Achieving 100% carbon-free electricity production in the Netherlands by 2035, while ensuring reliability and affordability; this aim was established by the Dutch government, which intensified the national climate ambitions (Minister voor Klimaat en Energie, 2023a). However, even without considering this
intensified sustainability aim, the reliability of the electricity system is expected to decline beyond 2028 and surpass its norm by 2033, with an expected loss of load of 14.2 hours per year (TenneT, 2024). Central to this challenge is the crucial need for system flexibility to secure reliability (TNO, 2023). This need is heightened by the widespread integration of variable renewable energy sources (VRES) and
an expected surge in demand due to electrification efforts (TenneT, 2023).

Several technologies, such as demand-side response, interconnection, and storage, can partially provide for system flexibility (Aurora Energy Research, 2021). However, during situations with high demand and low VRES supply, such as ’kalte dunkelflaute’, there is a need for firm dispatchable generation capacity. However, projections on the expected operating hours and needed capacity during these hours vary widely. Different scenarios project a range between 4 GW and 20 GW by 2050 (Sijm, 2024). Currently, about 18 GW of firm capacity is installed in the form of gas power plants, compared
to a total of 56 GW of installed generation capacity in the Netherlands (ENTSO-E, 2024). Given the sustainability aim, this capacity would need to be decarbonized. However, only 58% of the capacity is technically feasible for retrofitting to operate on hydrogen (den Ouden et al., 2023). Therefore, this
thesis is built on the premise that investments in carbon-free firm capacity are crucial to achieving the 2035 sustainability aim, with a main focus on retrofitting current gas power plants to hydrogen power plants and potentially investing in new power plants.

Therefore, this thesis researched policy instruments that stakeholders and experts perceive as effective for incentivizing investments in firm carbon-free dispatchable electricity generation capacity while considering the 2035 100% carbon-free electricity production aim, overall system sustainability, reliability, and affordability. Additionally, this thesis aimed to provide explanations for differences in perceptions.

The research employed a qualitative exploratory and explanatory approach, using semi-structured interviews as the data collection method. A total of 14 interviews were conducted: 5 with stakeholders from (semi-)governmental organizations, 4 with stakeholders from electricity generation companies, 3
with experts from research institutes, 1 with a financial expert, and 1 with a stakeholder from an environmental organization. The interview data was analyzed using thematic analysis. First, to identify patterns of uncertainty factors that can challenge investments. Second, to identify potential policy instruments to mitigate uncertainties and enhance investment incentives. Third, to examine the perceived effects of these policy instruments regarding their effectiveness and impacts on sustainability, reliability, and affordability. Lastly, an explanatory approach was applied to identify potential explanations for differences in perceptions.

Several interconnected factors were identified that increase uncertainty in projecting the viability of investment business cases compared to conventional practices. These factors include, but are not limited to, uncertainty in operational costs, operating hours, electricity prices, and potential price cap
implementation. Additionally, these uncertainties are influenced by factors including base load capacity, intermittent VRES supply, flexibility-providing technologies, and inflexible load...

Climate change demands a transition to a carbon-neutral energy system. In the Netherlands, this shift involves electrifying sectors, predominantly by increasing energy sources like solar PV and wind power. This comes with flexibility challenges during times with insufficient variable Renewable Energy Sources and extended periods with wind droughts, or a dunkleflaute which is a period of more or less two weeks with insufficient wind and a cold front. Electricity generation from molecule based fuels can play this flexible role to balance the system in the future. Hydrogen is a versatile energy carrier that can play this role in a low carbon manner. Hydrogen can be stored in large volumes underground in salt caverns and in depleted gas fields. To ensure security of supply in different scenarios it is necessary to understand what volume of hydrogen should be stored in storage facilities to withstand a dunkleflaute. What is also necessary is to understand with what speed this hydrogen should be injected and produced from storage facilities, in other words: in how many days the storage can empty and fill. The production of green hydrogen with which the storage is filled is produced through the process of electrolysis. There are different types of technologies to produce green hydrogen. This research also focuses on the trends in developments regarding electrolysers and their impact on the system. As well as on the policy goals set by European Union and the Dutch government. The method in which the research was set up is by determining the system characteristics and uncertainties and going through the motion of the modelling cycle multiple times. This research is conducted by simulating the Dutch energy system in Linny-R, a mixed integer linear programming software tool. The model is made for the years 2035 and 2050. A sensitivity analysis is done to determine the most influential keys in the system. Based on literature and this sensitivity analysis, a scenario analysis was determined. Many scenario’s were then tested in the model to determine their impact. The system is measured with the following KPI’s: Carbon emissions, Loss of Load Expectation and Expected Energy Not Supplied, System costs and Production cycles. The conceptualisation in this thesis details the intricacies of the Dutch energy system and its simulation within the Linny-R model, offering a foundational understanding essential for later analyses. This chapter dissects the components and operational settings of the model, emphasizing their significance in shaping outcomes. The Dutch energy system’s transition from fossil fuels to renewable energy sources is mapped within Linny-R, highlighting the interplay of various energy forms and the constraints inherent to the system. The setup includes explanations of Linny-R’s key entities and discusses the model’s execution over a yearly timeline with hourly steps to capture dynamic system behaviours. Special attention is given to the settings impacting computational efficiency and the incorporation of historical weather data to account for variability in renewable energy production. After discussing the system a framework is presented, detailing the external factors, policy levers, system relationships, and performance metrics that guide the analysis. The analysis focuses on verifying the model, conducting a sensitivity analysis, and beginning scenario discovery to test the model’s performance. Verification ensures the model accurately represents real-world systems by examining storage facilities’ behaviors and hydrogen-to-power conversion during low variable renewable energy supply (vRES) periods. Sensitivity analysis tests how changes in input parameters impact outputs, identifying critical inputs that influence the model’s performance and ensuring robustness. Key findings show that hydrogen and electricity demand parameters significantly affect system costs and efficiency. Scenario discovery assesses the model’s resilience under various conditions, including extreme weather years, to identify potential bottlenecks. This chapter establishes the model’s reliability and guides improvements in its predictive capabilities. The results show the findings from the scenario analysis aimed at evaluating the potential of underground hydrogen storage in the future energy system. These experiments investigate various performance parameters to inform decision-making for effective integration of underground hydrogen storage. Key findings include the impact of electrolyser capacity on hydrogen production and system efficiency, ii iii revealing that increased electrolyser capacity significantly reduces carbon emissions, though it must scale parallel to storage capacity to be effective. The analysis of different storage types highlights the importance of sufficient electrolysis capacity to fully utilize storage facilities. Concluding their dependence on one another. Additionally, scenarios exploring battery capacity, gas power plant use, and demand variations provide insights into optimizing the energy system while achieving policy goals. The results underscore the complex interplay between various components of the hydrogen storage system, emphasizing the need for balanced and integrated approaches to meet future energy demands and sustainability targets. The discussion interprets the research findings, emphasizing the anticipated demand for underground hydrogen storage and the required production capacity for 2035 and 2050. The study reveals that while there will be significant storage needs in 2035 due to hydrogen shortage, the demand will decrease by 2050 as renewable energy sources and electrolysis capacity increases. Economically and functionally, a combination of salt caverns and gas fields is recommended, with optimal configurations identified for injection and production capacities. The research also highlights the critical role of electrolysers and their efficiency. Limitations of the study are discussed and recommendations for future research directions suggest exploring blue hydrogen, integrating hydrogen flow dynamics, and considering regional energy needs. The study’s findings have practical implications for policy decisions for Dutch hydrogen storage

The European Commission (EC) has set ambitious targets of achieving 60 GW and 300 GW of offshore wind capacity by 2030 and 2050, respectively, to meet its energy and climate objectives. This push towards renewable energy necessitates the integration of hybrid offshore wind farms (OWFs) connected to multiple countries and markets, facilitating cross-border electricity connections, security of supply, and increased renewable energy integration. Hybrid projects, combining OWFs and interconnector transmission cables, play a crucial role in this transition, aiming to create a meshed offshore energy network in the North Sea.

The development of the European Target Model, incorporating Flow-Based Market Coupling (FBMC), Advanced Hybrid Coupling (AHC), and the Offshore Bidding Zone (OBZ), aims to address challenges in hybrid projects but introduces new price and volume risks. These risks, stemming from the unique market mechanisms of the OBZ and the increased dependency on interconnectors, lead to revenue uncertainties and potential curtailment for offshore wind farms (OWFs), complicating investment climates and hindering the achievement of renewable energy targets.

The main objective of this thesis is to identify the key factors leading to price and volume risks for hybrid projects and assess the effectiveness of mitigation measures. This is achieved by answering the main research question in this thesis: How do the offshore grid topology, onshore grid attenuations and the integration of renewable energy
sources influence price and volume risk and to what extend do regulatory and technological measures
mitigate these risks?
Aiding in answering this question, four subquestions have been introduced, aimed at identifying specific price and volume risks, exploring regulatory and technological mitigation measures, determining the most impactful risk factors on OWFs' economic viability, and evaluating the potential mitigation measures' effectiveness.

The research approach consists of two phases: qualitative desk research and quantitative modelling. The first phase involves a literature review to identify and categorize price and volume risks and mitigation measures, forming a risk framework. The second phase addresses the Risk Framework from phase 1 and uses it to extend the model from Kenis et al. (2023) to quantify the frequency and severity of the risks and ultimately determine the key factors leading to these risks. The primary research method applied in this thesis is a linear optimisation model mimicking the FBMC process of TSOs deployed in Julia. The methodology encompasses a four-key steps process. In the first step, the Case Determination, indicators are established to define case groups and systematically vary variables and isolate the primary considered variables, i.e. offshore grid topology, onshore grid attenuations, and renewable energy integration. In the second step, the Case Simulation, the base case (D-2), day-ahead market clearing (D-1) and redispatch (D-0) modelling steps of the FBMC process are simulated, followed by the added modelling step to distinguish between the capacity calculation and allocation volume risk and the calculation of the risk indicators. In the third step, the Case Group Analysis, case-specific results are collected and analysed per case group and an ex-post analysis of the FTR and TAG compensations is conducted. Th final step, the Cross-Case Group Analysis, involves aggregating and analysing all results with the aid of standardisation methods to create Risk Matrices.

The study identifies two key factors leading to price and volume risks: the transmission grid’s physical characteristic, i.e. the OBZ’s export capacity or FB domain as influenced by the offshore grid topology and onshore outages, and the market characterises of the bidding zones connected via the hybrid interconnector, i.e. the level of competition between the OBZ and onshore (renewable) generators for the allocation of scarce transmission capacity.
Changes in offshore grid topology primarily impact price and volume risks by altering the OBZ's export capacity, with increased transmission capacity generally reducing curtailment by capacity calculation but potentially affecting price collapses and curtailment by capacity allocation depending on onshore grid restrictions and market dynamics. Onshore grid attenuations similarly influence these risks, with high-priced zone outages typically increasing curtailment by capacity allocation and price collapses,
while low-priced zone outages increase curtailment by capacity calculation and positive non-intuitive price formation. The integration of renewable energy sources in onshore markets exacerbates competition for transmission capacity, leading to more frequent curtailment by capacity allocation and price collapses during high-wind hours.
Technological mitigation measures, i.e. flexible demand agents (e.g. offshore and onshore electrolysers), mitigate price and volume risks by increasing local demand in the OBZ, setting a floor price and raising electricity prices, and decreasing the need for wind exports, which reduces curtailment by the capacity allocation and calculation risks. FTRs effectively cover price spreads, prevent price collapses and non intuitive price formation. The TAG moderately compensates for curtailment by the capacity calculation volume risk.

Policy makers should actively promote the deployment of flexible demand technologies to balance supply-demand mismatches and support renewable energy generation. They should also decide on a support strategy for hybrid projects, either a merchant-based approach focusing on flexible demand deployment or a regulatory approach implementing FTRs and TAG, potentially including 2-sided capability-based CfDs for initial projects to address supply/demand mismatches. TSOs should strategically select inland landing points and prioritize grid enhancements to mitigate structural congestion and reduce hybrid projects' exposure to price and volume risks, while timely communicating potential delays in intra-zonal and cross-border transmission developments to developers. Developers should pro-actively invest in flexible demand assets to mitigate price and volume risk and increase OWF revenues, optionally focussing on strategic locations of onshore assets near landing points. Finally, uniform decision-making and alignment in hybrid project design and support instrument deployment across North Sea countries are crucial, potentially facilitated by establishing an independent Offshore Transmission System Operator and an Offshore Investment Bank to manage transmission assets and reallocate costs and benefits among stakeholders.

Renewable hydrogen is seen as an important element of a future decarbonized European Union. To reach the European Union’s ambitious goals for renewable hydrogen, a framework for regulating its hydrogen transmission infrastructures has been proposed, shaping how hydrogen transmission capacity via pipelines should be made available throughout the continent. With the European Hydrogen Backbone Initiative, the desires of existing fossil gas TSOs for hydrogen transmission capacity seem unlimited. However, there is a practical regulatory need for prioritising investments in hydrogen transmission capacity to keep renewable hydrogen an affordable and competitive means for decarbonization. Furthermore, scarce transmission capacity needs to be allocated between different users and uses, so that most value is made from our scarce resources. But how should regulators prioritise and allocate, when the future requirements for hydrogen transmission capacity remain highly uncertain in such a nascent, developing sector?

This thesis argues for a tailored regulatory framework for making hydrogen transmission capacity available. Rather than transferring the EU’s regulatory framework for fossil gas directly, it is crucial to explore various approaches systematically. Using the insights from property rights theory, this research compares the liberalized and unbundled fossil gas transmission systems of the EU and the US empirically, to identify a suitable regulatory model for the specific context of a nascent, developing hydrogen sector.

The findings suggest that the current EU regulatory framework is inadequate for developing a competitive renewable hydrogen value chain. Instead, a hybrid approach is proposed: employing a top-down TSO/DSO-like structure towards making decisions on transmission capacity within hydrogen clusters, and a bottom-up market-based approach between clusters. This integrated strategy aligns with regulatory and industry needs, mitigates investment risks, and supports the role of vertical-integration and long-term contracts across the developing renewable hydrogen value chain.

This thesis makes valuable academic and practical contributions to the regulation of transmission infrastructures in emerging sectors, addressing a significant gap in the current perspective on regulation. Policymakers and regulators are urged to consider these recommendations to ensure the successful development of a competitive renewable hydrogen value chain. Something that is not guaranteed under the proposed market design in the EU.

With the ever so rapid transition towards renewable energy, the offshore electricity transmission system has to expand. Towards 2050, a meshed offshore network is seen as a cost-effective solution to bring electricity to shore. Although there is no "one size fits all", a Cross-Border Cost Allocation procedure is the designated procedure to allocate costs across Member States. To gain insights into key criteria for the cost allocation of a meshed offshore network, Q methodology was used to explore perspectives. The four resulting perspectives showed that for the realisation of a 300 GW meshed offshore network, contributions from non-hosting Member States is essential. However, the current procedure to allocate costs will not be suitable, as there are many points of disagreement to be resolved first. In this regard, the research provides a first understanding of the problems at hand in allocating costs across borders for projects the size of a meshed offshore network.

An important process for navigating the uncertainties associated with the energy transition is power system planning. Energy system models are considered to be useful tools for supporting the power system planning process but are limited in several ways. Firstly, energy system models often have a high computational burden, limiting the possibility of conducting a large range of experiments. Secondly, to reduce their computational burden some energy system models have limited temporal detail, resulting in overestimation of VRE capacity in the system, underestimation of VRE curtailment, and undervaluation of flexible resources. Thirdly, many energy system models are considered to be ‘black boxes’ due to their high complexity and limited transparency. To address these problems related to models for power system planning, the Operation and Planning Model (OPM) has been developed in this study. The OPM is a myopic electricity system cost-optimisation model with a high level of temporal detail and a relatively low computational burden to allow for exploring the development of a national energy system, focussing on the interplay between demand, supply, and storage of electricity.
The OPM has been applied to a reference case and two targeted experiments on the development of the Dutch electricity system from 2030 to 2050. The reference case showed that in case natural gas-fired power plants with carbon capture and storage are included in the OPM, the electricity system becomes highly dependent on this technology for the provision of electricity and flexibility. If this technology is not included in the OPM, the maximum number of additional generation and storage units per year is shown to have a major impact on system development. In case this factor is sufficiently high to not limit investments, the system becomes mainly dependent on onshore wind for the provision of electricity and energy storage in underground hydrogen storage facilities for flexibility. In case this factor is limited to a lower level, the system develops a more balanced technology mix. Multiple recommendations are made for future research continuing on the work presented in this report.

1. Applying the OPM to more experiments can result in more in-depth insights into factors influencing the development path of the Dutch electricity system. This could entail analysing scenarios with variations of the costs for the different technologies to assess under which cost levels the system develops a favourable or unfavourable technology mix.
2. The spatial scope of the OPM can be expanded to assess the importance of cross-border trade for ensuring system reliability and gaining insights into the co-evolution of interconnected electricity systems.
3. The demand side is assumed to be inflexible in the OPM. Including demand side flexibility can result in a more accurate view of the electricity system's development between 2030 and 2050.
4. The used time series data is based on a single year. An alternative approach is suggested in which time series data from multiple years is used which would better represent that perfect forecasting of capacity factors and electricity demand for a future year is not possible.

The climate change is evident and a big contributor to the negative effects of the climate change is the energy production sector. Therefore, the energy production must shift towards a more environment friendly mix. Changing our energy sources to mostly renewable energy sources comes with many challenges.
The way the current Dutch electricity market is designed will lead to a drop in electricity prices on the wholesale market, when the market is penetrated with a high concentration of renewable energy sources. So the electricity market mechanism needs to be reformed to have a price determination system better suited for energy sources with low marginal costs. Furthermore, a capacity remuneration system needs to be implemented to create enough investment incentive in controllable energy capacity to maintain a high level of security of supply in the Dutch energy system during the energy transition.
There exist many different forms of capacity remuneration mechanisms, but the strategic reserve and capacity markets are examined to check which one would work best in the Dutch energy system. In a strategic reserve a central authority sets the capacity volume, which will be contracted by an operator. This operator will dispatch the contracted capacity when needed. In a capacity market a central authority determines the amount of capacity each consumer should acquire through buying capacity credits on the market.
To determine which capacity remuneration mechanism would deliver the highest level of security of supply, simulations of the Dutch energy system are run. The simulations were done using the models AMIRIS and EMLab, which are coupled to give a more accurate representation of reality. The coupling takes place in the Spine Toolbox. The capacity remuneration mechanisms were created in Python and can be activated as modules in the Spine Toolbox.
The vertices are sketched of the possible future energy scenario of the Netherlands in 2050. These vertices are the so called scenarios, regional governance, national governance, European CO2-governance and international governance. The simulations were run with a scenario in which the energy demand stays equal and with a scenario where the energy demand descends similar to the international governance scenario. The international governance scenario was chosen to base the simulations on, because the simulations make profit driven decisions, similar to the international governance scenario.
The results of the simulations show that, firstly, without any governmental interference, a (near) zero-carbon energy system will not be achieved in 2050. Secondly, when running the energy-only market in a realistic scenario, no shortage hours will occur and the system had sufficient generation capacity for supplying the demand, even in a "dunkelflaute" scenario. Thirdly, the basic version of the strategic reserve offered the least costly solution for society for providing sufficient security of supply, so no significant shortage periods will occur in a realistic scenario. Finally, the best option for maintaining security of supply in the Netherlands during the transition to a zero-carbon energy system is the implementation of the yearly capacity market.

The European Green Deal states that the European Union will have to cut 55% of carbon-dioxide (CO2) levels and implement a share of at least 40% of renewable energy sources in the electricity sector by 2030, compared to levels of 1990. While renewable energy technologies are effective in cutting CO2 levels, they also bring challenges like variability and unpredictability which affect power system stability. The TradeRES project was founded in order to create and test new innovative electricity market designs that incorporate near 100% renewable energy generation. Multiple research groups across the EU participate in TradeRES, including TU Delft and TNO. In order to be able to research future system stability, this project seeks to improve investment decision-making in the energy models EM-Lab and COMPETES, provided by TU Delft and TNO respectively. To fully utilize the sophistication of both models and to prevent development of a new model, this thesis focuses on the coupling of the models through soft-linking and its validation in a Dutch energy transition context.

This thesis presents a conceptual approach and implementation towards the aforementioned soft-linking. First, the definition and requirements of soft-linking are defined to mitigate ambiguity created by previous work. These requirements are then implemented in a conceptual model describing data exchange, data mapping and timing of the models in the context of soft-linking. The conceptual model describes how the strengths of both models are utilized in the coupling. EM-Lab is an agent-based model used for studying investment behavior and has strong policy and market modules. COMPETES is an optimization model that has a very sophisticated and detailed dispatch module. The nature of these models provide coupling potential and constraints. A series of design choices describe how these models interact in the soft-linking, and how the decision was made to couple specific modules from EM-Lab with COMPETES to improve overall investment decision-making.

The implementation entails the recreation of EM-Lab market modules with Python and the soft-linking of these modules with COMPETES using the software kit SpineToolbox. From EM-Lab, the CO2 market and the capacity market were recreated in Python. These modules could be used to complement COMPETES and improve overall investment decision-making. Pseudo-code of the implemented algorithms is provided and a thorough description of the programmatic interactions of the models is given. Also, the SpineToolbox implementation is shown and elaborated on.

To ensure correctness, the soft-linking is validated and verified. Standard verification methods like face validity and static functional testing are used. For validation, the soft-linking is used to generate results in case studies which have been used to validate COMPETES. These case studies resemble a Dutch energy transition scenario. The results from the soft-linking are then compared to the validated COMPETES results. As the differences in results could all be explained, there is no reason to assume the soft-linking is invalid.

Results of the soft-linking are provided and contain graphs regarding the CO2 market, capacity market, dispatch, and investment and decommissioning decisions. The CO2 market presents volatile and extreme results, begging the question whether the current implementation is sufficient for future power system analysis. However, the results do suggest that the soft-linking has effect on investment and decommissioning decision-making. In conclusion, additional work, like representation of mechanisms that help stabilize the CO2 prices, is required in order to use this soft-linking for future power system analysis. The potentials of soft-linking are explored and suggestions are made for future work.

To keep the generation adequacy of the power system up to standards, more and more countries in Europe are setting up capacity mechanisms. In a capacity mechanism power generation units receive payments for having their capacity available when this is needed (during moments of electrical supply shortage). These payments are received on top of payments that could be received from the energy markets or ancillary service markets [4]. This gives incentives to generation units to be available when needed and create a better investment climate in generation capacity. In this way, these capacity mechanisms can increase the security of supply. In the past, countries in Europe could implement such a capacity mechanisms locally, only local capacity providers (e.g. generation units) were allowed to participate. But the European Commission has developed new regulations which state that it is allowed for capacity providers to participate in cross­border capacity mechanisms. In this way capacity providers can receive additional payments from participating in foreign capacity mechanisms. But this raises questions, because the contribution (capacity value) of a capacity providers is thought to be dependent on its location. This thesis analyzes what the effect of the new EU regulations regarding cross-­border participation is on the payments resulting from capacity mechanisms. To answer this, the relevant EU wide regulations are analyzed and combined with the regulations of the capacity mechanism as implemented in Great Britain (at the time of writing), to find a likely implementation of a capacity mechanism in which cross­-border participation is allowed. A generation adequacy model was built and combined with the likely implementation of a capacity mechanism to analyze what the expected payments from the capacity mechanism will be to local and cross-­border capacity providers. This was done to analyze how attractive it is for capacity providers to participate in two capacity mechanisms. The generation adequacy model that is used consists of two areas, these areas represent Great Britain and France. For the model the same input data was used as in [38]. A Monte Carlo sampling method was used to analyze when payments are due. It was found that with the implementation of the new regulations regarding cross-­border participation in capacity mechanisms it is very attractive for capacity providers to be participating in two capacity mechanisms. But EU regulations set a limit on the amount of capacity that is allowed to participate in a cross­border capacity mechanism. Capacity providers have to compete with other capacity providers in a market based manner to be allocated to participate in a cross­-border capacity mechanism. This will likely lead to a break even point where participating in two capacity mechanisms generates an equal income as participating in just a local capacity mechanism. To analyze how much generation units contribute to the security of supply of a cross-­border capacity mechanism, the two area adequacy model was used. An analytical method was used to calculate the capacity value of the generation units. It was found that generation units can contribute to the security of supply of a cross­-border area, although it does support the area it is located in more than the cross-­border area. When the interconnection between the areas has a larger capacity, the effect of a generation unit to the cross-­border area becomes larger. It was concluded by implementing the new regulations in the model in this thesis, that the capacity-mechanisms do not give financial incentives to invest in generation capacity for the security of supply of a cross­-border area. This might lead to sub­optimal investments, because generation units can contribute to the security of supply of a cross­-border area.

The decarbonisation of the Dutch power system cannot be accomplished by electrification alone. Although offshore wind power is to play a leading part in the future Dutch power system, long-term energy storage and hard-to-electrify energy consumers are in need of other energy carriers as well. Hydrogen gas is able to provide this system essential. For the production of green hydrogen gas, offshore wind is a promising option because it has a high capacity factor, relative to other sustainable energy technologies. Vice versa, hydrogen production can strengthen the business case of offshore wind as the average power price will decreases as a result of increasing power grid penetration from renewable energy power generators. Furthermore, the expansion of offshore wind in the Netherlands may lead to high cable costs with increasing distances to shore and onshore grid congestion. Hydrogen production can circumvent these problems while continuing the decarbonisation of the Dutch energy system. This study aims to determine the most profitable offshore hydrogen wind hub configuration for 2030 and 2040. To determine the optimal configuration, this thesis evaluates two main considerations. First, whether onshore or offshore electrolysis is more profitable. Second, whether a bidirectional or unidirectional grid connection may increase the profitability of respectively the onshore or offshore electrolysis configuration. For this evaluation, six configurations are examined that aim to represent the spectrum of possibilities on how a 12 GW hydrogen wind hub could be integrated in the energy system. These configurations vary in their positioning of the electrolyser (onshore/offshore), electrolyser capacity (11.5/9.5/5.6 GW) and grid connection capacities (0/2/6 GW). To compare the profitability of each configuration, this thesis evaluates their cost and revenues. The cost analysis is conducted through a literature study. The revenue analysis is performed by modeling the hydrogen production of each configuration for a given weather year in order to establish the hydrogen production cost. Additionally, for the grid-connect configurations, the power revenues are estimated using the Plexos power market model. This evaluation reveals whether the grid connection configurations can profit from both volatile power prices (sell \& buy) and a stable hydrogen price. All analyses use a screenshot approach on the year 2030 and 2040. Thus, annual cost and annual revenues are expressed for these years. In the cost analysis, cost variations are taken into account for the HVDC-components, offshore installation factor and WACC. Also, different distances to shore of the wind hub are taken into account (i.e. 88, 209 \& 330 km). For the power revenue analysis, the power system state data on 2030 and 2040 are used from the 'Ten-year network development plan' of ENTSOG/ENTSO-E, which span over more than ten years. From this data, the 'Global ambition' scenario and the weather year 1982 are used. This 'Global ambition' scenario represents a pathway of centralised innovation. In order to establish future power prices, the Plexos power market modelling tool is used to solve an hourly Unit Commitment Economic Dispatch problem by Mixed Integer Linear Programming. This nodal model consist of 59 EU- and surrounding non-EU countries. Additionally, a hydrogen market price is established in which the feedstock sector is assumed to be price-setter as an international hydrogen market is non-existent for now. In 2030, onshore electrolysis is more economical than offshore electrolysis as the electrolyser investment cost and accompanying offshore installation cost are high. The dedicated hydrogen configurations and the grid connection configurations have equal hydrogen production cost; 3.10 €/kg. In 2040, onshore and offshore electrolysis are equally economical up to about 200 km from shore. At larger distances, offshore electrolysis is more economical. Uncertainty in the system cost and differences in system cost between onshore and offshore electrolysis and per distance to shore are found to mainly result from uncertainty in the offshore installation factor, the cost of HVDC component and the WACC. The bidirectional 2 GW grid connection of onshore electrolysis and the unidirectional 2 GW grid connection of offshore electrolysis both result in the same hydrogen production cost as the dedicated hydrogen configuration; 2.50 €/kg. Overall, considering the operation of a hydrogen wind hub through 2030 and 2040 within one life cycle, there is no significant advantage of grid connection as the break-even prices of the 2 GW grid connected configurations and the dedicated hydrogen configurations are similar. Nevertheless, a 2 GW grid connection might provide risk spreading for the investor and a lower total hydrogen subsidy amount to achieve a profitable configuration. The larger grid connection of 6 GW is definitely less profitable operating through 2030 and 2040. When assuming the future technological maturity of turbines with DC output, efficient electronic power converters (DC-DC) and electrochemical compression combined with optimistic cost reduction of the electrolyser, the hydrogen production cost decrease to 2.65 €/kg in 2030 and 2.30 €/kg in 2040. Given these production cost, the 2 GW grid connected configuration and dedicated hydrogen configuration become competitive with grey hydrogen production in 2040 based on natural gas price of 7.31 €/GJ and 80 €/tCO\textsubscript{2}. An important note is that the current CO\textsubscript{2} price already surpassed the price trajectory for 2030 as used in this study. Variations in turbine cost will affect the production cost as well. However, in this thesis the emphasis is more on the comparison of the configurations than on the absolute level of the production cost. For different turbine cost, the comparison remains similar as the turbine capacity is equal for all configurations. Therefore, a fixed cost reduction is used for the wind turbines. Future techno-economic development of in-turbine electrolysis will determine whether decentralised electrolysis becomes beneficial over centralised electrolysis. It is recommended that the North Sea offshore wind infrastructural planning must take into account the broader potential of 60 GW Dutch North sea wind in 2050 (+ 450 GW onshore in Europe) and the forthcoming power grid challenges in all North sea countries. For specifically offshore wind-based hydrogen production, electrolyser capacity planning towards and beyond 2050 should be considered as the economies of scale of hydrogen pipelines might favour offshore electrolysis as the overall cost might be lower. Future onshore electrolysis provides possible symbiosis with solar PV, nuclear \& natural gas power generation and industry thereby limiting grid congestion and increasing the electrolyser load factor. Future modelling efforts that aim to value the benefits of combined hydrogen and power production should focus on different demand-side-response and power-to-gas capacities as both affect the volatility of the power prices. Also, alternative trajectories of the CO\textsubscript{2} price and energy system scenarios should be incorporated in the power price modelling. Furthermore, the power market model can be improved by including the recovery of long run marginal cost, strategic bidding behaviour and sector coupling of power and heat.

In an energy-only market, private investors play a crucial role in realizing the security of supply. However, several specific characteristics inherent to his market design cause concern about whether this market design is suitable for system adequacy. Moreover, due to policy goals aimed at working towards low-carbon energy systems, these concerns are increased. In this light, many countries have implemented a capacity remuneration mechanism to increase the stability of the security-of-supply in their energy system. While earlier research has been conducted on this topic, we observe two knowledge gaps: 1) from a theoretical perspective, there is debate on the effectiveness of capacity remuneration mechanisms, especially on the role of seasonal storage, 2) from a methodological perspective, we find that there are no models that are equipped to consider myopic investments while having a high enough detailed operational model also to consider investments in (seasonal) storage and the impact of extreme weather scenarios. This research aims to fill these knowledge gaps by presenting a proof-of-concept of a myopic investment detailed operational (MIDO) model. In our thesis, we focus on system adequacy. However, by developing the MIDO model, we hope to enable researchers to analyze any problem related to long-term energy system development with a multi-time scale nature. At the center of the MIDO model are three sub-models: the investment decision model (ID), the future price (FP) model, and the present price model (PP). The first step in this loop is the present-price model, which generates highly accurate information on the operation of a market. After running a year in the PP model, information on the performance of all assets in a market is sent to the ID model. With this data, the ID model performs two tasks: invest based on limited information in an iterative greedy process and dismantle assets losing money. The ID model gets the information on the performance of investment assets under consideration from the FP model. The FP model generates less reliable information than the PP, but it does so very fast. After the investment decisions are made, this information is transferred to the PP model, and the loop starts from the beginning. In this way, a market is simulated with investment cycles, delayed responses, uncertainty, and risk upon investment decisions. This process enables the comparison of different forms of capacity remuneration mechanisms and the effect on the security-of-supply in an isolated energy system. We explore two distinctly different futures within our thesis to see if there is any added value in a capacity market in any of these futures. Moreover, within these futures, we analyze how a capacity market can help withstand an extreme-weather scenario. From this analysis, we find that a capacity market has added value in all scenarios, from the point of system adequacy but also a total consumer cost perspective. However, because we only have explored two futures, we do not argue that a capacity market will always positively impact the system adequacy within an energy system. Instead, we argue against the notion that seasonal storage on its own is always enough to reduce all shortages created in an energy-only market and disagree with the idea that seasonal storage makes capacity markets redundant. We identify two avenues for future research. First, researchers interested in generating more and better results should utilize the MIDO model to explore more future scenarios and compare different forms of capacity mechanisms. Second, research aimed at improving the MIDO model should focus on limiting the computational time generated by the investment loop and seek to expand on the model’s functionalities.

As the variable renewable energy share keep on increasing throughout the energy transition, power systems require more and different flexibility measures. Battery energy storage can provide these essential services that enable the energy system to carbonise and transform on short time scales. Energy arbitrage, the trading of electricity on the electricity markets, can create economic value for batteries. This research assesses the energy arbitrage opportunities for utility-scale battery energy storage in the Netherlands. It compares five different battery technologies and defines the optimal size and power capacity with a linear mixed-integer Matlab optimization model. Furthermore, the operation of for the most optimal technology is simulated for one year with a Model Predictive Control algorithm to be able to compare the effects of forecasting accuracy of the electricity prices on the estimated profits. The results show that according to optimized planning and dispatch in the operation of a battery system can lead to financial opportunities in the Netherlands regarding energy arbitrage for flow batteries. If not today, then in the future. It has been shown that towards 2030 the business case for battery energy storage will significantly increase due to decreasing capital costs and increasing price volatility with the rise of the VRES and phase-out of fossil energy sources. With this research, a contribution is delivered towards the realisation of commercially operating an independent utility-scale battery energy storage facility. Insights are provided on what battery configuration is best suited for energy arbitrage purposes and the effectiveness of simulating the optimized operation of a battery facility with a model predictive control method has been shown. This has lead to clearer insights into the profitability of operating a BESF in the Netherlands.

The goal of this thesis is to identify under which boundary conditions
there is a business opportunity for an innovative electric thermal energy storage, with regards to the future electricity and heat markets. To meet this target, a novel optimization model has been developed as the main tool for the analysis of the storage and its profitability under different situations.

Wind energy is the most promising renewable energy source for the Netherlands in the energy transition period. However, the investment costs of the offshore wind are huge. Until now, the government was supporting the investments in wind farms with subsidy schemes irrespective of the electricity market dynamics. The latest large-scale offshore wind projects in Germany and the Netherlands (Hollandse Kust Zuid 1 and 2) have been awarded zero-subsidy. However, in the Netherlands, the transmission costs of the offshore wind electricity are socialized. This would force the un-subsidized wind-farms to feed their electricity into the public grid exposing them directly to the whole sale electricity market. With large shares of wind penetration in the market, the value of the electricity is declining. At the same time, the intermittent nature of the renewable energy sources generates large demand for flexibility in the electricity system. These pros and cons of renewable energy sources create new opportunities for electrification of other sectors to support achieving Paris climate agreement goals of the country. Heat and hydrogen sectors are identified as potential flexibility options to facilitate the de-carbonization of the energy system by 2050. European electricity market simulation model COMPETES is identified as potential tool to assess the integrated systems at national level. However, the flexibility provided by heat and hydrogen demands with thermal and hydrogen storage technologies is not part of the model directly. Therefore, an optimization model is developed to determine the size of power to heat and power to hydrogen systems with least cost. The results of this problem determine the outlook for investments in power to heat and power to hydrogen technologies. The problem also determines the operational strategy of these units in response to the hourly power prices. Consequently, the coupled implications of the emerging electricity load from heat, hydrogen markets on the national power system is studied. Industrial heat, domestic district heat networks currently provided by combined heat and power gas plants in the Netherlands and the developments in hydrogen consumption market are taken as study cases for assessment. This work provided insights about the opportunities, threats and solutions for the involved stakeholders.

This paper presents a new theoretical approach to design a polycentric electricity sector. The study focuses on Lebanon and its electricity sector, and tries to reform the sector using a proposed polycentric structure. The study utilises the polycentric indicators and general structure, along with organisational modes, and electricity market design variables to come up with a standardised stepwise model, i.e. “Polycentric Market Design Framework”, to design a polycentric hybrid electricity sector. This is followed by applying it to the Lebanese case.

In 2015, the UN climate agreement was signed by the Netherlands, which has the central aim to “strengthen the global response to the threat of climate change by keeping a global temperature rise this century well below 2 degrees Celsius and to pursue efforts to limit the temperature increase even further to 1.5 degrees Celsius” (UNFCCC, 2018). To be able to achieve this, “a reduction of at least 60% of GHGs by 2050 with respect to 1990 is required from the transport sector” (EC, 2011). This research focuses on three methods that were identified by Kaack et al. (2018) for the reduction of emissions in the transport sector: increasing the efficiency of freight vehicles, reducing the carbon content of fuel used to transport freight and shifting freight to low carbon-intensity modes. To be able to stimulate the freight transportation sector to the three alternatives, a pricing policy that includes the CO2 emissions of the modes is identified: carbon pricing (Beuthe et al., 2002). Current literature has studied the influence of a carbon price on the container freight transport in the Netherlands while focusing on the modal shift (Zhang et al, 2014; Zhang et al, 2015) or researched the effects of internalizing the external costs on the Belgium freight transportation network (Beuthe et al, 2002). Furthermore, the influence of a carbon price on the potential for urban freight electrification in Madrid was researched by Arroyo et al. (2019). This research contributes to clarifying the effects of carbon pricing on the Dutch freight transportation. As current studies mainly focus on either the effects on the modal shift or the effects on the use of alternative fuels, these do not consider a combination of the effects and do not take into account the increase in the efficiency of the freight vehicles. Furthermore, the current literature focuses on a particular niche market (e.g. only container or a certain region). This research takes a broader view and looks at the influence of the carbon price on all commodities that have an origin, destination or both in the Netherlands. The main research question of this research is: HOW CAN THE FREIGHT TRANSPORTATION NETWORK USE IN THE NETHERLANDS BECOME MORE SUSTAINABLE, CONSIDERING MODAL SHIFT AND ALTERNATIVE FUELS? Currently, most freight is transported by trucks, which is a more expensive mode but has a high network density and enables faster transportation as there is no need for transhipment between modes (Platz, 2009). Inland waterway (IWW) is the second most used mode for freight transportation in the Netherlands (CBS, 2019b). IWW is a cheaper mode, but the transport is dependent on the available ports in the waterways network and is a slow mode of transportation. Rail freight transportation is used the least in the Netherlands (KiM, 2016). The rail mode can be cheap, however transhipment is expensive. Next to that, the trains are dependent on the railways service stations and do not reach high speeds due to inefficiencies (Islam & Zunder, 2018; Janic, 2008). When looking at the emissions of the modes, a clear difference between the emissions is identified: trucks emit up to 2.5 and 5 times more CO2 than IWW and rail respectively (KiM, 2016). This results in an unsustainable distribution: the mode that emits the most emissions is used the most while the most sustainable mode is used the least.

Increased variable renewable energy sources penetration in The Netherlands require more flexibility that could be provided by distributed energy resources located at small end-users combined with demand response. Aggregators could act as intermediary entities to exploit the flexibility potential of small end-users and create value for Distribution System Operators (DSOs) by delivering electric flexibility services that support congestion management.

Aggregator Eneco CrowdNett is planning to commission a pool of households which will have a combined system of solar-PV and residential Battery Energy Storage (BES) units. Next to optimizing the household’s self-consumption, these systems will jointly be able to deliver power to the grid. Therefore, the system as designed by Eneco CrowdNett is used as a case-study during this research.

This research aims to provide a comprehensive understanding of how the value of an Aggregator’s electric flexibility services can be determined for DSOs, without jeopardizing the business case for the Aggregator and the CrowdNett participants themselves. A tool that simulates the behavior of residential BES units connected to the LV distribution grid is developed and tested, followed by a reflection on its usability for other cases.

The system under review in this study is framed as a Unit Commitment Problem (UCP), in which the generation units are represented by CrowdNett’s residential BES units that primarily deliver local service, but can also deliver congestion management services through load shifting. Linear Programming (LP) is considered a useful method to solve the UCP, which is implemented in the modelling software Linny-R.

It can be concluded the value of Eneco CrowdNett’s electric flexibility services for DSOs can not be determined by exclusive using a Unit Commitment model with a LP solver to replicate the behavior of residential BES units located at the LV distribution grid.

The model rather provides a tool to generally assess whether an Aggregator is able to reduce congestions in a given distribution network without jeopardizing her own business case and that of the end-users owning the BES units. The model should be supplied with input data regarding residential demand profiles, PV production profiles and the power capacity of the LV substation before the model output can be compared with the expected costs of grid reinforcements on a case-by-case basis to determine the value for DSOs.

Market organisation on energy networks is increasingly complex due to frequent emergence of new markets within and related to energy infrastructure. This research is conducted in cooperation with the Dutch Ministry of Economic Affairs and Climate Policy, and analyses the impacts of role demarcation policies on the development of the electric vehicle charging infrastructure market in the Netherlands by applying Exploratory System Dynamics Modelling and Analysis. In-depth behaviour based sensitivity analysis and scenario discovery has highlighted the most relevant dynamics on the market development over a period of 20 years. Limiting or restricting market access for network companies has showed to effectively influence market attractiveness positively and price developments negatively, both mainly on the short-term (within the first period of 10 years). The most significant and uncontrollable effects of uncertainties occur mainly on the long-term, granting the decision-maker the opportunity to adjust previous decisions when more accurate predictions can be made concerning the development of a specific market.