Renewable energy resources like wind and solar have the potential to revolutionize our energy infrastructure and enable a decarbonized society. The intermittent nature of renewables poses a challenge to ensuring a consistent and reliable electricity supply. Hydrogen technology is emerging as a promising solution for stabilizing renewable energy systems. There is still significant technological development required to cost-effectively integrate hydrogen with renewable energy assets. Conventional PV solar installations require power electronics for their operation, like charge controllers and inverters. Not only are these power electronic components costly and in high demand, but they also degrade faster than PV solar panels. Removing power electronic components could significantly lower the investment costs associated with a PV solar park. This work focuses on how PV solar panels can be directly coupled to a modular alkaline electrolyzer, without grid-based buffering or the use of an inverter. Literature research revealed that hydrogen technology has seen little exploration in on-grid Hybrid Renewable Energy Systems (HRES) and no exploration in off-grid HRES. To appropriately investigate whether a directly-coupled HRES would be technically feasible, a megawatt-scale system was modelled and simulated. All elements of the HRES were modelled, duly accounting for physical limits and constraints. Components were sized and configured to complement one another, optimizing for maximum hydrogen production. To experimentally verify the validity of the proposed HRES, a 5 kW pilot system was constructed. To control the HRES, a new algorithm was developed using the Incremental Conductance maximum power point tracking algorithm as a basis. Within the new Maximum Hydrogen Production (MHP) algorithm, the step sizing was discretized and a variable step size was implemented which can be applied to any target slope. This allows for the system to target operational points which optimize hydrogen yield instead of electricity yield. Furthermore, the addition of tracking bias helped adjust for the asymmetric nature of the interaction between electrolyzer stacks and the PV solar park. Simulation results in The Netherlands demonstrated that the feasibility of the HRES is dependent on the configuration of the PV solar park and on the number of electrolyzer stacks in the system. Compared to industrial and research benchmarks, the proposed HRES increased hydrogen production by 14.9% and 4.2%, respectively. Dynamic 'm-tracking' of the MHP algorithm goal increased hydrogen production by 0.8% in months of high irradiance. Months with a lower average irradiance experienced an artefact in the MHP algorithm, resulting in prolonged periods of zero power output. An experimental setup confirmed the simulation results, showing that it is possible to control a system of PV solar panels directly coupled to a modular alkaline electrolyzer. Experimental results revealed the need for moving average filtering to prevent fluctuations due to changing conditions of the electrolyzer and the weather from causing poor algorithm tracking ability. The low performance of the experimental setup can be attributed to a low iteration and measuring frequency, which increase the likelihood of a tracking error due to rapidly changing operating conditions. Economic analysis of the proposed HRES yielded an LCOH of €3.44 per kg, 20% and 13% lower than industrial and research benchmarks, respectively. Therefore, an HRES featuring PV solar and modular alkaline electrolysis is technologically and economically viable without the use of charge controllers and inverters.

Hydrogen's competitiveness as a sustainable energy carrier depends greatly on its transportation and storage costs. Liquefying hydrogen for these purposes offers benefits like purity, versatility, and higher density. However, current industrial hydrogen liquefaction processes face efficiency and cost challenges, with a second-law efficiency below 25% and costs between 2.5-3.0 US$/kgLH2, and they are mainly limited to small-scale. Scaling up liquefaction plants is a potential solution to reduce costs, but existing models often overlook the economic and technical viability of the conceptual plants. Most reported liquefaction costs rely on "ballpark" estimation, hindering process economic comparisons between various processes. Industry-sponsored studies often use confidential data, limiting accessibility. Thus, this thesis aims to develop a comprehensive framework for modelling large-scale liquefaction processes and assessing their feasibility, focusing on the large-scale high-pressure hydrogen Claude-cycle liquefier concept. The technical analysis focuses on the preliminary designs of main equipment, such as compressors, turboexpanders, and heat exchangers, ensuring compatibility with existing technology limitations. Aspen Process Economic Analyzer (APEA) is employed to estimate the capital and operating expenditure. At 0.1 €/kWh electricity price, the techno-economic assessment of the 125 tonnes per day (TPD) Claude-cycle concept yields specific liquefaction costs (SLC) of 1.55 €/kgLH2. Sensitivity analysis shows electricity price has significant influence. Applying the established design approach, incorporating high-speed centrifugal compressors could reduce the SLC by 5.42% and potentially more. Scaling up to 250 and 500 TPD shows potential SLC reductions of 7.80% and 9.45%, respectively, at electricity price of 0.1 €/kWh. Future projections suggest a potential 12.6% SLC reduction as the Claude-cycle liquefiers matures. In an ideal scenario, with incentives and low-cost renewable electricity, costs could range from 0.87 to 1.09 €/kgLH2. Finally, a cost-scaling curve for hydrogen liquefaction plants are estimated based on the cost results from this study. The curve is comparable to existing cost curves reported by industrial and government joint research projects, validating the methodologies developed in this thesis. Moreover, an experience curve is also predicted using cost data from this study and data found in the literature. The curve indicates a 17% price decrease in hydrogen liquefiers with each doubling of global liquefaction capacity.

The economic engineering group at the DCSC uses Newtonian and analytical mechanics to model economic systems but makes no use of thermodynamics. The introduction of thermodynamics to the economic engineering framework would increase the extent of analysis and interpretation of economic systems in economic engineering. In this thesis the foundations of the thermodynamics of economic engineering are developed in order to include thermodynamic modeling of economic systems in the field of economic engineering. After the development of the thermodynamics of economic engineering theory, the theory is applied to analyze economic growth, factor productivity, and the value of a business. An axiomatic approach is taken to derive economic analogs to thermodynamic concepts. The meaning of an axiomatic approach is that these economic-thermodynamic analogs are developed in a logical order, e.g., the economic analog to temperature is not introduced before developing the economic analog to the first law. Key analogs between economics and thermodynamics are established in this thesis that include but are not limited to two fundamental economic laws, work as an expenditure, heat as an expense, temperature as a price level, and entropy as a quantity referred to as human capital in the thesis. By deriving key analogs, the thesis establishes the foundational principles of thermodynamics within economic engineering. Utilizing the theory of the thermodynamics of economic engineering results in applications to economic growth. Empirical growth accounting is modeled by the fundamental thermodynamic relationship. A relationship between linear production functions and Cobb-Douglas type production functions is shown by analyzing the productivity of an economy. Furthermore, a method to evaluate the worth of a business is created by determining the business' total potential earnings. Additionally, the thesis shares a vision of how to include thermodynamics within a control engineering framework. A higher-dimensional energy-based approach to model dynamical systems offers a way forward to include thermodynamic energy and entropy within control formalisms. Such a framework would account for availability and heat buildup in controlled dynamical systems. One potential application is to account for the heat build up that occurs in integrated circuits.

The worlds energy demand is rising as a result of industrial activity and advances in countries around the world. Fossil fuel sources are used to meet this demand for much of the world [1]. The way in which energy is handled causes pollution e.g., CO2 emissions, inducing climate change, therefore a more sustainable industry is desired [2, 3]. Carbon Capture and Utilization (CCU) is a way to use CO2 from the atmosphere or which would end up in the atmosphere, limiting its influence on the climate. Sustainable fuels or chemicals can be produced from the captured CO2, reducing the use of fossil fuels and fossil feedstock [4, 5]. Formic Acid is a favourable product from CO2 electrolysis. Only 2 electrons are required for one molecule Formic Acid, which results in a high normalized price ($/electron) [6]. COVAL Energy works on scaling-up and commercialization of CO2 electrolysis to Formic Acid. Coval has already an operational reactor on lab scale with promising performance, a conversion efficiency up to 90%. Although the reaction kinetics are limited by a poor distribution of reactants on the electrode surface. Previous research by Jos van der Maas showed a highly uneven flow distribution in the cell reactor [7]. Gas bubbles are formed inside the reactor, which likely limit the reaction. Consequences of this poor distribution of reactants and these bubbles are a lower energy efficiency and higher electrical resistance. The main question of this thesis is: How can the current knowledge of electrolysers be applied to improve the Coval electrolyser design regarding flow distribution and mitigation of the impact of dissolved gas production? Experiments were performed to gain knowledge about the bubble behaviour in the Coval electrolyser. Computational Fluid Dynamics (CFD) was used to screen design ideas on liquid distribution. Promising designs were assessed in a flow and gas bubble visualisation experimental setup, in which also the bubble behaviour was investigated. Finally, prototypes to be tested in the high pressure reactor were produced. Two auspicious designs were found. The first design has channels in the inter electrode gap. The results showed that with channels the velocity variation over the cell width was reduced. The second design has a manifold like geometry in a calm zone before and after the interelectrode gap. This resulted in an almost constant velocity over the cell width for the entire cell. Additionally, a larger inlet and outlet pipe to and from the cell improves flow homogeneity and reduces pressure dorp in these pipes. The gas fraction in the cell can be kept low by sloping the top part of the cell towards the outlet. A next step is to assess both designs in the high pressure reactor. Particular attention should be paid to the manufacturing of the design to avoid leakage and mechanical deterioration. It is recommended to measure pressure drop over the cell for better assessment of the designs.

Many of the high-performance portable electronics and electric vehicles (EVs) on the market depend on lithium-ion batteries (LIBs) as their primary energy source. If millions of EVs are to be manufactured each year, rigorous resource management for EV battery manufacturing, as well as a material- and energy efficient 3R system (reduce, re-use, recycle), will undoubtedly be required to assure the future sustainability of the automotive industry. Since lithium is only found at a few locations around the world, there is an inherent danger from a geopolitical standpoint when it comes to accessibility. Political turmoil or instability in the nations controlling these lithium stockpiles may have a detrimental impact on world supply. Spent LIBs can be viewed as an alternative source of lithium. Considering that used LIBs contain toxic organic electrolytes and heavy metals, recycling them reduces resource waste and environmental contamination. Due to the difficulty of handling its complex composition and distribution, most recycling efforts and industrial processes focus solely on recycling the cathode and ignore the proper treatment of the aged electrolyte. Recovery of the electrolyte is crucial for achieving the legally mandated recycling efficiency set by the European Commission, as the electrolyte typically comprises of 10-15 wt% of a LIB cell. Therefore, this study explores the feasibility of using crown ethers (12C4 and 15C5) to extract and recycle the lithium salt (LiPF6) from the electrolyte of spent LIBs. The extraction efficiency of these crown ethers is examined across various extraction conditions to identify the most favorable extraction condition. The results and findings obtained from the conducted experiments reveals that the extraction efficiency correlates with the mole ratio between crown ethers and lithium, up to a certain threshold (6:1 for 12C4 and 12:1 for 15C5) where further increase in mole ratio does not significantly enhance the extraction yield. The extraction yield displays an inverse relationship with temperature, indicating an exothermic extraction process that favors lower temperatures. Remarkably, varying the extraction time within the 5 to 30 min range exhibits negligible influence on extraction yield, suggesting rapid kinetics in the formation of the crown ether-lithium complex. Between the two crown ethers tested, 12C4 emerges as the more suitable option, achieving extraction yields of up to 60%. In contrast, the use of 15C5 necessitates larger quantities compared to 12C4 to achieve equivalent extraction yields. Consequently, using 15C5 not only increases the cost but also diminishes the overall process efficiency. Further research is proposed to conduct experiments for the extraction of the organic solvents in the electrolyte using CO2 and to develop methods for separating the extracted lithium from the crown ether without compromising the integrity of the crown ether, allowing for its reuse in subsequent extraction processes.

Steam utility systems supply process units with the required heat, rotational power, feed for steam methane reforming et cetera. This work is based on the steam network located at Shell Raffinaderij Nederland in Pernis. The refinery has grown over the years which has resulted in an extensive and complex steam network which interconnects old and new process units. Operating the network is difficult, especially predicting the effect of changes in the network or finding the optimal operating mode where costs are minimized. The aim of this study is to create a model of the steam network which can predict these effects and able to find the optimal operating point. The steam network is simulated in two models: one focused on hydraulic calculations and one on operational cost optimization. Both models are created in the software i-Steam from PIL, which is specialized in simulating and optimizing steam utility systems. The hydraulic model incorporates the pipelines and all steam producers and consumers connected to the network. The model is validated for four scenarios which arechosen to include varying ambient conditions and operating modes. The model is applied for testing the effects of a new unit which must be connected to the existing steam network. The optimization model is focused on steam and electricity production and uses the current market conditions, such as the prices of natural gas, electricity, water and CO2 emission. Another factor in optimizing the system is by comparing the steam production price with the steam price which can be taken in from the power generation plant 2 (PGP2). The software uses GAMS as an optimization tool which applies multi integer nonlinear programming to find the operating mode with the minimal operating cost. The pressure and temperature validation results for the hydraulic model are mostly within the 2.83% accepted uncertainty window. For certain areas the model indicates large steam surpluses over 10 t/h, which are probably due to bad flowmeters on the steam consuming side. The simulations of the new project resulted in the most promising connection to the existing steam network. For 18 barg steam consumption, the new unit should be connected to LS4413 with a backup connection for redundancy to LS980019. For 3 barg steam production, the economic feasibility of laying 250 meters of pipeline in order to be able to export 4 t/h has to be further researched. The optimization model is validated using monthly timestamps over a two-year period. Optimization of these timestamps resulted in an average operating cost reduction of 1-3 %, with one peak at 6%. The hydraulic model can simulate the effects of operating scenarios, retrofits and locates the bottlenecks in the steam network. The optimization model reduces the operating costs while providing each process unit with the required steam. Both models can help the employees working at the refinery to study new scenarios and advice in operating the network at its optimal point.

The current industrial application of carbon capture utilization and storage (CCUS) is limited due to technological drawbacks such as high energy demand and environmental pollution. Ionic liquids (ILs) and deep eutectic solvents (DESs) are considered promising alternative solvents for the capture of carbon dioxide (CO2). DESs are often characterized by high viscosities, which hinders industrial application. This problem might be solved by mixing the DES with an organic solvent. This study aims to assess the DESs choline chloride-ethylene glycol (ethaline) and choline chloride-urea (reline) mixed with methanol and propylene carbonate (PC) for their suitability as a medium for the combined capture and electrochemical conversion of CO2. Molecular dynamics (MD) simulations are performed to obtain the densities, the viscosities, the self-diffusivities, the ionic conductivities and insight into the molecular interactions of these mixtures. Independent MD simulations are performed of these mixtures with low concentrations of the solutes CO2, oxalic acid and formic acid. Complementary studies within the Bio-cel project are conducted to characterize the solubility and electrochemical reaction of CO2 and the techno-economics. The viscosities of the mixtures monotonically decrease for an increase of mole fraction of organic solvent, which is benign for the application of CCUS. The self-diffusivities of all constituents increase monotonically for an increase of mole fraction of organic solvent. The ionic conductivity is calculated based on the ion self-diffusivities. Ionic conductivity optima are found at a mole fraction of DES of approximately 0.6 for ethaline-PC and approximately 0.2 for ethaline-methanol and reline-methanol. For higher mole fractions of organic solvent, the ionic conductivity decreases due to a depletion of ions. Radial distribution functions (RDFs) are used to analyse the intermolecular interactions. RDF peaks between chloride-choline and chloride-ethylene glycol show an increase for an increasing mole fraction of organic solvent, which was unexpected. The numbers of hydrogen bonds decrease for addition of methanol to pure deep eutectic solvent. For addition of propylene carbonate, this decrease is less pronounced. The depletion of hydrogen bonds at low mole fractions of deep eutectic solvent is in correspondence with the decrease in viscosity and increase in self-diffusivities. The results indicate that, for the studied properties, deep eutectic solvents mixed with organic solvents are more favourable than pure deep eutectic solvents for the absorption and electrochemical conversion of CO2.

In this work, the added value of machine learning (ML) molecular force fields (FF) for the community of molecular simulations is showcased by successfully calculating transport properties of aqueous potassium hydroxide (KOH (aq)). Classical FFs use relatively simple interatomic potentials to simulate the nano scale. These simulations can predict macroscopic properties, such as density, heat of evaporation, viscosity, and self-diffusivity of the modeled materials. However, these FFs struggle to model materials in which more complicated interactions are relevant for the macroscopic behavior. Examples of such interactions are three-body interactions and chemical reactions. Quantum scale simulation methods are able to compute properties of materials in which these challenging interactions occur, although these methods are limited in length and time scales that can be modeled with realistic computational costs. Transport properties, such as viscosity, self-diffusivity and electric conductivity need these larger length and time scales to be determined accurately. ML can be used for a multi scale approach, bridging the gap between the quantum and the nano scale by training coefficients of general interatomic potentials. This provides the possibility of reaching the time and length scales of traditional molecular simulations with the accuracy of quantum mechanic models. KOH (aq) is selected to highlight the prospects of these multi scale techniques, as the self-diffusion of OH- in this electrolyte is dominated by proton transfer reactions, which has not been modeled successfully with classical FFs. Results of structure properties produced with ab initio molecular dynamics (AIMD, at quantum scale) simulations are compared with machine learning molecular dynamics (MLMD, at multi scale) simulations. There are no significant differences in the calculated shortest typical atomic distances and coordination numbers for both KOH (aq) and pure water systems. The determined transport properties are in the same order of magnitude as experimental results, although the calculated viscosity is overestimated and the self-diffusion of H2O and K+ are underestimated. This is because the system is simulated at a higher than experimental density and hydrogen bonding is overestimated with the selected quantum mechanics model. The proton transfer reactions are captured in the MLMD simulations, calculating the enhanced self-diffusion of OH- to be (6±2)e-9 m squared per second, which matches experimental results at infinite dilution.

In some countries, drying processes use up to 20% of the total energy consumption. Within the agriculture sector, drying of food and flowering products is a necessary step in production. A lot of companies make use of hot air dryers where the heat is gained by burning natural gas. A novel method is to use a heat pump assisted drying systems instead. Heat pump assisted drying realises a better product quality due to the ability of humidity and climate control of the drying medium: air. Additionally, there are possibilities for energy savings up to 50%. This thesis project is mentioned as the first step for an initiative to introduce heat pump drying into the horticulture sector. The project started almost 1 year ago and is still far from finished. Main goal was to get a good understanding of the product drying behaviour, drying capacities and the system requirements and footprints. Conclusions should determine whether there is a possibil-ity for market implementation or not. The results in this report are promising. Heat pump drying is a trending research topic in science, where new developments on predicting the dynamic drying behaviour of agricultural products show up every month. This study involves a computational model, where the dynamic process of drying flower bulbs is simulated. This model is validated by measurements on existing drying in-stallations. Building this model resulted in a good understanding about the flower bulb characteris-tics and the necessary drying capacities. Additionally, Heat pump drying systems are evaluated and a dynamically modelled. When both models are the drying process of FB’s can be optimized. The first protype of the HP drying system that will be used in further research will be shortly discussed. Conclusion of this report is that heat pump drying is a promising technique for drying of FB’s. The combination of technical advantages with energy savings, could lead to better product quality and lower production costs. The business case is strengthened by future perspectives where energy efficiency and reduction of CO2 emissions will more and more important due to climate change.

Many regions in the world depend heavily on expensive desalinated water for fresh water consumption, in particular tropical areas. Current mainstream desalination technologies (Reverse Osmosis and Multi-Stage Flash Evaporation) are quite energy intensive and thus costly. Today’s challenge is to design a desalination system that could run with local available renewable energy and provide affordable fresh water, even in the most arid environments. A potential fresh water production method that differs from mainstream technologies is Ocean Thermal Water Production (OTWP). This method makes use of high temperature and high relative humidity air in the tropics and condenses it against a cooled fresh water loop in a packed bed column. The system is expected to deliver fresh water at a competitive level once built at a larger scale. This master thesis project improves a previously researched OTWP model and validates the model by testing its output values against experiments done using an experimental setup at the TU Delft P&E laboratory. Taking into account the previous work done during the thesis of van der Drift [49] and Lopez [30], the theoretical background for building an OTWP model has been further described and expanded in this thesis. Three different direct contact condensation theories have been thoroughly examined. The first two theories suggest that heat and mass in the DCD are transferred through a constant laminar film on the packing [38] [1] [4]. The third theory is an add on to the laminar film model, and suggests that heat and mass is also transferred through the creation and dynamics of small droplets within packings [34]. The model and its 4 main submodels are fine-tuned to be able to reproduce the thermodynamics occurring in the experimental setup. The model is tested under different steady state conditions using experiments, to provide insight on the model’s robustness and reliability. The final improved simulation model is used to present conclusions on heat transfer, mass transfer and water production rates for the experimental setup. A brief economic analysis of the system is performed to arrive at an energy price of water for the OTWP experimental system. Although the final energy price for the OTWP setup is quite unfavorable, 14 kWh/m3 as opposed to 2-3.5 kWh/m3 for current desalination systems, tips to improve a possible future pilot facility are proposed. Here high yield and low cost are key requirements, and the design of a future pilot facility needs to be optimized using these two pillars.

To tackle the expected increase in fresh water shortage in the world, alternative water production methods are required. One such a possible method is Ocean Thermal Water Production (OTWP). This thesis continues on the innovative concept of the use of OTEC waste water as a cooling fluid for atmospheric water production introduced in previous work. In this thesis, an experimental study on a structured packed bed condenser column is presented. This work was carried out on an experimental OTWP set-up installed in the Process & Energy lab at the Delft University of Technology. Additionally, a numerical Python model was used to investigate the heat transfer and condensation characteristics of the packed bed column. The condenser function of the Python model was used to compare the prediction performances of different mass transfer coefficient and hydraulic correlations. The Python model simulations were compared both to the predictions of Aspen plus, an established chemical process software, and to the experimental results. The correlation by Olujic et al. (1999) was chosen as the most suitable for the transfer rate and hydraulic behavior predictions for the Python condenser model. A mean average error in the mass transfer predictions of 2.5 % and in the hydraulic predictions of 16.9% was reached in relation to the experiments. outperforms the Aspen plus model, that has respective mean average errors for the mass and pressure drop predictions of 9.5% and 13.0 % for the correlation proposed by Rocha et al. (1993). The Python model was extended with functions that calculate the pressure drop over the remaining necessary equipment for an OTWP plant. The aim of the developed model was to predict the processes in the OTWP condenser column and design a pilot-plant. The model was used to perform a sensitivity analysis on a large-scale column. A preliminary economic analysis identified that reducing the diameter of the condenser column reduces the cost of water production but increases the energy requirement. For an OTWP pilot-plant with a production of 25 m3/day, the chosen column diameter of 6.6 m leads to a system energy requirement of 3.5 kWh/m3 and a levelized cost of water production of 8.08 $/m3. Those production costs can be reduced by an optimization study of the full OTWP pilot-plant.

Of the global energy demand, 20% can be allocated to residential energy demand. Most of this energy is produced by fossil fuels, which raises the importance of energy production in a more sustainable way. In order to do this on the level of residential heating applications, the Dutch government aims to make its residential neighborhoods natural gas-free. An often considered solution is making residential areas all-electric. However, when considering the heating of these households based on electricity, high peaks may occur in the electricity grid due to simultaneous heating at times of high demand. This could cause problems regarding the capacity of the electricity grid. Subsequently, the generation of electricity is nowadays associated with relatively high CO2 emissions, raising the awareness for alternative methods of heating. One of these methods is district heating coupled to (more) sustainable energy sources. A problem occurring with this combination is a possible discrepancy between the supply and demand of energy. Therefore, it could be beneficial to implement thermal energy storage in district heating. This research assesses the feasibility of different configurations of thermal energy storage integrated into district heating. For this research, a case study is conducted in which district heating for a residential area coupled with thermal energy storage is modeled. The model is based on the thermodynamic equilibrium of the network and is able to compute the required characteristics and key performance indicators of the district heating network. For the case study, multiple scenarios have been created which assess different distribution characteristics and heat sources. For reference, an all-electric scenario has been designed as well. The results of the case study show that the implementation of thermal energy storage in district heating is able to lower peak loads on the heat source by two-thirds. This implementation goes paired with an increase in levelized cost of energy of 10-16% and 8-73% higher CO2 emissions, compared to district heating without storage and depending on the characteristics of the district heating net and its heat source. However, for certain heat sources, the advantages of thermal energy storage outweigh the drawbacks or thermal energy storage might even be considered to be inevitable. This is especially the case for renewable heat sources, of which its share in the future energy market is considered to be substantial. Also, the results show that every scenario considering district heating performs better on levelized cost of energy and CO2 emissions than the all-electric scenario. When designing new DH projects, it is key that different available heat sources will be considered and that an accurate trade-off is made between the advantages and drawbacks of thermal energy storage. This research is based on the comparison of various scenarios for a case study. Therefore, it does not focus on finding the optimal parameters for either district heating or thermal energy storage. For finding these optimal parameters, future research must be conducted.

The thesis discusses how alternative heat generation for furnaces can be implemented on the Shell Netherlands Refinery to become CO2 neutral by 2050 or sooner. The research analyses the current knowledge, and future alternatives for furnace heat generation and underlines the need for alternative solutions with net-zero emission impact. Furnaces are the equipment that heat process streams before the reactor or distillation column. Hydrogen firing, electrification, biofuel combustion, and heat pumps are the four main topics of alternative technologies that are discussed. The result is a roadmap including all relevant information for the applicability of technologies, developments, value drivers and credible scenarios. Revamping all Pernis’ fired heaters for hydrogen firing is a suitable option and has TRL 6. The ultra-low NOx burners are operational, but hydrogen is not integrated yet as a fuel, and combustion analysers are not field-tested. The blue hydrogen will not be 100% pure, so not all CO2 can be abated. Besides, switching between RFG and hydrogen can cause flame instabilities and a higher thermal NOx emission. The normalised CO2 abatement price against RFG operation, the cost of not emitting a tonne of CO2, is 13 /tCO2. Electrification, such as impedance and immersion heaters, have TRL 7 and are limited to relatively small duties, single-phase, and clean service. Radiant heaters can heat process streams with two-phase and coking services having TRL 2. The concept is proven, but no prototype is tested. Electrical heaters have high efficiencies and might have a yield benefit. However, the showstopper is the plot space availability of the refinery. The normalised CO2 abatement price against RFG operation for electrical heaters is 21 /tCO2. Upgrading biofuel to biomethane allows the gas to be interchangeable with natural gas. Suitable for combustion without any adjustment on the furnace if biomethane is injected into the national natural gas grid. Biomethane combustion, having TRL 7, only impacts the sites emission, and it seems to be an administrative solution, where trading in certificates will be dominating the market. The normalised CO2 abatement price against RFG operation for biomethane is 21 /tCO2. Heat pumps are used in refineries, and they can be used to reduce the furnace load but not to replace the furnace. The potential for replacing fired heaters with TRL 7 heat pumps is low since the maximum operating temperature is 160°C [1]. The development scenarios showing the energy consumption expects that low carbon-intense electricity will expand most, suggesting that electrification is the step forward for SNR. The usage and production of hydrogen tend to increase after 2050, and the amount of biomass is small and will most probably not be an available option for Pernis. Four credible scenarios show that it is possible to abate sufficient CO2. With electrification only, it is impossible to achieve the vision of 2050 due to the plot space constraint. The hydrogen and electrification scenarios are combined in a hybrid scenario, where most CO2 is abated. The net-zero CO2 operation of furnaces requires significant investments and technical developments.