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Hydrogen and regional energy infrastructure are significant for the European Green Deal and was the focus of the SuperP2G research Project (Synergies Utilising renewable Power Regionally by means of Power to Gas). Five national projects (Denmark, Netherlands, Germany, Austria, and Italy) cooperated to investigate power-to-gas feasibility. The energy crisis due to the war in Ukraine peaked during the project. The demand for green hydrogen increased as natural gas was reduced. In 2022, the cost of blue hydrogen was 9.5–12.6 e/kg. Higher electricity prices impacted the cost of green hydrogen less. Considering the 2021–22 level of electricity and gas prices, and the potential f lexibility of electrolysers, electrolytic hydrogen was on a par with blue hydrogen. On the long term, green hydrogen is assumed to be competitive around 2030. A fast ramping up and favourable electricity cost development could halve the hydrogen production cost until 2040 with investment being the major contributor to a cost reduction. Meanwhile, the smart operation of a wind/electrolyser system might achieve 24% reduction of its operation cost. The following measures are recommended to introduce green hydrogen on a large scale: 1) certification of green and low carbon hydrogen and a uniform CO2 price; 2) ensuring a level playing field across markets; 3) enabling policies to enhance European security of supply by increasing domestic production and diversifying imports; 4) fast ramping of renewable electricity generation; and 5) coordinated planning of hydrogen, methane, and electricity infrastructures.

The Climate Change Act recently enacted in Germany highlights the urgency of understanding the future demand for renewable fuels. In this study, we combine technological progress and socio-economic pathways in an energy system analysis to assess future renewable fuel demands in Germany. We apply the whole-system optimisation model, TIMES, to investigate transition pathways with varying electrification levels and socio-economic developments. The results show that renewable fuels demand varies between 388 PJ and 1310 PJ depending on the electrification rates. Furthermore, our findings demonstrate that considering socio-economic aspects and behavioural change, as represented by different Shared-Socio-economic Pathways, can significantly alter the demand for renewable fuels within a narrower yet still noteworthy range compared to the electrification scenarios. This provides country-level evidence highlighting the often-overlooked influence of social developments on demand projections. Consequently, it becomes crucial to prioritize the consideration of the climate mitigation potential arising from socioeconomic-induced changes in demand patterns within the broader framework of energy efficiency measures.

Load-shifting is a demand-side management (DSM) strategy to support the efficiency of the electricity grid during hours of peak demand. Load-shifting at the appliance level is an interesting topic to review, since appliance usage is one of the main inputs of the load-profile analysis. More literature reviews on load-shifting at the appliance level are required, as this is a specific issue in the body of literature on load-profile research, though only a limited number of studies are available at this time. It is also essential to focus on appliance usage patterns to improve our understanding of the impacts and characteristics of different appliances. Existing studies on load-shifting have used commonly structured literature reviews; our work addresses the transparency of each stage and substage in the selection of the final list of studies. The findings show that efficiency has been achieved in installed-capacity reductions; costs, including those of emission reductions; and peak consumption reductions. The most frequently used method in load-shifting at the appliance level is to develop load-shifting optimization algorithms. This work contributes by providing a transparent process of drawing up a systematicity literature review as a source of knowledge and grounded theory. It also contributes to specific research on load-shifting at the appliance level by highlighting and discussing the key findings for the reader. In particular, it contributes to improving energy efficiency by describing load-shifting methods at the appliance level and identifying both controllable and uncontrollable appliances. This detailed literature review at the appliance level can make valuable contributions in support of decision- and policymaking by illuminating new dynamic systems specifically in load-shifting and in demand-side management in general for energy efficiency purposes.

Renewable fuels of non-biological origin (RFNBOs) are needed to decarbonize hard-to-electrify sectors which rely on liquid or gaseous fuels, such as long-haul shipping. The EU's Delegated Act on RFNBOs defines renewable hydrogen by considering rules on additionality as well as temporal and geographical correlation of the electricity used. For a Danish case study, we examine the impact on the capacity expansion problem of an energy hub producing renewable hydrogen, e-methanol, and e-ammonia using a mixed-integer linear problem formulation. We analyze the investments in production capacity, storage assets, and Power Purchase Agreement (PPA) volume under different fuel price assumptions for 2030. We find that e-methanol (combined with limited storage to secure hydrogen supply to the synthesizer) provides the best business case with a PPA volume based on the maximum allowed electrolyzer size.

The European Commission recently proposed requirements for the production of renewable fuels as these are required to decarbonize the hard-to-electrify parts of the industrial and heavy transport sectors. Power-to-X (P2X) energy hubs enable efficient synergies between energy infrastructures, production facilities, and storage options. In this study, we explore the optimal operation of an energy hub by leveraging the flexibility of P2X, including hydrogen, methanol, and ammonia synthesizers by analyzing potential revenue streams such as the day-ahead and ancillary services markets. We propose EnerHub2X, a mixed-integer linear program that maximizes the hub’s profit based on current market prices, considering the technical constraints of P2X, such as unit commitment and non-linear efficiencies. We investigate a representative Danish energy hub and find that without price incentives, it mainly sells renewable electricity and produces compressed hydrogen. A sufficient amount of renewable ammonia and methanol is only produced by adding a price premium of about 50% (0.16 €/kg) to the conventional fuel prices. To utilize production efficiently, on-site renewable energy sources and P2X must be carefully aligned. We show that renewable power purchase agreements can provide flexibility while complying with the rules set by the European Commission.

Energy system modeling is a commonly used method to provide policy recommendations and insight to transformation pathways of energy systems. However, the low open-source availability of the frameworks in practice often leads to low interpretability and transparency of energy modeling system configurations. The configuration of an energy model entails how its system components, such as power plants, storage systems and grids operate, and which parameters are used to define them. In order to understand the impact of different model configurations and working principles on the model output, a thorough comparison between various modeling frameworks is necessary. This work thereby consists of a comparison of five open-source energy system modeling frameworks (OS-ESMFs) oemof, GENeSYS-MOD, Balmorel, urbs and GENESYS-2 on the mathematical level and spotlights selected methodological differences in renewable energy system modeling. The comparison shows diversity in the complexity of selected system components and helps to define the best use-cases and scales of application for each framework. Impacts of modeled features on the results were demonstrated by implementing two harmonized scenarios depicting the German electricity system using each framework. While similar model results were obtained for both scenarios, some differences were present, especially in the long-term expansion planning model. Some of those differences could be traced back to the identified modeling differences.

Recent European and German climate targets call for a faster power system transition towards variable renewable energy sources. With the increasing importance of Open Science, several Open Source models have been developed in recent years. However, only a few studies exist that compare their performance against each other. Therefore, this study performs a comprehensive model comparison of five mature Open Source power sector models. For this purpose, we apply eight fully harmonized and simplified one-year scenarios for the German power sector, to analyze deviations in model results. First, an in-depth analysis of two base scenarios for 2016 and 2030 reveals that linear programming-based models differ substantially from models with pre-implemented dispatch orders. Other deviations occur across all models and are mainly caused by the indifferent use of flexibility options such as storage and transmission. Second, variations of parameters and characteristics with a political significance are individually applied to the 2030 base scenario to identify their impact on model results. This includes CO2 emission budgets, increased demands by sector coupling, coal exit strategies, and renewable generation shares. The results prove that some models are far more sensitive to these parameters than others, and renewable generation shares alone are not sufficient to reach desired effects in emission reductions. Finally, a comprehensive scenario for 2030 combines all measures to evaluate general trends that result from the most recent updates in German energy policy. Model results indicate that the new targets require substantially increased investments into renewable generation capacities, storage, and transmission.

A radical adjustment to current energy systems will be imperative in achieving the Paris Agreement. This paper analyses the holistic 2050 Danish energy system and particularly its future transport sector, which aims to be fossil fuel independent. Using a linear optimisation tool (Balmorel-OptiFlow), the role of electrofuels is analysed at a high temporal and geographic resolution for the Nordic + German region. Electrofuel technologies have been investigated and incorporated into the energy model creating a comprehensive catalogue of alternative fuel pathways. Results reveal an energy system with a high reliance on variable energy sources. Electrofuels that utilise biomass have been found to be more economically attractive compared to electrofuels using carbon capture. Biomass costs, fuel demands, and electricity prices drive the competition between the evaluated alternative fuel pathways. Carbon capture technologies are found to not play a role in the production of transport fuels unless future biomass resources are more limited or costly than expected. Additionally, it has been found that temporal resolution can greatly affect results when modelling alternative fuel pathways. The study concludes that electrofuels - particularly those using biomass - can play a prominent role in future transport sectors.

As the world progresses towards a cleaner energy future with more variable renewable energy sources, energy system models are required to deal with new challenges. This article describes design, development and applications of the open source energy system model Balmorel, which is a result of a long and fruitful cooperation between public and private institutions within energy system research and analysis. The purpose of the article is to explain the modelling approach, to highlight strengths and challenges of the chosen approach, to create awareness about the possible applications of Balmorel as well as to inspire to new model developments and encourage new users to join the community. Some of the key strengths of the model are the flexible handling of the time and space dimensions and the combination of operation and investment optimisation. Its open source character enables diverse, worldwide applications for exploratory energy scenarios as well as policy analysis as the applications outlined demonstrate. The existing functionality and structural suitability for extensions make it a useful tool for assessing challenges of the ongoing energy transitions. Numerous model extensions have been developed as different challenges to the energy transition have arisen. One of these includes the option of running the model with unit commitment. To meet new challenges, further development is needed and consequently the article outlines suggestions for future development, such as including transport of local biomass as part of the optimisation and speeding up the model.