Trends in tools and approaches for modelling the energy transition

Chang, Miguel; Thellufsen, Jakob Zinck; Zakeri, Behnam; Pickering, Bryn; Pfenninger, Stefan; Lund, Henrik; Østergaard, Poul Alberg

doi:10.1016/j.apenergy.2021.116731

Cited by 239 publications

(80 citation statements)

References 133 publications

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“…In light of the already mentioned challenges of modelling energy systems ( [4,5], MESS) was developed with a set of design goals in mind and was deeply inspired by Calliope [6]. This choice was made to attempt to mitigate the consequences of an additional model in the literature and to improve the interoperability among multiple models.…”

Section: Methodsmentioning

confidence: 99%

“…Chang et al [5] recently updated and expanded the work initiated by Pfenninger et al and, by reviewing a set of modelling tools, identified current trends in the field of energy modelling. Specifically, they found that, in recent years, modellers have addressed some of the aforementioned challenges through increased cross-sectoral synergies, growing attention to open access and open-source publications as well as temporal resolution improvement.…”

Section: Introductionmentioning

confidence: 99%

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The Potential of Simulating Energy Systems: The Multi Energy Systems Simulator Model

et al. 2021

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Energy system modelling is an essential practice to assist a set of heterogeneous stakeholders in the process of defining an effective and efficient energy transition. From the analysis of a set of open-source energy system models, it emerged that most models employ an approach directed at finding the optimal solution for a given set of constraints. On the contrary, a simulation model is a representation of a system used to reproduce and understand its behaviour under given conditions without seeking an optimal solution. In this paper, a new open-source energy system model is presented. Multi Energy Systems Simulator (MESS) is a modular, multi-energy carrier, multi-node model that allows the investigation of non optimal solutions by simulating an energy system. The model was built for urban level analyses. However, each node can represent larger regions allowing wider spatial scales to be represented as well. In this work, the tool’s features are presented through a comparison between MESS and Calliope, a state of the art optimization model, to analyse and highlight the differences between the two approaches, the potentialities of a simulation tool and possible areas for further development. The two models produced coherent results, showing differences that were tracked down to the different approaches. Based on the comparison conducted, general conclusions were drawn on the potential of simulating energy systems in terms of a more realistic description of smaller energy systems, lower computational times and increased opportunity for participatory processes in planning urban energy systems.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

The Potential of Simulating Energy Systems: The Multi Energy Systems Simulator Model

et al. 2021

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“…These can substantially affect the energy supplying cost, especially for off-grid RES. Moreover, energy system models have been developed with the focus on taking a smart energy system cross-sectoral approach to the analysis of ESS (Chang et al, 2021;Lund et al, 2021). Recent literature studies on national and global levels have identified that EES will be vital to increase the RE penetration either in the grid connected mode or the offgrid mode (Jacobson et al, 2017;Blakers et al, 2017;Esteban et al, 2012).…”

Section: Accessmentioning

confidence: 99%

Quantifying techno-economic indicators' impact on isolated renewable energy systems

Javed

Ma²,

Mousavi

et al. 2021

iScience

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Addressing climate change with the rising global energy usage necessitates electricity sector decarbonization by rapidly moving toward flexible and efficient off-grid renewable energy systems (RESs). This paper analyzes the wind and solar micro-grids, with batteries and pumped hydro storage for a robust off-grid RES techno-economic operation, while considering diverse multi-objective optimization cases. This research has considered the RES variable operational losses in the developed methodology and relations between different indicators are evaluated, revealing a basic understanding between them. The results reveal that the reliability index is inversely related to the oversupply index, while directly related to the system self-sufficiency index. The cost of energy is more sensitive to technical indicators rather than the storage cost and so can be used as a primary monetary index. Energy and cost balance analysis showed that 16%-20% of the used energy was drained in RES operational losses, which were usually ignored in previous studies.

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“…In the context of the continuous refinement of carbon emission reduction in various countries, many researchers and policymakers are paying more attention to the regional impacts of the national carbon emission targets and actions [1] , [2] , [3] , which is key for identifying the exact location of emitters and its environmental impacts, like power plants. In some countries, such as China [4] and India [5] , coal power is the main power supply and carbon dioxide emission source now and is facing fast and important transformation pressure under the carbon emission reduction targets.…”

Section: Introductionmentioning

confidence: 99%

A rule-based method to downscale provincial level power sector projection results to plant level

Cui

Weng

et al. 2021

MethodsX

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Usually, previous studies on the future development pathway of coal power are based on the economic models to provide the administrative pathways, or the coal-fired power plants dataset to provide bottom-up pathways with the multi-scenario hypothesis. However, these two methods above are difficult to be combined: there is a gap between the comprehensive consideration of economic, policy, and environmental factors, with the high spatial resolution of technology and space. This study narrows the gap between regional projection and unit data, and also considers the uncertainty of the operating units with the Monte Carlo Method. Firstly, we evaluate the score of each unit according to its technical parameters and other attribute information, which is based on a sufficient dataset of coal-fired power units with their geographical spatial coordinates. And next, the probability distribution function is built according to the scores of the candidate units. Then, we do sampling from the candidate units until the total capacity reaches the regional projection of the coal power development goal. Based on this method, we could identify the spatial distribution probability of coal-fired power units in the future, and therefore it can help us explore the environmental impacts in high-resolution space. The method calculates the probability of operating status of candidate units using technical and attribute information-base scores with Monte Carlo method. This paper describes the uncertainties in determining the spatial distribution of future power plants, and verifies the robustness of the results. This method narrows the scale gap between regional projection and unit-level data.

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Trends in tools and approaches for modelling the energy transition

Cited by 239 publications

References 133 publications

The Potential of Simulating Energy Systems: The Multi Energy Systems Simulator Model

The Potential of Simulating Energy Systems: The Multi Energy Systems Simulator Model

Quantifying techno-economic indicators' impact on isolated renewable energy systems

A rule-based method to downscale provincial level power sector projection results to plant level

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