The Experts below are selected from a list of 4080 Experts worldwide ranked by ideXlab platform
Paul E. Dodds - One of the best experts on this subject based on the ideXlab platform.
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Characterising the Evolution of Energy System Models Using Model Archaeology
Environmental Modeling & Assessment, 2015Co-Authors: Paul E. Dodds, Ilkka Keppo, Neil StrachanAbstract:In common with other types of complex Models, Energy System Models have opaque structures, making it difficult to understand both changes between model versions and the extent of changes described in research papers. In this paper, we develop the principle of model archaeology as a formal method to quantitatively examine the balance and evolution of Energy System Models, through the ex post analysis of both model inputs and outputs using a series of metrics. These metrics help us to understand how Models are developed and used and are a powerful tool for effectively targeting future model improvements. The usefulness of model archaeology is demonstrated in a case study examining the UK MARKAL model. We show how model development has been influenced by the interests of the UK government and the research projects funding model development. Despite these influences, there is clear evidence of a strategy to balance model complexity and accuracy when changes are made. We identify some important long-term trends including higher technology capital costs in subsequent model versions. Finally, we discuss how model archaeology can improve the transparency of research model studies.
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Hydrogen and fuel cell technologies for heating: A review
International Journal of Hydrogen Energy, 2015Co-Authors: Paul E. Dodds, Francis Li, Adam D. Hawkes, Will Mcdowall, Iain Staffell, Philipp Grunewald, Paul EkinsAbstract:The debate on low-carbon heat in Europe has become focused on a narrow range of technological options and has largely neglected hydrogen and fuel cell technologies, despite these receiving strong support towards commercialisation in Asia. This review examines the potential benefits of these technologies across different markets, particularly the current state of development and performance of fuel cell micro-CHP. Fuel cells offer some important benefits over other low-carbon heating technologies, and steady cost reductions through innovation are bringing fuel cells close to commercialisation in several countries. Moreover, fuel cells offer wider Energy System benefits for high-latitude countries with peak electricity demands in winter. Hydrogen is a zero-carbon alternative to natural gas, which could be particularly valuable for those countries with extensive natural gas distribution networks, but many national Energy System Models examine neither hydrogen nor fuel cells for heating. There is a need to include hydrogen and fuel cell heating technologies in future scenario analyses, and for policymakers to take into account the full value of the potential contribution of hydrogen and fuel cells to low-carbon Energy Systems.
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integrating housing stock and Energy System Models as a strategy to improve heat decarbonisation assessments
Applied Energy, 2014Co-Authors: Paul E. DoddsAbstract:The UK government heat strategy is partially based on decarbonisation pathways from the UK MARKAL Energy System model. We review how heat provision is represented in UK MARKAL, identifying a number of shortcomings and areas for improvement. We present a completely revised model with improved estimations of future heat demands and a consistent representation of all heat generation technologies. This model represents all heat delivery infrastructure for the first time and uses dynamic growth constraints to improve the modelling of transitions according to innovation theory. Our revised model incorporates a simplified housing stock model, which is used produce highly-refined decarbonisation pathways for residential heat provision. We compare this disaggregated model against an aggregated equivalent, which is similar to the existing approach in UK MARKAL. Disaggregating does not greatly change the total residential fuel consumption in two scenarios, so the benefits of disaggregation will likely be limited if the focus of a study is elsewhere. Yet for studies of residential heat, disaggregation enables us to vary consumer behaviour and government policies on different house types, as well as highlighting different technology trends across the stock, in comparison with previous aggregated versions of the model.
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methodologies for representing the road transport sector in Energy System Models
International Journal of Hydrogen Energy, 2014Co-Authors: Paul E. Dodds, Will McdowallAbstract:Energy System Models are often used to assess the potential role of hydrogen and electric powertrains for reducing transport CO2 emissions in the future. In this paper, we review how different Energy System Models have represented both vehicles and fuel infrastruc- ture in the past and we provide guidelines for their representation in the future. In particular, we identify three key modelling decisions: the degree of car market segmen- tation, the imposition of market share constraints and the use of lumpy investments to represent infrastructure. We examine each of these decisions in a case study using the UK MARKAL model. While disaggregating the car market principally affects only the transition rate to the optimum mix of technologies, market share constraints can greatly change the optimum mix so should be chosen carefully. In contrast, modelling infrastructure using lumpy investments has little impact on the model results. We identify the development of new methodologies to represent the impact of behavioural change on transport demand as a key challenge for improving Energy System Models in the future.
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Methodologies for representing the road transport sector in Energy System Models
International Journal of Hydrogen Energy, 2014Co-Authors: Paul E. DoddsAbstract:Energy System Models are often used to assess the potential role of hydrogen and electric powertrains for reducing transport CO2 emissions in the future. In this paper, we review how different Energy System Models have represented both vehicles and fuel infrastructure in the past and we provide guidelines for their representation in the future. In particular, we identify three key modelling decisions: the degree of car market segmentation, the imposition of market share constraints and the use of lumpy investments to represent infrastructure. We examine each of these decisions in a case study using the UK MARKAL model. While disaggregating the car market principally affects only the transition rate to the optimum mix of technologies, market share constraints can greatly change the optimum mix so should be chosen carefully. In contrast, modelling infrastructure using lumpy investments has little impact on the model results. We identify the development of new methodologies to represent the impact of behavioural change on transport demand as a key challenge for improving Energy System Models in the future. © 2013, Hydrogen Energy Publications, LLC. Published by Elsevier Ltd. All rights.
Will Mcdowall - One of the best experts on this subject based on the ideXlab platform.
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Hydrogen and fuel cell technologies for heating: A review
International Journal of Hydrogen Energy, 2015Co-Authors: Paul E. Dodds, Francis Li, Adam D. Hawkes, Will Mcdowall, Iain Staffell, Philipp Grunewald, Paul EkinsAbstract:The debate on low-carbon heat in Europe has become focused on a narrow range of technological options and has largely neglected hydrogen and fuel cell technologies, despite these receiving strong support towards commercialisation in Asia. This review examines the potential benefits of these technologies across different markets, particularly the current state of development and performance of fuel cell micro-CHP. Fuel cells offer some important benefits over other low-carbon heating technologies, and steady cost reductions through innovation are bringing fuel cells close to commercialisation in several countries. Moreover, fuel cells offer wider Energy System benefits for high-latitude countries with peak electricity demands in winter. Hydrogen is a zero-carbon alternative to natural gas, which could be particularly valuable for those countries with extensive natural gas distribution networks, but many national Energy System Models examine neither hydrogen nor fuel cells for heating. There is a need to include hydrogen and fuel cell heating technologies in future scenario analyses, and for policymakers to take into account the full value of the potential contribution of hydrogen and fuel cells to low-carbon Energy Systems.
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methodologies for representing the road transport sector in Energy System Models
International Journal of Hydrogen Energy, 2014Co-Authors: Paul E. Dodds, Will McdowallAbstract:Energy System Models are often used to assess the potential role of hydrogen and electric powertrains for reducing transport CO2 emissions in the future. In this paper, we review how different Energy System Models have represented both vehicles and fuel infrastruc- ture in the past and we provide guidelines for their representation in the future. In particular, we identify three key modelling decisions: the degree of car market segmen- tation, the imposition of market share constraints and the use of lumpy investments to represent infrastructure. We examine each of these decisions in a case study using the UK MARKAL model. While disaggregating the car market principally affects only the transition rate to the optimum mix of technologies, market share constraints can greatly change the optimum mix so should be chosen carefully. In contrast, modelling infrastructure using lumpy investments has little impact on the model results. We identify the development of new methodologies to represent the impact of behavioural change on transport demand as a key challenge for improving Energy System Models in the future.
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Insights into Scotland's climate and Energy policies from Energy Systems modelling
Fraser of Allander Economic Commentary, 2012Co-Authors: Will Mcdowall, Gabrial Anandarajah, Paul EkinsAbstract:Energy System Models are powerful tools for examining the dynamics of a transition to a sustainable Energy System. Here, we report the first application of a two-region version of the UK MARKAL Energy System model that explicitly represents Scotland and the rest of the UK as distinct regions. We use this model to examine the implications of Scotland’s carbon and renewable Energy targets, in the context of the targets legislated for the UK as a whole.
Wolf Fichtner - One of the best experts on this subject based on the ideXlab platform.
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Integrating residential Energy efficiency measures into optimizing urban Energy System Models
2020Co-Authors: Kai Mainzer, Russell Mckenna, Wolf FichtnerAbstract:Due to the complexity and importance of Energy-political decisions, optimization Models, which are able to capture the many interactions between different Energy carriers and technologies, have become common tools for decision support. Especially for regional Energy Systems, i.e. for the scope of single municipalities, demand side residential efficiency measures, like domestic retrofitting or the installation of efficient lighting and white goods, are vital tools for reducing and shaping the future Energy demand. These measures, however, are commonly not integrated well in optimization Models – or not at all. This paper proposes a new method for the integration of residential efficiency measures in optimizing urban Energy System Models, which seeks to remedy with these issues. Efficiency measures are modelled as technologies which are able to convert Energy between carriers with given conversion rates, e.g. in the case of LEDs from electricity to luminous Energy and heat. In order to achieve this, demand is fed into the model as an Energy services demand. This allows the model to choose from a range of available technologies which are able to satisfy this demand. The model results for a German municipality show that the techno-economic incentives for investing in more efficient demand- and supply-side technologies are not sufficient: while a slow shift to more efficient building insulations and appliances can be observed, it is not enough in order to reach the German government’s greenhouse gas reduction plans. If these plans are enforced in the model, however, more efficient technologies are employed on the supply side as well as on the demand side. These findings can be used by policymakers in the form of local Energy efficiency roadmaps, which are tailored to the specific setting of municipalities.
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Reducing Energy time series for Energy System Models via self-organizing maps
Information Technology, 2019Co-Authors: Hasan Ümitcan Yilmaz, Edouard Fouché, Thomas Dengiz, Lucas Krauß, Dogan Keles, Wolf FichtnerAbstract:Abstract The recent development of renewable Energy sources (RES) challenges Energy Systems and opens many new research questions. Energy System Models (ESM) are important tools to study these problems. However, including RES into ESM strongly increases the model complexity, because one needs to model the fluctuant, weather-dependent electricity production from RES with a high level of granularity. This leads to long execution times. To deal with this issue, our objective is to reduce the input time series of ESM without losing their Energy-related key characteristics, such as weather-dependent fluctuations in production or peak demands. This task is challenging, because of the variety and high-dimensionality of the data. We describe a carefully engineered data-processing pipeline to reduce Energy time series. We use Self-Organizing Maps, a specific kind of neural network, to select “representative days”. We show that our approach outperforms the existing ones with respect to the quality of ESM results, and leads to a significant reduction of ESM execution times.
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reducing computing time of Energy System Models by a myopic approach
Energy Systems, 2014Co-Authors: Sonja Babrowski, Tobias Heffels, Patrick Jochem, Wolf FichtnerAbstract:In this paper, the performance of the existing Energy System model PERSEUS-NET is improved in terms of computing time. Therefore, the possibility of switching from a perfect foresight to a myopic approach has been implemented. PERSEUS-NET is a linear optimization model generating scenarios of the future German electricity generation System until 2030, whilst considering exogenous regional characteristics such as electricity demand and existing power plants as well as electricity transmission network restrictions. Up to now, the model has been based on a perfect foresight approach, optimizing all variables over the whole time frame in a single run, thus determining the global optimum. However, this approach results in long computing times due to the high complexity of the problem. The new myopic approach splits the optimization into multiple, individually smaller, optimization problems each representing a 5 year period. The change within the generation System in each period is determined by optimizing the subproblem, whilst taking into account only the restrictions of that particular period. It was found that the optimization over the whole time frame with the myopic approach takes less than one tenth of the computing time of the perfect foresight approach. Therefore, we analyse in this paper the advantages and draw-backs of a change in the foresight as a way of reducing the complexity of Energy System Models. For PERSEUS-NET it is found that the myopic approach with stable input parameters is as suitable as the perfect foresight approach to generate consistent scenarios, with the advantage of significantly less computing time.
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Network constraints in techno-economic Energy System Models: towards more accurate modeling of power flows in long-term Energy System Models
Energy Systems, 2013Co-Authors: Christoph Nolden, Anke Eßer-frey, Valentin Bertsch, Martin Schönfelder, Wolf FichtnerAbstract:Power Systems are subject to extensive structural changes as a result of the fact that the share of renewable energies in power supply will increase significantly within the next decades. This requires the transport of large amounts of electricity, e.g. from the North Sea to the large load centres. Moreover, the decentralized installations for the generation of electricity (e.g. PV) need to be integrated in the lower voltage power grids without violating net-safety constraints. As a consequence, the grid load in the System will rise to an extent that is hardly manageable with existing power grid capacities. Therefore, while mostly neglected to date, the importance of considering the power grid in Energy System Models increases significantly. Within this paper, different examples will be given how network constraints can be considered in techno-economic Energy System Models with a focus on capacity expansion planning and a long-term time horizon. Firstly, a multi-period linear optimization model will be presented, which comprises the System equations for power generation and transmission. The latter is analyzed with the help of a DC power flow model. Secondly, the usage of an AC power flow modeling tool for a detailed representation of the medium and low voltage power grid will be described. Finally, we will present an illustrative example application of a new mathematical approach for grid modeling in techno-economic Energy System Models.
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New Developments in Modeling Network Constraints in Techno-economic Energy System Expansion Planning Models
Zeitschrift für Energiewirtschaft, 2012Co-Authors: Martin Schönfelder, Anke Eßer-frey, Wolf Fichtner, Vincent Heuveline, Michael Schick, Thomas LeibfriedAbstract:ZusammenfassungDiese Arbeit basiert auf Groschke et al. (Z. Energiewirtsch. 33(1):14–22 2009 ) und setzt die Beschreibung neuer Entwicklungen im Bereich der Integration technischer Netzrestriktionen in techno-ökonomischen EnergieSystemmodellen mit Fokus auf der Kraftwerksausbauplanung und einem langfristigen Zeithorizont fort. Basierend auf der Präsentation aktueller und zukünftiger Entwicklungen im deutschen EnergieSystem werden zunächst Anforderungen an zukünftige EnergieSystemmodelle abgeleitet. Die folgende Analyse des derzeitigen Forschungsstandes auf diesem Gebiet zeigt einen Mangel an Modellen mit langfristigem Zeithorizont in Verbindung mit hochpräzisen Lastflussberechnungsmethoden auf. Deshalb wird im Rahmen dieser Arbeit ein erster Ausblick auf eine neue mathematische Herangehensweise gegeben, welche sich bereits als vielversprechender Ansatz erwiesen hat, um den identifizierten Herausforderungen gerecht zu werden.AbstractThis paper is based on Groschke et al. (Z. Energiewirtsch. 33(1):14–22 2009 ) and continues the description of new developments in modeling network constraints in techno-economic Energy System Models with a focus on capacity expansion planning and a long-term time horizon. Based on the presentation of recent and future developments in the German Energy System, current challenges in Energy System modeling are derived. The following analysis of the state of research reveals a lack of high-precision load flow calculation in current Energy System Models with a long-term time horizon. Hence, this paper presents an outlook on a new mathematical approach, which already proved as a promising method to meet the challenges identified.
Morgan Bazillian - One of the best experts on this subject based on the ideXlab platform.
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osemosys the open source Energy modeling System an introduction to its ethos structure and development
Energy Policy, 2011Co-Authors: Mark Howells, Alison Hughes, S. Silveira, Holger Rogner, C Heaps, Joseph F. Decarolis, Socrates Kypreos, Neil Strachan, Hillard G Huntington, Morgan BazillianAbstract:This paper discusses the design and development of the Open Source Energy Modeling System (OSeMOSYS). It describes the model's formulation in terms of a 'plain English' description, algebraic formulation, implementation'in terms of its full source code, as well as a detailed description of the model inputs, parameters, and outputs. A key feature of the OSeMOSYS implementation is that it is contained in less than five pages of documented, easily accessible code. Other existing Energy System Models that do not have this emphasis on compactness and openness makes the barrier to entry by new users much higher, as well as making the addition of innovative new functionality very difficult. The paper begins by describing the rationale for the development of OSeMOSYS and its structure. The current preliminary implementation of the model is then demonstrated for a discrete example. Next, we explain how new development efforts will build on the existing OSeMOSYS codebase. The paper closes with thoughts regarding the organization of the OSeMOSYS community, associated capacity development efforts, and linkages to other open source efforts including adding functionality to the LEAP model.
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OSeMOSYS: The Open Source Energy Modeling System
Energy Policy, 2011Co-Authors: Mark Howells, Hillard Huntington, Alison Hughes, Niall Strachan, S. Silveira, Holger Rogner, C Heaps, Joseph F. Decarolis, Socrates Kypreos, Morgan BazillianAbstract:This paper discusses the design and development of the Open Source Energy Modeling System (OSeMOSYS). It describes the model's formulation in terms of a ‘plain English' description, algebraic formulation, implementation—in terms of its full source code, as well as a detailed description of the model inputs, parameters, and outputs. A key feature of the OSeMOSYS implementation is that it is contained in less than five pages of documented, easily accessible code. Other existing Energy System Models that do not have this emphasis on compactness and openness makes the barrier to entry by new users much higher, as well as making the addition of innovative new functionality very difficult. The paper begins by describing the rationale for the development of OSeMOSYS and its structure. The current preliminary implementation of the model is then demonstrated for a discrete example. Next, we explain how new development efforts will build on the existing OSeMOSYS codebase. The paper closes with thoughts regarding the organization of the OSeMOSYS community, associated capacity development efforts, and linkages to other open source efforts including adding functionality to the LEAP model.
Mark Howells - One of the best experts on this subject based on the ideXlab platform.
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supporting security and adequacy in future Energy Systems the need to enhance long term Energy System Models to better treat issues related to variability
International Journal of Energy Research, 2015Co-Authors: Michael Welsch, Mark Howells, Morgan Bazilian, Neil Strachan, Mohammad Reza Hesamzadeh, Brian O Gallachoir, Paul Deane, Daniel M Kammen, Lawrence Edmund Jones, Goran StrbacAbstract:As the shares of variable renewable generation in power Systems increase, so does the need for, inter alia, flexible balancing mechanisms. These mechanisms help ensure the reliable operation of the electricity System by compensating for fluctuations in supply or demand. However, a focus on short-term balancing is sometimes neglected when assessing future capacity expansions with long-term Energy System Models. Developing heuristics that can simulate short-term System issues is one way of augmenting the functionality of such Models. To this end, we present an extended functionality to the Open Source Energy Modelling System (OSeMOSYS), which captures the impacts of short-term variability of supply and demand on System adequacy and security. Specifically, we modelled the System adequacy as the share of wind Energy is increased. Further, we enable the modelling of operating reserve capacities required for balancing services. The dynamics introduced through these model enhancements are presented in an application case study. This application indicates that introducing short-term constraints in long-term Energy Models may considerably influence the dispatch of power plants, capacity investments, and, ultimately, the policy recommendations derived from such Models.
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incorporating flexibility requirements into long term Energy System Models a case study on high levels of renewable electricity penetration in ireland
Applied Energy, 2014Co-Authors: Michael Welsch, Mark Howells, Morgan Bazilian, Brian O Gallachoir, Paul Deane, Fionn Rogan, Holger RognerAbstract:Efforts to meet climate change mitigation and Energy security targets spur investments in variable renewable Energy sources. Their implications for the operation of power plants are frequently investigated drawing on unit commitment and dispatch Models. However, the temporal granularity and operational detail these Models consider is commonly omitted in the broader family of long-term Energy System Models. To compensate this short-coming, these two types of tools have sometimes been ‘soft-linked’ and harmonised for limited simulation years. This paper assesses an alternative approach. We examine an extended version of an open source Energy System model (OSeMOSYS), which is able to capture operating reserve and related investment requirements within a single tool. The implications of these model extensions are quantified through comparison with an Irish case study. That case study examined the effects of linking a long-term Energy System model (TIMES) with a unit commitment and dispatch model (PLEXOS). It analysed the year 2020 in detail, applying a yearly temporal resolution that is over 700 times higher than in OSeMOSYS. Without increasing temporal resolution (and computational burden) we show that results of the enhanced OSeMOSYS model converge to results of TIMES and PLEXOS: Investment mismatches decrease from 21.4% to 5.0%. The OSeMOSYS analysis was then extended to 2050 to assess the implications of short-term variability on future capacity investment decisions. When variability was ignored, power System investments in 2050 were found to be 14.3% lower. This might imply that Energy policies derived from such long-term Models – of which there are many – may underestimate the costs of introducing variable renewables and thus meeting climate change or Energy security targets.
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Incorporating flexibility requirements into long-term Energy System Models – A case study on high levels of renewable electricity penetration in Ireland
Applied Energy, 2014Co-Authors: Michael Welsch, Mark Howells, Morgan Bazilian, Brian O Gallachoir, Paul Deane, Fionn Rogan, Holger RognerAbstract:Efforts to meet climate change mitigation and Energy security targets spur investments in variable renewable Energy sources. Their implications for the operation of power plants are frequently investigated drawing on unit commitment and dispatch Models. However, the temporal granularity and operational detail these Models consider is commonly omitted in the broader family of long-term Energy System Models. To compensate this short-coming, these two types of tools have sometimes been ‘soft-linked’ and harmonised for limited simulation years. This paper assesses an alternative approach. We examine an extended version of an open source Energy System model (OSeMOSYS), which is able to capture operating reserve and related investment requirements within a single tool. The implications of these model extensions are quantified through comparison with an Irish case study. That case study examined the effects of linking a long-term Energy System model (TIMES) with a unit commitment and dispatch model (PLEXOS). It analysed the year 2020 in detail, applying a yearly temporal resolution that is over 700 times higher than in OSeMOSYS. Without increasing temporal resolution (and computational burden) we show that results of the enhanced OSeMOSYS model converge to results of TIMES and PLEXOS: Investment mismatches decrease from 21.4% to 5.0%. The OSeMOSYS analysis was then extended to 2050 to assess the implications of short-term variability on future capacity investment decisions. When variability was ignored, power System investments in 2050 were found to be 14.3% lower. This might imply that Energy policies derived from such long-term Models – of which there are many – may underestimate the costs of introducing variable renewables and thus meeting climate change or Energy security targets.
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Modelling elements of Smart Grids - Enhancing the OSeMOSYS (Open Source Energy Modelling System) code
Energy, 2012Co-Authors: Michael Welsch, Joseph F. Decarolis, Sascha Hermann, Mark Howells, Morgan Bazilian, Holger RognerAbstract:'Smart Grids' are expected to help facilitate a better integration of distributed storage and demand response options into power Systems and markets. Quantifying the associated System benefits may provide valuable design and policy insights. Yet many existing Energy System Models are not able to depict various critical features associated with Smart Grids in a single comprehensive framework. These features may for example include grid stability issues in a System with several flexible demand types and storage options to help balance a high penetration of renewable Energy. Flexible and accessible tools have the potential to fill this niche. This paper expands on the Open Source Energy Modelling System (OSeMOSYS). It describes how 'blocks of functionality' may be added to represent variability in electricity generation, a prioritisation of demand types, shifting demand, and storage options. The paper demonstrates the flexibility and ease-of-use of OSeMOSYS with regard to modifications of its code. It may therefore serve as a useful test-bed for new functionality in tools with wide-spread use and larger applications, such as MESSAGE, TIMES, MARKAL, or LEAP. As with the core code of OSeMOSYS, the functional blocks described in this paper are available in the public domain. © 2012 Elsevier Ltd.
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osemosys the open source Energy modeling System an introduction to its ethos structure and development
Energy Policy, 2011Co-Authors: Mark Howells, Alison Hughes, S. Silveira, Holger Rogner, C Heaps, Joseph F. Decarolis, Socrates Kypreos, Neil Strachan, Hillard G Huntington, Morgan BazillianAbstract:This paper discusses the design and development of the Open Source Energy Modeling System (OSeMOSYS). It describes the model's formulation in terms of a 'plain English' description, algebraic formulation, implementation'in terms of its full source code, as well as a detailed description of the model inputs, parameters, and outputs. A key feature of the OSeMOSYS implementation is that it is contained in less than five pages of documented, easily accessible code. Other existing Energy System Models that do not have this emphasis on compactness and openness makes the barrier to entry by new users much higher, as well as making the addition of innovative new functionality very difficult. The paper begins by describing the rationale for the development of OSeMOSYS and its structure. The current preliminary implementation of the model is then demonstrated for a discrete example. Next, we explain how new development efforts will build on the existing OSeMOSYS codebase. The paper closes with thoughts regarding the organization of the OSeMOSYS community, associated capacity development efforts, and linkages to other open source efforts including adding functionality to the LEAP model.