Istvan Heckl

Process synthesis involving multi-period operations by the P-graph framework

Abstract The P-graph (process graph) framework is an effective tool for process-network synthesis (PNS). Here we extended it to multi-period operations. The efficacy of the P-graph methodology has been demonstrated by numerous applications. The unambiguous representation of processes and the availability of the axioms defining combinatorially feasible structures facilitates the development of efficient algorithms to determine maximal structures, solution structures, and optimal structure for processes. However, it is presumed that single-period operation prevails. It implies that the operating conditions and the load of each operating unit remain unchanged, i.e., steady-state operation. This is usually true for the chemical industry but often not in agriculture or where seasonal effects are important. The current work proposes a multi-period operation wherein the load of operating units varies from period to period to accommodate demand, assuming operating conditions remain steady in each period. A modeling technique is proposed to represent operating units in the multi-period operation. The different periods are connected by “fictitious” streams, which ensures, that the unit is sized properly.

Solution of separation network synthesis problems by the P-graph methodology

The current work demonstrates that separation-network synthesis (SNS) problems can be transformed into process-network synthesis (PNS) problems: the SNS problems constitute a particular class of PNS problems. Thus, the transformed SNS problems are solvable by resorting to the P-graph methodology originally introduced for the PNS problems. The methodology has been unequivocally proven to be inordinately effective.

Regional Optimizer (RegiOpt) – Sustainable energy technology network solutions for regions

Abstract Developing energy strategies for the future is an important strategic task for regions and municipalities. Renewable based technologies and decentralized energy supply based on regional resources have the potential to locally and regionally increase added value, provide new jobs, decrease the dependency on limited fossil resources as well as on external energy providers and may have a positive impact on ecological stability. Regional Optimizer (RegiOpt) software tool is based on the concept of Process Network Synthesis (PNS) (Friedler et. al, 1995 and Halasz et. al, 2005) and of the Sustainable Process Index (SPI) (Kotscheck et. al., 1996 and Sandholzer et. al., 2005). Both methodologies are combined in RegiOpt to enable the user to create economically optimal sustainable energy technology networks and at the same time evaluate them with respect to environmental sustainability. Inputs to the software are (renewable) resources (e.g. amount of crops available for energetic use, biowaste, waste heat, etc.) and regional energy demand profiles. Both resource provision and energy demand can be provided in time dependent form. On top of that the user may supply contextual information like costs and prices of particular resources and services. Result of the calculation with RegiOpt is the economically optimized technology network that fulfils the energy needs defined by the user and renders the highest regional added value. RegiOpt also provides the ecological footprint according to the SPI methodology. The user is able to calculate different scenarios based on different input data. RegiOpt software tool will be provided in two versions. Web based “Conceptual Planner” as a simple analysis for regional stakeholders and an “Advanced Designer” for a more detailed technology network scenario generation meant for expert use.

Reduced super-structure for a separation network comprising separators effected by different methods of separation

Among separation systems, the ones comprising separators effected by different separation methods have been steadily gaining attention lately. Our earlier work has revealed that it is exceedingly complicated to optimally synthesize via super-structure any of these separation networks featuring simple and sharp separators, multiple feed and product streams, and mixed products. This complication can be substantially lessened by constituting a reduced super-structure for the network of interest. This super-structure profoundly simplifies the mathematical model and decreases the computational time required to yield the results identical to those obtained from the original super-structure.

Waste to energy for small cities: Economics versus carbon footprint

The main activities in Waste to Energy processing include waste generation, collection, separation, transportation, conversion, energy distribution, and ultimate waste disposal. Waste to Energy carries a trade-off between energy generation and the energy spent on collection, transport and treatment. Major performance indicators are cost, Waste Energy Potential Utilisation, and Carbon Footprint. This presentation analyses the potential of small cities to substitute part of their fossil fuels use by energy derived from Municipal Solid Waste. Several factors are considered in the study. The impact of waste logistics and the losses from energy distribution systems – natural gas pipeline and electricity grid are the most significant ones on the side of the supply chain. Further, the waste processing part, including the energy recovery from the waste involves the evaluation of a number of technologies linked with each other to form a distributed integrated processing system. In this study, the options for converting waste into thermal energy include (a) biogas digestion and burning and (b) waste incineration with off-gas cleaning. It is also possible to use the biogas in advanced cogeneration systems based on engines or fuel cells. The proposed procedure takes all these options into account and derives the optimal processing configuration from the waste generation to energy supply and residual waste deposition to landfill.

Customized solvers for the operational planning and scheduling of utility systems

Abstract The paper explains a paradigm for the integration of engineering knowledge with the search strategy of a Branch and Bound algorithm. The optimization is fairly generic and addresses industrial applications comprising power-generating units. The solution concerns the allocation of the units over time and considers expected variations in the heat load and power. The engineering knowledge exploits the Hardware Composites, a conceptual tool for the operation of utility systems. The knowledge is capitalized at three different levels: (i) to exclude redundant combinations of decision variables, (ii) to prioritize the branching of the algorithm, and (iii) to prune the binary tree. Using a non-commercial LP, an MILP solver is designed and compared with highly-valued, state-of-the-art commercial solvers. The comparisons are particularly impressive in that the customized development outperforms the sophisticated packages and accommodates accelerations of at least two orders of magnitude.

Designing Sustainable Supply Chains in the Energy-water-food Nexus by the P-graph Methodology

The P-graph or process graph framework is both a representation and a methodology that can be shown to be extremely useful as a modelling tool in various areas. P-graphs are directed bi-partite graphs that give an unambiguous representation of any process that can be expressed as a network. It is based on rigorous axioms and combinatorial analysis. The result is a maximal structure, solution structures, and an optimal structure of the network for the process of interest. All of these are feasible and meet design requirements. There is freely available software which automates much of the application of the methodology. The P-graph framework is most useful in the initial design phase of a process where the requirements, the feedstocks, the outputs, and the necessary process structure or network may not be precisely defined, but there is a need to generate alternatives which are feasible to start the design process. For this reason, we propose the P-graph framework as an effective means of generating alternative networks which can represent the nexus of energy, water, and food for the purpose of looking for the most cost effective and sustainable options.

Process Network Synthesis for Benzaldehyde Production: P-graph Approach

a Department of Chemical and Environmental Engineering, Universidad Nacional de Colombia, Bogotá, Colombia b Department of Computer Science and Systems Technology, University of Pannonia, Veszprém, Egyetem u.10 H-8200, Hungary c Faculty of Information Technology, Pázmány Péter Catholic University, Práter u. 50/A, 1083 Budapest, Hungary d Department of Systems Engineering, Universitaria de Investigación y Desarrollo, Calle 9 No. 23-55, Bucaramanga Colombia e Department of Chemical Engineering, Kansas State University, 1005 Durland Hall, Manhattan, Kansas 66506, USA argoti@k-state.edu

Modeling Multi-period Operations using the P–graph Methodology

A new modeling technique is presented here for handling multi-period operations in process-network synthesis (PNS) problems by the P-graph (process graph) framework. Until now, the P-graph framework could only handle single-period operating units. It means that the operating conditions and the load of each unit remain unchanged throughout its operation. This assumption is usually true for the chemical industry but may be false in agriculture or in other areas where seasonal effects are important. Hence, the current work proposes the notion of multi-period operation wherein the load of an operating unit may vary from period to period. Subsequently, a modeling technique is proposed to represent operating units in the multi-period operation. The idea is to represent separately the physical body of an operating unit and the operations in each period. Surprisingly, to achieve these tasks, there is no need to dramatically change or augment the basic structure of the P-graph methodology, e.g. with a new type of multi-period unit, but the already available constituents are adequate.

PNS solutions: A P-graph based programming framework for process network synthesis

A novel programming framework has been developed for the P-graph-based methodology to provide a standardized software environment for different classes of process-network synthesis (PNS) problems. The P-graph framework has been proven highly successful; its applicability encompasses wide-ranging areas such as reactionpathway identification, vehicle-routing problems and business-process modeling. A uniform programming paradigm has been proposed here to integrate various available solution engines and interfaces of different types of PNS problems into a single system. A client server architecture with a standardized communication protocol has also been developed, which renders it to be deployable by various client programs with different features, possibly implementable in different programming languages, or adoptable by varied solvers customized for specific problems. Numerous P-graph-based algorithms have been implemented to demonstrate the efficacy of the P-graph framework.