RE-ASSUME: A Decision Maker's Guide to Evaluating Energy Scenarios, Modeling, and Assumptions

Mai, Trieu; Logan, Jeffrey; Blair, n F.; Sullivan, Patrick; Bazilian, Morgan

doi:10.2172/1090954

Cited by 33 publications

(41 citation statements)

References 33 publications

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“…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%

“…The possibility to scrutinize model results is essential for credibility [16] and the development of public trust in the modelling results, particularly as participation in the design of energy pathways becomes increasingly important [31]. Being widely utilized for policy advice, the trade-off between being policy-relevant without being policyprescriptive is of vital importance for model-based research [30].…”

Section: Scientific Standardsmentioning

confidence: 99%

“…the open energy modelling initiative [14]) advocate scientific principles in energy systems research. Linked to the policy relevance of model based research, the modeller decision-maker interface is another challenge [10,15,16]. Several approaches for handling some of these challenge exist.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

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

Hilpert¹,

Günther²,

Kaldemeyer³

et al. 2017

Preprint

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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.

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Section: Challenges In Energy System Modellingmentioning

confidence: 99%

Section: Scientific Standardsmentioning

confidence: 99%

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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

show abstract

“…Complexity sector coupling, temporal and regional resolution, input data, result processing [15][16][17] Uncertainty epistemic, aleatory, linguistic, decision, planning [18,20,21] Interdisciplinary Modelling inclusion of the human dimension, energy-water-food nexus, common transdiciplinary understanding [22][23][24] Scientific Standards transparency, repeatability, reproducibility, scrutiny, scientific progress [25][26][27][28][29] Model Utilization usability, applicability, re-useability, result communication [26,[30][31][32] 3.1.1. Complexity Diversification, distributed generation and stronger integration of energy sectors with versatile interdependencies are growing challenges for energy system modellers.…”

Section: Aspects Literaturementioning

confidence: 99%

A Qualitative Evaluation Approach for Energy System Modelling Software—Case Study Results for the Open Energy Modelling Framework (Oemof)

Hilpert¹,

Kaldemeyer²,

Wiese³

et al. 2017

Preprint

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Abstract:The research field of energy system analysis is dealing with increasingly complex energy systems and their respective challenges. Moreover, the requirement for open science has become a focal point of public interest. Both drivers have triggered the development of a broad range of (open) energy models and frameworks in recent years. However, there are hardly any approaches on how to evaluate these tools in terms of their capabilities to tackle energy system modelling challenges. This paper describes a first step towards a flexible evaluation of software to model energy systems. We propose a qualitative approach as an useful supplementary to existing model fact sheets and transparency checklists. We demonstrate the applicability by evaluating the newly developed "Open Energy Modelling Framework" with respect to existing challenges in energy system modelling. The case study results highlight that challenges related to complexity and scientific standards can be tackled to a large extent while the challenges of model utilization and interdisciplinary modelling are only tackled partially. However, the challenge of uncertainty remains for the most part unaddressed at present. Advantages of the evaluation approach lie in its simplicity, flexibility and transferability to other tools. Disadvantages mostly stem from its qualitative nature. Our analysis reveals that some challenges in the field of energy system modelling cannot be addressed by a software as they are on meta level like model result communication and interdisciplinary modelling.

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“…As an equilibrium model, EPPA (Morris 2008) includes CSP and PV technologies as imperfect substitutes for conventional generators to represent a set of aspects particular to variable renewables, including integration challenges. These three model types each have distinct advantages and disadvantages, but that discussion is outside the scope of this report; for more on model classification, see Mai et al (2013b) and Van Beeck (1999).…”

mentioning

confidence: 99%

Advanced Methods for Incorporating Solar Energy Technologies into Electric Sector Capacity-Expansion Models: Literature Review and Analysis

Sullivan¹,

Newman²,

Margolis³

2014

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RE-ASSUME: A Decision Maker's Guide to Evaluating Energy Scenarios, Modeling, and Assumptions

Cited by 33 publications

References 33 publications

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

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

A Qualitative Evaluation Approach for Energy System Modelling Software—Case Study Results for the Open Energy Modelling Framework (Oemof)

Advanced Methods for Incorporating Solar Energy Technologies into Electric Sector Capacity-Expansion Models: Literature Review and Analysis

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RE-ASSUME: A Decision Maker's Guide to Evaluating Energy Scenarios, Modeling, and Assumptions

Cited by 33 publications

References 33 publications

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

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

A Qualitative Evaluation Approach for Energy System Modelling Software&mdash;Case Study Results for the Open Energy Modelling Framework (Oemof)

Advanced Methods for Incorporating Solar Energy Technologies into Electric Sector Capacity-Expansion Models: Literature Review and Analysis

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A Qualitative Evaluation Approach for Energy System Modelling Software—Case Study Results for the Open Energy Modelling Framework (Oemof)