Alternative fuels can help the maritime shipping industry to lower its emissions. However, there are commercial risks that surround the adoption of these cleaner fuels. A book & claim based carbon insetting initiative could reduce these commercial risks and accelerate the decarbonization of the maritime shipping industry. Carbon insetting is the process of funding an emission reduction within the sector where the emissions that are being compensated originate from, through the purchase of certificates.

Book & claim facilitates the generation and trade of certificates for certain products & their properties. Combining carbon insetting with the book & claim chain of custody concept enables the generation and trade of scope 3 CO2 certificates for shippers when vessels bunker alternative fuels. Effectively enabling shippers that want their goods to be transported sustainably to pay the price premium for using alternative fuels, thereby facilitating change and sustainability in maritime shipping, without a change in logistics.

The purpose of this master’s thesis is to understand how the concept of book & claim based carbon insetting can enhance the competitive position of the port of Rotterdam for the bunkering of alternative fuels. By simultaneously understanding what potentially the most effective way is to implement this concept at the port. This is achieved through a literature review, together with a workshop conducted for Port of Rotterdam Authority (PoRA) employees.

The workshop results show that the participants have different views on how a book & claim based carbon insetting initiative should be approached. The participants’ answers covered a range, lying on two different ends of the spectrum for potential starting points.

A book & claim based carbon insetting initiative at the port of Rotterdam can potentially enhance the port’s competitive bunkering position for alternative fuels. Implementing this concept in the port would create a clear demand stream for alternative fuels, which will enable the scaling of the supply of alternative fuels within the port, improving their affordability.

Three frameworks were identified that each have their own approach to implementing book & claim based carbon insetting in the maritime shipping industry. These frameworks were evaluated based on six criteria, which were formulated from the results of the workshop. All three frameworks were evaluated for two scenarios based on the two different starting points addressed by the workshop participants.

Based on the above research results, a business strategy has been formulated for the PoRA regarding book & claim based carbon insetting. This proposed business strategy consists of general recommendations and a range of possible approaches the PoRA could take to support the concept.

Book & claim based carbon insetting for the maritime shipping industry is still in its infancy. It has the potential to lower the commercial risks surrounding the adoption of alternative fuels, accelerating the development of a market for sustainable shipping. In turn, accelerating the decarbonization of the maritime shipping industry while potentially enhancing the competitive bunkering position of the port of Rotterdam for alternative fuels if such an initiative is set up in the port.

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

Grid congestion, which results from a larger demand for electricity transport than the available transport capacity, is a challenge in the Dutch energy transition. The growing pace of decentralized renewable energy development in less densely populated areas and the electrification of demand leads to congestion, which potentially hinders the connection of new renewable projects to the grid and slows down the energy transition.

Due to the intermittent behaviour of renewable resources, the grid connection capacity is not used to its full capacity at all times. Cable pooling is introduced as a possible solution to congestion, allowing an existing and a new renewable resource to share a grid connection and improving the utlilisation of the current grid infrastructure.

This thesis’ main objective is to develop a calculation framework to assist developers to evaluate the economic potential of a cable pooling location by optimizing the Net Present Value (”NPV”) of a shared grid connection, considering technical, regulatory, legal, and financial aspects. It aims to provide developers with a tool for making a preliminary decision on whether to continue development for a potential cable pooling location.

The Dutch context is used to identify different grid connecting possibilities, different combinations of wind and solar to form a hybrid farm and different revenue streams. These are used in a methodology to find the optimal installed capacity of the added resource and the impact of on-site storage to one of the hybrid farms. The approach considers the influence of market prices on the technology specific cable pooling business case at an hourly level and accounts for long-term market developments. Other factors accounted for in the tool are the hourly export capacity, defined as the residual space after the export of the existing farm, land size and costs of installation.

A case study of a solar farm oriented to the east-west is used to test the tool and draw conclusions on the potential of cable pooling for this case study. The additions of a wind and solar resource with either south or east-west generation all yield positive NPV values with the highest values seen for the wind addition.

Sensitivity tests for technical and economic inputs show that the results are sensitive to weather data and various economic inputs, but the results of this case study are robust. The case study however considers a relatively large grid connection. Generalizing the results by considering a smaller grid connection shows the value of complementary production patterns.

The impact on the cost-benefit framework by adding a battery is considered. The addition of a battery adds value by peak-shifting the produced energy, but not enough to cover the costs of the battery without any subsidy or alternative revenue streams.

In conclusion, cable pooling shows potential for this case study, for different revenue streams and additions. The tool used to obtain the results can be tailored to different case studies and input scenarios and shows the economical attractiveness of a cable pooling location, based on the Dutch context. The Dutch context shows a promising potential for cable pooling as a method to deal with congestion, but not many projects are present yet. Considering different parties sharing one grid connection, coming to an agreement on the terms can form a hurdle. Therefore, the introduction of more transparent cable capacity calculations by DSOs and a separate subsidy for cable pooling projects could help incentivize the development of more cable pooling projects. The impact of developments such as the ”Use-itor-lose-it” on the cable pooling potential should be monitored closely. Other solutions to dealing with congestion, such as using the fault reserves, should not be disregarded.

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.

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.

Sustainable energy transition is the need of the hour, more so, because of the accelerated effects of climate change. This necessitates rapid, continuous, and persuasive political and technological approaches to enable an ecosystem of green alternatives for countries to support their net-zero ambitions. One such emerging technology approach is green hydrogen, which is hydrogen produced from renewable sources. Green hydrogen is considered as a versatile energy carrier to support transitioning of industries, energy systems and transport, towards sustainability. As such, globally, many countries have increasingly considered green hydrogen as a part of their decarbonisation plans. Today, at least 26 countries have adopted hydrogen policy strategies and supporting policy instruments. However, mere adoption is not enough – a test of policy effectiveness is required to evaluate whether policies will be executed in keeping with their stated objectives, whether the various policy instruments/tools introduced to support overall strategies will be collaborative or may conflict with one another, and whether the policies will address issues systematically or ad hoc. It becomes important to understand whether policy strategies and instruments, the underlying processes, and their characteristics - collectively called a policy mix- could actually support policy goals, objectives, and ambitions of various countries.

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.

The electrification of modern-day society keeps increasing and the demand for electricity grows along with it. Technologies like EVs and heat pumps are both part of the new types of demand, while PV systems and wind farms are meant to be our main new sources of generation. Contrary to traditional resources connected to the electricity network, most of these resources tend to be placed and operated in a distributed manner, increasing the demand for transport capacity within the LV and MV grid. This demand cannot always be met however, which leads to situations of congestion.

This thesis seeks to reduce this congestion by means of optimising the grid topology in line with the seasonal variations in the supply and demand of electricity. This is done by means of implementing a two-stage reconfiguration algorithm. The benefit of network reconfiguration is that it is a short-term and low-cost solution which can be implemented by the DSO without relying on other external parties.

In the first stage of the reconfiguration algorithm, the positions of the normally open switches within the network are optimised in order to adjust the power flow therein. These optimised positions are subsequently used in the second stage to calculate the network variables. The first stage is implemented as a MILP optimisation in Python, while the second stage consists of a Newton-Raphson calculation in the commercial software PowerFactory. This distinction is made to enhance the accuracy of the final network parameters, while still being able to optimise the switch positions in a deterministic manner.

Rather than day-ahead or real-time reconfiguration, as is often considered in most literature, this thesis focuses on seasonal reconfiguration to accommodate for the manual operation of the switches present within the MV grid in the Netherlands. These manually operated switches severely reduce the frequency by which reconfiguration actions can be performed, but that does not mean that the topology of the grid cannot be enhanced.

The presented reconfiguration algorithm is able to consistently reduce congestion within the analysed network, completely removing it or reducing its severity. It also outperforms two optimisation options in PowerFactory with regards to the objective function value. Those being an iterative exploration of meshes and a genetic algorithm.