法研究

将复杂非线性公用工程系统参数优化进一步扩展到流程结构与蒸汽参数的同步联合优化，并结合典型实例给出了建模方法。根据该模型特点，采用混合连续进化算法，对算例进行了解算，获得了较为理想的结果。算例表明，该方法虽增加了模型的非线性，但减少了问题的规模，并有利于实际全局最优解的获得，更加真实的反映了系统的非线性。     

多级制冷系统超结构优化及其应用研究

在多级制冷系统超结构的基础上，以年操作费用与设备年折旧费用之和的年度总费用最低为目标函数，建立了多机制冷系统优化的混合整数非线性规划。利用该模型对乙烯裂解装置乙烯-丙烯复叠制冷系统进行了优化研究，优化后系统比原制冷系统年度总费用下降15%，经济效益明显。     

Optimal operation scheduling of wind power integrated with compressed air energy storage (CAES)

This study optimises and compares the operation of a conventional gas-fired power generation company with its operation in combination with wind power and compressed air energy storage (CAES). A mixed integer non-linear programming (MINLP) formulation is developed for the optimisation problem. Limits in ramp rate, capacity, and minimum on/off time, as well as start-up cost constraints, are considered for the modelling of conventional units. Injected and produced power constraints, storage, air balance and CAES-operation limits are considered in the CAES modelling. Two objective functions (profit maximisation and cost minimisation) are modelled. Without considering capital costs, it is found that the use of CAES results in 43% higher operational profits and 6.7% lower costs in a market environment.     

Studies on the retrofit of heat exchanger network based on the hybrid genetic algorithm

The retrofit of heat exchanger networks (HENs) is an important branch of investigation for systematic heat integration. The studies on the economical and efficient retrofit techniques are very important for the high energy-consumption enterprises to save energy, protect environment and improve their market competitiveness. Because the retrofit of HEN is an optimization problem normally solved by a mixed integer nonlinear program (MINLP) which requires enormous solution space, it is very difficult to solve it with the traditional optimization methods. In this paper, by the analysis of an existing heat exchanger network, the hybrid genetic algorithm is applied to obtain the optimal retrofitted HEN with full utilization of the existing heat exchangers and structures. Two examples are taken to show the better effect of the retrofit method with the optimal new heat exchangers and re-piping cost and energy saving.     

Identifying optimal cleaning cycles for heat exchangers subject to fouling and ageing

Fouling of heat exchangers causes reduced heat transfer and other penalties. Regular cleaning represents one widely used fouling mitigation strategy, where the schedule of cleaning actions can be optimised to minimise the cost of fouling. This paper investigates, for the first time, the situation where there are two cleaning methods available so that the mode of cleaning has to be selected as well as the cleaning interval. Ageing is assumed to convert the initial deposit, labelled ‘gel’, into a harder and more conductive form, labelled ‘coke’, which cannot be removed by one of the cleaning methods. The second method can remove both the gel layer and the coke layer, but costs more and requires the unit to be off-line longer for cleaning. Experimental data demonstrating the effects of ageing are presented. The industrial application is the comparison of cleaning-in-place methods with off-line mechanical cleaning. A process model is constructed for an isolated counter-current heat exchanger subject to fouling, where ageing is described by a simple two-layer model. Solutions generated by an NLP-based approach prove to be superior to a simpler heuristic. A series of case studies demonstrate that combinations of chemical and mechanical cleaning can be superior to mechanical cleaning alone for certain combinations of parameters.     

A Risk-Based Performance Analysis of Plate-andFrame Heat Exchangers Subject to Fouling: Economics of Heat Exchanger Cleaning

Fouling is one of the major uncertainties associated with the operation and maintenance of plate-and-frame heat exchangers (PHEs) in the steel and process industries. The decision regarding periodic maintenance (i.e., cleaning) to meet the target performance level is generally based on both thermal and economic behavior of the process. In this paper, we present a cost model that includes the risk level and the scatter parameter of random fouling growth models. Two models (namely, power law and exponential fouling growth) are integrated in the model. The non-dimensional cost function of reduced time is examined by considering dimensionless cost parameters, representing additional cost due to a decrease in effectiveness, pumping power cost, anti-foulant cost, cleaning cost, additional pumping power cost of the standby unit during cleaning, and miscellaneous costs. These dimensionless cost elements are examined for a PHE operating in the steel industry. The results are presented in terms of the risk level and scatter parameter for the underlying fouling models. Furthermore, a simplified closed-form solution is also obtained to study the optimal cycle time, which represents the minimum cost of operation and maintenance of heat exchangers. It is found that the optimum dimensionless cost increased by about 21 and 14% for the power law and exponential fouling models, respectively, as the risk level decreased from 0.5 to 0.01     

The cost of uncertainty in capacity expansion problems

The goals of this paper are to present a two‐stage programming model for the capacity expansion problem under uncertainty of demand and explore the impact of this uncertainty on cost. The model is a mixed integer nonlinear programming (MINLP) model with the consideration of uncertainty used to maximize the expected present value of utility profits over the planning horizon, under the constraints of rate of return and reserve margin regulation. The results reveal that the uncertainty harms the profit seriously. In this paper both microeconomics and mathematical programming are used to analyse the problem. We try to observe the economic behaviour of the utility with uncertainty involved. We also investigate the influence on the cost of uncertainty of each economic parameter. Copyright © 1999 John Wiley & Sons, Ltd.     

Planning the optimum cleaning schedule based on simulation of heat exchangers under fouling

An investigation of variations in outlet temperatures of heat exchangers under fouling was carried out. The simulation of heat exchangers was performed by employing a linear fouling deposit function. The formation of deposits reduces heat exchangers effectiveness. There is inherently a linear nature between outlet and inlet temperatures of heat exchangers. The outlet temperatures can also be affected by up‐stream exchangers serving the same streams, and the up‐stream influence can be transferred in the heat system. The mathematical model of the cleaning cycle was outlined, based on the objective function of minimizing cost in unit operation time. According to the results, some heat exchangers can be given cleaning priority when the system is shut down, in order to maximize economic benefit. © 2011 Wiley Periodicals, Inc. Heat Trans Asian Res; Published online in Wiley Online Library ( wileyonlinelibrary.com/journal/htj ). DOI 10.1002/htj.20384     

Energy saving opportunities in heat integrated beverage plant retrofit

This paper presents practical applications of mathematical programming for energy integration in a large beverage plant. The opportunities of heat integration between batch operations were analysed by a mixed integer linear programming (MILP) model, which was slightly modified by considering specific industrial circumstances. The feasibility of combined electricity, heating and cooling production was studied using a simplified MILP model, developed for the selection of an optimal polygeneration system. The superstructure includes cogeneration systems with different prime movers (steam turbine and gas turbine), and a trigeneration system with a back-pressure steam turbine. The proposed heat integration scheme and the selected cogeneration system may improve a company’s economic performance and reduce its environmental impact.     

Exergetic optimization of shell and tube heat exchangers using a genetic based algorithm

In the computer-based optimization, many thousands of alternative shell and tube heat exchangers may be examined by varying the high number of exchanger parameters such as tube length, tube outer diameter, pitch size, layout angle, baffle space ratio, number of tube side passes.In the present study, a genetic based algorithm was developed, programmed, and applied to estimate the optimum values of discrete and continuous variables of the MINLP (mixed integer nonlinear programming) test problems. The results of the test problems show that the genetic based algorithm programmed can estimate the acceptable values of continuous variables and optimum values of integer variables. Finally the genetic based algorithm was extended to make parametric studies and to find optimum configuration of heat exchangers by minimizing the sum of the annual capital cost and exergetic cost of the shell and tube heat exchangers. The results of the example problems show that the proposed algorithm is applicable to find optimum and near optimum alternatives of the shell and tube heat exchanger configurations.     

Power generation expansion planning with emission control: a nonlinear model and a GA‐based heuristic approach

This paper presents an application of genetic algorithms (GA) for solving the long‐term power generation expansion planning (PGEP) problem, a highly constrained nonlinear discrete optimization problem. The problem is formulated into a mixed integer nonlinear programming (MINLP) program that determines the most economical investment plan for additional thermal power generating units over a planning horizon, subject to the requirements of power demands, power capacities, loss of load probability (LOLP) levels, locations, and environmental limitations. Computational results show that the GA‐based heuristic method can solve the PGEP problem effectively and more efficiently at a significant saving in runtime, when compared with a commercial optimization package. Copyright © 2005 John Wiley & Sons, Ltd.     

基于If Then Else规则的热电联产系统能量调度方法

为了降低热电联产系统能量调度算法计算的复杂度,减少计算时间,提出了一种基于If-Then-Else规则的热电联产系统能量调度方法。通过引入逻辑变量来描述设备的启停状态和工作模式,建立混合逻辑动态模型,在模型预测控制的框架下,根据实时电价以及本地能源、电力负荷和热力负荷的预测结果,为模型中的二元决策变量赋值,从而将模型中的混合整数线性规划问题转化为线性规划问题。最后,通过仿真将本文提出的方法和混合整数线性规划方法进行比较,结果表明,本文所采用的方法在性能上几乎没有损失,平均计算时间降低65%。     

用模拟退火算法改进管壳式换热器的优化设计

介绍了一种由两级管壳式换热器组成的换热器系统的优化设计数学模型，数学模型属于典型的有约束非线性规划问题。目前对有约束非线性规划问题还没有通用的求全局最优解的算法。转轴直径搜索可行方向法(DSFD方法)是一种比较有效的求解有约束非线性规划问题的算法。但它只能得到局部最优解。将模拟退火(Simulated Annealing)算法结合DSFD算法，构成了一种DSFD—SA—DSFD算法。在应用模拟退火算法的同时引入了罚函数法．将有约束非线性问题转化为无约束非线性问题。计算结果表明，DSFD—SA—DSFD算法能较快得到换热器优化问题的最优解，克服了单纯用DSFD算法只能得到局部最优解和单纯用SA算法效率不高的缺点。图3表11参8     

Assessing wind uncertainty impact on short term operation scheduling of coordinated energy storage systems and thermal units

Renewable resources, especially wind power, are widely integrated into the power systems nowadays. Managing uncertainty of the large scale wind power is often known as one of the most challenging issues in the power system operation scheduling. Additionally, energy storage systems (ESSs) have been widely investigated in the power systems owing to their valuable applications, especially renewable energy smoothing and time shift. In this paper, a stochastic unit commitment (UC) model is proposed to assess the impact of the wind uncertainty impact on ESSs and thermal units schedule in UC problem. Wind uncertainty is modeled based on the two measures. First, the wind penetration level is changed with respect to the basic level. Second, the wind forecasting error is modeled through a normal probability distribution function with different variances. The ESSs are modeled based on several technical characteristics and optimally scheduled considering different levels of the wind penetration and forecasting accuracies. The proposed formulation is a stochastic mixed integer linear programming (SMILP) and solved using GAMS software. Simulation results demonstrate that the wind uncertainty have a considerable impact on operation cost and ESSs schedule while proposed optimum storage scheduling through the stochastic programming will reduce the daily operational cost considerably.     

Use of C-factor for monitoring of fouling in a shell and tube heat exchanger

Heat exchangers operating in process industries are fouled during operations and results in decrease in the thermal efficiency of a heat exchanger. Once the thermal efficiency decreases to a minimum acceptable level, cleaning of the equipment becomes necessary to restore the performance. This paper uses C-factor as a tool for investigation of the performance of a heat exchanger due to fouling which consequently gives information regarding the extent of fouling developed on the heat transfer surfaces. The fouling parameters are predicted by measurements of flow rate and pressure drop. In contrast to most conventional methods, the extent of fouling can be detected considering the flow rate and pressure drop when the heat exchanger operates in transient states. The C-Factor is first calculated through out cleaning period and then compared with the clean and the design value. The results show that the proposed tool is very effective in detecting the fouling developed and the corresponding degradation in heat transfer efficiency of a heat exchanger. Hence the results of this work can find applications in predicting the reduction in heat transfer efficiency due to fouling in heat exchangers that are in operation and assist the exchanger operators to plan cleaning schedules.