It is anticipated that the decarbonisation of the entire energy system will require the introduction of large shares of variable renewable electricity generation into the power system. Long term integrated energy systems models are useful in improving our understanding of decarbonisation but they struggle to take account of short term variations in the power system associated with increased variable renewable energy penetration. This can oversimplify the ability of power systems to accommodate variable renewables and result in mistaken signals regarding the levels of flexibility required in power systems. Capturing power system impacts of variability within integrated energy system models is challenging due to temporal and technical simplifying assumptions needed to make such models computationally manageable. This paper addresses a gap in the literature by reviewing prominent methodologies that have been applied to address this challenge and the advantages & limitations of each. The methods include soft linking between integrated energy systems models and power systems models and improving the temporal and technical representation of power systems within integrated energy systems models. Each methodology covered approaches the integration of short term variations and assesses the flexibility of the system differently. The strengths, limitations, and applicability of these different methodologies are analysed. This review allows users of integrated energy systems models to select a methodology (or combination of methodologies) to suit their needs. In addition, the analysis identifies remaining gaps and shortcomings.

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In this paper, we quantify the energy transition and economic consequences of the long-term targets from the Paris agreement, with a particular focus on the targets of limiting global warming by the end of the century to 2 and 1.5 °C. The study assumes early actions and quantifies the market penetration of low carbon technologies, the emission pathways and the economic costs for an efficient reduction of greenhouse gas (GHG) emissions such that the temperature limit is not exceeded. We evaluate the potential role of direct air capture (DAC) and its impact on policy costs and energy consumption. DAC is a technology that removes emissions directly from the atmosphere contributing to negative carbon emissions. We find that, with our modelling assumptions, limiting global temperature to 1.5 °C is only possible when using DAC. Our results show that the DAC technology can play an important role in realising deep decarbonisation goals and in the reduction of regional and global mitigation costs with stringent targets. DAC acts a substitute to Bio-Energy with Carbon Capture and Storage (BECCS) in the stringent scenarios. For this analysis, we use the model MERGE-ETL, a technology-rich integrated assessment model with endogenous learning.

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Approximately 2 out of 10 people in the world still live without access to electricity. The UN "Sustainable Energy to All e SE4All" initiative aims at eradicating this electricity access deficit by 2030. To estimate the financial effort required to achieve this target we analyse two long-term scenarios developed by the Paul Scherrer Institute and the World Energy Council, which describe two alternative economic and energy system developments. We focus on developing Asia, Latin America and Sub-Saharan Africa, which currently have the largest percentage of population without access to electricity. We couple a long-term energy system model with regional econometric models that forecast population electrification rates. We find that establishing universal electricity access by 2030 requires significant, but attainable investments in power generation infrastructure, and results in low impacts on primary energy demand and CO 2 emissions.