MESAP / TIMES — Advanced Decision Support for Energy and Environmental Planning

Remme, Uwe; Goldstein, Gary; Schellmann, Ulrich; Schlenzig, Christoph

doi:10.1007/978-3-642-50282-8_8

Cited by 21 publications

(9 citation statements)

References 3 publications

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“…The basis of the approach is the model TIMES Local, derived from the TIMES model generator [13]. An energy system is mapped in bottom-up technological detail as a network of processes (e.g.…”

Section: The Times Local Stuttgart Modelmentioning

confidence: 99%

“…Reference year for weather data and generation profiles is the year 2011. Detailed information regarding the model can be found in [13][14][15]. The focus of scenario analysis is the evaluation of the development of this energy system under consideration of an increased penetration rate of electric mobility, which has systematic repercussions on other traffic, the overall power generation and consumption as well as the achievement of local greenhouse gas emission reduction targets.…”

Section: The Times Local Stuttgart Modelmentioning

confidence: 99%

See 1 more Smart Citation

Sustainable Concept and Economic Evaluation of a Solar-Powered Hydrogen Generation Unit

Langenbucher

Brodecki²,

Wiesmeth³

et al. 2020

Adv. Mater. Lett.

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Section: The Times Local Stuttgart Modelmentioning

confidence: 99%

Section: The Times Local Stuttgart Modelmentioning

confidence: 99%

Sustainable Concept and Economic Evaluation of a Solar-Powered Hydrogen Generation Unit

Langenbucher

Brodecki²,

Wiesmeth³

et al. 2020

Adv. Mater. Lett.

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“…Bottom-up models are characterized by their high level of technological detail and are used to study the entire energy sector on the regional, national, or global scale. We explain the bottom-up approach with a schematic of a model used at the national scale shown in Figure 6 [273]. The inputs to the model are shown with inward pointing arrows: the bottom-up model requires modules that forecast the national energy demand (for instance, by using the end-use accounting approach) and primary energy supply both from imports and national energy resources.…”

Section: Bottom-up Modelsmentioning

confidence: 99%

Modeling and Simulation of Energy Systems: A Review

2018

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Energy is a key driver of the modern economy, therefore modeling and simulation of energy systems has received significant research attention. We review the major developments in this area and propose two ways to categorize the diverse contributions. The first categorization is according to the modeling approach, namely into computational, mathematical, and physical models. With this categorization, we highlight certain novel hybrid approaches that combine aspects of the different groups proposed. The second categorization is according to field namely Process Systems Engineering (PSE) and Energy Economics (EE). We use the following criteria to illustrate the differences: the nature of variables, theoretical underpinnings, level of technological aggregation, spatial and temporal scales, and model purposes. Traditionally, the Process Systems Engineering approach models the technological characteristics of the energy system endogenously. However, the energy system is situated in a broader economic context that includes several stakeholders both within the energy sector and in other economic sectors. Complex relationships and feedback effects exist between these stakeholders, which may have a significant impact on strategic, tactical, and operational decision-making. Leveraging the expertise built in the Energy Economics field on modeling these complexities may be valuable to process systems engineers. With this categorization, we present the interactions between the two fields, and make the case for combining the two approaches. We point out three application areas: (1) optimal design and operation of flexible processes using demand and price forecasts, (2) sustainability analysis and process design using hybrid methods, and (3) accounting for the feedback effects of breakthrough technologies. These three examples highlight the value of combining Process Systems Engineering and Energy Economics models to get a holistic picture of the energy system in a wider economic and policy context.

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“…44 The UKTM model is based on the model generator, The Integrated MARKAL-EFOM System, which is developed and maintained by the Energy Technology Systems Analysis Program of the International Energy Agency. [45][46][47][48][49] The UKTM explicitly represents the technology and fuel choices across different sectors under decarbonisation objectives for the UK. These choices are made based on what is economically optimal (i.e.…”

Section: Aims Of the Projectmentioning

confidence: 99%

Public health air pollution impacts of pathway options to meet the 2050 UK Climate Change Act target: a modelling study

et al. 2018

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BackgroundThe UK’sClimate Change Act 2008(CCA; Great Britain.Climate Change Act 2008. Chapter 27. London: The Stationery Office; 2008) requires a reduction of 80% in carbon dioxide-equivalent emissions by 2050 on a 1990 base. This project quantified the impact of air pollution on health from four scenarios involving particulate matter of ≤ 2.5 µm (PM2.5), nitrogen dioxide (NO2) and ozone (O3). Two scenarios met the CCA target: one with limited nuclear power build (nuclear replacement option; NRPO) and one with no policy constraint on nuclear (low greenhouse gas). Another scenario envisaged no further climate actions beyond those already agreed (‘baseline’) and the fourth kept 2011 concentrations constant to 2050 (‘2011’).MethodsThe UK Integrated MARKAL–EFOM System (UKTM) energy system model was used to develop the scenarios and produce projections of fuel use; these were used to produce air pollutant emission inventories for Great Britain (GB) for each scenario. The inventories were then used to run the Community Multiscale Air Quality model ‘air pollution model’ to generate air pollutant concentration maps across GB, which then, combined with relationships between concentrations and health outcomes, were used to calculate the impact on health from the air pollution emitted in each scenario. This is a significant improvement on previous health impact studies of climate policies, which have relied on emissions changes. Inequalities in exposure in different socioeconomic groups were also calculated, as was the economic impact of the pollution emissions.ResultsConcentrations of NO2declined significantly because of a high degree of electrification of the GB road transport fleet, although the NRPO scenario shows large increases in oxides of nitrogen emissions from combined heat and power (CHP) sources. Concentrations of PM2.5show a modest decrease by 2050, which would have been larger if it had not been for a significant increase in biomass (wood burning) use in the two CCA scenarios peaking in 2035. The metric quantifying long-term exposure to O3is projected to decrease, while the important short-term O3exposure metric increases. Large projected increases in future GB vehicle kilometres lead to increased non-exhaust PM2.5and particulate matter of ≤ 10 µm emissions. The two scenarios which achieve the CCA target resulted in more life-years lost from long-term exposures to PM2.5than in the baseline scenario. This is an opportunity lost and arises largely from the increase in biomass use, which is projected to peak in 2035. Reduced long-term exposures to NO2lead to many more life-years saved in the ‘CCA-compliant’ scenarios, but the association used may overestimate the effects of NO2itself. The more deprived populations are estimated currently to be exposed to higher concentrations than those less deprived, the contrast being largest for NO2. Despite reductions in concentrations in 2050, the most socioeconomically deprived are still exposed to higher concentrations than the less deprived.LimitationsModelling of the atmosphere is always uncertain; we have shown the model to be acceptable through comparison with observations. The necessary complexity of the modelling system has meant that only a small number of scenarios were run.ConclusionsWe have established a system which can be used to explore a wider range of climate policy scenarios, including more European and global scenarios as well as local measures. Future work could explore wood burning in more detail, in terms of the sectors in which it might be burned and the spatial distribution of this across the UK. Further analyses of options for CHP could also be explored. Non-exhaust emissions from road transport are an important source of particles and emission factors are uncertain. Further research on this area coupled with our modelling would be a valuable area of research.FundingThe National Institute for Health Research Public Health Research programme.

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MESAP / TIMES — Advanced Decision Support for Energy and Environmental Planning

Cited by 21 publications

References 3 publications

Sustainable Concept and Economic Evaluation of a Solar-Powered Hydrogen Generation Unit

Sustainable Concept and Economic Evaluation of a Solar-Powered Hydrogen Generation Unit

Modeling and Simulation of Energy Systems: A Review

Public health air pollution impacts of pathway options to meet the 2050 UK Climate Change Act target: a modelling study

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