Reinventing the energy modelling–policy interface

Strachan, Neil; Fais, Birgit; Daly, Hannah

doi:10.1038/nenergy.2016.12

Cited by 73 publications

(61 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…reform of the electricity market [74]). The UK is also an example of a country where energy models, in particular ESOMs, have come to form an important part of an active science-policy interface (see [75] and [76]). …”

Section: Towards An Improved Representation Of Actors and Behaviour Imentioning

confidence: 99%

“…[120] and [121]). It is also possible that for meaningful policy engagement, models might need to be applied in a more iterative, participatory fashion with key decision makers [76], following a "modelling as a service" strategy where policymakers participate more actively in the process, rather than a "modelling as a product" approach where analysis is undertaken remotely from stakeholders and later presented as a fait accompli [122].…”

Section: Implications For Research and Science-policy Discoursementioning

confidence: 99%

See 1 more Smart Citation

Actors behaving badly: Exploring the modelling of non-optimal behaviour in energy transitions

2017

Energy Strategy Reviews

View full text Add to dashboard Cite

There are real political and social barriers to climate mitigation that arise from multiactor dynamics and micro-economic decisions. Exploratory analysis that captures key uncertainties in the energy system, including behaviour, is crucial for policy design aimed at achieving ambitious greenhouse gas (GHG) mitigation targets. This paper explores the case for developing policy assessments that include non-optimal behaviour in energy systems modelling. A stochastic system dynamic model of the energy system that features multiple actors with differentiated behaviours is used to investigate energy transition pathways that deviate from strict economic rationality. The results illustrate the risks of basing GHG reduction strategies on analysis that overlooks key insights into decision making from fields such as behavioural economics and political science. KeywordsEnergy systems modeling; climate policy; decarbonization; behavioral economics; uncertainty; Highlights• Dynamic stochastic model of energy transitions used to explore actor behaviour • Uncertainty analysis explores impact of sub-optimal actor choices and policies • Behaviour could be as significant as the techno-economic drivers of transitions • Climate targets difficult to achieve without idealised assumptions about behaviour • Energy systems modelling must expand consideration of socio-political factors

show abstract

Section: Towards An Improved Representation Of Actors and Behaviour Imentioning

confidence: 99%

Section: Implications For Research and Science-policy Discoursementioning

confidence: 99%

Actors behaving badly: Exploring the modelling of non-optimal behaviour in energy transitions

2017

Energy Strategy Reviews

View full text Add to dashboard Cite

show abstract

“…A detailed description of the challenges will be given in the following sections. [13,16,[30][31][32] Model Utilization usability, applicability, re-useability, result communication [10,16,33,34] …”

Section: Challenges In Energy System Modellingmentioning

confidence: 99%

“…In the light of resource scarcity and environmental concerns, interdisciplinary research consequently becomes increasingly important [9]. At the same time, there exists a serious social responsibility for modellers as model results are widely used to support policy decisions [10]. Therefore, adhering to scientific standards in energy system modelling is an important matter for model development and application.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Addressing Energy System Modelling Challenges: The Contribution of the Open Energy Modelling Framework (oemof)

Hilpert¹,

Günther²,

Kaldemeyer³

et al. 2017

Preprint

View full text Add to dashboard Cite

These authors contributed equally to this work. AbstractThe process of modelling energy systems is accompanied by challenges inherently connected with mathematical modelling. However, due to modern realities in the 21st century, existing challenges are gaining in magnitude and are supplemented with new ones. Modellers are confronted with a rising complexity of energy systems and high uncertainties on different levels. In addition, interdisciplinary modelling is necessary for getting insight in mechanisms of an integrated world. At the same time models need to meet scientific standards as public acceptance becomes increasingly important. In this intricate environment model application as well as result communication and interpretation is also getting more difficult.In this paper we present the open energy modelling framework (oemof) as a novel approach for energy system modelling and derive its contribution to existing challenges. Therefore, based on literature review, we outline challenges for energy system modelling as well as existing and emerging approaches. Based on a description of the philosophy and elementary structural elements of oemof, a qualitative analysis of the framework with regard to the challenges is undertaken. Inherent features of oemof such as the open source, open data, non-proprietary and collaborative modelling approach are preconditions to meet modern realities of energy modelling. Additionally, a generic basis with an object-oriented implementation allows to tackle challenges related to complexity of highly integrated future energy systems and sets the foundation to address uncertainty in the future. Experiences from the collaborative modelling approach can enrich interdisciplinary modelling activities.Our analysis concludes that there are remaining challenges that can neither be tackled by a model nor a modelling framework. Among these are problems connected to result communication and interpretation.

show abstract

Meeting the Modeling Needs of Future Energy Systems

et al. 2017

View full text Add to dashboard Cite

Structural changes in the energy sector have created considerable challenges for regulators, energy consumers, and suppliers. Energy researchers rely on quantitative modeling approaches to address these challenges. At the Karlsruhe Institute of Technology, we have developed several models to analyze today's and the future's energy markets to address the challenges for electricity networks as a result of intermittent renewable and decentralized power and heat supply and to find solutions for integrating demand response. This paper presents a survey of these approaches and discusses further challenges. The developed models have proved to be suitable for answering a range of research questions related to structural changes. As the energy sector remains in a constant state of flux, these models need to be further developed. This means coupling different energy sectors and markets and improving their technical accuracy as well as their spatial and temporal resolutions.

show abstract

Reinventing the energy modelling–policy interface

Cited by 73 publications

References 19 publications

Actors behaving badly: Exploring the modelling of non-optimal behaviour in energy transitions

Actors behaving badly: Exploring the modelling of non-optimal behaviour in energy transitions

Addressing Energy System Modelling Challenges: The Contribution of the Open Energy Modelling Framework (oemof)

Meeting the Modeling Needs of Future Energy Systems

Contact Info

Product

Resources

About