METIS – An energy modelling tool to support transparent policy making

Sakellaris, Kostis; Canton, Joan; Zafeiratou, Eleni; Fournie, Laurent

doi:10.1016/j.esr.2018.08.013

Cited by 16 publications

(8 citation statements)

References 7 publications

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“…Current energy models are not usable for non-experts, such as practitioners [21,28]. It is therefore expected that practitioners make limited use of energy models due to the complexity of energy models.…”

Section: Propositions On the Use Of Energy Models By Municipalitiesmentioning

confidence: 99%

“…Simulation model (using Long-rangeEnergy Alternatives Planning (LEAP software) [27] All stakeholders involved could run and modify the model themselves and even modify it according to their needs. The model has a large sensitivity for a multitude of assumptions METIS simulation model [28] A current understanding of quantitative tools by policymakers is often missing HOMER optimisation [29] Most models and tools currently used do not provide both economic and environmental analysis of energy systems, which can lead to the design of sub-optimal systems Housing Stock Energy Model (HSEM) [30] Many HSEMs are lacking in transparency and modularity and that they are often limited in scope and limited in their utility. Behavioural responses are blurred in HSEMs.…”

Section: Conflicts Of Interestmentioning

confidence: 99%

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The Use of Energy Models in Local Heating Transition Decision Making: Insights from Ten Municipalities in The Netherlands

et al. 2021

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In 2018, the Dutch national government announced its decision to end natural gas extraction. This decision posed a challenge for local governments (municipalities); they have to organise a heat supply that is natural gas-free. Energy models can decrease the complexity of this challenge, but some challenges hinder their effective use in decision-making. The main research question of this paper is: What are the perceived advantages and limitations of energy models used by municipalities within their data-driven decision-making process concerning the natural-gas free heating transition? To answer this question, literature on energy models, data-driven policy design and modelling practices were reviewed, and based on this, nine propositions were formulated. The propositions were tested by reflecting on data from case studies of ten municipalities, including 21 experts interviews. Results show that all municipalities investigated, use or are planning to use modelling studies to develop planning documents of their own, and that more than half of the municipalities use modelling studies at some point in their local heating projects. Perceived advantages of using energy models were that the modelling process provides perspective for action, financial and socio-economic insights, transparency and legitimacy and means to start useful discussions. Perceived limitations include that models and modelling results were considered too abstract for analysis of local circumstances, not user-friendly and highly complex. All municipalities using modelling studies were found to hire external expertise, indicating that the knowledge and skill level that municipal officials have is insufficient to model independently.

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Section: Propositions On the Use Of Energy Models By Municipalitiesmentioning

confidence: 99%

Section: Conflicts Of Interestmentioning

confidence: 99%

The Use of Energy Models in Local Heating Transition Decision Making: Insights from Ten Municipalities in The Netherlands

et al. 2021

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“…For the practical purpose of evaluating long-term policy in the electricity sector, GEP models are then the approach favoured by policy makers [11]. In fact, a report by the European Commission finds that the majority of the pressing electricity market design questions for competitive markets can be represented in optimisation models such as the GEP [23] and the European Commission itself has selected this approach for the model it has commissioned to perform policy analysis [48]. In fact, 90% of energy system models available commercially or academically aim to address the questions asked by policy makers [49].…”

Section: Uncertainty Inside the Modelmentioning

confidence: 99%

Long-Term Uncertainty In Electricity Market Modelling, Policy, and Planning

Scott¹

2021

SSRN Journal

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I have been lucky with my supervisors and collaborators who I am glad to thank. Firstly, I would like to thank Prof. Pedro Carvalho for the support, ideas, dedication, flexibility, and encouragement that contributed to every part of this work. I would like to also thank Prof. Carlos Silva for the encouragement and flexibility shown with me throughout this journey as well as his continuous support in allowing me to pursue my diverse interests.Next, I would like to thank Dr. Audun Botterud for the encouragement, ideas shared, detailed and diligent input, and hosting me in such a friendly and supportive manner at the MIT, an experience from which I gained a lot. I would like to thank my collaborators Felix Diawuo and Diana Neves for the interesting research topics that kept me distracted and interested and the friendship provided along the way. I would also like to thank Patricia Baptista for the advice and input provided to Felix and myself. I would like to thank my InnoEnergy Lisboa colleagues Sonia, Kaisa, Julia, and Eduardo for the support, distraction, and friendship as well as the many others from the MIT Portugal Program, IN+, and InnoEnergy.Perhaps most importantly, I wish to thank my partner, Filipa de Almeida, without whom I surely would not have begun, let alone completed, this thesis. Her love and support in this endeavour, as in all things, makes anything possible. I also cannot thank enough my parents for their support in all forms on which I have always been so fortunate to be able to rely on. I am forever grateful for the love, sacrifice, guidance, proof-reading, and upbringing they provided me that has allowed me to chase my interests around the world, any and all achievements are always entirely due to them.

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“…Jensen et al [20] observes that hydrogen has a strengthened role when less bio-energy is assumed available. METIS simulates both energy systems and energy markets for electricity, gas and heat [21]. In [22], a scenario with full carbon neutrality by 2050 is studied.…”

Section: Introductionmentioning

confidence: 99%

Assessment of the Contribution of Power-To-Hydrogen to the Flexibility of the Future European Energy System

Joskin¹,

Pavičević

Magni

et al. 2022

34th International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems (ECOS 20

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The European Commission is planning to become climate-neutral by 2050. At the power sector level, this implies turning to renewable sources such as PV panels and wind turbines. However, the intermittence of variable renewable sources is making this task more complex and putting at risk the power sector security of supply. Coupling sectors is a solution to that problem. In particular, power-to-hydrogen is getting more and more attention. This is about using electricity when it is abundant to synthesize hydrogen which can then be used for various purposes. The first goal of this work was to add the power-to-hydrogen sector into the unit-commitment and power dispatch model Dispa-SET. The second objective was to soft-link Dispa-SET with the long-term investment model JRC-EU-TIMES and investigate the benefits of this sector in terms of curtailment, total costs, CO2 emissions, etc. The linking between JRC-EU-TIMES and Dispa-SET allowed to observe the importance of power-to-hydrogen in using the extra renewable production and avoiding curtailment. Indeed, 20% of the total renewable production is used to produce hydrogen. This highlights the importance of sector coupling in future energy systems. Moreover, the results showed that hydrogen storage is not seasonal. Finally, the importance of validating system feasibility provided by long-term planing models was demonstrated as TIMES overestimates renewable production by 15% compared to Dispa-SET.

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METIS – An energy modelling tool to support transparent policy making

Cited by 16 publications

References 7 publications

The Use of Energy Models in Local Heating Transition Decision Making: Insights from Ten Municipalities in The Netherlands

The Use of Energy Models in Local Heating Transition Decision Making: Insights from Ten Municipalities in The Netherlands

Long-Term Uncertainty In Electricity Market Modelling, Policy, and Planning

Assessment of the Contribution of Power-To-Hydrogen to the Flexibility of the Future European Energy System

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