Off-grid hydrogen supply from solar or wind sources to hydrogen-based steelmaking can reduce CO₂ emissions. However, the techno-economic feasibility of different supply chain configurations remains uncertain. This study evaluates 61 off-grid hydrogen supply chains for a 15 Mt. steel/year plant in 2030, considering renewable energy sources (onshore/offshore wind, solar, and overseas options), transmission technologies (cables, pipelines, trucks, and ships), storage technologies (compressed gaseous hydrogen, liquid hydrogen, ammonia, methanol, and liquid organic hydrogen carriers), and seasonal storage locations (at the energy source or steelmaking plant). Onshore truck transmission of hydrogen is found to be unpromising due to the significantly higher cost compared to alternative transmission technologies. When the transmission technology is not truck, chains with underground compressed hydrogen storage achieve the lowest levelized cost of hydrogen (LCOH) at 3.8–5.6 €₂₀₂₀/kg H₂, outperforming other options. When underground hydrogen storage is not feasible, liquid organic hydrogen carriers present the next lowest cost. Chains utilizing ammonia, methanol, and liquid hydrogen exhibit lower efficiency, higher renewables capacity requirement, and consequently higher LCOH, making them less attractive. Electricity transmission lowers the LCOH of compressed hydrogen chains compared to hydrogen pipeline transmission, but for other chains the trend is reversed. Hydrogen storage near the steelmaking plant reduces costs by enabling the reuse of boil-off hydrogen in liquid hydrogen chains, but for other chains storing hydrogen near the renewable energy source lowers the cost. Impacts of input uncertainties on the LCOH, limitations of this study, and suggestions for future studies are also presented.

Coffee processing encompasses the conversion of coffee cherries into marketable products, including the removal of outer layers to produce green coffee and, in extended chains, their roasting into roasted coffee, and grinding into ground coffee. Calculating the carbon footprint (CF) in coffee processing is crucial for identifying and mitigating key sources of greenhouse gas (GHG) emissions. Utilizing the Life Cycle Assessment (LCA) methodology, the current study quantifies the CF associated with Robusta dry coffee processing by collecting primary data through interviews with coffee producers and visits to coffee processing units, roasting, and grinding facilities in Wayanad, India. The study identifies GHG emission hotspots across two scenarios. Scenario A includes transportation of dried coffee beans from farm to coffee processing unit, green coffee production, packaging, roasting, and grinding at a local unit, while Scenario B covers local transportation of green coffee beans from India to The Netherlands, green coffee production, packaging, and its transportation from India to The Netherlands. Cultivation and harvesting of coffee cherries, consumer-level preparation and use, and disposal of coffee products are outside the scope of this study. The functional unit is defined as 1 kg of green coffee for both scenarios. Findings show that the CF equals 0.62 and 0.38 kg CO_2eq per kg of green coffee for scenarios A and B, respectively. Roasting (78 % of CF), and sea transportation (66 % of CF) emerged as the main hotspots of GHG emissions for scenario A, and scenario B, respectively.

Importing substantial amount of green hydrogen from countries like South Africa, which have abundant solar and wind potentials to replace fossil fuels, has attracted interest in developed regions. This study analyses South African strategies for improving and decarbonizing the power sector while also producing hydrogen for export. These strategies include the Integrated Resource Plan, the Transmission Development Plan, Just Energy Transition and Hydrogen Society Roadmap for grid connected hydrogen production in 2030. Results based on an hourly resolution optimisation in Plexos indicate that annual grid-connected hydrogen production of 500 kt can lead to a 20–25% increase in the cost of electricity in scenarios with lower renewable energy penetration due to South African emission constraints by 2030. While the price of electricity is still in acceptable range, and the price of hydrogen can be competitive on the international market (2–3 USD/kgH₂ for production), the emission factor of this hydrogen is higher than the one of grey hydrogen, ranging from 13 to 24 kgCO2/kgh₂. When attempting to reach emission factors based on EU directives, the three policy roadmaps become unfeasible and free capacity expansion results in significant sixteen-fold increase of wind and seven-fold increase in solar installations compared to 2023 levels by 2030 in South Africa.

The transition of the European iron and steel industry (ISI) towards low-carbon manufacturing is crucial for the European Union (EU)’s 2050 climate neutrality objective. One emerging solution is electrification by using hydrogen (H₂) as iron ore reductant, which increases specific electricity use per tonne of steel up to 35 times compared to the conventional, most adopted coal-based technology. This study develops three scenarios, encompassing a moderate to an accelerated ISI transition, to evaluate the impact of the ISI decarbonisation on the power system CO₂ emissions, generation mix and volume, and marginal prices in 2030. The study first estimates future electricity and H₂ demand by considering country-specific technologies deployment and energy intensities. Then, these estimates serves as input to the model METIS to simulate European power system operations through a unit commitment and economic dispatch problem. The study shows that the power system can accommodate a transition of the ISI that substitutes 28% of the coal-based production with low carbon technologies, mainly based on H₂. This leads to a 25% reduction in direct CO₂ emissions and a demand increase of 20 TWh of electricity and 40 TWh_HHV of H₂. Furthermore, a 50% reduction in indirect power system emissions is achieved, compared to 2018, thanks to the substantial renewable power capacity deployment foreseen in the coming years. The study also demonstrates that a reduction of indirect CO₂ emissions by over 85% can be achieved by deploying 1.2 and 2.7 GW of renewable power generators, and 200 and 400 MW of electrolyser capacity for each million tonne of steel produced annually with low-carbon technologies. Additional renewable capacity that ensures green steel production is also key to maintaining stable electricity prices.

This research aims to investigate the potential impact of national policies on the attainment of Europe's goal of achieving net-zero greenhouse gas emissions by 2050. Specifically, it analyses the effects of policies on the power sector, by evaluating capacity expansion portfolios, import reliance, and costs by 2050. A linear programming model, the IESA-EUPS, is utilized to optimize the expansion and operation of the power system, considering 28 nodes and hourly temporal resolution. The study includes five scenarios from 2020 to 2050, with varying levels of biomass and nuclear penetration based on existing member state policies. Results show that by 2050, changes mainly occur in the interplay between firm capacities and cross-border transmission levels. Limiting biomass can significantly increase nuclear energy generation, while enforcing all policies leads to a 40 % rise in cross-border transmission by 2050, due to imbalances between countries. Some member states, such as Spain and Finland, are less affected, whereas others are heavily reliant on firm nuclear capacities. Western European countries with strict biomass and nuclear restrictions may see a boost in nuclear installations in countries allowing it. Member states without both nuclear and biomass may rely more on variable renewables, resulting in surplus electricity and increased LCOE.

We propose an index to quantify and analyse the impact of climatological variability on the energy system at different timescales. We define the climatological renewable energy deviation index (credi) as the cumulative anomaly of a renewable resource with respect to its climate over a specific time period of interest. For this we introduce the smooth, yet physical, hourly rolling window climatology that captures the expected hourly to yearly behaviour of renewable resources. We analyse the presented index at decadal, annual and (sub-)seasonal timescales for a sample region and discuss scientific and practical implications. credi is meant as an analytical tool for researchers and stakeholders to help them quantify, understand, and explain, the impact of energy-meteorological variability on future energy system. Improved understanding translates to better assessments of how renewable resources, and the associated risks for energy security, may fare in current and future climatological settings. The practical use of the index is in resource planning. For example transmission system operators may be able to adjust short-term planning to reduce adequacy issues before they occur or combine the index with storyline event selection for improved assessments of climate change related risks.

This study evaluates the technoeconomic impacts of direct and indirect electrification on the EU's net-zero emissions target by 2050. By linking the JRC-EU-TIMES long-term energy system model with PLEXOS hourly resolution power system model, this research offers a detailed analysis of the interactions between electricity, hydrogen and synthetic fuel demand, production technologies, and their effects on the power sector. It highlights the importance of high temporal resolution power system analysis to capture the synergistic effects of these components, often overlooked in isolated studies. Results indicate that direct electrification increases significantly and unimpacted by biomass, CCS, and nuclear energy assumptions. However indirect electrification in the form of hydrogen varies significantly, between 1400 and 2200 TWh_H2 by 2050. Synthetic fuels are essential for sector coupling, making up 6–12% of total energy consumption by 2050, with the power sector supplying most hydrogen and CO₂ for their production. Varying levels of indirect electrification impact electrolysers, renewable energy, and firm capacities. Higher indirect electrification increases electrolyser capacity factors by 8%, leading to more renewable energy curtailment but improves system reliability by reducing 11 TWh unserved energy and increasing flexibility options. These insights inform EU energy policies, stressing the need for a balanced approach to electrification, biomass use, and CCS to achieve a sustainable and reliable net-zero energy system by 2050. We also explore limitations and sensitivities.

To achieve the European Union's goal of climate neutrality by 2050, negative emissions may be required to compensate for emissions exceeding allocated carbon budgets. Therefore, carbon removal technologies such as bioenergy with carbon capture (BECCS) and direct air capture (DAC) may need to play a pivotal role in the power system. To design carbon removal strategies, more insights are needed into the impact of sustainable biomass availability and the feasibility of carbon capture and storage (CCS), including the expensive and energy-intensive DAC on achieving net-zero and net-negative targets. Therefore, in this study the European power system in 2050 is modelled at an hourly resolution in the cost-minimization PLEXOS modelling platform. Three climate-neutral scenarios with targets of 0, -1, and -3.9 Mt CO₂/year (which agree with varying levels of climate justice) are assessed for different biomass levels, and CCS availability. Findings under baseline assumptions reveal that in a climate-neutral power system with biomass and CCS options, it is cost-effective to complement variable renewable energy with a mix of combined cycle natural gas turbines (CCNGT) for flexibility and BECCS as base load to compensate for the CO₂ emissions from natural gas and additional carbon removal in the net-negative scenarios. The role of these technologies becomes more prominent, with -3.9 GtCO₂/year target. Limited biomass availability necessitates additional 0.4–4 GtCO₂/year DAC, 10–50 GW CCNGT with CCS, and 10–50 GW nuclear. Excluding biomass doubles system costs and increases reliance on nuclear energy up to 300 TWh/year. The absence of CCS increases costs by 78%, emphasizing significant investments in bioenergy, nuclear power, hydrogen storage, and biogas. Sensitivity analysis and limitations of the study are fully discussed.

To meet the European Union's 2050 climate neutrality target, future electricity generation is expected to largely rely on variable renewable energy (VRE). VRE supply, being dependant on weather, is susceptible to changing climate conditions. Based on spatiotemporally explicit climate data under a Paris-proof climate scenario and a comprehensive energy conversion model, this study assesses the projected changes of European VRE supply from the perspective of average production, production variability, spatiotemporal complementarity, and risk of concurrent renewable energy droughts. For the period 2045–2055, we find a minor reduction in average wind and solar production for most of Europe compared to the period 1990–2010. At the country level, the impact of climate change on average VRE production is rather limited in magnitude (within ±3% for wind and ±2% for solar). The projected mid-term changes in other aspects of VRE supply are also relatively small. This suggests climate-related impacts on European VRE supply are less of a concern if the Paris-proof emission reduction pathway is strictly followed. Based on spectral analysis, we identify strong seasonal wind-solar complementarities (with an anticorrelation between -0.6 and -0.9) at the cross-regional level. This reduces the demand for seasonal storage but requires coordinated cross-border efforts to develop a pan-European transmission infrastructure. The risk of concurrent renewable energy droughts between a country and the rest of Europe remains non-negligible, even under the copperplate assumption. Central Western European countries and Poland are most vulnerable to such risk, suggesting the need for the planning of adequate flexibility resources.

The decarbonisation of the iron and steel industry is expected to significantly increase its electricity consumption due to higher levels of electrification and the partial shift to hydrogen as iron reductant. With its batch processes, this industry offers large potential for the application of demand response strategies to achieve electricity cost savings. Previous research has primarily focused on investigating the demand response potential for currently operating manufacturing processes and partly for future low-carbon processes. This study aims to consolidate this knowledge and apply it to a modelling analysis that investigates the demand response potential of two new low-carbon technologies: the hydrogen-based direct reduction of iron with electric arc furnace technology (H2-DRI-EAF) and the blast furnace basic oxygen furnace technology retrofitted with carbon capture (BF-BOF-CCUS). A cost optimisation approach is applied to plant configurations with varying parameters relevant for flexibility, such as electrolyser and storage sizes, and in the context of future electricity prices. Multiple price profiles are selected to encompass uncertainties on the development of the power system. The potential for a H2-DRI-EAF plant is 3–27 times higher than for a BF-BOF-CCUS, with electricity costs savings potentials of 35% and 3%, respectively. The study finds that electricity prices have the most significant impact on the profitability of investing in electrolyser overcapacities, which enable operating costs reduction. Therefore, the profitability of these investments are strongly dependent on future power system configurations.

Proper thermal management can improve the efficiency of hydrogen storage chains based on liquid organic hydrogen carriers (LOHC). The energy and exergy efficiencies of 24 LOHC chains, which are differentiated by two hydrogen sources (SEL: hydrogen from electrolyzer and SINDU: industrial by-product), three hydrogen consumers (CPEMFC: proton exchange membrane fuel cell, CSOFC: solid oxide fuel cell, and CINDU: industrial consumer), and four LOHC pairs are calculated based on thermodynamic modeling. Possible strategies for the heat integration between the heat sources (including hydrogenation heat, heat generated by hydrogen consumer, and the high-temperature LOHC fluids) and the heat sinks (including LOHC preheating, hydrogen preheating, dehydrogenation, and external heating purposes) are designed for these chains. In the four selected LOHC pairs, dibenzyltoluene (DBT) is found to be the most favorable LOHC pair for the implementation of WHR strategies, mainly because of low heat demand for preheating (8.9% of the stored hydrogen energy) and a high dehydrogenation rate. The WHR strategies significantly improve the energy efficiency of LOHC chains by up to 21.7% points for the chains with CINDU and 40.8% points for chains with CSOFC or CPEMFC, which makes LOHC chains more efficient than traditional compressed or liquid hydrogen chains in several scenarios, i.e., the DBT chain with CPEMFC have the highest energy efficiency (70.4% for SEL/69.5% for SINDU), while the DBT chain with SINDU and CSOFC has the highest exergy efficiency (60.6%). For the remaining combinations of the remaining hydrogen sources and consumers, the compressed hydrogen chains are the most efficient.

In power system studies the unit commitment problem (UC) is solved to support market decisions and assess system adequacy. Simplifications are made to solve the UC faster, but they are made without considering the consequences on solution quality. In this study we thoroughly investigated the impacts of simplifications on solution quality and computation time on a benchmark set consisting of almost all the available instances in the literature. We found that omitting the minimum up- and downtime and simplifying the startup cost resulted in a significant quality loss without reducing the computation time. Omitting reserve requirements, ramping limits and transmission limits reduced the computation time, but degraded the solution significantly. However, the linear relaxation resulted in less quality loss with a significant speed-up and resulted in no difference when unserved energy was minimized. Finally, we found that the average and maximum capacity factor difference is large for all model variants.

In power system modelling the unit commitment problem is used to simulate the wholesale electricity market. A solution to the unit commitment problem is a least-cost schedule that contains information regarding the capacity factors of each generator, the total CO2 emissions, and unserved energy per hour. However, since there might be a large variety of (sub)-optimal solutions, these characteristics might be arbitrary and conclusions about them may be presumptuous.In this article, we illustrate this by running multiple experiments on a future European power system. Each scenario was run multiple times by adding additional terms to the objective function such as the minimization and maximization of generator capacity factors, carbon emissions, and loss of load hours. The results showed that schedules can be equivalent in terms of cost, but that relative capacity factors, emissions, and loss of load hours could differ by large factors.

European electricity markets ensure the matching between supply and demand at all times. Due to their time-scale operations, the balancing markets are the last resources to achieve so and ensure the grid frequency. The increasing shares of non-dispatchable power capacities intensify the demand for flexibility. District heating systems (DHs) are potential sources of flexibility if interface technologies are in place like CHP or power-to-heat, together with thermal storage. This study assesses the technical potential of DHs to contribute to frequency containment reserves (FCR), automatic and manual frequency restoration reserves (aFRR and mFRR) markets. Through a review of case-studies, we gain insight and derive appropriate assumptions to estimate the potential at country and EU levels. Based on the POTEnCIA Central scenario up to 2050 — a description of the evolution of the EU energy system with the assumption of no further policies introduced beyond 2017 —, we find that the potential is highest for the provision of aFRR, followed by mFRR and FCR. Specifically, the aFRR technical potential is currently 32 GW — 4 times the aFRR contracted in 2019 in the EU — and it only slightly decreases by 2050. Overall, this study highlights the lack of data on current (and future) DHs and their variety in size and composition. A sensitivity analysis is performed by examining different scenarios for DHs deployment. This research emphasizes the large untapped potential to exploit flexibility from DHs, however, the evaluation of the actual potential shall be done on a case-by-case basis.

In the EU28, the meat and dairy supply chains emitted 360 Mt CO2-eq or 80% of all agricultural CH4 and N2O emissions in 2016, which must be reduced to reach net-zero greenhouse gas emissions by 2050. Our research explores how far these emissions can be reduced by combining field tested mitigation measures for beef cattle, dairy cattle, swine, sheep, and synthetic fertilizers. Many mitigation measures targeting enteric fermentation, manure management, and fertilizer application have been experimentally tested; however, the impact of combining measures is relatively unexplored. To address this knowledge gap, we use graph theory to create combinations of measures for which we calculate the overall mitigation potential. From previous review studies, we identified 44 measures and formulated rules on impossible and mandatory combinations of measures. Based on the resulting sets of feasible cliques in the graphs and a simplified technological baseline, we estimate that the combinations with the highest reductions reduce CH4 and N2O emissions from beef cattle by 57%, dairy cattle by 47%, swine by 70%, sheep by 48%, and synthetic fertilizers by 44%. Together, they can reduce CH4 and N2O emissions in the EU28 from meat and dairy production by 54%, and for agriculture overall by 42%. This indicates that implementing more measures in the meat and dairy sectors can create room for further reduction than in the existing modelled pathways for the EU28. However, technical measures are incapable of fully eliminating agricultural CH4 and N2O, so there remains a need for CO2 removal technologies.

We model the evolution of the Central Western Europe power system until 2040 with an increasing carbon price and strong growth of variable renewable energy sources (vRES) for four electricity market designs: the current energy-only market, a reformed energy-only market, both also with the addition of a capacity market. Each design is modelled for two decarbonisation pathways: one targeting net-zero emissions by 2040 for a 2 °C warming limit, and the other targeting −850 Mt CO₂ y‾ for a 1.5 °C warming limit. We compare these scenarios against the high-level objectives of delivering low-carbon electricity reliably to consumers at the lowest possible cost. Our results suggest that both 2 °C and 1.5 °C compliant systems could be achieved and deliver electricity reliably. In terms of cost, we find the 1.5 °C warming scenarios lead to system costs which are twice as high as the 2 °C scenarios due to the high cost of negative emission technologies – in particular direct air carbon capture (DAC). To make a 1.5 °C target more affordable, policymakers should investigate lower cost alternatives in other sectors, and increase research and development in DAC to reduce its cost.

Europe's capacity to explore the envisaged pathways that achieve its near- and long-term energy and climate objectives needs to be significantly enhanced. In this perspective, we discuss how this capacity is supported by energy and climate-economy models, and how international modelling teams are organised within structured communication channels and consortia as well as coordinate multi-model analyses to provide robust scientific evidence. Noting the lack of such a dedicated channel for the highly active yet currently fragmented European modelling landscape, we highlight the importance of transparency of modelling capabilities and processes, harmonisation of modelling parameters, disclosure of input and output datasets, interlinkages among models of different geographic granularity, and employment of models that transcend the highly harmonised core of tools used in model inter-comparisons. Finally, drawing from the COVID-19 pandemic, we discuss the need to expand the modelling comfort zone, by exploring extreme scenarios, disruptive innovations, and questions that transcend the energy and climate goals across the sustainability spectrum. A comprehensive and comprehensible multi-model framework offers a real example of “collective” science diplomacy, as an instrument to further support the ambitious goals of the EU Green Deal, in compliance with the EU claim to responsible research.

The single-unit commitment problem (1UC) is the problem of finding a cost optimal schedule for a single generator given a time series of electricity prices subject to generation limits, minimum up- and downtime and ramping limits. In this paper we present two efficient dynamic programming algorithms. For each time step we keep track of a set of functions that represent the cost of optimal schedules until that time step. We show that we can combine a subset of these functions by only considering their minimum. We can construct this minimum either implicitly or explicitly. Experiments show both methods scale linear in the amount of time steps and result in a significant speedup compared to the state-of-the-art for piece-wise linear as well as quadratic generation cost. Therefore using these methods could lead to significant improvements for solving large scale unit commitment problems with Lagrangian relaxation or related methods that use 1UC as subproblem.

To mitigate climate change a renewable energy transition is needed. Existing power systems will need to be redesigned to balance variable renewable energy production with variable energy demand. We investigate the meteorological sensitivity of a highly-renewable European energy system using large ensemble simulations from two global climate models. Based on 3×2000 years of simulated weather conditions, daily wind and solar energy yields, and energy demand are calculated. From this data, 1-, 7- and 14-days events of extreme low renewable energy production and extreme high energy shortfall are selected. Energy shortfall is defined as the residual load, i.e. demand minus renewable production. 1-day low energy production days are characterised by large-scale high pressure systems over central Europe, with lower than normal wind speeds. These events typically occur in winter when solar energy is limited due to short day lengths. Situations of atmospheric blocking lead to long lasting periods of low energy production, such 7- and 14-days low production events peak late summer. High energy shortfall events occur due to comparable high pressure systems though now combined with below normal temperatures, driving up energy demand. In contrast to the low energy production events, 1-, 7- and 14-days high shortfall events all occur mid-winter, locked to the coldest months of the year. A spatial redistribution of wind turbines and solar panels cannot prevent these high-impact events, options to import renewable energy from remote locations during these events are limited. Projected changes due to climate change are substantially smaller than interannual variability. Future power systems with large penetration of variable renewable energy must be designed with these events in mind.

District heating represents a viable way to reduce carbon dioxide emissions in the built environment. This paper aims to assess the extent to which the market revenues of multiple heat production technologies can cover their fixed costs in a competitive wholesale district heating market. Marginal-cost pricing is applied in a case study of the Netherlands. A linear programming model incorporating heat supply and demand is developed to obtain hourly dispatch and heat market prices. It is concluded that low carbon heat generation technologies tend to have low short-run marginal costs. All examined heat producers have an under-recovery of fixed costs in a range between 60% and 90% except the waste incineration combined heat and power plant. It has an overall return on investment of 44% and 12% within the reference and heat pump scenario respectively. Although marginal-cost pricing may ensure cost-efficient dispatch, the market revenues are far from enough to recoup the investment costs for the majority of the heat producer, let alone the network costs. Significant additional remuneration is required to sustain a competitive heat market and ensure sufficient investment in new generation capacity in the long run.