The ongoing electrification of the Dutch energy system, driven by ambitious 2050 climate targets, is causing increasing congestion in medium- and low-voltage electricity networks. A key challenge lies in the mismatch between rapidly increasing renewable electricity generation and the limited capacity of the grid infrastructure. This imbalance not only delays the energy transition but also obstructs economic growth, as businesses and consumers struggle to connect new renewable projects to the grid. Residential Battery Energy Storage Systems (R-BESS) are considered a key flexibility solution to mitigate this problem. However, if operated purely for market profit, especially through arbitrage and participation in the imbalance market, R-BESS can unintentionally exacerbate grid congestion. This thesis investigates how congestion-neutral operation of R-BESS can be implemented to ensure their contribution to a stable and resilient grid. This thesis investigates how the concept of congestion-neutral operation, a relatively new design approach that aims to prevent residential batteries from contributing to peak grid load, can be applied to the integration of R-BESS. While R-BESS are often deployed to maximize economic returns through market participation, this research focuses on the impact of this implementation and investigates operational strategies that explicitly avoid increasing grid congestion. The central research question addressed is: How can congestion-neutral R-BESS be integrated into Dutch electricity networks to mitigate net congestion while balancing techno-economic trade-offs? A mixed-method approach was applied. The qualitative phase involved literature review and interviews with involved actors (distribution system operators, aggregators, and policy advisors) to identify key technical and institutional design elements for congestion-neutral R-BESS. The quantitative phase implemented a Mixed-Integer Linear Programming model in PyPSA to simulate R-BESS behavior at aggregator level under various market scenarios. The model was applied to a real Dutch medium-voltage substation (MSR), with scenario analyses for 2024 and 2030, supported by sensitivity and robustness testing on weather variability and system parameters. Results show that uncoordinated R-BESS operation substantially increases congestion, particularly in the imbalance market. The outcomes are summarized in Table 1. Congestion-neutral strategies, in particular time constraints, significantly reduced negative grid impacts. For example, applying time constraints reduced new congestion events by half for day-ahead and imbalance 2024 scenarios. However, mitigation periods also decreased with more than 25% for both scenarios. In addition, time-constraint operation preserved economic viability in the day-ahead market: total system costs increased by only 0.9% (2024) and 1.3% (2030), when combining battery trading with self-consumption (”value stacking”). However, for the imbalance market, total system costs increased by 3.47% and 5.09% under time-constraint operation. The study highlights key trade-offs between grid impact and business model profitability. It also identifies limitations, including single-node focus and perfect foresight assumptions.
Practical recommendations include enabling congestion-neutral R-BESS through flexible constraints, distinguishing day-ahead and imbalance market, and clear coordination between DSOs and aggregators. Future research should extend to multinode grids, explore dynamic real-time signals, and further integrate market design for congestion-neutral flexibility services. All results of this thesis are open source. The complete model developed for this research is publicly available at: https://github.com/Tanneheemsbergen/pypsa-NL2025

This research aims to explore the behavioural diversity and bounded rationality within an Energy Hub (EH) under congestion management with a modelling tool such as Agent-Based Modelling (ABM). The model incorporated rotational load shedding, adaptive capacity allocation, PV panels, and a dashboard. The model also incorporated behavioural drivers, such as the symbiosis of participants with different Social Value Orientations (SVO) and other factors that influences load shifting. The ABM was compared with real-world data of participants in an EH. The results show that altruistic and pro-social populations perform the best in short-term, while the competitive populations adapt over time in long-term. Gamification could be a strategy to use the social factors to engage diverse participants in interactive activities and support collaboration. Time-of-Use (ToU) pricing could be a strategy to add next to the dashboard to engage diverse competitive and individualistic participants to load shift. Proportional load shedding could be another strategy to provide for a more equitable way to load shedding. This study provides a system-level perspective, showing how heterogenous and homogenous IC compositions influence demand response outcomes. This model can be used in future case studies to analyse collaboration patterns, test interventions, and the recommended strategies.

The energy transition is creating congestion on the low-voltage electricity grid, threatening reliability and slowing sustainable development. To address this, Distribution System Operators (DSOs) are turning to household flexibility measures. However, most current approaches assume households behave uniformly, overlooking important behavioral differences.

This thesis uses an Agent-Based Model to simulate five household profiles (Conscientious Individuals, Structure Seekers, Status-Driven, Responsibles, and Self-Developers) and their participation in three flexibility measures: smart EV charging, solar PV curtailment, and flexible heat pump control. Awareness campaigns are included as a soft intervention. Profiles and parameters were informed by literature and interviews with Dutch DSOs. Scenarios reflect current conditions and two future policy paths, including the planned abolition of net metering.

Results show large differences in participation across profiles. Conscientious Individuals and Responsibles adopt early, while Status-Driven households are least likely to engage. Summer feed-in peaks can be fully mitigated in ideal conditions, but reducing winter peaks proves more difficult due to limited uptake of heat pump flexibility.

The study shows that behavioral segmentation adds critical value to energy modeling. Targeted engagement strategies based on user profiles can help DSOs design more effective, inclusive flexibility programs, aligning grid stability efforts with real-world household behavior.

PJM Interconnection, the largest regional transmission organization in the United States, is facing mounting pressure to accelerate the interconnection of new energy generation resources to meet load while maintaining system reliability and minimizing rate payer impacts. The interconnection process- the procedure through which new generation projects get connected to the existing transmission grid is a key bottleneck in the clean energy transition. Over the past decade the queue of projects waiting to get interconnected in PJM has grown to greater than the total installed capacity in PJM. Each year the average time in queue has increased, as have the costs assigned to projects for network upgrades required to connect them to the grid. Meanwhile, while the MW of new generation resources coming online has decreased each year, load continues to increase and the grid is becoming capacity constrained, one symptom of which is the capacity market clearing with record small margins the last two years. In the face of large and increasing queue sizes and wait times, interconnection reforms are receiving increased attention from policy makers, advocates, and academics. One such reform is wider adoption of Energy Resource Interconnection Service (ERIS) agreements....

Decision-making about sustainable energy development often constitutes not only choices about which technology to adopt but also the dependencies of these technological choices on the social, economic and political helms within the context they are applied. For Uganda, juggling some of the country’s innate challenges like poverty and lack of energy access whilst managing limited resources magnifies the complexity of its development efforts. Thus, crafting actionable policies and strategies to achieve the country’s development goals requires a harmonious interplay of the country’s social, technical, economic and political perspectives. Literature on sustainable energy development encompassing the different perspectives is growing. However, there is a knowledge gap in research that covers all the mentioned perspectives for Uganda.

This research focuses on rural electrification because rural communities comprise 74% of the country’s total population and hold the key to attaining the country’s sustainable energy development goals. From this, we derive the main research question: What are the plausible pathways for rural electrification development in Uganda, considering the techno-economic, socio-technical, and political perspectives, using a serious game? The main aim for including a serious game in this research is to study the tool's potential in streamlining the multi-faceted decision-making process. A pre-existing game was selected and adapted to the Ugandan context to include institutional roles, the choice of suitable rural electrification technology and other subsidy measures. The information needed for the adaptations was gathered using a mixed methods analysis approach. The information included Uganda’s feasible energy generation alternatives, the criteria for analysis of the different generation alternatives and the main actors in the arena. This was done through reviews of relevant policies, surveys and interviews with relevant stakeholders. The findings from the game, which constitute adapting institutional roles, the choice of suitable rural electrification technology and other subsidy measures, were then proposed. The game also proved to be a beneficial tool to foster learning and collaboration amongst relevant energy stakeholders.

Baggage as a Service (BaaS) is a new concept that aims to separate baggage from passengers to make air travel more convenient. The study aims to analyze its CO2 footprint with four sub-questions guiding the research. The first sub-question is to identify all relevant elements for the BaaS carbon footprint, while the second aims to create a mathematical model to calculate the CO2 emissions of BaaS. The third sub-question involves numerical analysis of a case study of Bagbooking to determine its CO2 footprint, while the fourth sub-question compares BaaS CO2 footprint to that of normal air travel. The main findings present a rich conceptual model outlining two logistics chains for baggage and passengers without baggage, analyzing the emissions sources and transport modes. An Excel model was developed to calculate the CO2 emissions of Bagbooking and the comparison of the fourth sub-question.
The study analyzed the emissions of each Bagbooking customer and identified the sources contributing to the carbon footprint, highlighting the contribution of each stage in the logistics chain. Five scenarios were identified with varying effectiveness in reducing emissions, building on each other progressively to reach the emission levels of normal air travel. The first measure involves optimizing baggage collection and distribution, resulting in a decrease in emissions from the actual +56% of Bagbooking to 46% compared to normal air travel, reduced to +29% by encouraging sustainable transportation. Transporting cargo in the extra space created in the belly hold of passenger flights since the absence of baggage would reduce emissions by -63% compared to normal air travel. The adoption of trains or green modes can further reduce the percentage. Specific recommendations for Bagbooking are included. Future research could use more specific input data, consider the impact of increased BaaS usage, and include factors like failed deliveries and the use of ferries and intercontinental BaaS services.

The Dutch government has set an ambitious goal: by 2030, greenhouse gas emissions in the Netherlands should be 49% lower than they were in 1990.But even though geothermal energy is gaining recognition given the high heating demand in the Netherlands and its subsurface potential, implementation of this technology, especially in urban areas, is stagnating. A threefold-knowledge gap was identified in literature. First, it was identified that the viability of geothermal energy is case-specific. Therefore, the lack of knowledge about geothermal energy implementation in metropolitan setting results in uncertainty about the possible trade-offs of stakeholders and makes stakeholders wary of entering the market. Second, it is unclear how and to what extend regional norms, rules and regulations influence development of geothermal systems in urban areas after policy has been adopted. Third, significance of social acceptance is being discussed in a growing number of studies, however it is unclear how social acceptance may be operationalized in policy implementation research. Therefore, this thesis addresses the question how and to what extent institutions influence the success of the geothermal energy policy implementation process in urban areas in the Netherlands. The aim of this research is to consistently track institutions in geothermal energy policy implementation in urban areas in the Netherlands. For this purpose, a comparative case study has been designed to contrast the geothermal policy implementation process of two municipalities, The Hague and Nieuwegein, that share similarities in urban development, external context and type of geothermal technology, but differ in policy outcome. To structure the individual case analysis, a theoretical framework is developed that utilizes elements from the Multiple Streams Framework (MSF) by Kingdon and the Institutional Analysis and Development (IAD) Framework by Ostrom. From the findings it can be concluded that taking institutions into consideration influences the political and policy flow directly. The primary issues raised by the comparative analysis relate to social, ethical, and politically significant transactions. The lengthy policy implementation process was tainted by a general (mis)trust of the decisionmakers, and concerns were focussed about the equitable allocation of risks and rewards and the willingness to work together for a sustainable system.

Climate change intensifies the frequency and severity of floods - the most devastating and costly climate-induced hazard. Government adaptations such as dikes or beach nourishments are important, yet insufficient in the face of worsening hazards. They reduce the hazard probability, but the local actions at the household level determine the extent of damages and inequalities in its distributional impacts on various societal groups. To design effective policies and risk reduction strategies it is critical to quantify the speed and scope of the household adaptation uptake and the resulting damage prevention. This is especially the case for distributional impacts (i.e., how different societal household groups adapt), which are often neglected. Quantifying both aggregate and distributional impacts of household climate change adaptation (CCA) on flood risk fosters the design of tailored flood risk management policies which allocate resources to the societal groups that need them most. This thesis presents a state-of-the-art agent-based flood model in downtown Shanghai, China to understand the role of household CCA in reducing coastal flood risk both in its aggregate and distributional impacts. To model the households’ exposure to climate-induced floods we overlayed the geolocations of 18.039 residential buildings with 21 inundation maps that depict dike failures and dike overtopping under different climate-change scenarios. We further parameterized households using context-specific micro-level survey data from Shanghai and depicted households’ adaptation decisions using an extended version of the Protection Motivation Theory. Our results show that autonomous household adaptation (adaptation without government policy) to climate change plays an essential role in reducing flood damage in downtown Shanghai. However, despite the considerable adaptation uptake, the residual damages increase over time due to the effects of sea level rise and land subsidence. This shows that autonomous household adaptation alone is insufficient to keep pace with the increasing severity of climate-related flooding, as it is constrained by barriers in the form of adaptation measure costs and regulations. Thus, additional policies are needed to overcome these barriers. These policies should take into account differences in adaptation behaviour and damage prevention among societal household groups. Specifically, our results indicate that households with lower worry, self-efficacy, and income adapt measurably slower to climate-induced floods, which makes these household groups significantly more vulnerable to flooding.

The shifts towards more use of electric vehicles and more use of renewable energy sources create the need for Vehicle-to-Grid (V2G) technology. To penetrate the market, the development of V2G business models is critical. However, there are no sustainable V2G business models determined yet. Therefore, this research focused on what the key components are for such business models focusing on the Netherlands. By applying a qualitative approach, this study analyzed the actor's environment, technological developments, and three cases. After that, semi-structured interviews were conducted interviewing eleven experts with regards to the development of sustainable V2G business models. The results showed that there are three themes (business environment, business model, sustainability), twenty-six categories, and 229 components. This research provided an overview of the key components in a business model framework categorized into three use cases: Public V2G charging, V2G for homeowners (Vehicle-to-Home), and V2G for office/building owners (Vehicle-to-Building). The results showed that the business environment is vital and that the Dutch market is at the moment not ready for V2G to be commercial because of institutional, technical, and standardization issues. However, there is also potential due to the increasing trend of EVs, increasing grid congestion, decreasing costs of V2G charging infrastructure, and other trends.

Selection of industrial sites is a complex issue that requires careful consideration of a wide range of factors. Classical location decision-making overemphasize the role of economic factors while the energy related factors are often neglected. This research supports the energy transition by means of rethinking the location decision-making problem concerning Energy-Intensive Industries (EIIs). The main objective is to determine how the suitability of sites of industry clusters in Europe will change because of the energy transition. Two industry clusters in Europe are selected and used as test cases for analysis. To offer understanding of the suitability of cluster locations to a changing energy medium, a procedure to conduct analysis is developed and applied. The necessity to develop the analysis procedure is motivated by the lack of a methodology to serve as a commonly accepted framework for the analysis of industrial location problems in the context of energy transitions. The outcomes of the so-called factor analysis procedure enable to reason on the suitability of the sites of the clusters to the envisioned future renewable environment. To ensure validity of data and of findings, insight emerging from the literature and assumptions made by the author, are triangulated with the opinion of stakeholders and experts in the field. The research concludes that the energy transition will have a severe impact on the suitability of sites of the investigated EII clusters in Europe. The rationale being that, state-of-the-art sites are not suitable to a fully transitioned word. Exploring the future points to necessary changes that the sites have to undergo in order to suit a transitioned word. The findings emerging from the analysis, are meant for investors and traders that are interested in siting and industry modernization. Ideally, the methodology developed to study EIIs can be extended to other industrial sectors. I will be necessary to analyze the novel decision space and evaluate the factors at play on the novel location problem under investigation. Future research efforts should internalize the dynamics that govern the location decision of EII clusters described in research and use them to better understand the effects of possible failures of intervention.

The Dutch carpet tile industry is one of the most polluting and unsustainable industries worldwide, with a waste product that is only fit for landfilling. This thesis set out to model the industry and conclude on effective sustainability increasing measures. It was identified that the creation of one carpet tile (0.25 square meters) causes a global warming equivalent of 4.9 kilograms CO2-equivalent units and requires up to 78 megajoule of energy. With the current material composition of a carpet tile, no fully sustainable supply chain can be achieved. The recycling of these materials is simply too costly and too difficult. This makes for the downcycling of end-of-lifecycle (EOL) carpets into building insulation material the most effective form of disposal, only achieving a 31% reduction in environmental effects at best. This is a far cry from the envisioned full circularity by the carpet industry. In order to achieve a fully sustainable carpet industry, a shift in problem ownership is required. Currently, the consumer and government are paying for the inability of the carpet industry to produce a carpet that is (fully) recyclable. Once a carpet is sold, the costs of disposal are the responsibility by whoever buys the carpet, and the environmental costs affect welfare and are thus a governmental problem. This study advices a product-service system, where through leasing contracts and deposit systems, the carpet manufacturer remains the owner of a carpet at its EOL. Through this system, the carpet manufacturer is incentivized to produce a carpet that is more easily recyclable, or to establish a market and create demand for the EOL product. This study set out to discover how the current generation of carpets can be diverted from landfills and be used to establish a sustainable industry. It can be concluded that recycling cannot be achieved, and downcycling needs further exploration as it requires the establishment of a new market. Thus, it is concluded that the current generation of carpets is unfit to create any sort of sustainable supply chain, and efforts are best invested in the establishment of a new type of carpet which is more easily recyclable.

Hydrogen as an energy carrier is seen as an important option to reduce the CO₂ emissions in the transport sector. However, limited research is done into the possibilities of using a hydrogen truck in freight road transport. This article considers the following question: Under which techno-economic boundary conditions a hydrogen fuel-cell tractor semi-trailer (hereafter called: hydrogen truck) is a feasible option for long-haul freight road transport in Europe? This paper uses a Total cost of ownership (TCO) analysis to identify these conditions. While looking into the cost components of the TCO and comparing this with a diesel truck, the boundary conditions for feasibility arise. This thesis identifies three sorts of boundary conditions. First of all, the availability of hydrogen refuelling stations (HRS) and the deployment of the hydrogen truck. Secondly, the affordability (TCO) of a hydrogen truck is primarily determined by the economy of scale. The effects of this are the most influential for the production of hydrogen and the hydrogen truck. Thirdly, the most important robustness in operation boundary conditions are the hydrogen storage techniques and there fuelling speed. Insight in this assists in the creation of policy for zero-emission freight transport.

In the light of the global transition away from fossil fuels, a multitude of solutions are implemented in the Netherlands. A transition towards electrification of appliances is part of these solutions. Usage of heat and mobility is increasingly electrified. This trend is expected to increase over the upcoming years. This electrification will have an impact on the electricity demand and will impact the electricity grid. Furthermore, a transition towards a more decentralized electricity production can be noticed. The introduction of high quantities of these renewables will have major consequences for the low voltage grid. The integration of these transitions in the distribution grid is one of the main challenges for a distribution system operator. However, the transition towards electrical appliances might also possess opportunities to create smart solutions to solve for higher electrical demand and loads within the electricity grid. The batteries of electric vehicles might be utilized to aid the functioning of the grid. The introduction of this charging technique might defer necessary investments for grid reinforcement within the distribution system based on the introduction of higher electricity demand.

During the next few decades, a significant increase in the use of intermittent renewable energy sources is expected in the Netherlands as well as a general increase in electricity consumption. Due to the increased demand as well as a more uncertain, volatile supply, substantial upgrades and redesign of the current Dutch electricity grids are needed. These upgrades will inevitably require large investments as the design and installation of electricity grids is costly. Additionally, the investments are lumpy and irreversible. It is therefore important that the investments will be made in such a way that the future grids will operate successfully, supplying consumers with the demanded electricity at sufficient quality with a low rate of interruptions. Recently, the Netherlands has been divided into 30 energy regions, which allows the Netherlands to work on its climate agreements both from a regional and from a national level. These regions will work on generation and consumption of electricity and heating as well as on the energy infrastructures needed to supply this energy. This aim of this research paper has been to create a method that can be used to design suitable electricity distribution networks for the energy regions in the Netherlands. One approach to designing electricity grid topologies is with the use of graph theory heuristics, which has shown to be a useful way of approaching the electricity design problem by discretising plots of land into a graph. The research paper has shown that by taking into account spatial constraints specific to the Dutch regions, more valid networks can be created. This further leads to increased implementability of the final networks in addition to a reduction in the possibility for unforeseen costs related to building on certain plots of land. The proposed method aims to minimise the investment costs of the future regional electricity distribution networks in the Netherlands, taking both cable lengths and capacities into account. A radiality constraint is applied, ensuring that the network is connected but does not contain any cycles. A flexible way of ensuring that the final networks do not overlap with unavailable land is thereafter applied and demonstrated. A heuristic method aiming to minimise network length is applied before assigning the required capacities to the network. An improvement procedure is performed in order to further reduce investment costs. The cost function is formulated as a non-linear function, incorporating the characteristic that savings can be made by combining lines in order to create a shorter, high-capacity network instead of a longer, low-capacity network. The proposed method has thereafter been verified with respect to the problem formulated and demonstrated using a case study on the energy region Goeree-Overflakkee. Experimental results have also been generated in order to assess the effectiveness of the method. In comparison to an alternative simultaneous topology and production optimisation, it has been found that the proposed method leads to a shorter final network that additionally leads to lower total investments costs.  

Barriers to CO₂ abatement impede their materialisation. In this research the Y-factor was used in expert interviews to gather information on the barriers to the materialisation of four abatement options in the Netherlands: Insulation, Carbon Capture Storage, Biofuels and Geothermal energy. The potential of these options for the Netherlands is relevant, although no acceleration of their realisation has taken place. The Y-factor proved to be a suitable research method to systematically research materialisation barriers from a system’s perspective as it included barriers related to costs and financing, multi-actor complexity, physical interdependencies and behaviour. The supporting stories of the barrier scores and links between barriers revealed the complexity of materialisation. Additional scoping of abatement options and clarification of barrier definitions can increase informative value of the supporting stories and increase the scoring quality. Researching abatement options when using a system’s perspective can improve the understanding of barriers to CO₂ abatement.

Electric mobility is considered as the next step towards sustainable mobility. Within the Netherlands, as one of the leading countries if it comes to electric mobility, the market share of battery electric vehicles is still limited to 0,2 percent. Many studies are executed on consumer behaviour regarding electric vehicles. But no studies are found based on users with actual experience with battery electric vehicles. A theoretical framework was developed to create better understanding on how actual user experience relates with perception, attitude and adoption behaviour. The Q-experiment shows four shared perspectives among experienced battery electric vehicle users, which are all positive. Differences were found comparing these perceptions with perceptions from unexperienced consumers found in literature. Interestingly, the result suggests positivity among experienced users is not only caused by usual vehicle characteristics as drivetrain. But also, by brand image, self-identity and innovations on user interface. Suggesting that experience influences perception on BEV usage, it is interesting to understand how to bring experience towards non-experienced users.