Modelling net-zero emissions energy systems requires a change in approach

Energy modelling can assist national decision makers in determining strategies that achieve net-zero greenhouse gas (GHG) emissions. However, three key challenges for the modelling community are emerging under this radical climate target that needs to be recognized and addressed. A first challenge is the need to represent new mitigation options not currently represented in many energy models. We emphasize here the under representation of end-use sector demand-side options due to the traditional supply side focus of many energy models, along with issues surrounding robustness in deploying carbon dioxide removal (CDR) options. A second challenge concerns the types of models used. We highlight doubts about whether current models provide sufficient relevant insights on system feasibility, actor behaviour, and policy effectiveness. A third challenge concerns how models are applied for policy analyses. Priorities include the need for expanding scenario thinking to incorporate a wider range of uncertainty factors, providing insights on target setting, alignment with broader policy objectives, and improving engagement and transparency of approaches. There is a significant risk that without reconsidering energy modelling approaches, the role that the modelling community can play in providing effective decision support may be reduced. Such support is critical, as countries seek to develop new Nationally Determined Contributions and longer-term strategies over the next few years

Modelling net-zero emissions energy systems requires a change in approach

Energy modelling can assist national decision makers in determining strategies that achieve net-zero greenhouse gas (GHG) emissions. However, three key challenges for the modelling community are emerging under this radical climate target that needs to be recognized and addressed. A first challenge is the need to represent new mitigation options not currently represented in many energy models. We emphasize here the under representation of end-use sector demand-side options due to the traditional supply side focus of many energy models, along with issues surrounding robustness in deploying carbon dioxide removal (CDR) options. A second challenge concerns the types of models used. We highlight doubts about whether current models provide sufficient relevant insights on system feasibility, actor behaviour, and policy effectiveness. A third challenge concerns how models are applied for policy analyses. Priorities include the need for expanding scenario thinking to incorporate a wider range of uncertainty factors, providing insights on target setting, alignment with broader policy objectives, and improving engagement and transparency of approaches. There is a significant risk that without reconsidering energy modelling approaches, the role that the modelling community can play in providing effective decision support may be reduced. Such support is critical, as countries seek to develop new Nationally Determined Contributions and longer-term strategies over the next few years

Techno-economic Modelling of Large Scale Compressed Air Energy Storage Systems

Interest in integrating energy storage systems into the power grid has increased in Europe over the past decade due to strategies to overcome the intermittent nature of renewable electricity sources. One of these technologies is compressed air energy storage (CAES). The main purpose of this paper is to examine the technical and economic potential of CAES systems. In this work, two configurations a) Adiabatic Compressed Air Energy Storage (A-CAES); and b) Conventional Compressed Air Energy Storage (C-CAES) were modelled using the ECLIPSE suite of process simulation software. The nominal compression and power generation of both systems were given at 100MWe and 140MWe respectively. For each mode of operation an energy analysis was carried out. Energy use was calculated and compared for each system mode. Based on the results of mass and energy balances, an economic evaluation of the systems was conducted. Technical results showed that the overall efficiency of the A-CAES system would be 64.7%, considerably better than that of the C-CAES system at 52.6%. However it could be seen in the economic analysis that the breakeven electricity selling price (BESP) of the A-CAES system was 152€/MWh, much higher than that of the C-CAES system at 95€/MWh on average