1,458 research outputs found
Re-use of an ontology for modelling urban energy systems
The use of ontologies for the interoperability of software models is widespread, with many applications also in the energy domain. By formulating a shared data structure and a definition of concepts and their properties, a language is created that can be used between modellers and - formalised in an ontology - between model components. When modelling energy systems, connections between different infrastructures are critical, e.g. the interaction between the gas and electricity markets or the need for various infrastructures including power, heat, water and transport in cities. While a commonly shared ontology of energy systems would be highly desirable, the fact is that different existing models or applications already use dedicated ontologies, and have been demonstrated to work well using them. To benefit from linking data sources and connecting models developed with different ontologies, a translation between concepts can be made. In this paper a model of an urban energy system built upon one ontology is initialised using energy transformation technologies defined in another ontology, thus illustrating how this common perspective might benefit researchers in the energy domain. ©2010 IEEE
Simulating the impact of urban transport infrastructure design on local air quality in Beijing
Urban transport infrastructure can result in the physical, psychological and environmental separation of neighborhoods, public space
and pedestrian network, leading to negative impacts on citizensâ daily commutes, social activities and health. In this paper, we
simulate the impacts of road network design on individual activity patterns, travel mode choices and air pollution using an
agent-based model. The simulation model is applied to a case study in Beijing and the air pollution heat maps are produced for road
network designs comparing with the real-time pollution data. This illustrates the potential value of such simulation models which
generate activities for a given urban layout and transport network, and shows how human behavior can impact air qualit
An integrated optimisation platform for sustainable resource and infrastructure planning
It is crucial for sustainable planning to consider broad environmental and social dimensions and systemic implications of new infrastructure to build more resilient societies, reduce poverty, improve human well-being, mitigate climate change and address other global change processes. This article presents resilience.io, 2 a platform to evaluate new infrastructure projects by assessing their design and effectiveness in meeting growing resource demands, simulated using Agent-Based Modelling due to socio-economic population changes. We then use Mixed-Integer Linear Programming to optimise a multi-objective function to find cost-optimal solutions, inclusive of environmental metrics such as greenhouse gas emissions. The solutions in space and time provide planning guidance for conventional and novel technology selection, changes in network topology, system costs, and can incorporate any material, waste, energy, labour or emissions flow. As an application, a use case is provided for the Water, Sanitation and Hygiene (WASH) sector for a four million people city-region in Ghana
Water and energy systems in sustainable city development: a case of Sub-saharan Africa
Current urban water and energy systems are expanding while increasing attention is paid to their social, economic and environmental impacts. As a research contribution that can support real-world decision making and transitions to sustainable cities and communities, we have built a model-based and data-driven platform combining comprehensive database, agent-based simulation and resource technology network optimization for system level water and energy planning. Several use cases are demonstrated based on the Greater Accra Metropolitan Area (GAMA) city-region in Ghana, as part of the Future Cities Africa (FCA) project. The outputs depict an overall resource landscape of the studied urban area, but also provide the energy, water, and other resource balance of supply and demand from both macro and micro perspectives, which is used to propose environmental friendly and cost effective sustainable city development strategies. This work is to become a core component of the resilience.io platform as an open-source integrated systematic tool gathering social, environmental and economic data to inform urban planning, investment and policy-making for city-regions globally
Simulating residential electricity and heat demand in urban areas using an agent-based modelling approach
Cities account for around 75% of the global energy demand and are responsible for 60-70% of the global greenhouse gasses emissions. To reduce this environmental impact it is important to design efficient energy infrastructures able to deal with high level of renewable energy resources. A crucial element in this design is the quantitative understanding of the dynamics behind energy demands such as transport, electricity and heat. In this paper an agent-based simulation model is developed to generate residential energy demand profiles in urban areas, influenced by factors such as land use, energy infrastructure and user behaviour. Within this framework, impact assessment of low carbon technologies such as plug-in electric vehicles and heat pumps is performed using London as a case study. The results show that the model can generate important insights as a decision support tool for the design and planning of sustainable urban energy systems
Integrated design of transport infrastructure and public spaces considering human behavior: A review of state-of-the-art methods and tools
In order to achieve holistic urban plans incorporating transport infrastructure, public space and the behavior of people in these spaces, integration of urban design and computer modeling is a promising way to provide both qualitative and quantitative support to decision-makers. This paper describes a systematic literature review following a four-part framework. Firstly, to understand the relationship of elements of transport, spaces, and humans, we review policy and urban design strategies for promoting positive interactions. Secondly, we present an overview of the integration methods and strategies used in urban design and policy discourses. Afterward, metrics and approaches for evaluating the effectiveness of integrated plan alternatives are reviewed. Finally, this paper gives a review of state-of-the-art tools with a focus on seven computer simulation paradigms. This article explores mechanisms underlying the complex system of transport, spaces, and humans from a multidisciplinary perspective to provide an integrated toolkit for designers, planners, modelers and decision-makers with the current methods and their challenges
An agent-based decision support framework for a prospective analysis of transport and heat electrification in urban areas
One of the main pathways that cities are taking to reduce greenhouse gas emissions is the decarbonisation of the electricity supply in conjunction with the electrification of transport and heat services. Estimating these future electricity demands, greatly influenced by end-usersâ behaviour, is key for planning energy systems. In this context, support tools can help decision-makers assess different scenarios and interventions during the design of new planning guidelines, policies, and operational procedures. This paper presents a novel bottom-up decision support framework using an agent-based modelling and simulation approach to evaluate, in an integrated way, transport and heat electrification scenarios in urban areas. In this work, an open-source tool named SmartCityModel is introduced, where agents represent energy users with diverse sociodemographic and technical attributes. Based on agentsâ behavioural rules and daily activities, vehicle trips and building occupancy patterns are generated together with electric vehicle charging and building heating demands. A representative case study set in London, UK, is shown in detail, and a summary of more than ten other case studies is presented to highlight the flexibility of the framework to generate high-resolution spatiotemporal energy demand profiles in urban areas, supporting decision-makers in planning low-carbon and sustainable cities
Metabolic effects of diets differing in glycaemic index depend on age and endogenous GIP
Aims/hypothesis
High- vs low-glycaemic index (GI) diets unfavourably affect body fat mass and metabolic markers in rodents. Different effects of these diets could be age-dependent, as well as mediated, in part, by carbohydrate-induced stimulation of glucose-dependent insulinotrophic polypeptide (GIP) signalling.
Methods
Young-adult (16 weeks) and aged (44 weeks) male wild-type (C57BL/6J) and GIP-receptor knockout (Gipr â/â ) mice were exposed to otherwise identical high-carbohydrate diets differing only in GI (20â26 weeks of intervention, nâ=â8â10 per group). Diet-induced changes in body fat distribution, liver fat, locomotor activity, markers of insulin sensitivity and substrate oxidation were investigated, as well as changes in the gene expression of anorexigenic and orexigenic hypothalamic factors related to food intake.
Results
Body weight significantly increased in young-adult high- vs low-GI fed mice (two-way ANOVA, pâ<â0.001), regardless of the Gipr genotype. The high-GI diet in young-adult mice also led to significantly increased fat mass and changes in metabolic markers that indicate reduced insulin sensitivity. Even though body fat mass also slightly increased in high- vs low-GI fed aged wild-type mice (pâ<â0.05), there were no significant changes in body weight and estimated insulin sensitivity in these animals. However, aged Gipr â/â vs wild-type mice on high-GI diet showed significantly lower cumulative net energy intake, increased locomotor activity and improved markers of insulin sensitivity.
Conclusions/interpretation
The metabolic benefits of a low-GI diet appear to be more pronounced in younger animals, regardless of the Gipr genotype. Inactivation of GIP signalling in aged animals on a high-GI diet, however, could be beneficial
Evaluating the Impact of an Integrated Urban Design of Transport Infrastructure and Public Space on Human Behavior and Environmental Quality: A Case Study in Beijing
Urban transport infrastructure can result in the physical, psychological and environmental separation of neighborhoods, public spaces and pedestrian networks, leading to negative impacts on citizensâ daily commutes, social activities and the quality of the ecosystem. An integrated design of transport infrastructure and public space is beneficial for mediating these negative impacts. In this paper, we propose an integrated methodology, which combines urban design, computational scenario evaluation and decision-making processes, based on a conceptual model of human and ecological needs-driven planning. To evaluate the impacts of the road network and public space design on individual outdoor activities, travel behavior and air pollution, an agent-based model is demonstrated. This model is then applied to a case study in Beijing, leading to hourly traffic volume maps and car-related air pollution heat maps of a baseline road network-public space design
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