This paper describes a general modeling approach for optimal planning of energy systems subject to carbon and land footprint constraints. The methodology makes use of the source–sink framework ...derived from the analogies with resource conservation networks used in process integration. Two variants of the modeling approach are developed for some of the important technologies for carbon emissions abatement: liquid biofuels in transportation, and carbon dioxide capture and storage in power generation. Despite the positive impact on environment, widespread use of these technologies has certain disadvantages. In case of biofuels, their production may strain agricultural resources, that are needed also for satisfying food demands. At the same time, carbon capture and storage is rather expensive technology and its practical implementation in power facilities must be carefully considered and planned. Optimum utilization of both technologies is identified with flexible and expandable mathematical modeling framework. Case studies are used to illustrate the variants of the methodology.
► This paper addresses water usage network with regeneration processes. Multiple contaminants and two types of water using processes are taken into regard. Simultaneous one stage optimization method ...was developed to synthesize the network. ► Merits of the approach are illustrated by examples that contain design problem with: structural issues, cost function and regeneration processes, fixed load and fixed flow rate water using processes, regeneration recycles elimination, over-constrained feasible region. ► The proposed approach generates solutions that are optimal or a set of near optimal networks.
Water network (called also water allocation) problem has been addressed in more than 200 papers to date – see recent reviews by
Jeżowski (2010) and
Foo (2009). Though various solution methods have been developed they all have some limitations. This paper addresses water usage network with regeneration processes. Multiple contaminants and two types of water using processes are taken into regard. Simultaneous one stage optimization method was developed to synthesize the network. In order to solve complex MINLP formulation we propose to apply meta-heuristic optimization – adaptive random search method.
The paper contains detailed solution algorithm. Several examples with specific features are solved to show efficiency and flexibility of the approach.
The optimal design of large-scale heat exchanger networks is a quite difficult task not only due to its non-linear characteristics but also due to a great number of local optima in its solution ...space. An explicit analytical solution of stream temperatures for the superstructure heat exchanger networks was developed, which reduces number of decision variables significantly. Based on this solution, a mathematical model for synthesis of heat exchanger networks was formulated for searching the optimal configuration of a heat recovery system by a hybrid genetic algorithm. For large-scale heat exchanger networks, a monogenetic algorithm based on the optimization of sub-networks is proposed. In the first step of the optimization, the hybrid genetic algorithm is applied to the synthesis of the whole heat exchanger network for finding the functional groups (sub-networks) rather than the chromosomes (positions of the heat exchangers and splits of the streams) and genes (areas and heat capacity flow rates). Then the monogenetic algorithm for evolution of the functional groups is carried out to improve the HEN. This procedure was applied to examples taken from literature and better results were obtained.
This paper addresses problem of designing water usage network that consists of fixed flow rate water using processes. A design method is founded on the solution of mixed-integer linear programming ...(MILP) model of network superstructure. The application of optimization to solve basic formulation of network synthesis has been reported in some works. However, this approach applies certain extensions of the standard formulation that allow accounting for several industrial scenarios. In particular, it is possible to apply various performance indices and imposing conditions on continuous variables as well as on network topology. Multiple contaminant case is easily accounted for. At least but not at last, the method is able to generate several solutions of identical values of major performance indices but of different structure and other features. All these possibilities are available within single optimization framework. Several examples are given to illustrate advantages of the approach.
This paper addresses design of
waste
water
treatment
network (WWTN) by hybrid approach. This is a sequential method applying insight-based techniques followed by mathematical programming. The water ...pinch analysis and wastewater degradation concepts are employed to develop an initial structure. Based on this solution a superstructure is created. The superstructure is the starting point for nonlinear optimisation. The decision variables are both structure of junctions (mixers and splitters) and flow rates. The optimisation model is solved by a simple but robust optimisation algorithm. The design approach can be used for synthesis and also, under some conditions, for retrofit of wastewater treatment networks. The efficiency and robustness of the approach is illustrated using literature examples and industrial cases.
The work addresses systematic simultaneous approaches to designing two process systems: heat exchanger network (HEN) and water network (WN). In both cases stochastic optimization techniques were ...applied, adaptive random search for WN and genetic algorithms for HEN. In the case of HEN design the approach is tailored for HEN retrofit and accounts for standard apparatus with discrete values of construction parameters. The aim of the paper is twofold. First, it is shown how a general problem analysis can be used for a choice of proper stochastic optimization approach to the problem. The second objective is to explain how to make use of optimization method properties and problem features to enhance efficiency and robustness of optimization. Water network design problem was solved with adaptive random search procedure applied as general-purpose optimizer for superstructure optimization model formulated in equation form. Genetic algorithms approach was applied for HEN retrofit. This is also simultaneous method based on superstructure optimization. Novel superstructure and structure representations were developed to enhance the optimization. The examples of application proved that both approaches allow reaching best solutions from the literature or even better ones in some cases.
The paper addresses a random search optimization method for nonlinear problems with continuous variables. The approach, called LJ-MM algorithm, deals with both unconstrained and constrained ...optimization problems. The algorithm was developed on the basis of the so called Luus–Jaakola (LJ) one, which was successfully used by several researchers to solve chemical and process engineering problems. The LJ-MM approach is aimed at highly multi-modal problems with sharp peaks. The major change in comparison with the LJ algorithm consists in different scheme of search space reduction rate. The tests carried out for several unconstrained and constrained problems proved its high performance for multi-modal problems with sharp peaks in particular. Also, they showed that it is the robust solver even in cases of problems with a smoother function. In all cases the performance of the LJ-MM approach depends only slightly on starting points and parameter setting. The detailed analysis of the test results and the comparison with the original LJ algorithm and others stochastic solvers is given in the paper.
The work deals with heat exchanger network (HEN) targeting under heat capacity flow-rates of streams disturbances. In particular, the aim is to calculate all pinches that can exist in a HEN with ...utilities of minimum cost when stream heat capacity flow-rates (
CPs) are allowed to change within given ranges. It is assumed that the disturbances are stochastic. The knowledge of pinches at certain as well uncertain data is of great importance in designing HENs. For instance, Pinch Technology is based on pinch phenomenon and its influence on HEN operation and design. In case of parameter disturbances, this is even more important since additional application in HEN’s control (see e.g.
1,2). It is worthnoting that in case of disturbances, pinches behave in very complex manner as it was shown in
1–5. A rigorous approach has been developed for calculating all feasible locations of pinches that can occur in minimum utility cost of HENs operating at varying heat capacity flow-rates of process streams. The method is based on recursive solution of mixed-integer linear programming (MILP) optimisation model that requires quite moderate number of binary variables. Examples of method application and analysis of results are presented in the work.
