شهرهای پایدار - مدل سازی عرضه و تقاضای انرژی شهری
|کد مقاله||سال انتشار||تعداد صفحات مقاله انگلیسی||ترجمه فارسی|
|9310||2005||14 صفحه PDF||سفارش دهید|
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Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Applied Energy, Volume 82, Issue 2, October 2005, Pages 167–180
A model of urban energy consumption has been developed using energy supply data and post-code information. The model simulates spatial and diurnal variations in energy demand, and also models the effect of energy-management measures and associated reductions in CO2 emissions. A linear programming optimisation module is used to identify the most cost-effective measures to achieve specified CO2 or energy reduction-targets. When combined with data from an associated attitudinal survey, the model can be used to assess the potential for CO2 reduction in the urban environment.
The potential threats posed by global-climate change and the need to achieve substantial cuts in CO2 emissions were recognised in the UK government’s Energy White Paper , which declares an aspiration to achieve a cut of 60% of current levels by 2050. The White Paper also identified a clear role for local government to contribute towards reducing greenhouse-gas emissions. Guidance on the role of local authorities to reduce energy consumption has been in place for many years ; similarly, the OECD has also reported on local action  in reducing consumption and improving quality-of-life. The local government association produced an energy-policy statement in 1998 and updated guidance in 2004  and . International comparisons of the different approaches of different towns and cities have also been made . However, although the technology exists to improve dramatically energy efficiency , these technical improvements are not being made on a large scale. The non-technical barriers, including attitude and behaviour, are key reasons for this lack of progress. The successful authorities and regional bodies are ones in which there are well-functioning networks of local authorities, utilities and the public, private and voluntary sectors to deliver energy efficiency improvements and promote the use of renewable energy . However, there has until recently been little concerted effort to link the technological and social-economic issues involved in managing the energy requirements of a sustainable city, and, where data have been made available, it is still difficult fully to evaluate the impact of carbon-reduction measures . A recent survey identified that most local authorities are not yet fully addressing climate change issues , although a small number have made good progress . A far greater number of local and regional bodies must implement measures to reduce greenhouse-gas emissions. However, despite the need for evidence that the measures implemented are, or have been, effective, there are no clear mechanisms for predicting and monitoring these emission reductions at a local to regional level; the Sustainable Development Commission through its dCARB-UK project  identified the need for a series of different models to identify cost-effective approaches and assess progress in reducing CO2 emissions. The work described here stems from a project which aimed at analysing both technological and socio-economic aspects of domestic and commercial energy-consumption and use the results to produce a model for urban energy-management, which could account for both factors. Some of the detailed findings of the project have been published elsewhere (see , ,  and ); the purpose of this paper is rather to describe the methodology and capabilities of the model. Patterns of energy consumption in the urban environment are highly diverse, being influenced by a range of environmental, technical, social and economic factors. The aim of this work was to produce a Geographical Information System (hereafter GIS) software-tool to allow an assessment of the impact of urban growth and aid the management of energy consumption by the optimisation of demand-side management, energy-saving measures, embedded generation and use of renewable resources. Creation of a user-friendly software-package, encompassing the full range of energy management issues suitable for the general user, was beyond the scope of the project; the emphasis was rather to construct a framework for energy-management modelling for use as a research tool. A major consideration in developing the model of energy management was to develop a methodology for the incorporation of the full diversity of factors influencing consumption, and a comprehensive representation of energy use without the need for extensive use of large datasets. A description of energy use was therefore formulated using a combination of parametric and non-parametric equations governed by a relatively small set of function parameters. A further advantage of the parameterisation approach lies in the ease of its extension to modelling hypothetical energy-management situations. The model’s capabilities were extended by the incorporation of a linear programming module, which allows the optimisation of algebraically expressed decision variables subject to user-specified constraints and is more fully discussed below. The optimisation package gives the model genuine deductive capabilities, rather than being restricted to generating the results of ‘what-if’ scenarios. The project has concentrated on a particular UK city, Leicester, as a case study. The first step in the model’s development was a detailed statistical analysis of urban energy demand for a cross-section of different consumer types. Electricity consumption data logged at half-hour intervals were available for an entire year and therefore analysed as a function of time of day, day of week and season. The second step was to assess attitudes towards various energy-management strategies. This social aspect is crucial as it allows an estimation of the likely uptake of energy-management measures. The third step was to develop a simulation model to assess both the energy flows within the area and carbon-dioxide emissions, and how they might be affected under different energy-management regimes. The simulation model incorporates embedded generation technologies, such as photovoltaic (PV) panels and energy-saving measures such as low-energy light bulbs. Account is taken of infrastructure limitations, as well as capital and running costs to assess the optimum strategy for a given growth scenario. The final step was the introduction of a GIS software tool to act as an interface to allow the user to display the results geographically. The software tool’s modelling and optimisation output, in conjunction with the results of the attitudinal research, should benefit city planners and local and regional governments in identifying cost-effective energy-management measures in urban areas. Equally, it should help utilities to assess the opportunities for power generation within a sustainable-energy framework and the likely effects on energy demand of energy-efficiency measures. City dwellers would benefit from more effective urban planning.
نتیجه گیری انگلیسی
The work has advanced the understanding of energy use in a city, investigated consumers’ (domestic and business) attitudes to energy conservation and energy pricing issues, as well as quantified the potential of solar PV, solar thermal and energy from waste in the urban environment. It has also brought together this knowledge in a versatile optimisation model whose results have the potential to be of great assistance to local authority planners. Currently the model simulates energy management in the city of Leicester and requires an ‘expert’ user to run it, but it has been designed in such a way that alterations can easily be made in order to study any city to make it more user-friendly.