Qualitative modelling of sustainable energy scenarios: An application and extension of the Bon Qualitative Input-Output model

Climate change is one of the major challenges facing economic systems at the start of the 21st century. Reducing greenhouse gas emissions will require both restructuring the energy supply system (production) and addressing the efficiency and sufficiency of the social uses of energy (consumption). The energy production system is a complicated supply network of interlinked sectors with 'knock-on' effects throughout the economy. End use energy consumption is governed by complex sets of interdependent cultural, social, psychological and economic variables driven by shifts in consumer preference and technological development trajectories. To date, few models have been developed for exploring alternative joint energy production-consumption systems. The aim of this work is to propose one such model. This is achieved in a methodologically coherent manner through integration of qualitative input-output models of production, with Bayesian belief network models of consumption, at point of final demand. The resulting integrated framework can be applied either (relatively) quickly and qualitatively to explore alternative energy scenarios, or as a fully developed quantitative model to derive or assess specific energy policy options. The qualitative applications are explored here.

Input/output linearization using dynamic recurrent neural networks

This paper brings together two areas of research that have received considerable attention during the last years, namely feedback linearization and neural networks. A proposition that guarantees the Input/Output (I/O) linearization of nonlinear control affine systems with Dynamic Recurrent Neural Networks (DRNNs) is formulated and proved. The proposition and the linearization procedure are illustrated with the simulation of a single link manipulator.

Dynamic input/output linearization using recurrent neural networks

A dynamic recurrent neural network (DRNN) is used to input/output linearize a control affine system in the globally linearizing control (GLC) structure. The network is trained as a part of a closed loop that involves a PI controller, the goal is to use the network, as a dynamic feedback, to cancel the nonlinear terms of the plant. The stability of the configuration is guarantee if the network and the plant are asymptotically stable and the linearizing input is bounded.

Comparison of multifactor productivity indicators for real estate sectors using the OECD input-output database

"Research on the international comparison of productivity has gained significant interest throughout several previous decades. Relatively little work has however been done in the real estate sector. This paper aims to develop a new productivity measurement framework for the international comparison of the real estate sector based on the newly-published OECD input-output database. Three multifactor productivity indicators are formulated using the ratio of the sectoral final demand to value added, the intermediate output to intermediate input and the total output to total input effect respectively in the input-output table. Historical analyses and comparisons are also carried out to indicate the differences of productivities of the real estate sectors in seven selected countries. Findings can improve the understanding of how technological, organisational and policy influences combine to affect productivity growth and aid the policy makers, real estate agencies and researchers in evaluating the competitive ability of the real estate sector."

Comprehensive embodied energy analysis framework

The assessment of the direct and indirect requirements for energy is known as embodied energy analysis. For buildings, the direct energy includes that used primarily on site, while the indirect energy includes primarily the energy required for the manufacture of building materials. This thesis is concerned with the completeness and reliability of embodied energy analysis methods. Previous methods tend to address either one of these issues, but not both at the same time. Industry-based methods are incomplete. National statistical methods, while comprehensive, are a ‘black box’ and are subject to errors. A new hybrid embodied energy analysis method is derived to optimise the benefits of previous methods while minimising their flaws. In industry-based studies, known as ‘process analyses’, the energy embodied in a product is traced laboriously upstream by examining the inputs to each preceding process towards raw materials. Process analyses can be significantly incomplete, due to increasing complexity. The other major embodied energy analysis method, ‘input-output analysis’, comprises the use of national statistics. While the input-output framework is comprehensive, many inherent assumptions make the results unreliable. Hybrid analysis methods involve the combination of the two major embodied energy analysis methods discussed above, either based on process analysis or input-output analysis. The intention in both hybrid analysis methods is to reduce errors associated with the two major methods on which they are based. However, the problems inherent to each of the original methods tend to remain, to some degree, in the associated hybrid versions. Process-based hybrid analyses tend to be incomplete, due to the exclusions associated with the process analysis framework. However, input-output-based hybrid analyses tend to be unreliable because the substitution of process analysis data into the input-output framework causes unwanted indirect effects. A key deficiency in previous input-output-based hybrid analysis methods is that the input-output model is a ‘black box’, since important flows of goods and services with respect to the embodied energy of a sector cannot be readily identified. A new input-output-based hybrid analysis method was therefore developed, requiring the decomposition of the input-output model into mutually exclusive components (ie, ‘direct energy paths’). A direct energy path represents a discrete energy requirement, possibly occurring one or more transactions upstream from the process under consideration. For example, the energy required directly to manufacture the steel used in the construction of a building would represent a direct energy path of one non-energy transaction in length. A direct energy path comprises a ‘product quantity’ (for example, the total tonnes of cement used) and a ‘direct energy intensity’ (for example, the energy required directly for cement manufacture, per tonne). The input-output model was decomposed into direct energy paths for the ‘residential building construction’ sector. It was shown that 592 direct energy paths were required to describe 90% of the overall total energy intensity for ‘residential building construction’. By extracting direct energy paths using yet smaller threshold values, they were shown to be mutually exclusive. Consequently, the modification of direct energy paths using process analysis data does not cause unwanted indirect effects. A non-standard individual residential building was then selected to demonstrate the benefits of the new input-output-based hybrid analysis method in cases where the products of a sector may not be similar. Particular direct energy paths were modified with case specific process analysis data. Product quantities and direct energy intensities were derived and used to modify some of the direct energy paths. The intention of this demonstration was to determine whether 90% of the total embodied energy calculated for the building could comprise the process analysis data normally collected for the building. However, it was found that only 51% of the total comprised normally collected process analysis. The integration of process analysis data with 90% of the direct energy paths by value was unsuccessful because: • typically only one of the direct energy path components was modified using process analysis data (ie, either the product quantity or the direct energy intensity); • of the complexity of the paths derived for ‘residential building construction’; and • of the lack of reliable and consistent process analysis data from industry, for both product quantities and direct energy intensities. While the input-output model used was the best available for Australia, many errors were likely to be carried through to the direct energy paths for ‘residential building construction’. Consequently, both the value and relative importance of the direct energy paths for ‘residential building construction’ were generally found to be a poor model for the demonstration building. This was expected. Nevertheless, in the absence of better data from industry, the input-output data is likely to remain the most appropriate for completing the framework of embodied energy analyses of many types of products—even in non-standard cases. ‘Residential building construction’ was one of the 22 most complex Australian economic sectors (ie, comprising those requiring between 592 and 3215 direct energy paths to describe 90% of their total energy intensities). Consequently, for the other 87 non-energy sectors of the Australian economy, the input-output-based hybrid analysis method is likely to produce more reliable results than those calculated for the demonstration building using the direct energy paths for ‘residential building construction’. For more complex sectors than ‘residential building construction’, the new input-output-based hybrid analysis method derived here allows available process analysis data to be integrated with the input-output data in a comprehensive framework. The proportion of the result comprising the more reliable process analysis data can be calculated and used as a measure of the reliability of the result for that product or part of the product being analysed (for example, a building material or component). To ensure that future applications of the new input-output-based hybrid analysis method produce reliable results, new sources of process analysis data are required, including for such processes as services (for example, ‘banking’) and processes involving the transformation of basic materials into complex products (for example, steel and copper into an electric motor). However, even considering the limitations of the demonstration described above, the new input-output-based hybrid analysis method developed achieved the aim of the thesis: to develop a new embodied energy analysis method that allows reliable process analysis data to be integrated into the comprehensive, yet unreliable, input-output framework. Plain language summary Embodied energy analysis comprises the assessment of the direct and indirect energy requirements associated with a process. For example, the construction of a building requires the manufacture of steel structural members, and thus indirectly requires the energy used directly and indirectly in their manufacture. Embodied energy is an important measure of ecological sustainability because energy is used in virtually every human activity and many of these activities are interrelated. This thesis is concerned with the relationship between the completeness of embodied energy analysis methods and their reliability. However, previous industry-based methods, while reliable, are incomplete. Previous national statistical methods, while comprehensive, are a ‘black box’ subject to errors. A new method is derived, involving the decomposition of the comprehensive national statistical model into components that can be modified discretely using the more reliable industry data, and is demonstrated for an individual building. The demonstration failed to integrate enough industry data into the national statistical model, due to the unexpected complexity of the national statistical data and the lack of available industry data regarding energy and non-energy product requirements. These unique findings highlight the flaws in previous methods. Reliable process analysis and input-output data are required, particularly for those processes that were unable to be examined in the demonstration of the new embodied energy analysis method. This includes the energy requirements of services sectors, such as banking, and processes involving the transformation of basic materials into complex products, such as refrigerators. The application of the new method to less complex products, such as individual building materials or components, is likely to be more successful than to the residential building demonstration.

An input-output-based linkage measurement framework

This study proposed an input-output-based linkage measurement framework, which is a multi-level hierarchy, omni-direction decision-making model and takes the impact of capital into account. This framework had resolved the critical deficiencies and inherent limitations of the existing methods and was used to explore the real estate and construction linkages.

Análise de ecossistemas aquáticos através do método input-output : estudo de caso lagoa Itapeva (sistema lagunar costeiro do Rio Grande do Sul)

A enorme complexidade dos sistemas ecológicos tem sido uma grande barreira para a compreensão e o gerenciamento da problemática ambiental. Neste sentido a modelagem matemática é uma valiosa ferramenta, devido a sua capacidade de organizar as informações disponíveis sobre estes sistemas e de fazer previsões a seu respeito para diferentes condições. Desta forma a análise de sistemas naturais vem sendo abordada de diferentes maneiras, sendo que nas últimas décadas a teoria de ecossistemas expandiu-se e ramos específicos, que permitem seguir e predizer a evolução de ecossistemas, foram formulados. Um destes enfoques, conhecido como análise do fluxo de insumo-produto, pode ser utilizado para explicar o funcionamento e estrutura dos subsistemas de um ecossistema através da descrição dos fluxos de matéria ou energia. A análise do fluxo de insumo-produto pode ser representada através de dois modelos: o modelo determinístico ou o modelo estocástico, tendo sua origem em estudos de caso com o objetivo de analisar a econômica norte-americana, sendo uma extensão prática da teoria clássica de interdependência geral. Este trabalho faz uma abordagem sintética da evolução desta análise, avaliando dados teóricos e principalmente dados referentes à Lagoa Itapeva. A análise de input-output (determinística e estocástica) com o propósito de obter informações no que diz respeito aos fluxos (matéria e energia), é bastante simples; sendo que os modelos determinísticos se prestam melhor para traçar um panorama global e para obter projeções para as variáveis já os modelos estocásticos são mais complexos, mas provêem uma descrição mais acurada. Na Lagoa Itapeva os processos determinísticos demonstraram um baixo índice de ciclagem do carbono entre os três compartimentos em estudo e o fluxo preferencial na normalização corresponde ao compartimento dos produtores primários, isto decorre de não existir loop nos compartimentos em estudo e também não existir fluxos em dois sentidos. Em relação à avaliação estocástica foram observadas uma baixa relação no sentido espacial superfície-meio-fundo da lagoa, e uma boa distribuição espacial norte-centro-sul. Quanto à distribuição temporal, foi constatada uma baixa concordância entre os dados analisados e os dados reais quanto das análises realizadas em intervalos de tempo pequeno (horas) e uma boa concordância nas medidas feitas quando o intervalo foi significativo (meses). Também em relação à Lagoa Itapeva, foi verificado nas análises estocásticas, utilizando-se operadores espaciais, que como a dinâmica biológica nem sempre é linear, os organismos não podem acompanhar imediatamente e perfeitamente as mudanças do ambiente, resultando em tempos de residência de matéria significativamente baixo. Além da análise dos fluxos ligados a este ecossistema lagunar, foram desenvolvidas técnicas de correção e adaptação de dados referentes à amostragem ocorrida na Lagoa durante um ano de campanha. Assim, propõe-se uma nova perspectiva no uso desta metodologia de forma simples e de fácil manipulação matemática.

The input-output model

Includes bibliography