Nasser Ayoub

Superstructure-based design and operation for biomass utilization networks

This paper is providing a design and evaluation methodology for biomass utilization networks (B-NETs) planning in local areas. The methodology is an effort to integrate various exertions of many researchers as well as stakeholders in the biomass field including process technologies, local area classification and renewable energy mechanisms to design and evaluate B-NETs. The proposed design methodology has three steps: classification, problem formulation and suggesting solution methods. The core part of planning the B-NETs utilization methodology is the superstructure that is a super class model for the processes of biomass utilization networks that has to be built for the local area. The biomass utilization superstructure (BUSS) relates the biomass resources to their products, available processes, and possible future processes of utilization in static manner. Although the local area BUSS is static in nature, it shows the decision makers what kinds of B-NETs are, or can be, available in their area. It is important to note that for each super class process there exists a number of elemental technologies, or what we call unit process (UP), that can perform the job under the same condition with different processing constraint. To support the design and operation process a technological information infrastructure (TII) needs to be built to work as an information pool and simulation tool. With the support of TII and the BUSS different scenarios can be synthesized, analyzed and compared. Scenarios development enables the designer to check processing alternatives as well as biomass promotion mechanisms that fit the concerns of various stakeholders. The results of the methodology application can be given in the form of suggestions of a specific network class(es) or scenarios that can be applied in a class of localities with the same characteristics. Following to methodology configuration, a proposal for optimization methods is discussed and a case study for comparing biomass network scenarios in mountainous city is introduced.

Demand-driven optimization approach for biomass utilization networks

Abstract Building Biomass Networks (B-NETs) is one of the techniques used to overcome the seasonal fluctuation in biomass supply and tapping new utilizations ways. The B-NETs are built based on a super class model for the available and possible kinds of utilization processes in the local area. Hence, the decision of selecting possible networks and scenarios can be made before using optimization methods to fix on the optimal network. In this paper, an optimization model for a Demand-driven biomass processing network is proposed. This is done through selecting alternative production paths for the same product depending on the resources availability. The unit process capacities and biomass resource availability constraints were presented to overcome their limitations in the local area. The genetic algorithms (GAs) were used in solving the problem because of their ability to deal with large search spaces and capability to calculate material flows, through networks, with no previous estimations.

A planning support system for biomass-based power generation

Abstract When planning biomass-based power generation, planners should take into account the different stakeholders along the biomass supply chains, e.g. biomass resources suppliers, transport, conversion and electricity suppliers etc. Also the planners have to consider the social concerns about environmental and economical impacts of establishing the biomass systems. Accordingly, in order to overcome these struggles in sustainable manner, we should take into account the new environmental institutions, e.g. RPS (Renewable Portfolio Standard) to promote them as well as the bioenergy production systems. To address the problems mentioned above, a Planning Support System (PSS) for biomass-based power generation is developed. This paper introduces the general structure for the PSS at both national and local levels of the biomass planning process. The PSS is a user-oriented system which employs data visualization, data analysis and simulation methods in interaction with the knowledge and intentions of the users to provide them with understandable results. A case study on planning forestry residues utilization at the national level is presented.

A methodology for designing and evaluating Biomass Utilization Networks

Abstract This paper presents a methodology for designing and evaluating Biomass Utilization Networks, BUN, in local areas. Therefore, the proposed methodology assumes the great importance of establishing the BUN superstructure for the area under study, which relates the biomass resources to their products, available processes and possible future processes of utilization. Using the developed network superstructure, the quantitative data of the local biomass resources, the bioproducts demands, the redundant resources and processes, due to low amount, low demand, or technical problems, are excluded. Then two types of network structures were set upped, the first is the reference models that show the current situation with its possibilities for improvements and the second type is future network structures that can be established excluding or partly including, the current utilization strategy. The resulted network structures are used as a blue print for different scenarios of integrated biomass utilization systems that can be evaluated in comparison to the reference scenario. Optimizing the different scenarios allows us to define the bottlenecks in the biomass utilization system that limits its total throughput. Solving the optimization problem of the selected network structure in the local level needs high rank of details where each resources supply chain includes wide range of Unit Processes, UPs, that meet domestic circumstances e.g. logistics, production facilities, and so on. The GA was used to solve this optimization problem as a powerful tool in solving such combinatorial problems considering three optimization criterions, e.g. costs, emissions, energy consumption to congregate the different economical and environmental burdens of the established BUN.