The Netherlands is looking to decarbonize its economy and replace natural gas from Groningen and Russia with different energy carriers. Dutch government has been mainly stimulating renewable electricity production, CO2 capture and storage (CCS) and sustainable heat generation (RVO, 2022) to address these challenges. While these technologies are an indispensable part of CO2 reduction strategies, for full decarbonization of the economy more advanced technologies (Hammingh et al., 2022), new materials, mitigation solutions and negative emission technologies are required (Yang et al., 2022). To both reach full climate neutrality, and to replace Russian gas with green alternative, a renewable molecule is vital. The main alternative for fossils that is currently deployed is green electricity. Green electricity is an effective way to replace fossil fuels, but not all industries can replace their liquid or gaseous fuels with electricity. For those industries the Netherlands envisions green hydrogen to be the sustainable alternative. In their climate agreement the Dutch government has set the goal to have 3-4 GW of green hydrogen production via electrolysis installed in 2030. Currently, this goal seems difficult to achieve as the green hydrogen industry struggles to kick off. This is in large due to the fact that there is a gap in literature and policies between research projects and full scale green hydrogen production. Policies are needed to accumulate economies of scale to reach a price level at which green hydrogen is competitive with fossil alternatives or other forms of low-carbon hydrogen. The goal of this research is to identify a robust policy strategy that will enable the Dutch industry and government to reach the goals for hydrogen production...

According to International Energy Agency (IEA), the demand for high value chemicals (HVC) will increase by 60% to a total of 400 Mt/year by 2050, leading to an increase of 30% in direct CO2 emissions. However, the Paris agreement forces the sector to reduce its emissions by 90-100% in 2050 compared to 1990. This induces the need for a more sustainable character in the petrochemical industry to produce HVC with net-zero emissions by 2050.
Steam cracking is expected to be still the leading production technique for HVC in 2050. Therefore, this research focuses only on petrochemical clusters containing a steam cracker.
Accordingly, the research question to be answered was: How can existing petrochemical clusters containing a steam cracker be transformed to produce
HVC with net-zero emissions in 2050? This thesis aims to look into the potential of alternative feedstocks and combine them with other decarbonisation options for steam cracking to produce HVC with net-zero emissions by 2050 from a cradle-to-gate perspective.
A base model was created of a petrochemical cluster containing a steam cracker capable of serving the global market (3900 kt HVC/year) to answer the research question. The base model was used to develop six models with different decarbonisation options capable of accepting alternative feedstock. Decarbonisation options were based on carbon capture and storage (CCS), both post and pre-combustion, electrification and hydrogen. The alternative feedstock was sourced from the renewable materials: vegetable oils, animal fats, crude tall oil and lignocellulosic biomass. Also, plastic waste (recycled) and synthetic (FT wax and naphtha) feedstock made from captured CO2 and hydrogen were included. The maximum percentage of HVC produced from alternative feedstock was assumed to be 25% due to uncertainties and limitations in the availability of alternative feedstock. The rest of the HVC was yielded from a mixture of fossil feedstock (naphtha, LPG, ethane, gas oil and butene). Different experiments were performed to estimate the emission reduction potential of separate or combined decarbonisation options with HVC yields originating from alternative feedstock ranging from 0% to 25%. The supply chain and associated CO2 emissions of the feedstock were also analysed. Next to determining the emission reduction, the quantitative data from the models were also used to assess the levelized cost of zero emissions HVC and the geographical and infrastructural limitations of decarbonisation options. One problem was the residual fossil fuel gas from the process, possibly leading to unwanted emissions elsewhere if not appropriately handled. In conclusion, the only decarbonisation options capable of dealing with this problem are CCS and auto-thermal reforming combined with CCS. Together with renewable feedstock, from a cradle-to-gate perspective, these options are capable of reaching net-zero emissions or even negative emissions when fossil and renewable feedstock supply chain emissions are drastically reduced. For future research, it is advised to not only focus on producing HVC with steam cracking but also consider other greenfield production method capable of producing HVC with renewable resources. A comparison with the proposed pathways in this research would provide valuable insights.

The Russian invasion of Ukraine has created a renewed focus on both climate change and security of supply of energy. The European Commission’s Green Deal highlights the importance of the clean energy carrier ’low-carbon hydrogen’ to combat climate change. Simultaneously, in the new REPowerEU package, the European Commission emphasises the potential of low-carbon hydrogen as an alternative to the scarce natural gas. The quantities the European Commission aims for in these proposals are difficult to produce in Europe. Low-carbon hydrogen therefore needs to be imported. The main objective of this research is to develop a framework for all relevant players in both market and government on what mitigation measures to take for different risks for security of supply. It therefore answers the following research question: How can the security of supply of the low-carbon hydrogen import flow be organised, in a dynamically evolving market?

The data has been gathered by qualitative methods and has subsequently been analysed through a newly developed theoretical framework. This theoretical framework consists of the dynamic market theory of de Jong [1985], the transaction cost theory of Williamson [1979] and security of supply framework of [CIEP, 2019].

This research has shown that the newly developed theoretical framework is suitable to analyse both the development and security of supply of the gas market and the low-carbon hydrogen market. It has also helped to shed light on very recent developments since the current gas crisis only started when this research already had begun. The dynamics between the market and the government in the gas-market were shown and it became evident that the current market-focused approach has not worked, given the current crisis. This research has shown that this market approach is two-sided: firstly, the Netherlands was dependent on the spotmarket without having long-term contracts. Secondly, most mitigation measures in case of disruption were also organised by the market. Therefore, this research has combined different risks with suitable mitigation measures and shows which ones should be regulated or taken by the government: in the introduction phase, important mitigation measures that should be focused on are: I) commercial storages II) the ability to switch fuels and carriers and III) foreign and security policy. In the expansion phase the same mitigation measures are important and new ones arise, these are: I) diversification to type of carrier, II) diversification to geographic source, III) resilience in infrastructure and IV) strategic storages.

The development of a low-carbon hydrogen import value chain is crucial to combat
climate change. In order to secure the supply of low-carbon hydrogen, a right balance should be found in the trade-off between the organisation by the market and the government. This thesis presents a newly developed framework that contributes to approaching this balance.

In the transition towards climate neutrality by 2050 green hydrogen can contribute as a clean and widely applicable energy vector. However, domestic production by electrolysis in the Netherlands will not be able to produce enough hydrogen for the estimated demand. Import of hydrogen will thus be crucial. The Port of Rotterdam (PoR) will play a vital role herein as the port has set the goal to become the hydrogen hub of North-Western Europe. To transport hydrogen, solutions are being evaluated since the molecule has a very low volumetric energy density at ambient conditions. Among others, liquid ammonia (LNH3) is under investigation as an import method since it has favourable storage conditions, a flexible end-use, and a high volumetric energy density. After landing in the PoR, ammonia can be decomposed by catalytic cracking. This technology is, however, still under development for this application and economic data on its performance are lacking. Furthermore, this import method must compete against domestic production and is subject to deep uncertainty since characteristics of the novel hydrogen economy are unknown. This study evaluates the impact of uncertainties on the techno-economic performance of various ammonia-based energy hub designs in the PoR in many scenarios. An ammonia-based hub is an import terminal with a catalytic cracker, direct ammonia sale, and a hydrogen fuel cell. The evaluation is performed by answering the following research question: How do uncertainties and competition impact the techno-economic performance of various ammonia-based energy hub designs in the PoR? The core part of this research is performed by computationally modelling the ammonia-based energy hub in the multi-actor field, and simulating its behaviour for numerous possible futures in the period between 2030 and 2040. The first phase of the research is used to find quantitative performance indicators to evaluate the techno-economic performance of an ammonia-based energy hub. Subsequently, an extensive literature research executed to (1) map global and local market actors, (2) research available ammonia decomposition technologies, and (3) find exogenous factors that can be varied numerically in a scenario analysis. Simultaneously, conceptual models are made of energyhub design options and of the multi-actor field in which the hub is situated. In a third research phase, the multi-actor field and the energy-hub are modelled in Linny-R. The problem is formulated as a mixed-integer linear programming problem herein; the net cash flow of all actors is the optimization variable in this paradigm. To generate datasets that serve as input for the simulations in Linny-R, a python model has been written. Lastly, generated results from Linny-R are analysed to get insights and formulate recommendations for the PoR and further research.

The Port of Rotterdam is developing a hydrogen and CO2 pipeline bundle for industry in NRW. By applying a Multi-Criteria Analysis to this case, a model is created that evaluates this pipeline bundle against the criteria of the industry in North Rhine-Westphalia. The system analysis is used as the basis for the model, industry objectives are used as key performance indicators, and external factors affecting the system are included as parameters. Experiments with the model have shown that in addition to technical and economic aspects, policy and social consensus must be closely monitored for the future succes of the pipeline bundle.

Because of the climate crisis the world is facing, all sectors must move towards a more sustainable future. In the Netherlands, the industry sector emits large amounts of CO2 because of the heavy reliance on fossil-fuels and large electricity demand. The Paris agreement and the Green Deal forces the industry sector to rapidly transition towards more sustainable practices, which can be achieved if the correct synergies are established. The multi-actor nature and the technical and operational dependencies that industrial clusters have, makes optimal decision-making extremely important in working towards that net zero future. Innovations that re- duce the emissions are limited, but they exist and provide (intermediary) solutions to adhere with the imposed regulations. Furthermore, the industrial clusters are subject to numerous different factors that influences the behaviour of actors within the cluster. The issue faced is to understand how the transition of an industrial cluster is influenced by exogenous factors and how actors in such an integrated environment should invest, while keeping in mind that both the industrial clusters and the individual actors have to remain profitable and have differing investment behaviour. Current studies fall short in identifying, analysing and understanding how multi-actors in an institutional en- vironment relate to the technical options and the exogenous factors engaging with that system in an industrial setting. Identifying an optimal investment trajectory that such an industrial cluster should follow to adhere with the regulations whilst staying profitable with a multi-actor configuration requires different integrated methods and other tools. This thesis will address that problem through the following main research question: What is the effect of multiple exogenous factors on the optimal investment trajectories of indus- trial clusters in the Netherlands with multiple investment options? This question has been answered through exploratory research combined with a modelling approach. The first step in the exploratory research required attaining insights in what the current state of is multi-actor invest- ments. This in combination with looking at how they are structured contractually has been the main foundation for the literature review. A case study analysis has been conducted of an industrial cluster located in Geleen, called Chemelot. This allowed for analysing decarbonizing investment options and looking at what exogenous factors influence the industrial cluster. The investment options attempt to move Chemelot away from fossil-fuels as energy source and move towards lower emitting sources such as electricity. The information gathered served as an input to put together a methodology which captured the exogenous factors, interactions in the industrial cluster and the sustainable investment options in an optimization model. Using this, the optimization model was constructed using Linny-R, a Mixed Integer Linear Programming op- timization software developed by Dr. P.W.G. Bots. The model produced quantifiable results as well as serve as a proof of concept for the methodology that is presented to incorporate exogenous factors and sustainable investment options in the energy transition. The model also gives insights in what effect the exogenous factors have on the investment behaviour of actors within industrial clusters by showing cash flows, both individually and collectively and through an investment curve for the cluster. The economic performance is considered to be the leading metric in this research. Finally, using the results, the implications of implementing exogenous factors and sustainable investment options in an optimization model are discussed. The research outcomes show that CCS and electrification are favourable investments for Chemelot to remain profitable and cope with increasing prices of commodities and CO2. The model results has provided insights in the effect that exogenous factors have on the energy transition of an industrial cluster. More specifically, it showed that a cap on CO2 and increasing the price of CO2 emitted really accelerates the rate at which actors make investments in sustainable options. Added to that, increasing the price of other commodities such as natural gas and naphtha also forces actors to move away from those commodities and look for alternatives that provide the same product or energy without having to compensate the CO2 emissions related to them. Other factors such as limited infrastructure restrict industrial clusters in the amount of products they can produce and restrict them from innovating towards less emitting processes. Electrification of certain processes is possible, but increases the electricity demand with enormous amounts. With limited electricity infrastructure to provide those amounts, the innovation cannot be realized and therefore, halting the transition for an industrial cluster. The findings suggest that because of these exogenous factors, the actors will move towards electricity demanding innovations that do not make use of fossil-fuels and invest in CCS options. However, the methodology presented should be used as directing future research in looking at how industrial clusters should engage in the energy transition. The dependencies existing between actors in an industrial clusters and how different investments II may adjust these dependencies are identifiable using the methodology presented in this research. Ending with a general conclusion, the investment behaviour of industrial cluster changes because of multiple exogenous factors that influence the system. The increase in commodity prices combined with CO2 capping reg- ulations cause actors to invest more quickly into sustainable investment options to adhere with the regulations, but it also causes them to compromise their production levels in some scenarios to remain profitable. Actors downstream are dependent on the investments made by actors upstream since they rely on the output of those upstream actors to develop the final products that they sale. This combination generates valuable insights from a systems perspective but also from a multi-actor perspective.

Offshore Wind Farms (OWFs) have developed into an integral part of the European energy transition in the fight against climate change. The North Sea, with its excellent wind conditions and soil characteristics, as well as ports and industrial energy consumers nearby, has become the epicenter of offshore wind development. The coming years will mark the start of commercial OWFs reaching their end-of-life. As a result, OWF owners must consider decommissioning, which includes all measures performed to return an OWF site, close to its original state, as is reasonably practicable. This socially and academically relevant subject is studied in this thesis, which offers a multi-disciplinary view on the impact of partial and complete decommissioning. It uses an established scientific theory for social acceptance for renewable energy innovations and critically assesses its applicability. Ultimately, this thesis makes recommendations for the promotion of social acceptance for decommissioning OWFs.

The world needs to decarbonize, and that includes the transport sector, which accounts for almost a quarter of the GHG emissions. Electrification and hydrogen-powered transport are increasing significantly. But, a new category of hydrogen-based fuels (synthetic fuels) could be part of the solution as well. Synthetic fuels are fuels that are made from CO2 and low-carbon hydrogen. Their use would reduce GHG emissions and mitigate the negative effects we have on climate change. Also, they are compatible with existing infrastructure, which increases the possibility of becoming part of the energy mix in the short term. Despite the increasing attention, there is a lack of literature that combines qualitative research with quantitative insights and a lack of research on the macro-environment of the synthetic fuel system.

This study aims to provide an extensive overview of the critical internal and external uncertainties that influence the synthetic fuel supply chain. Additionally, the study wants to look at the impact of the identified factors by using scenarios to model future developments. Scholars are highlighting the potential of synthetic fuels, and the International Energy Agency expects them to play a role in the future energy mix. However, high costs and regulatory uncertainty might prove to be significant barriers to their development. The synthetic fuel system is complex, and their are a lot of factors with that impact each other and a lot of uncertainty in terms of how key factors will develop in the future. The research question focuses on the potential of synthetic fuels in the future. This research uses an integrated approach to look at the system, as the important factors are highly dependent of each other.

A PESTEL-analysis was done to highlight the different categories of factors influencing the synthetic fuel supply chain. The Political, Economic, Social, Technological, Environmental and Legal factors together form the driving forces and uncertainties surrounding synthetic fuels. After an extensive literature study to create thorough understanding of the synthetic fuel system, relevant literature was reviewed and discussed to identify the most important factors and uncertainties. These factors are elaborately discussed and then summarized and categorized. The factors with high impact were done reviewed and discussed further with quantitative experiments. The critical uncertainties were quantified by analyzing scenarios in a Mixed-Integer Linear Programming (MILP) model using the program Linny-R. The mix of qualitative and quantitative research makes it possible to understand the synthetic fuel system better. Using Linny-R, the system was modelled in a simplified way by linking the relevant feedstocks, processes and products. The advantage of Linny-R is that it is very suited for looking at integrated systems. The identified factors have a lot of interdependencies and that makes it interesting to look at the impact of uncertainties on multiple factors at the same time.

The results showed the major impact the energy price and the electrolyzer Capex have on the hydrogen and subsequent synthetic fuel prices, as they are at least twice as expensive as fossil fuels on the short term. The high current prices for renewable energy weigh heavily on the hydrogen costs, which in turn has a major impact on the costs for synthetic fuels. The results also show the importance of renewable energy availability, as the average price increases significantly due to the intermittency of renewable energy sources. This intermittency leads to lower capacity factors for the electrolyzer, which increases the electrolysis costs per tonne hydrogen. These two factors are the main cost drivers of hydrogen and finding the right balance between the capacity factor and cheap energy is key for reaching an optimal synthetic fuel price. Technological developments and efficiency gains will decrease the price significantly in the future. However, it will definitely remain challenging to become competitive in the short term. In the longer term, there is potential if adequate regulatory support is provided and hydrogen prices continue to decrease due to innovation and scalability. Hydrogen production, and even more so, synthetic fuel production in countries with favourable conditions for renewable energy could lead to lower prices than local production. A potential disadvantage is more competition and geopolitical tensions making the supply chain riskier, requiring a higher rate of return. Because the model also incorporated the fossil fuel production and the carbon emissions, the impact of policy could also be taken into account. While the results show that the impact of policy measures like carbon pricing is definitely lower than the impact of significant hydrogen cost reductions, it is clear that this policy does make synthetic fuel production more attractive. The integrated approach of the system shows that multiple developments are needed for the ambition of cost-parity for synthetic and fossil fuels. While this cost-parity may never be reached, under the right circumstances the synthetic fuel price can become very close. Additional policy measures like blend-in quota and higher subsidies could further increase the demand.

The results highlight the challenges but also the potential of synthetic fuels. In order to make them part of the inevitable transition to sustainable alternatives for the transport sector, governments, policymakers, international organisations and customers need to align their efforts to collectively (partly) shift towards synthetic fuels. This is a big opportunity to reduce GHG emissions and reach the climate targets from the Paris Agreement.

Building Information Modelling (BIM) has significantly improved the efficiency of construction projects. Using BIM tools provides various opportunities for cost management professionals to improve their cost management services' quality, speed, accuracy, value, and sophistication. Despite these benefits, BIM implementation for infrastructure projects can be quite challenging as these projects are highly complex. Very few organisations (who deal with infrastructure) have implemented BIM higher than BIM 4D in their projects. Therefore, this study investigates the challenges organisations face while implementing BIM 5D for infrastructure projects and identifies ways to minimise these challenges and enhance the BIM 5D process. The research methodology for this research is based on a literature study and interviews conducted with experts from Arcadis. This thesis first explores the challenges faced by organisations while implementing BIM 5D for infrastructure projects. In addition, this thesis also looks into the steps the building sector took to enhance the BIM 5D implementation and how these steps can be fine-tuned to suit the infrastructure projects. Based on these two points, recommendations are created for organisations dealing with infrastructure projects to BIM 5D, depending on their role in the project. The results show that the project managers should be targeted first to promote the use of BIM 5D. The expertise of BIM front runners should be utilised in projects, and a standard BIM Execution Plan should be prepared and followed by involving both designers and cost managers. The BIM 5D processes also need to be tailored to suit the needs of specific (larger) clients.

Because of the expected growing implementation of large scale water electrolysis, an apparent opportunity arises to implement systems in which the by-product oxygen is harnessed by using it as a raw material in another process. This is also known as an oxygen synergy, an example of industrial symbiosis.
A procedure to design and evaluate the performance of this kind of systems was devised by following guidelines of chemical process design and systems thinking. The method starts by defining the system’s spatial and temporal boundaries as well as a design goal. Then, it is further described by determining the systems’ elements, inputs and outputs, as well as its operation mode. All this information comprises the initial design space and, is organized in
a graphical representation also known as a superstructure of options.
Taking into account the socioeconomic environment of the energy transition in the Netherlands between 2020 and 2030, this methodology was used to design an industrial cluster with two oxygen producers and four oxygen users. This consist of an Air Separation unit (ASU), a Polymer Electrolyte Membrane (PEM) electrolyzer, an Auto-Thermal Reformer (ATR), an Oxy-fuel combustion power plant (OXFC), as well as two gasification processes: one for H2 production (referred to as B-to-H2), and the other for methanol synthesis (referred as
B-to-MeOH). Additionally, the option of importing or exporting O2 to another location is added. Then, this initial set of options is translated into a Multi Integer Linear Programming (MILP) problem with the help of Linny-R, a graphical specification language to solve optimization problems. The MILP includes both capital and operational costs (also referred to as CAPEX and OPEX), and aims to select a configuration that yields the highest benefits.
Furthermore, three different scenarios were devised to evaluate different techno-economic conditions. The scenario PEM 2020 includes current CAPEX and OPEX for the electrolyzer, while PEM 2030 examines the effects of lower costs expected for this technology. Furthermore, the scenario Small ASU, analyses the effects of having a smaller O2 production capacity in
the cluster. Because of the input and output prices selected, the selection the fist scenario just includes the ASU. However, for the PEM 2030, the electrolyzer is also selected, and the final configuration includes both O2 producers. For the final scenario, no process is selected.
Then, when the output prices are varied, the topology selection changes. As when a product reaches a certain price, which is high enough to cover both the capital and operational expenses, the technology is present in the final configuration. These minimum selling prices are compared with reference values found in literature, to validate them. It was determined
that model is able to roughly evaluate the operation and profitability of all the presented options, and thus can be used as a first evaluation method to discard options that are not economically attractive. However, the greatest limitation lies in the concept design phase, because the most optimal solution might not be included in the initial set of options.
This process turned out to also be useful when comparing the effects of operating with and without synergies. For the cases evaluated, the benefits are higher when the main O2 provider is the PEM electrolyzer. In most of the business cases the obtained benefits are two times
higher, than when the ASU is used. Furthermore, because of expected lower electricity prices and capital expenses for electrolysis’s, the business cases with O2 synergies are likely to be more beneficial in the future. As the only economically attractive option for current techno-economic data is a synergy to produce H2 via ATR.
Finally, a relationship between the O2 price and the minimum H2 required price to invest in an electrolyzer was found for techno-economic specifications, one for the year 2020 and one for 2030. At low H2 market prices, the benefit from selling O2 improves the business case for the electrolyzer. This correlations can be useful for further oxygen synergies research, or industrial gas suppliers and electrolyzer suppliers, who want to render appeal to their business cases by finding synergy opportunities. If the devised methodology is further developed it can be used to model the oxygen demand and supply between various clusters, or find other opportunities in which an industrial symbiosis might be economically attractive. Furthermore, the effects of other external effects can be also modeled. For example, the variation in raw material prices or a policy to
reduce CO2 emissions. Though it still needs to be further tested, it has been proven that the superstructure model can be used as a first evaluation method to discard options that are not economically attractive, and to evaluate different configurations with and without operating
under industrial symbiosis.

The Dutch economy is at present largely driven by fossil fuels, including the chemical industry. To achieve the goals set by the Paris Climate Agreement, the industry needs to decarbonise by switching to renewable sources. However, the industry faces many barriers in this climate transition. This research analyses the Dutch chemical site Chemelot, one of the largest sources of greenhouse gas emissions in the Netherlands. Chemelot uses primarily natural gas and naphtha as energy and feedstock resources. Currently, a debate is ongoing on Chemelot whether electricity or hydrogen should be the main focus of replacing fossil fuels and raw materials, as these are the most potential eco­innovation alternatives. These eco­innovations pose a technology battle for dominance. The site users on Chemelot need to make decisions now, which will have consequences for both society and firms in the future. There are multiple types of factors that affect eco­innovation adoption. This study created a new framework that distinguishes Technological factors from Non­technological factors because it is desir­ able to gain early insight in both: Technological factors so that the decision can be based on what benefits best for the future industry and society; Non­technological factors to identify barriers and op­ portunities in time and how to deal with these. The Non­technological factors are distinguished between External and Internal factors, with External factors reflecting the environment in which a firm operates and Internal factors considering firm­specific characteristics. The objective of this study is therefore to identify relevant factors that affect the adoption of eco­innovations with the ultimate goal of decarbon­ ising the Chemelot site. Hence, this research aims at answering the following research question: What drives the technology battle for eco­innovation adoption on Chemelot? This exploratory and descriptive research investigated Chemelot as the main unit of analysis. It is a single and embedded case study design. This research started by reviewing the literature regarding the topics of technology battles, technology dominance, adoption, barriers in the chemical industry, and eco­innovations. Based on the literature review, a framework was made containing factors that affect eco­innovation adoption. Additionally, factors were added to the framework based on conversations with experts. The framework was then validated by interviewing experts and conducting a Best­Worst Method analysis. The Best­Worst Method is a suitable Multi­Criteria Decision­Making tool when eval­ uating multiple factors when objective metrics are lacking. Experts were asked to indicate the factors according to relevance with regard to eco­innovation adoption in the chemical industry. Additionally, the weights indicated by the participants were normalised using the Best­Worst Method to compare the factors. In total, 14 participants participated in the semi­structured interviews with questions to gain deeper knowledge about the technology battle between eco­innovations on Chemelot. The site users on Chemelot have to make decisions for eco­innovations now, which will have con­ sequences for future society and industry. Since the consequences of the eco­innovation choices are influenced by both Technological and Non­technological factors, this research created a new frame­ work of factors affecting eco­innovation adoption. This research found that the sub­factor Regulatory Pressure is the most relevant in the set of Non­technological External factors. In the Non­technological Internal factors, Firm’s Strategy is found to be the most relevant sub­factor, closely followed by Firm’s Management. In the set of Technological factors, the sub­factor Capex is found to be the most relevant factor. The normalised weights of all the factors show that the Non­technological External factors are the most relevant factors for eco­innovation adoption for the Chemelot site. Furthermore, the Techno­ logical factors appear to be equally relevant as Non­technological Internal factors because they hardly rank higher. The results from the conducted interviews show that experts define a successful energy & raw ma­ terial transition when the environmental impact of greenhouse gasses is reduced while simultaneously maintaining employment, innovation, economic welfare, and adding value to society. The barriers the site users face on Chemelot to reduce environmental impact are: cross­sectoral collaboration among actors, sufficient availability of renewable energy and raw materials, lack of effective policy, high degree of integrated plants and processes, differently aligned strategies of the site users compared to Chemelot’s, increasing pressure by lobbies and society, a failing market always that proposes fossil technologies as the cheapest option rather than providing sustainable eco­innovation alternatives mak­ ing investment difficult, and the lacking or insufficient infrastructure. The opportunity Chemelot has are: the high degree of integrated plants because they offer synergies, advanced R&D facilities, the innova­ tion and knowledge centre Brightlands Chemelot Campus, and highly experienced and knowledgeable experts. The technology battle between eco­innovations on Chemelot is twofold. For the heat­generating application, the technology battle is fought between hydrogen and electricity. The direct use of elec­ tricity is much more efficient for this application, because energy losses during the initial conversion of electricity to hydrogen are avoided and because no flue gases are released that contain energy when generating heat from electricity. Nevertheless, hydrogen technology for this application is being pushed by the actors, despite the fact that it is a less favourable alternative. This could have serious consequences for Chemelot since this is a much more expensive alternative. Furthermore, this research concluded that the technology battle for dominance is fought between the incumbent technologies and eco­innovations rather than between hydrogen and electrification. Both electrification and hydrogen are indispensable technologies required in this climate transition but will depend on the application. Moreover, site users continue to maintain their fossil assets while this is expensive and greenhouse gas emissions reduction is limited. They are reluctant to switch to disruptive eco­innovations because of the aforementioned barriers. Continuing the investments, in turn, raises the barrier for the site users to adopt eco­innovations due to the longer payback periods. Delaying the adoption of eco­innovation can be explained by the lack of a positive business case. The business case is reflected by the Technological factors Capex, Opex, and Efficiency, and is in­ dicated as a prerequisite. This affects the intrinsic motivation of the site users, which is reflected by the Non­technological Internal factors. However, site users are motivated by external pressures such as regulations, subsidies, market pressures, and rising emission taxes, which are reflected by Non­ technological External factors.

How well spent is public money concerning sustainability goals? How effective and efficient are these policies? Even though it is widely acknowledged that actions against climate change are urgently needed in the near future, policy makers little insight in how potential policies can be designed most effectively. To evaluate the impacts of sustainability policies on industry, such as carbon taxes and hydrogen subsidies, policies should be included within industrial cluster models. This policy modelling approach leads to effective and efficient use of public finance and time. This research foresees in this demand by applying a module thinking strategy. This allows for the creation of plug-and-play policy modules that can be used in future research to determine the most effective or efficient policy to achieve sustainable industrial clusters. To this end, scope variables are identified that provide buttons to design policies. Future research should focus on validating these scope variables to a further extend and potentially enable generalisation of the policy modules. The authors choice to use linear optimization resulted in only being able to evaluate generation based policies (like feed-in tariffs). Designing also investment based policies (like lump-sum subsidies) requires further attention.

The Port of Rotterdam Authority (PoRA) aims to be CO2 neutral by 2050. To achieve this goal, they have proposed three steps to make an energy transition. The transition focuses on shifting from fossil energy towards renewable energy, like wind energy, hydrogen and geothermal heat. The Port of Rotterdam (PoR) is an important area to make this energy transition in, as it accounts for 20% of the Netherlands’ green house gas emissions...

The Dutch energy-intensive industry relies heavily on fossil-fuelled energy sources for production processes, being responsible for one third of CO2 emissions in the Netherlands. The road to CO2 neutrality by 2050 requires a massive transformation of the industrial sector: sustainable supply and (re-)use of industrial heat, CO2 capture and storage and improved efficiency and circularity are some of the routes that the transition of industry may follow. In the light of the European Green Deal, a rapid mobilization of investments is required in order to reap their benefits before 2050. In this context, new forms of cooperation within energy-intensive industrial clusters have the potential to accelerate the delivery of innovative solutions. Multi-actor and technical dependencies offer synergetic possibilities that make collaborative decision-making of great importance in a situation of profound transformation. The challenge is to understand how to systematically manage and govern such inter-firm collaborations to favour the transition of industrial clusters, while balancing actor profit and cluster welfare. Formal governance mechanisms such as bi- and multilateral contracts play a critical role in this respect, regulating the distribution of costs and benefits of investment projects, while consolidating the exchange of the resulting products to reduce the uncertainty of flows. As a result, the adoption of different forms of contracts needs to be carefully considered when evaluating investment options for decarbonization. Although the transition of the energy-intensive industry has been studied from different angles, current approaches fall short in analysing and understanding the relation between the technical (hardware) level and multi-actor (and institutional) context of an industrial complex. However, integrated methods and tools are needed to identify optimal transition paths, while enabling a dynamic evaluation of investments decisions under diverse multi-actor configurations. This thesis addresses the problem by means of the following main research question: “What are the implications of implementing contractual structures in optimization models to support optimal investment decisions in the decarbonization of industrial clusters?” Answering this question requires an exploratory research design combined with a modelling approach. The initial exploratory steps involve gaining insight in the field of contractual governance using elements of Transaction Costs Economics and Game Theory. A case study analysis of the industrial cluster located in the Port of Rotterdam is conducted alongside the literature study, analysing key investment projects for decarbonization and the underlying contractual network. As part of the hard-to-electrify (and therefore hard-to-abate) sectors, the Rotterdam cluster attempts to transition to a new energy system by switching from fossil fuels to electricity, low-carbon hydrogen and green hydrogen. Thus, a focus on hydrogen as fuel and for power generation is established with respect to investments’ evaluation. As a final step resulting from the exploratory approach, hypotheses on the impact of contracts on the transition of industrial clusters are formulated, together with the experimental setup required for hypotheses’ testing. The information gathered in the exploratory steps serves as input to develop a novel methodology to incorporate contractual structures in optimization models. The output of these research steps is translated into an integrated optimization model of the Rotterdam cluster using Linny-R, a software tool developed by Dr. P.W.G. Bots that applies Mixed Integer Linear Programming (MILP) optimization. Besides the quantification of results of hypothesis testing, the model provides a proof of concept of the developed methodology to include contractual structures in the analysis of investment decisions for the energy transition. In addition, the model provides measurable insights in the effects of contractual structures on the transformation of industrial clusters, specifying the cash flow of the total cluster and its distribution among individual actors as the main metric for the evaluation of the economic performance. Optimal investment curves and resulting CO2 emissions are finally analysed as determinants of the cash flows obtained from the model experiments. As a result, implications of the implementation of contracts in optimization models are observed and discussed. As part of the research outcomes it is found that, without an explicit implementation of contractual agreements, results obtained from MILP may be characterized by a distorted allocation of cash flows, in which sacrifices of some actors in the form of negative cash flows are compensated by higher profits of other cluster’s members. These kind of results are clearly misleading in the identification of an optimal transition path. Thus, the proposed methodology adds value to MILP-based approaches. The model results show that contracts do have an effect on the transition of the industrial sector. In fact, adopting different contractual structures shifts investment decisions overtime, affecting the timescale of investments and the associated CO2 reduction. Bilateral contracts seem to yield the highest benefits for the modelled system, both from an economic and environmental perspective, as contract terms are tailored to the specific needs of the contractual parties. This makes off-takers less constrained than with multilateral contracts, whose advantages can be fully observed in thick markets. Although the findings suggest that there may not be a universal, one-size-fits-all approach in establishing a set of contracts that best supports investment projects under all possible conditions, the proposed methodology is effective in providing direction for the next steps to make decarbonization projects an investable prospect in the energy-intensive industry. More precisely, barriers identified via the implementation of contracts specify areas of need for targeted policy action, addressing the creation of greater economic incentives for the integration of investment options. With specific respect to hydrogen applications, regulated revenue support in combination with policies recognising the higher social value of low-carbon/green hydrogen products may be relevant options to take into consideration. From a managerial perspective, the methodology allows to identify and address dependencies among investment options which may strengthen or jeopardize each other. Relevant examples for hydrogen integration are the need for increased CO2 savings and/or the need to complement green hydrogen with additional measures to capture refinery fuel gases to improve the business case of such projects. Other implications consist in the need to carefully rethink the relationship between producers and off-takers to gradually adapt it to market developments. As a general conclusion, implementing contractual structures in MILP enables a more accurate representation of the behaviour of rational actors, allowing for a dynamic analysis of the system’s behaviour. Not only the incentives arising for each contracting party are taken into account in selecting optimal transition paths, but also synergies and externalities arising from the combination of technical options are optimized. This generates more valuable insights from a multi-actor and system perspective. This research suggests several research avenues that can be pursued. First and foremost, further research should be conducted to provide understanding of possible consequences of combining diverse policy interventions with contractual structures. It is possible that contracts will play a greater role in determining the revenue generation of investment options when more policies that provide specific economic incentives for decarbonization are introduced. Moreover, besides incorporating a higher level of detail and improving input data, adjustments to the proposed model could be performed to simulate a shift in contractual structures that follows the (hydrogen) market developments. Moreover, additional model expansions could allow to examine the consequences of blue and green hydrogen integration on the incumbent grey hydrogen suppliers. Finally, building upon the results of this research, the performed study could be replicated for clusters in different locations. A cross-case analysis would then reveal whether location significantly influences the identification of optimal contractual structures to support the energy transition.

The energy transition requires significant investments in new power generation, storage, and transmission technology to achieve emission reduction targets while ensuring a stable supply of electricity. However, the increasingly complex, uncertain nature of the power system creates challenges for investors and requires advanced research and modeling. An exploratory analysis is preformed to determine if and how energy system optimization modeling can be used to explore the long-term economic feasibility of investments in the power sector in light of the energy transition. A modeling framework is developed utilizing energy system optimization modeling paired with the uncertainty analysis, modeling to generate alternatives, to explore and provide insights into the profitability of investments in the range of possible near-optimal power system configurations that meet government emission reduction targets. We apply the modeling framework in a case study of the Dutch power system, focusing on investments in the 2030 time frame. The case study is used as a proof of concept of the developed methodological. The case study finds that the developed modeling framework can provide insight into the range of near-optimal power system configurations that meet emission reduction targets and, through an economic analysis, can shed light on the economic feasibility of different technologies. In the particular case of the Netherlands, the case study finds a wide range of possible future near-optimal energy systems exist to meet emission reduction targets, but a lack of profitability of investments indicate policy mechanisms or alternative market arrangements are needed to ensure economic incentives exist for the necessary investments. Further research should include a parametric uncertainty analysis to provide a complete and comprehensive overview, including all types of uncertainty in the system and to identify the affects different types of uncertainty have on the profitability of investments.

By signing the Paris Climate Agreement, The Netherlands has committed itself to curtail its CO2- emissions in order to keep global warming well below 2°C above pre-industrial levels. Pivotal to achieve these targets is the phase-out of CO2-intensive electricity generation technologies and investments in renewables. Current investments aiming to decarbonise the electricity system are predominantly allocated to solar PV and off- and onshore wind energy. However, this trajectory might change as the development of Dynamic Tidal power (DTP) might soon enable The Netherlands to harvest the North Sea’s currently unutilised tidal currents to generate clean electricity. DTP uses a 30-70 kilometre long dam perpendicular to the coast to capture the North Sea’s tidal currents. The alternating currents that proceed parallel to the coast create a hydraulic head over the dam, which turbines in the dam convert into electricity. However, the variable availability of solar irradiation, wind, and tidal currents makes it increasingly complex and costly to match electricity supply and demand as their shares in the electricity mix increase. To ensure electricity security, freely dispatchable energy generators (e.g. natural gas, biomass or coal turbines) are deployed to cover the electricity load that could not be met by the variable renewable energy (VRE) generators. However, due to the fuel used to generate electricity, dispatchable energy sources tend to emit CO2 and bear higher marginal energy generation costs than VRES. To address this problem, the portfolio shares of solar PV, offshore wind, onshore wind and DTP that minimise the need for dispatchable backup capacity and the energy generation costs were computed in this study. Due to its novelty, special attention was paid to the effect of DTP on a VRE system’s ability to efficiently match supply and demand. In order to achieve these objectives, a novel application of the Modern Portfolio Theory (MPT) was used. The MPT originates from the stock market but is often used to comprise VRE portfolios that maximise the electricity output. However, as the aim was to minimise the residual load, demand-variability was introduced into the MPT. Existing literature had not covered this topic. Hence, by assessing to what extent including demand-variability in the MPT affects the selection of efficient VRE portfolios, this study filled a gap in the literature and serves as a starting point for future research into the application of the MPT. In total, three different electricity demand scenarios were optimised; the contemporary load profile (1), increased peak loads due to an extreme penetration of electric vehicles (EV) and electric heat pumps (HP) (2), and a flat load profile due to an extreme penetration of demand-responsive measures (3). The most efficient portfolio shares for each demand scenario were found by computing how 35GW should be distributed among solar PV, offshore wind, onshore wind and DTP in order to minimise the need for backup capacity and energy generation costs. The results of this study indicate that regardless of the demand profile, The Netherlands’ VRE system would be most cost-efficient in meeting demand when comprised of approximately 75% DTP and 25% offshore wind. However, only under the condition that the DTP-dams are geographically dispersed. Geographically dispersed DTP-dams, for example, located in Zeeland (south of The Netherlands) and off the coast of Texel (north of The Netherlands), cancels out the volatility in the electricity output caused by high and low tide. This reduces a VRE system’s volatility in electricity output and stabilises the electricity output from the dispatchable backup system, which minimises the system’s electricity generation costs. However, in terms of the amount of backup capacity required, it was found that a system comprised entirely of DTP with an integrated battery storage system would be even more efficient. The battery storage system eliminates all variability in the electricity output from DTP, which minimises the need for dispatchable backup capacity. However, as battery storage costs are significant (approx. 100,000 €/MWh), it is unlikely that a DTP-dam with a storage system large enough to flatten its electricity output is economically viable under the current market circumstances. This might change when DTP is combined with other storage systems or if battery storage costs reduce due to learning-effect, economies of scale or technical innovations. As DTP is still in its initial development phase, it is not certain DTP will successfully penetrate the power generation market. If DTP fails to enter the market, the current VRE system (61% solar PV, 8% offshore wind and 31% onshore wind) is fairly cost-efficient. However, if the aim is to reduce the amount of dispatchable backup capacity required to ensure energy security, future investments should be allocated to offshore wind. The overarching conclusion is that there is no unequivocal VRE portfolio that is most efficient to meet demand as it depends on the perspective taken (required backup capacity versus electricity generation costs). However, this study shows that the current VRE system benefits from the inclusion of DTP, both in terms of the required amount of backup capacity and the system’s energy generation costs. Only if DTP is combined with a large battery storage system to flatten its electricity output do the system’s energy generation costs surpass the costs of the current VRE system. In regards to the effect of including demand-variability in the MPT, it was found that demand variability has a limited effect on the selection of efficient VRE portfolio shares. Only in a scenario (2) with increased peak loads did the share of offshore wind slightly increase. This is due to the fact that the peaks in electricity supply from offshore wind coincide with the peaks in demand from electric HP (winter).

Hydrogen is widely considered an essential energy carrier that has the potential to accelerate the energy transition. The Netherlands does not have the resources to fulfil the expected hydrogen demand by domestically produced hydrogen. By realising hydrogen import terminals, the Port of Rotterdam can maintain its dominating position as the (renewable) energy port in North-West Europe. This study, in which the Port of Rotterdam is used as a case study, focuses on the uncertainties hampering the realisation of hydrogen import terminals. While earlier studies have been conducted on hydrogen import, we identify two research gaps: 1) the necessity to optimise the scaling of hydrogen import terminals and 2) the inclusion of hydrogen use in multiple sectors. Through a literature review, three categories of uncertainty have been identified that are often present in hydrogen systems; economic, technical, and geopolitical uncertainties. The categories of uncertainty have been used as a guideline to identify uncertainty present in assessing the integrated hydrogen system in the Port of Rotterdam. A model that represents this system has been developed in Linny-R. Linny-R is a graphical specification language to solve Mixed-Integer Linear Programming problems. This model allowed us to adjust input parameters such as production capacities and prices, hydrogen demand, and infrastructural changes to study the identified uncertainties through sensitivity analyses and scenarios. The results of this research illustrate the need for hydrogen import to meet the projected hydrogen demand. However, hydrogen import is not cost-competitive compared to domestically produced hydrogen. This study highlights the potential to reduce costs in the production, conversion to the carrier, and shipping stage of the supply chain. Currently, Ammonia (NH3) is the cheapest hydrogen carrier followed by Liquid Organic Hydrogen Carrier (LOHC), and Liquid hydrogen (LH2). Long-term contracts are required to manage the hydrogen import transactions to resolve economic uncertainty. Technical uncertainty relates to the scaling of hydrogen import terminals and the end-user sectors’ preferences for a specific hydrogen carrier. Based on the technical characteristics of the three hydrogen carriers, LH2 shows the highest potential to supply all end-user sectors. However, LOHC and NH3 also have advantages in specific areas. Moreover, the early stage of development in LH2-technology fuels the need for LOHC and NH3, leaving the debate on which hydrogen carrier is preferred open. Furthermore, the scaling of hydrogen import terminals is complicated by the presence of salt-caverns in the northern part of The Netherlands because they provide a cheap alternative for large-scale hydrogen storage. Geopolitical uncertainties related to the hydrogen import supply chain processes are highly dependent on the production capabilities in the export countries and the distance of those countries to the Port of Rotterdam. Additionally, other nearby located ports can also realise import terminals, attracting hydrogen import, diminishing the potential dominant position of the Port of Rotterdam. However, a first-mover position could manifest the Port of Rotterdam as a dominant player in the global hydrogen market. More generally, hydrogen import terminals could provide security against geopolitical forces as it safeguards the diversity of the Dutch energy mix. We identified several avenues for future research. First, researchers interested in expanding the model’s functionalities could focus on 1) modelling a variable renewable electricity price, 2) including salt-caverns and specific hydrogen export, 3) adjusting our model by allowing only filled vessels to arrive, 4) including the Willingness To Pay (WTP) of various end-user sectors, 5) applying a method that allows the investigation of numerous possible futures. A more general recommendation is to add a new model to analyse investments and support companies’ business cases by integrating hydrogen end-user sectors’ WTP. Finally, we especially encourage policymakers to explore and support the possibility to realise one or more hydrogen import terminals, even in case of a lacking business case, to improve the strategic position of the Port of Rotterdam with regards to economic and geopolitical advantages.

In this thesis the potential of demand response among households in The Netherlands is studied. The methodology is based on the conceptual design of an Agent-Based Model for the adoption of domestic demand response by households. From this model the subsequent flexibility in the electricity system will be brought forward.

A review of the current literature has made apparent that the total potential of the flexibility in households is not clear. Previous research has studied the potential in some appliances to perform demand response actions and this has led to some insight in appliance performance as flexibility providers. Moreover, top-down system studies have looked at households consumption and have derived flexibility potential through this method. However, a bottom-up analysis of household potential for demand response has not been performed; let alone for the Dutch electricity system.

Moreover, the willingness of households to adopt domestic demand response has not been researched. This is an important factor in determining the total flexibility that can become available to the system.

The analysis provided some key findings. Firstly, there are at least 7 types of highly prevalent appliances in Dutch households that are suitable for providing flexibility to the grid. High consumption and continuously operating appliances offer the greatest potential in terms of all-time flexibility, but other appliances can still be very useful for peak mitigation. Especially with the low investment costs for "unlocking" the flexibility in these devices over time, a large set of appliances can provide useful flexibility.

Moreover, household analysis showed that most clusters of households already have high importance for energy efficient behaviour and the spread of the number of appliances in households is low.

Finally, the policy analysis provided insight in the types of policy measures that can be encountered in the future. Regulatory change that will make it easier for aggregators and utilities to provide ancillary services with aggregated loads will benefit the system, but are difficult to incorporate in the conceptual design of the model. Providing more insight for consumers into their own consumption and capacity subscriptions are other measures that could motivate households in one way or another to perform domestic demand response. Moreover, some form of mandatory offerings of 'smart' appliances could make sure households have demand response ready appliances in their homes.

By reviewing the technology, policy and consumer behavior, the research has analysed the state of development of domestic demand response. The Diffusion of Innovations theory together with the archetype identification shows which archetypes are more likely to adopt and which archetypes are more likely to be considered opinion leaders.
The influence of different policy measures is seen both in households themselves and their willingness to adopt as with the technologies that will enable providing flexibility.

This research investigates the diffusion of Shore Power in ports. Shipping Companies and ports are dependend on the strategies of each other. Using Game Theory and Agent Based Modelling, the network and parties are simulated.

Acknowledged by the United Nations as part of their sustainable development goals, reduction of greenhouse gas emissions is paramount in preserving our planet for future generations. Electrication in the industrial sector is considered one of the energy transition pathways that can contribute to meeting the emission reduction targets of the Paris Agreement. An important barrier that needs to be overcome in order to fully adopt its potential is uncertainty and its risk to the implementation of different electrication alternatives. The absence of information that illustrates the effect of uncertainty on the performance of these alternatives decreases the stability of business cases and hinders the decision-making process. To filll a part of this knowledge gap, this research performed a case-study revolving around a mixed integer linear programming (MILP) model of an integrated chemical cluster in the Port of Rotterdam. The effect of the uncertain factors on the KPIs was analyzed using an exploratory modelling and analysis (EMA) approach. In addition, a key opportunity of the MILP model was utilized by changing the objective function to look at individual and collective actor optimization perspectives. This research implicates that EMA can be an effective approach to explore the effect of various uncertain factor on industrial systems undergoing electrication. Furthermore, when the goal is to perform a broad uncertainty analysis that allows for easy implementation of actor optimization perspectives while requiring only limited information about the uncertain factors in the form of sampling bandwidths, the combination of EMA and MILP can be a powerful tool.