Europe’sambition to become the world’s first climate-neutral continent by 2050 presentsseveral challenges in the domain of variable renewable energy generation andthe development of sustainable energy carriers. In support of this mission, theNorth Sea is identified as a promising energy source, to be efficientlyharnessed through the deployment of system-integrated offshore energy hubs combining wind farms withoffshore electrolysis. The discussion around hydrogen’s role as a renewablefuel in a high variable renewable energy energy system and its contribution tostable, systemic decarbonisation is acknowledged and relevant literatureexamined.

TenneT,alongside other European TSOs, has proposed certain hub layouts as a part ofseveral studies and reports looking into the various aspects of ofshore enegryhubs. However, limited information exists on the financial attractiveness ofthese conceptual hubs for investors and developers. This study aims todetermine the optimal configuration of such energy hubs from the standpoint of economic viability.

A modularmathematical model is developed to represent offshore energy hubs, enabling thetesting of multiple configurations across various energy scenarios. Parameterssuch as electrolysis capacity, interconnection capacity, and ownershipstructures are varied, generating a range of configurations evaluated underdifferent price profiles for electricity and hydrogen. The model is applied to a case study based on the2x2 GW offshore hub configuration, aligned with the North Sea Wind Power Hubprogramme. Results point to a weak business case for electrolysers under thedatasets used. However, configurations featuring smaller electrolysers co-ownedwith relatively larger wind farms exhibit lower investment costs and greatereconomic benefit compared to those with larger electrolysers and smaller windfarms.

The thesisextends the analysis to consider implications for policy, tendering procedures,and broader socioeconomic dynamics. Strategies such as phased build-out andpublic ownership of power-to-gas infrastructure are explored as potentialenablers of hydrogen integration into offshore wind systems. Finally, concernsabout energy security, heightened by recent disruptions in global supplychains, particularly in the energy sector, are discussed. This shifts the focusbeyond pure economic considerations, toward the strategic value ofsystem-integrated offshore hubs and their supporting infrastructure.

The increasingly integrated renewable energy sources have a strong intermittency in electricity supply, resulting in increasing mismatches between electricity supply and demand. This has led to an increase in imbalances in the electricity grid, heightening the need for regulating power, such as flexible assets. Currently, the balancing markets are experiencing a high volatility in system imbalance and imbalance prices, resulting in market and system instability.

Previous studies have largely focused on how renewable energy sources lead to an increase in system imbalance and have stressed the need for flexible assets. Furthermore, several studies show that flexible assets can make significant profits in today's balancing markets by optimising their implicit balancing strategy. However, little attention has been devoted to the price incentives provided by the different pricing designs in the EU and how their remuneration structure affects the implicit balancing behaviour of flexible assets. As flexible assets are increasingly deployed on the balancing market, any strategic or gaming behaviour might have a significant negative impact on grid stability and system costs. Therefore, this research aims to answer the following research question:

What implicit balancing behaviour do flexible assets show in different imbalance settlement designs and what balancing market design recommendations can be provided based on this?

This research question is explored using mainly a quantitative approach. First, a literature review on European balancing markets is provided, explaining how the EU Balancing Guideline forms a framework for the balancing markets in EU. Furthermore, the balancing markets in the Netherlands and Belgium, which serve as case studies in the modelling, are explored in detail. Then, two linear optimisation models are developed to simulate the balancing markets of both countries and to show how the price incentives provided by the markets influence the behaviour of a flexible asset that aims to optimise its profit. Additionally, the impact of the asset's implicit balancing, following three different strategies, on imbalance prices and the asset's own profit is examined. A comparison is made between the results under the two different pricing designs, showing how different design choices affect the opportunities for strategic behaviour and potential market exploitation. The main insights obtained can be summarised as follows:

- A flexible asset can, under certain circumstances, exploit the market with gaming behaviour, in which it intentionally amplifies the imbalance price and thereby enlarges its own profit.
- Marginal pricing, provides a larger opportunity window for strategic and gaming behaviour compared to the averaging of marginal prices. Establishing the imbalance price based on the average of all marginal prices during an ISP can mitigate the asset's effect on the imbalance price, but can eventually not prevent extreme imbalance prices either.
- There are advantages and disadvantages to both single and dual pricing. Single pricing provides a more stable pricing system, but is limited in discouraging overreactive implicit balancing. The dual pricing design discourages overreactive balancing stronger, but this can lead to great losses for BRPs, increasing their financial risks, and can decrease market stability.
- The volume of the system imbalance plays an important role; in ISP with lower system imbalances, flexible assets can only increase the imbalance price to a very limited extend, before a market saturation point is reached where all system imbalance is balanced implicitly. With higher system imbalances, flexible assets can push the imbalance price to much higher, or even extreme values.

As balancing markets evolve with increasing volatility in system imbalances and higher volumes of flexible assets, transaction costs are expected to rise due to higher levels of market participation, growing complexity in forecasting, and potential market saturation effects in quarter-hours with lower system imbalances. These expectations for future conditions emphasise the need for pricing designs that ensure grid stability and market efficiency. Therefore, this research provides several recommendations:


- TSOs should consider re-evaluating the overall pricing design for FRR and imbalance. These two pricing designs are highly interconnected, as imbalance prices should reflect the costs made for FRR. Marginal pricing has both advantages and disadvantages, as it can reduce strategic bidding for FRR, but can reward gaming behaviour in implicit balancing, leading to market instability. A different pricing design might provide a more stable market, where strategic implicit balancing is discouraged.
- The choice between single and dual pricing needs to be carefully considered. Based on this research's findings, single pricing leads to less risks for BRPs and contributes to market stability. However, additional research into the decision-making process of flexible assets under the risks present in both pricing designs is needed to be able to make a stronger recommendation.
- Adjusting other market design variables could help reduce volatility, such as loosening FRR qualification requirements to encourage flexible assets to provide FRR instead of implicit balancing and reducing the ISP to five minutes. Yet, further research is needed to assess the full implications of adjusting these design choices.

The findings presented by this research contribute to current efforts to improve balancing market designs, by showing that both pricing designs have vulnerabilities that allow flexible assets to exploit the market under certain circumstances, which is inconsistent with the objectives of the balancing market. The discussed design choices and future research recommendations contribute to improving balancing markets, to regain grid stability and market efficiency.

However, there are some limitations to consider. The model contains significant simplifications, such as the aggregation of multiple flexible assets into a single asset, which does not fully capture the decision-making process of multiple individual actors with a flexible asset in the real world. Additionally, the assumption that the flexible asset has perfect information and foresight does not correspond to reality. Furthermore, the heuristic optimisation method used may not always produce the optimal strategy for the flexible asset. Based on these limitations, several suggestions for future research are made. For example, using a bi-level optimisation method might provide more refined results of the asset's strategic behaviour. Future research could also consider the wider context of the market, such as how imbalance pricing influences the decision-making processes of numerous BRPs acting simultaneously, without perfect or with limited market information. An analysis from a game-theoretic point of view, showing the interactions among various actors, might lead to more refined or different outcomes when the different pricing designs are compared.

This study investigates the impact of spatial constraints and economic land-use considerations on the optimal placement of large-scale Battery Energy Storage Systems (BESS) within the Dutch high-voltage (HV) grid. In the rapid transformation of the Dutch electricity system—characterized by an increasing penetration of variable renewable energy sources (vRES) and a rising need for grid flexibility—BESS have emerged as a pivotal technology for congestion management, renewable integration, and frequency regulation. However, the absence of a systematic strategy for BESS siting creates inefficiencies in grid planning, escalates system costs, and introduces uncertainty for both market participants and the Transmission System Operator (TSO), TenneT.

To address this gap, the research poses the primary question: “What is the impact of spatial constraints and economic land-use considerations on the optimal placement of large-scale BESS from the perspective of the TSO in the Dutch HV grid?” This is further subdivided into three sub-questions: (1) identifying the key considerations in the BESS development and placement process as derived from academic literature and expert interviews; (2) assessing how restrictions related to competing land uses and exclusion zones affect optimal BESS placement; and (3) evaluating the influence of incorporating land costs on BESS siting outcomes.

The study employs a mixed-methods approach, integrating a comprehensive literature review, expert interviews with TenneT representatives and market participants, and an optimization model implemented in PyPSA-Eur. The model simulates BESS deployment scenarios under two temporal snapshots—2023, reflecting current grid conditions, and 2040, a future state with high electrification and stringent decarbonization targets. Three scenarios are analyzed: a BASE scenario with minimal spatial restrictions, a COL scenario that factors in regional land costs, and an EXCL scenario that enforces strict spatial exclusion zones.

Results from the 2023 analysis indicate that enforcing exclusion zones leads to a 43% reduction in deployable BESS capacity, with land costs exerting a relatively minor impact. In contrast, the 2040 simulations reveal a heightened dependency on BESS for grid stability, where the EXCL scenario still reduces capacity by 19%. Notably, certain nodes that initially received minimal BESS allocation under strict spatial constraints later demonstrate a significant increase in capacity, underscoring an intrinsic system requirement for storage despite suboptimal placement conditions.

Further findings highlight the grid’s adaptive responses, including the expansion of cross-country high-voltage direct current (HVDC) connections, particularly between the Netherlands and Great Britain, and stable average line loading and peak frequency metrics. These outcomes suggest that while spatial constraints influence the localization of BESS, the overall grid performance can be maintained through alternative measures such as transmission expansion and flexible generation.

The study concludes with policy recommendations advocating for a national BESS deployment roadmap, streamlined permitting processes, and differentiated grid connection fees to prioritize locations that maximize system benefits. This research bridges the gap between energy infrastructure planning and land-use policy, offering actionable insights for TSOs, BESS developers, and policymakers to foster a resilient, cost-effective, and spatially integrated energy system.

Green hydrogen production through electrolysis is increasingly recognized as a critical pathway for decarbonizing the energy sector. However, the integration of electrolyzers with renewable energy systems presents several technical and economic challenges. Renewable energy sources such as wind and solar are inherently variable, leading to fluctuating power inputs that impose dynamic operating conditions on electrolyzers. These fluctuations result in degradation mechanisms, such as start-stop cycles, partial load operation, and power ramping, which reduce efficiency and impact long-term performance and economic viability. While technical challenges related to degradation have been investigated in prior research, the role of hydrogen support mechanisms, such as price premiums, in addressing these challenges remains underexplored.

This thesis extends an existing optimization framework to incorporate degradation effects into the modeling of electrolyzer performance. Degradation is represented asdynamicreductions in efficiency that evolve based on operational conditions, including cycling and variable load profiles. A rolling horizon approach is employed to simulate the cumulative impact of degradation over time, enabling the study of electrolyzer operations under realistic renewable energy inputs. The model evaluates two distinct scenarios: one in which electrolyzers operate without external policy intervention, and another where hydrogen support mechanisms are integrated into the framework. This separation allows for an examination of how these factors independently influence electrolyzer scheduling, efficiency, and the economic viability of green hydrogen production.

The findings indicate that degradation significantly influences electrolyzer performance under variable renewable energy conditions, with dynamic operating profiles leading to efficiency losses over time. The inclusion of hydrogen support mechanisms in the analysis highlights their potential to improve economic feasibility by partially mitigating the financial challenges posed by variability. However, the results are contingent on model assumptions and emphasize the importance of considering operational and market-specific factors when assessing the impact of such mechanisms.

By addressing both technical and economic aspects, this thesis contributes to the understanding of howelectrolyzers performunder variable power inputs and howpolicy mechanisms might influence their operation. The results provide a foundation for further research into optimizing electrolyzer performance and integrating green hydrogen into renewable energy systems.

The Dutch electricity grid is facing significant pressure due to increased intermittent renewable energy generation, advancements in electrification and the rise of major electricity users. Transmission capacity has already reached its limit in several regions in the Netherlands. This leads to network congestion, which delays sustainable development in the energy sector and creates an unnecessary rise of electricity prices. Congestion problems exist in multiple EU countries. ACER has proposed the split of several electricity bidding zones in the EU as a solution to mitigate grid congestion. One of these proposed splits is the separation of the electricity bidding zone of the Netherlands into two bidding zones: a northern and a southern bidding zone. This split will separate the northern provinces of Friesland, Groningen, Drenthe and Overijssel from the other provinces in the Netherlands. Splitting large bidding zones into smaller zones could improve market efficiency by providing more accurate price signals. This will theoretically also lead to less congestion in the long term. While research has been conducted on the proposed split of the bidding zone split in Germany, research about a split in the Netherlands and its effects on the Dutch electricity market is lacking. Therefore, this thesis has investigated the following research question: "How will splitting the electricity bidding zone in the Netherlands impact commercial cross-border exchanges and electricity prices in the Day-Ahead market in the Netherlands and its neighboring countries, and what risks does this split cause for energy companies?

To answer this question, a literature review was performed on the bidding zone split of Germany and Austria in 2018, which shows similarities to the proposed Dutch bidding zone split. Furthermore, a model was created with Plexos optimization software to do a nodal analysis of the Netherlands before the split, as well as a scenario analysis of the Netherlands before and after the split. These analyses used a backcast of September 2022 until December 2022. Lastly, the risks for energy companies due to the split were identified. These are the key findings of the research:

1. The neighboring zones next to Germany and Austria suffered from unscheduled flows from Germany. These unscheduled flows form a problem for the Dutch electricity grid as well. The DE-AT split reduced these unscheduled flows but did not achieve all desired effects concerning congestion resolution because of the remaining internal congestion in the German electricity system. The same may be true for the Netherlands and its proposed split.
2. Austria experienced higher electricity prices post-split. Similar consequences are expected of the Netherlands, where the south of the Netherlands will experience higher electricity prices. The north of the Netherlands, which has a relatively low demand and high renewable capacity, will experience reduced prices.
3. The reduction of market liquidity in Austria after the split was only found in long-term contracts, and can be resolved by adapting the terms of these contracts.
4. Nodal prices in the Netherlands in the evaluated period resulted in a distribution of two price groups: high-priced nodes in the west and low-priced nodes in the east of the Netherlands. This difference in nodal prices can be explained by three reasons: the load density in the west, congestion patterns in the high-priced areas, and the geographical positions of fossil power plants.
5. The scenario analysis, which varied inter-zonal commercial transmission capacity between the new Dutch zones and its neighboring zones, found some interesting results. It was observed that an available transmission capacity of 30\% or below creates a significant price difference between the northern and southern NL zone, while above 50\% prices converged. In the scenarios with low available transmission capacity, the northern NL zones reached prices of 0€/MWh. The scenario that is the closest to the predicted after-split situation has price differences between the northern and southern zones. An experiment was executed to investigate the effect of the split on large electricity users, e.g. a large zinc factory with a capacity of 150 MW. In the investigated 4 months, the factory would pay 1.4M€ more for electricity in the southern zone than in the northern zone.
6. Due to the possible price differences in the NL zones, energy companies face risks. It is advised that the current state of their asset portfolio should be assessed based on the location of contracted or owned electricity supply and the location of consumers. By investing in new generation projects in the southern zone, energy generation companies can potentially increase their profits due to the increased electricity prices in the southern zone after the split.

Further research is needed to provide a more exact calculation of the new commercial transmission capacity between the new NL zones and to include the bidding zone split in Germany to capture the full extent of changes in the Dutch bidding zone split. Lastly, a congestion analysis before and after the split can show policymakers and grid operators if congestion has improved and whether a bidding zone split in the Netherlands is worth it.

Hydrogen is emerging as plausible energy carrier to decrease the global dependency on fossil fuels. Hydrogen production based on renewable energy and electrolysis is a technically mature and well-researched production process. Production processes based on large electrolyzers result in varying and relatively high (between €4/kg and up to ± €14/kg) levelized costs of hydrogen - attributable to high electrolyzer and electricity costs. This research evaluates the potential of an off-energy-grid PV and small- capacity electrolyzer based hydrogen production process. The assessed smaller-capacity electrolyzers result in less than a quarter of most electrolyzer costs (€/kW). The cost reduction combined with the avoided electricity costs due to grid connection, allow for market competitive LCOHs within the range of ± €2,15-5/kg hydrogen depending on the hydrogen outflow system chosen for the farm. This research shows that the low electrolyzer and electricity costs of an off-energy-grid PV and small-capacity electrolyzer based hydrogen farm - with running hours limited to the average sun equivalent hours while including a water supply system (source, treatment, distribution across farms, etc.) and a hydrogen outflow system (collection across farm, possible compression) - has technical feasibility and market potential.

Offshore wind energy plays a key role in the renewable energy transition but faces significant obstacles due to increased project costs and complexities associated with supply chain bottlenecks. These challenges are compounded by inadequate tender and contract designs, which fail to effectively address macroeconomic challenges and supply chain constraints. Ensuring proper allocation of benefits, costs, and risks among key stakeholders is essential for mitigating these issues and achieving successful project development. This study employs an institutional analysis followed by a stylized quantitative model to represent the bargaining dynamics between developers and turbine suppliers. The research systematically examines key transactions and interactions among stakeholders—governments, developers, and turbine manufacturers. It evaluates how these entities manage financial risks and benefits and analyzes the adequacy of current tender frameworks in mature offshore wind markets, including the Netherlands, Denmark, Germany, and the United Kingdom. Through this analysis, the study proposes five key recommendations: linking tender roadmaps to decarbonization targets, aligning non-price and price criteria across markets, extending construction timelines and supporting design flexibility, prioritizing advanced-stage projects and balancing incentives, and shifting from financial offers to government equity participation. These recommendations aim to create a more robust framework for offshore wind development. Future research should include comparative analyses of tender mechanisms across various global markets to account for regional differences. Additionally, examining vertical integration within the offshore wind value chain—such as the acquisition of partners or infrastructure development by developers—could offer valuable insights into reducing coordination challenges. Incorporating a broader range of supply chain partners into the research will further enhance understanding of industry dynamics and inform more effective practices.

Currently, restricting the utilisation of fossil fuels and thereby limiting global warming to remain below 2ºC stands as one of the most crucial challenges confronting us. The electricity sector is one of the main contributors of CO2 emissions, but it is changing in a rapid pace with a decarbonizing rate which is faster compared to all other fossil sectors. To facilitate the decarbonizing of the electricity sector, optimisation models can provide a valuable framework to gather information about the futuristics of the electricity market. As optimisation models can handle all sort of characteristics like demand and supply which should always be the same, certain policies, energy security, economic development and costs they play an important role in the transition toward more renewables and less fossil fuels. However, these optimisation models do not always present the right solution as societal factors are mostly missing, which can lead to misleading results.
In this paper we will specifically look at the D-EXPANSE optimisation model from the University of Geneva and incorporate two societal aspects. This will be implemented as a hindcasting exercise to examine whether or not it will improve the model compared to the regular model where no societal factors are implemented. This is applied on 31 European countries from 1990 until 2019. The societal aspects that are included in the D-EXPANSE model are public acceptance and heterogeneity of actors. Public acceptance is incorporated in the optimisation model with specifically limiting the CO2 emissions per country with the help of survey data provided from 2009 until 2023 in combination with the set global European emission targets. Heterogeneity of actors is implemented by specifically adjusting the weighted average cost of capital per technology per country per year.
The main results are that it is still unclear whether or not the implementation of societal factors improves the accuracy of the model as a whole. For the implementation of public acceptance 9 out of the 18 countries experience a positive change regarding the error compared to the model where no societal factors are implemented. For the implementation of heterogeneity of actors 13 out of the 26 countries experienced an improvement, and for the combination of both factors 12 out of the 22 countries showed improvements. With this in mind, it is not justifiable that the implementation of public acceptance and/or heterogeneity of actors in this way improves the model which is shown as a hindcasting exercise.
This thesis fails to provide evidence supporting the idea that the inclusion of societal factors enhances the capabilities of optimisation models. This contradicts existing literature, which emphasizes that the incorporation of societal factors is a primary reason why optimisation models struggle to accurately predict the future. One potential explanation for this discrepancy in our findings may lie in the specific methods used to implement actor heterogeneity and public acceptance in the model. For the public acceptance model, it is shown that there is still room for improvement with a different upper limit for the amount of CO2 emissions per country. This can increase accuracy up to 5 percentage points. Therefore, future research should focus on refining the implementation of societal factors, especially considering the accelerating pace of decarbonisation in the electricity sector. Factors such as supply and demand, electricity costs, and energy security remain crucial features that cannot be underestimated. Moreover, with the increasing integration of renewables into the electricity generation, societal factors will continue to exert a growing influence on the progress and implementation.

Currently, hydrogen consumption is heavily concentrated within larger inflexible industrial applications, where it is produced onsite for further downstream processing. Considering traditional production pathways have a high emission intensity, electrolytic hydrogen production could prove an essential decarbonization pathway for existing, unabated consumers and additional hard-to-abate industrial applications. While legislative frameworks limiting unwanted effects of the electrolytic hydrogen transition are being drafted, it is important to provide policymakers with quantitative data on the effects of this legislature. Other than emissions intensity standards, additionality principles are being considered in a number of these frameworks to further minimize unwanted effects. One of the central principles of additionality is a temporal-correlation requirement, which synchronizes renewable electricity generation with electrolyzer consumption over a predetermined period. The length of this period could significantly affect the intermittency of electrolyzer operations. Although this has been subject to debate, it has seen little attention in literature within the context of industrial applications, which bring substantial additional downstream constraints. It is imperative to understand the effects of these additionality principles quantitatively within the context of their dominant application, heavy industry. This could aid policymakers to arrive at a framework that minimizes the adverse effects of electrolytic hydrogen production while preventing cost increases that hinder widespread adoption.

A mixed-integer linear-programming problem is formulated to model an onsite electrolytic hydrogen production facility for a larger industrial downstream process. The downstream flexibility and temporal correlation constraints in this model are generalized to study their potential antagonistic effects abstractly. The downstream flexibility constraints considered are the minimum partial-load and the period over which production has to match the desired output, mimicking further downstream supply chain constraints. The model employs integrated design and operations optimization, considering the cost-optimal production facility will vary depending on the legislature and downstream process.

The results indicate that temporal correlation requirements affect the production costs of hydrogen as a consequence of limiting the operational flexibility. Additionally, strict temporal correlation requirements exacerbate the escalation of these costs. The availability of a geological storage site reduces the effects of temporal correlation requirements and DSP inflexibility on production costs. Regarding emissions, at current allowance prices, the ETS is not sufficient for emissions abatement of onsite electrolytic hydrogen production. On the other hand, temporal correlation requirements are an effective tool for reducing the attributable emissions intensity. However, a focus on emissions abatement for onsite electrolytic hydrogen production, without adjustments to the ETS, risks cost inefficient sectoral emissions reduction without reducing system emissions, due to leakage to other sectors.

The decarbonization of the energy system is driven by the electrification process and the expansion of variable renewable energy capacity. Green hydrogen, produced through electrolysis powered with renewable electricity, represents a major complementary vector that can support this transition. By enabling long-term storage, it addresses the challenges arising from the unpredictability of a renewable energy-based electricity system. It represents a backup and increases the reliability of the electricity system.

In an interconnected decarbonized system where energy carriers are interdependent, new sector-coupling dynamics emerge. Energy-only markets, in theory, yield socially optimal levels of installed capacity across both sectors assuming rational participants and perfect markets. However, risk-averse behaviour among market participants might lead to underinvestment in generation capacity, undermining the efficacy of hydrogen backup.

The main objective of this research is to assess the adequacy of market designs in attracting socially optimal levels of investment in electrolyzers and storage capacity within a decarbonized and integrated system with risk-averse agents.

The stylized stochastic equilibrium model formulated is solved by using the Alternating Direction Method of Multipliers algorithm. Participants formulate their strategy based only on market prices, which are influenced by 18 scenarios that differ in terms of electricity demand, hydrogen demand and variable renewable energy sources availability. The demand for electricity and hydrogen is considered price-elastic.

An energy-only market, an energy market supported by a capacity market for electricity generators, and an energy market supported by capacity markets for both electricity and hydrogen generators are tested under different degrees of risk aversion.

The analysis confirms how risk aversion, by increasing the risk premium required, entails a reduction in installed capacity. Underinvestment is combined with a general reduction in the served energy and an increase in energy prices and frequency of periods of high prices. These trends are more considerable in the hydrogen market, where agents are exposed to risk from the uncertainties in both hydrogen demand and electricity prices.

The energy-only market is more sensitive to the impact of risk aversion due to the absence of risk trading opportunities. In this case, the increase in energy prices is the only solution to recover the risk premium.
Introducing a capacity market for dispatchable electricity generators mitigates the impact of risk aversion in the electricity sector. However, this exacerbates performance issues in the hydrogen market during scarcity periods by amplifying hydrogen price fluctuations. On the other hand, incorporating a capacity market for hydrogen counteracts the effects of risk aversion on the hydrogen sector. This dual approach not only benefits the hydrogen sector but further improves the electricity sector’s adequacy and reduces consumer costs.

Capacity markets are an effective instrument to hedge risk, but their application in an integrated system has to be consistent and include both electricity and hydrogen generation capacity. Furthermore, the strong dependence of hydrogen generation on electricity prices advocates for a direct instrument to hedge risk for renewable generators such as contracts for difference, as an adequate vRES capacity improves the whole system’s performance by reducing hydrogen prices and increasing its availability.

Integrating renewables in the electricity system in a cost-efficient way requires massive transmission system investments and the efficient use of available transmission capacity. Markets are pivotal in the latter, especially in coordinating flows between countries. In the European Union, flow-based market coupling (FBMC) arose as the preferred market-based cross-border capacity allocation method, which has recently been extended to the CORE region, involving 12 countries of the EU. While the expansion of the flow-based methodology brings the EU closer to a single internal electricity market, its complexity and scale hinders analytical efforts of market participants, system operators and regulators. They conduct analysis to obtain insights into price formation, to enhance coordination as well as a more efficient use of assets. The limited and fragmented data available on flow-based domain strategies of TSOs and cost structures of participants obstructs the analysis.

This thesis attempts to bridge the gap between stylized academic models on FBMC and real-world market outcomes, to be able to reason about operational day-ahead markets via these simplified models. To this end, a multi-step modelling process is carried out to forecast day-ahead zonal market prices and cross-border flows. Inverse optimisation is utilised to recover cost functions on a bidding zone and technology level. This is followed by a spatial reconstruction of the static grid, which is subsequently used to infer the flow-based domain based on historical observations. The model-based approach has the added benefit of being interpretable, and can be adjusted for structural and regulatory market changes.

Inverse optimisation has proven to be able to recover aggregated technology cost functions with which real-world market outcomes can be forecasted in a tractable way. The model developed in this work is shown to outperform a commercially available, machine-learning-based algorithm in forecasting day-ahead prices. The limitations of reconstructing flow-based domains using publicly available flowbased market data are identified. Analysis concludes that while the ability to recover cross-border flows is sensitive to the shape and size of the inferred domains, the performance of price forecasts is robust against the quality of domain inference. The delivered work is argued to yield valuable insights to both market participants optimising their assets, and regulators structurally assessing the effects of flow-based domain configurations on welfare outcomes of real-world day-ahead markets.

This thesis aimed to investigate the potential of the EU’s carbon border adjustment mechanism (CBAM) to promote sustainable adjustments in the production process of semiconductor machines, considering uncertainties in carbon accounting. The research combines a review of existing literature, a case study analysis of a selected semiconductor company, and a policy analysis of the EU’s CBAM to provide insights into the ability of the CBAM to promote the use of sustainable materials in the semiconductor industry.
The literature review highlighted the significance of life cycle assessment (LCA) as a carbon accounting tool and its potential to assess the relevant embedded emissions for the CBAM. The review showed indeed that LCA could be useful to assess the first phases of the production of the raw materials. Additionally, the review showed that it is less useful as a decision-making tool due to the fact that decision-making regarding the CBAM requires the consideration of other parameters as well, not only the environmental ones. Additionally, the review revealed the novelty of the EU’s CBAM regarding the carbon accounting tools and the CBAM’s design. At the same time, it highlighted the relevance of this research project.
The statistical sensitivity analysis (SSA) conducted as an element of the case study showed that there exists a significant variation in the total embedded emissions of the semiconductor machine depending on the kind of steel and aluminium used. This highlighted the opportunity for improvements in the embedded emissions caused by the semiconductor machines. The SSA is also used to evaluate the cost-benefit analysis (CBA) of the implementation of green steel and aluminium in semiconductor machines. The CBA showed that a high reduction in embedded emissions is required to achieve a break-even level with the costs of sustainable steel and aluminium. However, this reduction also depends on the design and implementation of the CBAM. The stakeholder analysis highlighted the actors, transactions, frictions, and games caused by the implementation of the CBAM. A concluding policy analysis was conducted to present possible implementations of the CBAM. The analysis showed that under the current circumstances for the CBAM to be successful in promoting sustainable changes in the semiconductor machine, while considering the uncertainty in the carbon reporting process, an unrealistically
high carbon price is needed to break even. The analysis, however, indicated a bright spot; if global electricity production becomes less carbonintensive, the CBAM may work very well in promoting sustainable materials. Thus, this thesis concludes that for this case study the EU’s CBAM is not effective in promoting sustainable adjustments in semiconductor machines. However, this conclusion is obtained for this specific case with its specific extreme policy scenarios. Therefore, further research could be conducted in assessing other policy scenarios or carbon accounting tools and test how they evaluate the CBAM on its potential to promote the use of sustainable materials in other industries as well.

Offshore bidding zones will eventually result in lower revenues for offshore wind farm owners due to a lower electricity volume and price risk, especially when flow-based market coupling and advanced hybrid coupling are implemented in the electricity system. This results in a demand to improve the investment climate for offshore wind farm owners. One measure that can be taken to improve this climate can be by introducing CfD schemes.

Because of the number of different design elements, designing a CfD for a specific situation can be seen as a complex process that considers many factors tailored to offshore bidding zones. This research will give an overview of some CfD design choices that need to be taken with their consequences.

This thesis looks into the following designs:

- The conventional CfD design
- The advanced CfD design
- The capability-based CfD design
- The capability-based CfD design with a cap and floor strike price
- The financial CfD design with a reference generator
- The financial CfD with weather data as reference