This thesis presents a life cycle assessment (LCA) comparing the environmental impacts of three electrolyzer technologies: Smart Alkaline Electrolyzer (SAE), Proton Exchange Membrane (PEM), and conventional Alkaline Electrolyzer (AEC). SAE, a novel technology distinguished by its modularity and scalability, offers seamless integration with renewable energy sources (RES). The study's scope, encompassing a cradle-to-gate analysis for 1 MW electrolyzers in Spain powered by solar PV, highlights the critical influence of electricity sources on environmental impacts. SAE outperformed PEM in seven of the eight assessed impact categories—climate change, terrestrial acidification, freshwater eutrophication, marine eutrophication, terrestrial ecotoxicity, ozone depletion, and photochemical oxidant formation potential (PCOF)—with a notable reduction in Global Warming Potential (GWP) at 7.39 kg CO₂ eq per kg H₂. Compared to AEC, SAE performed better in three impact categories and similar results in others. Key drivers of environmental impact were identified, with copper usage in power electronics being a significant contributor. The sensitivity analysis showed that 30% reduction in copper usage improved SAE's performance across 5 impact categories compared to AEC (climate change, acidification: terrestrial, eutrophication: marine, ozone depletion, PCOF: terrestrial ecosystems). The study identifies the key drivers of impacts within each electrolyzer and clearly delineates the subsystems of the BoP to make the comparison and analysis clear and to assess the overall impacts. The study also provides a structured and consistent inventory for the electrolyzers, enabling easy inclusion of other electrolyzer technologies, which several studies recommend.

This research focuses on establishing the most effective way to provide flexible power generation via gas turbines with hydrogen in 2040 from a techno-economic perspective. Assisting policymakers and energy companies in making informed decisions about future strategies. The increase in intermittent renewable energy capacity increases the pressure for flexible, dispatchable energy generation to bridge gaps when solar or wind energy is unavailable. Currently this flexible power generation can be produced via Combined Cycle Gas Turbines (CCGT) that run on natural gas, producing green house gasses in the process.
To conduct this research, a multi-criteria analysis is performed on the CCGT in Moerdijk for the year 2040. Comparing an alternative relying on blue hydrogen, one relying on green hydrogen, and one relying on a blend of blue and green hydrogen against the continuation of running on natural gas. This method established a systematical approach to evaluate and compare different alternatives based on multiple criteria, while aiding to narrow the knowledge gap in understanding the combined effect that different technologies have on flexible power generation. This analysis resulted in the continuation on natural gas as a fuel for the CCGT being the top performer. However, assuming the need for a sustainable alternative, the top performer was different for each of the three forecasts. In the forecast with a low installed capacity of renewable energy, the top performing option is to use blue hydrogen as a fuel. In the central forecast, the alternative that combines blue and green hydrogen as a fuel is the top performer, in the high forecast, green hydrogen takes the lead.
Two sensitivity analyses, decreasing the impact of capital expenditure and overall system efficiency in the analysis, revealed a decrease in the performance of natural gas and an increased performance of green hydrogen alternative. The results show that the lack of adaptability problems and capital expenditure outweigh the large CO2 emissions and CO2 related costs of the continuation of using natural gas as a fuel. Regulations or incentives to decrease the capital expenditure of alternatives running on hydrogen can greatly stimulate the development towards more sustainable flexible power generation.
The energy demand for the CCGT in Moerdijk in 2040 is determined based on three different forecasts for the year 2040. Using electricity data from the CCGT in Moerdijk, along Dutch energy data from 2023, three running profiles are established. This revealed that the running profiles are bound by the limitations of the CCGT across the forecast.
For each of these alternatives, the total annual cost is calculated by optimising the production capacity of hydrogen storage, the storage capacity, and the hydrogen flow for each hour throughout the year.
To reveal the problems and opportunities associated with implementing the alternatives for the year 2040, interviews with professionals in the energy sector are conducted. These interviews showed great challenges towards the technical and infrastructural adaptability of implementation of the hydrogen based alternatives, and great challenges for the alternative on natural gas from operational longevity and dependability perspective.

As electrification progresses, marked by the increasing adoption of heat pumps, electric vehicles (EVs), and electric cooking, household electricity consumption is surging. This rise is pushing low voltage electricity networks to their capacity limits. Expanding and enhancing the grid to be more adaptable and intelligent is crucial, yet such transformations require substantial investment and time and cannot be achieved overnight. A practical interim solution to this challenge involves optimizing electricity consumption within residential areas through the formation of energy communities. These communities allow households to collectively manage their energy use, especially during peak load periods, thereby reducing strain on the electricity network.

An energy community typically comprises a designated area or neighborhood where households aim to produce and consume electricity locally as much as possible. Additionally, these communities actively adjust their energy consumption patterns to avoid peak loads, significantly reducing the need for extensive investments in electrical infrastructure. To encourage participation, a demand response program is implemented that financially rewards households for adjusting their usage during peak times. This strategy not only facilitates more efficient grid management but also provides incentives for participating stakeholders.

This research presents a case study from the Sporenburg neighborhood in Amsterdam, where an energy community model is being tested. The study aims to identify the factors that contribute to the success of such communities. Sporenburg is an ideal case study due to its equipped smart meters and Amsterdam's ambitious climate goals, which necessitate a higher rate of electrification. Although currently stable, projections suggest that by 2050, Amsterdam’s electricity demand could increase threefold to fivefold compared to 2022 levels. The primary research question this study addresses is: What are the critical factors, categorized into distinct groups, that contribute to the success of the energy community?

The research is structured into three sections focusing on different aspects of the energy community: the technical system, organizational structure, and individual perspectives. It identifies critical success factors, differentiated into essential conditions for success and contributory factors. The study employs various analytical methods, including a technical analysis of Sporenburg, stakeholder analysis, and a survey.

The Dutch electricity network is shifting from a centralized, unidirectional system to a decentralized, bidirectional one, driven by renewable energy integration and increased electrification. This transition poses challenges, particularly low-voltage grid congestion. The study investigates the role of smart appliances in mitigating congestion through demand response initiatives. It identifies regulatory uncertainty, insufficient financial incentives, and lack of standardized communication protocols as barriers to adoption. Using qualitative interviews and Critical Transactions Theory, the research recommends regulatory intervention, direct load control, and unified communication standards to enhance grid resilience. Future research should incorporate social factors and assess standards for smart appliances.

In October 2023 congestion is issued in the HIC Rotterdam. As a result businesses can no longer establish, expand or electrify. A potential solution to free up grid capacity is that of an energy hub. This study evaluates future scenarios for the development of an industrial energy hub by utilising the EMA method. A study is done on the details of the congestion problem in the HIC Rotterdam in order to distinguish possible solutions. By exploring technologies applicable in an energy hub and applying exclusion criteria the potential for energy hub integration in the HIC Rotterdam is assessed. Based on the outcomes of a data inquiry a choice is made on an industrial cluster to model. Factors influencing the cluster’s development in the future are drafted and scenarios are designed that describe the potential evolution of the cluster. The electricity system of the industrial cluster is modelled and its data analysed. The model of the electricity system is translated into a model that generates future states of the industrial cluster. Through EMA these scenarios are evaluated.

The congestion problems faced in the HIC will last until project ’Loadpocket Simonshaven’ is commissioned in 2027-2029. Until then, energy hubs might be valuable in creating grid capacity. Making shared use of an electricity connection can already create some extra capacity, however the implementation of large electrification projects is most influenced by the availability of additional grid capacity. As becomes clear from the simulation results. In addition, a promising integration option is the inclusion of an electricity generation unit in the energy hub of which multiple exist in the HIC Rotterdam.

This master thesis provides a review of dynamic energy contracts and their role in shifting electricity consumption in households in the Netherlands. In this research the mixed-methods approach is used to identify changes in electricity consumption behavior of consumers with a dynamic energy contract compared to consumers with a fixed energy contract. Dynamic energy contracts are recently introduced in line with the Clean Energy for all package of the European Commission (2019) and the need for more flexibility regarding electricity consumption in individual households. Qualitative research found that individual households are only willing to be flexible in their demand with activities that are not time-critical such as washing and cleaning, while there was almost no demand flexibility with activities such as cooking and watching television. Based on real-time consumer data of a Dutch energy supplier, a difference-in- difference (DiD) regression analysis is performed to analyze the effect of dynamic energy contracts on electricity consumption. This study revealed that consumers with a dynamic energy contract have a different consumption behavior pattern compared to their own behavior pattern under a different contract and compared to consumers with a fixed energy contract. These findings indicate that the dynamic energy contract can change the consumption behavior pattern of individual households, which can be explained by paying the hourly electricity price in this type of contract. This research can form an inspiration and knowledge base for future research that can elaborate on the role of dynamic energy contracts in demand load shifting.

With the phasing out of the Net Energy Metering (NEM) scheme, the energy market is shifting towards alternative solutions like independent energy storage, already successful in countries like Belgium and Germany.
However, a single solution dominating the market is unlikely due to continuous innovation and the limitations of individual battery systems for prosumers and Distribution System Operators (DSOs). Community energy storage (CES) emerges as a promising alternative but lacks a defined business model, particularly for Dutch residential communities.
This study delves into the implementation of centralized community energy storage systems to boost prosumer profitability and mitigate grid congestion in the Dutch solar residential market, in the wake of the NEM scheme phase-out. Community energy storage applications are identified, along with their respective potential business models. The optimal application, in terms of prosumer profitability and grid relief, is selected, and its associated business model is developed using the Morphological business model designed for energy communities. Furthermore, a practical approach for integration is proposed, based on regulatory and market constraints, to enhance the potential for large-scale emergence. This approach includes defining key roles and responsibilities of stakeholders within the community and the corresponding allocation of value. Subsequently, a technical system design topology is outlined for each defined community. This system design delves into engineering details to analyze the energy interaction possibilities between consumers and the grid, along with the corresponding financial implications. Accordingly, the CES application’s performance is simulated and evaluated both technically and financially. The potential is presented by simulating the interactions between the community, the grid, and the optimal battery system. This optimal interaction arises from an optimization problem formulated to provide the optimal battery size and its corresponding energy profiles that minimize the total community cost. Finally, an energy distribution mechanism is carried out through conditional decision making to evaluate the cost and profitability allocation among consumers within the community.
The findings highlights the optimal application of CES, combining energy sharing with energy arbitrage, which significantly enhances the value of prosumers’ surplus PV energy, outperforming standard tariffs and avoiding grid feedback charges. This approach also provides consumers with access to more affordable shared community energy, while aiding DSOs in alleviating grid congestion and improving infrastructure capacity. The study suggests that the most effective strategy for widespread CES adoption involves collaboration between housing cooperatives and Energy Service Companies (ESCOs). Financially, this model entails
community managers overseeing initial investments, complemented by household contributions via usagebased or fixed service fees. The business model’s success is influenced by the type of grid connection, with Behind-The-Meter (BTM) offering flexibility but lacking standardization, and Front-of-The-Meter (FTM) encountering challenges related to community energy taxation. Modelling the optimal operation for both BTM and FTM connections demonstrates a significant decrease of energy costs and contribution to grid relief, highlighting load smoothing and peak shaving as key benefits. The research concludes that centralized CES systems can substantially elevate prosumer profitability and reduce grid congestion, leading to considerable energy savings and enhanced grid performance in the Dutch solar residential market.
To support the expansion of Community Energy Storage (CES) systems and energy communities, policymakers are advised to revise energy taxation policies and create frameworks aiding community grid formation, including simplifying regulations and offering incentives for residential initiatives. Researchers should adopt a multidisciplinary approach to explore regulatory, technical, economic, social, and environmental impacts on CES, focusing on regulatory effects, grid dynamics, cost-benefit models, community engagement, and environmental benefits. Industry stakeholders, such as Distribution System Operators, energy providers, Energy Service Companies, and housing cooperatives, should apply these research insights to develop and implement CES systems, fostering partnerships to address challenges and innovate in energy solutions, particularly in the evolving landscape post-Net Energy Metering, to enhance the role of community storage in sustainable energy systems.

As the transition towards a sustainable energy system gains momentum, the concept of energy hubs has emerged as a promising solution to make the existing energy system more efficient. This thesis aims to investigate the contribution of energy hubs to network management in the Dutch energy system. The research questions focus on identifying the key components and objectives of energy hubs, understanding the roles and interests of stakeholders involved, assessing the effectiveness of energy hubs in achieving policy goals, and exploring the opportunities and threats they present to the Distribution System Operator (DSO).

The study employs a mixed-methods approach, combining theoretical analysis, stakeholder interviews, SWOT analysis, and case studies. Through a comprehensive literature review, a holistic understanding of energy hubs is established, providing a foundation for further analysis. Stakeholder interviews offer insights into the perspectives and interests of various actors in the energy sector, shedding light on the roles they play and the potential benefits of energy hubs.

The thesis analyses the theoretical and practical value of energy hubs, considering their potential to optimise network capacity, enhance renewable energy integration, and improve system flexibility. SWOT analysis allows for a thorough examination of the strengths, weaknesses, opportunities, and threats associated with energy hubs. The analysis of case study projects further enriches the findings by providing real-world examples and highlighting their applicability in practice.

The results demonstrate that energy hubs have the potential to contribute significantly to network management, offering benefits such as reduced grid congestion, increased renewable energy utilisation, and enhanced collaboration among stakeholders. However, limitations exist, including the need for a clear definition, standardised legal procedures, and a comprehensive understanding of the specific conditions under which energy hubs are most suitable.

This thesis contributes to the existing knowledge on energy hubs and their impact on network management. It offers a comprehensive analysis of their key components, stakeholder dynamics, policy implications, and practical considerations. The research findings provide valuable insights for both academia and industry, informing future research directions and aiding DSOs in harnessing the full potential of energy hubs to facilitate the transition towards a sustainable and resilient energy system.

Sustainability is a crucial topic in the day to day life as well as in industries. With the help of innovation and new technologies, the negative impacts on sustainability can be decreased. During the development of technologies, the concept of sustainability should be included at all times. This can be done with the help of sustainability assessment methods. However, companies (like the case company of this study) often only adopt one or a few sustainability assessment methods in their product development process. These methods might not necessarily be suitable for the technology under investigation. Furthermore, guidance on when to use which method can be identified as missing within the literature and in practice.

This thesis study aims to fill this gap by developing decision support for the selection of a sustainability assessment method during technology development. Coming from a comprehensive set of sustainability aspects (social, environmental and economic), during the thesis the focus was put on the environmental aspect exclusively. A literature study is used to identify a set of the possible sustainability assessment method. The identified methods are compared to a set of selection criteria based on the method's acceptance, type of assessment, and sustainability pillar covered. Four methods/method groups are identified as suitable for the defined criteria and the study scope. The selected methods are analyzed in more detail to gain a deeper understanding. Based on the knowledge acquired, a flow chart is developed to support selecting the most suitable sustainability assessment method. In order to be able to compare the selected assessment method with other available method, a ranking is developed. The ranking is based on a qualitative comparison and data obtained from the literature. The ranking is displayed in two ways, by a set of spiderweb diagrams and a ranking with numbers. A partial validation of the developed ranking is done by applying two methods to a use case and comparing the practical results with the theoretical ones. Here a mismatch between the ranking obtained from the theoretical data and the one from practical experience can be identified.

The result of the study is the development of decision support consisting of a flowchart and method ranking. Once both steps are followed, it should be possible to provide a fast and easy method selection for non-experts. Furthermore, the common practice of using only one sustainability assessment method (Life Cycle Assessment) is looked into. It can be seen that no sustainability assessment method is best in all criteria and application cases. Therefore, it is impossible to define one most suitable method in all cases. Choosing the right method depends on the scope (substance, product, or material) and the intended outcome. Thus, relying solely or predominantly on Life Cycle Assessment cannot be recommended. Alternative methods should be adopted and applied, also within the case company.

According to the Paris agreement in 2015, global warming should be limited by applying new innovative technologies in the industry in order to keep the global temperature 2 degrees Celsius above pre-industrial levels. Governmental organisations, institutes and manufacturing companies themselves are concerned about high emissions and all together are making efforts to find and apply more appropriate technologies to reduce GHG emissions. This research focuses on the chemical industry, from the perspective of the chemical industrial cluster, and presents a way to identify the most suitable technologies for decarbonisation. The concept of an industrial cluster has the view of interconnected companies located in industrial proximity and there is a perspective of cooperation in order to find a way to reduce emissions. This cooperation, however, creates complexity as the companies will have to cooperate on a financial, technical and social level.

In order to study the topic, a specific case study was chosen to study, which is the Port of Moerdijk industrial cluster. Using publicly available data, three are chemical manufacturing companies and the one is a glass packaging manufacturing company, which is taken into account. The cluster analysis, results that companies are already strongly interlinked by exchanging material streams and utilities, which is an example of existing industrial symbiosis. The main raw material is naphtha, while energy is produced mainly by burning natural gas. This explains the high emissions of the cluster, around 2.8 Mt CO2/y, while the biggest emitter is the steam cracker unit (55% of the total emissions). Based on the cluster analysis, various options for decarbonisation are studied, such as alternatives for feedstock, energy carriers and the alternative processes itself.

The proposed scenario for the cluster of Moerdijk is, investing in the partial substitution of fossil-based naphtha feedstock with 10% co-feed of bionaphtha and 10% co-feed of waste plastic oil. Implementation of the electrification of the steam cracker, the steam boilers and the glass production processes and finally, Carbon Capture & Storage (CCS) technology is recommended. By implementing the recommended combination of decarbonisation options, it is estimated that by 2035 this will result in reduction of 45% of cluster emissions.

After the proposal of the final scenario for the case study, an attempt is made to generalise this analysis, and thus a way towards a decision framework is presented. Essentially, a list of actions is presented, which someone could follow to find the appropriate solution for another chemical industrial cluster. In this framework, all the social, environmental, economic and technical sectors are taken into account. This leads to a rather complex topic that should be solved or at least simplified. This study can be used by decision makers of a chemical manufacturing company, which is a part of an industrial cluster, as a tool in order to follow the right steps to conclude the most suitable option for decarbonisation.  The advantage of studying this topic from an industrial cluster perspective is the decrease of individual investment costs by investing in a common solution with shared infrastructure.

The Iron and Steel (I&S) industry is the largest contributor to man-made greenhouse gas emissions. The products of the I&S industry are a constant necessity, e.g. for civil infrastructure. In addition, their processes are interwoven with coal and natural gas properties, which classifies this industry as a ’hard-to-abate’ sector. Furthermore, fundamental technology changes in process and energy utilisation practices are required to fully decarbonise the I&S industry before 2050. Steel processes are divided into two major production routes, the blast furnace and the direct reducing plant. Focusing on the carbon avoidance route, the hydrogen-based direct reduction process is the most promising to decarbonise the I&S industry in Europe due to its ability to use natural gas as an intermediate energy source. Several techno-economic assessments have explored the energy, emissions, and economic potential of such conceptual systems, concluding that carbon emissions are highly sensitive to the CO2 intensity of consumed electricity. However, none have used the electricity mix to estimate the electricity price and associated CO2 missions on an hourly basis to investigate the performance of such systems. Therefore, a case study is proposed of Tata Steel Netherland (TSN), which has recently announced its intention to switch towards hydrogen-based steel through the DRI-REF route. The modelling and simulation research method is used to assess this case-specific process’s technical, environmental, and economic performance in 2030. A conceptual model is developed employing the findings of the literature review. Hourly data from the national electricity mix are acquired from the EMF v7.0 model from the company Blueterra, and TSN provides specific process characteristics. From this approach, several simulations could be made for different hydrogen volumes to evaluate the performance of the DRI-REF system in the Dutch context. The simulations showed a significant shift in energy sources for increasing hydrogen volumes, which leads to a reduction of 70.1% in direct CO2 emissions under the 2030 energy market conditions. However, if the indirect electrical emissions are considered, this reduction potential is only 2.2% CO2 reduction. Although this demonstrates that in 2030 the CO2 intensity of the electricity mix is approximately the breakeven point between NG and H2 production, this development also shows a major shift from CO2 emissions towards the electricity producers. Additionally, the electricity price breakeven point is a factor 3 lower than is currently estimated by using the IPKA0 electricity generation capacity scenario of Tennet. As a result, the levelised cost of production increases by 34.9% for the maximum Htextsubscript2 volume compared to NG-based production, with electricity and capital investments as the largest increasers. Furthermore, the hourly electricity price and associated CO2 emissions data enabled to determine the variability over time. A significant increase in the interquartile spread in emissions and cost calculations is observed for increasing hydrogen volumes. This implies that in the future when electricity is predominantly produced by volatile renewable energy sources such as wind or solar energy, the production uncertainty will increase significantly if this industry shifts towards hydrogen. However, this also increases the potential of flexibility technologies. Industries with flexible production processes can thrive in the Dutch environment as they could provide load-balancing services.

This report presents an analysis of the emergence of residential batteries from a consumer’s perspective and their effect on the load peak of the distribution grid. First, the future of residential batteries was evaluated in social and technical context by mapping the present situation, its trends, and its possible drivers. Three different battery control strategies were analysed: maximising self-consumption, market price arbitrage, and load peak reduction. The corresponding battery profile was determined with a rule-based approach. Second, load summation was used to simulate battery development scenarios within the distribution network, after which the effect of residential batteries was determined on a selected substation with a load peak analysis. From consumer perspective, residential batteries are driven by the phase-out of the net-metering scheme, increasing wholesale daily price spread, a decline of investment costs, or renewed tariff structures. The results showed that residential batteries become economically attractive when net-metering is abolished and the daily electricity price spread increases. The load profile results of the selected substation show a reduction of both size and number of overload hours for all control methods in case of medium and low emergence of residential batteries. In case the batteries are used to reduce individual load peaks, this reduction is largest and is smallest when batteries are used for market price arbitrage. Battery usage for self-consumption and peak reduction mainly operate during summer months when PV generation is higher. Therefore, demand load peaks in winter are not relieved as much. Although it was found that grid reinforcement is still not alleviated for the selected substation, the maximum and minimum load peak are unified leading to a reduction of required reinforcement capacity. It is found that retail price regulations strongly influence which control method will be dominant. Incentives to increase self-consumption or reduce load peaks will relieve pressure on the grid. However, critical grid congestion moments are not explicitly relieved. Therefore, further research is required to identify methods to utilise the batteries for DSO control during critical peak moments or winter seasons with low self-consumption usage.

As the energy transition is starting to accelerate, the Dutch industrial sector is in danger of falling behind with its decarbonisation efforts. Green hydrogen is often suggested as a key-player to decarbonize the industry, replacing fossil fuels used for process heat generation as well as in hydrogen feedstock production. As there are an increasing number of projects that aim to produce green hydrogen and a Dutch hydrogen backbone is scheduled for completion 2030, the question remains how green hydrogen has to be priced in order to be competitive with its alternatives. This research project assesses the economic competitiveness of green hydrogen based on its alternatives towards 2050 for the Dutch industry. It compares four different process heat generation fuels and technologies as well as four hydrogen production alternatives to green hydrogen for hydrogen feedstock production, by using an altered levelized cost of energy method. The costs of these alternatives are based on a 25 year lifetime, assessed over investment in 2021, 2025, 2030 and 2035 with a commodity and CO2 price forecast up to 2065. The results are divided over two scenarios. Scenario I aims to demonstrate the real LCOE for green hydrogen alternatives at the time of investment and Scenario II compares the alternatives from 2021 to 2050 combined with business as usual costs up to the four investment moments. The results show the development of the economic competitiveness of green hydrogen based on the cost development of its alternatives over the coming years. The order of sectors where green hydrogen competitiveness is the highest are high temperature process heat generation, followed by hydrogen feedstock, medium temperature process heat generation and low temperature process heat generation in 2030. It can be seen that fuel costs are by far the largest part of the LCOE of all the alternatives that are assessed, which implies investment decisions ought to be made based on the expected fuel costs and not so much on overnight capital costs of investment. It can also be seen that for the majority of all investigated investment moments for the two scenarios, that the most economically sound investment options simultaneously is the option that contributes most in terms of pollution through CO2. This is a prudent indication that the current free market forces unfortunately do not aid the transition towards a lower polluting industry without nudging or pushing them into the right direction. This implies that well directed policy measures are vital to free market forces to take the first step towards lower pollution. With this research a contribution to science is delivered in assessing and implementing suggestions for improving the LCOE method as well as using the LCOE for process heat generation and hydrogen feedstock production, when comparing fossil fuels with sustainable energy sources across various industrial sectors. A comprehensive overview of the research green hydrogen alternatives presents insights in costs corresponding to four different investment moments for the Dutch industry.

In earlier times the climate crisis was ignored. However, these days it is acknowledged as one of the most important challenges the world is facing. With increased awareness of anthropogenic emissions, most sectors are changing rapidly. One of those sectors is the offshore wind energy sector. As a consequence of the Paris Climate Agreement, the European Commission adoptedan offshore renewable strategy that aims to install at least 60 GW of offshore wind by 2030 and up to 300 GW by 2050. With the increasing capacity of offshore wind being constructed, new wind farms will move gradually further offshore. This, therefore, requires a need for significant investments in large-scale wind farms and in the required grid infrastructure to be able to transmit the large amounts of electricity produced offshore to the consumers onshore.Thus the need for cost-efficient integration of the North Sea transmission arises. Currently, existing offshore wind farms are being investigated as potential gateways in order to achieve this offshore transmission network integration in a cost-efficient manner.In this master thesis project, the effects of various future connection schemes and market setups on the business cases of offshore wind farms were investigated. The study focuses on a location in the North Sea close with similar geographical characteristics as a large sandbank called the Doggerbank. First, a literature study was performed to obtain background knowledge about the offshore situation. Relevant assets were identified, multiple offshore gridtypologies were found and different offshore governance models and market setups have been identified. In addition, the theoretical background of constructing a business case for offshore wind farms from a Dutch and British perspective was explored. The main cost drivers were identified and can be distinguished in capital expenditures and operational expenditures. In addition, these cost categories were quantified in order to set up a business case for an offshore wind farmat a specified location. The cost category taking up most of the investment was found to be the grid connection, taking approximately 30% of the total investments. In addition, British built wind farms require more initial investment with respect to the Dutch wind farms, due to a difference in governance models between the countries. Next, the methods by which a wind farm can collect income was explored. Various categories were identified being; revenueby selling the commodity, power purchase agreement, financial support schemes and green certificates. Historical wind data was used to determine a wind profile. In addition, the historical market data was added to quantify the cash flow of an offshore wind farm. Last, an expression of the Levelized Cost of Energy (LCOE) was found for a Dutch and British constructed offshore wind farm respectively.To obtain insights into the effects of the North Sea transmission integration on the business case of offshore wind farms, a scenario-based modelling & simulation approach was adopted. First, a conceptual model has been developed. This was done by, first, identifying the situationin which the problem occurs and second, determining the modelling scope. Next, the in- and outputs were explained and the simplifications used for the model were presented accordingly. Various scenarios were developed in order to be able to simulate distinct future situations in which a wind farm may be required to operate. These system changes are predominantly caused by different connection scenarios or by a change in market setups. First, a base model was developed, to understand the basic operations of a wind farm. Next, the reference case using a Dutch and British wind farm connected to their own national electricity market was simulated that represents the current situation of existing offshore wind farms. Then, a cross-border connection was added to the reference case under the current home market setup. Subsequently, a change in market setup, the offshore bidding zone, was introduced.The first insights were obtained through simulation of the reference case, which represents the current situation. Large wind farm projects far from shore were found to be most likely still dependent on support through subsidy schemes. This holds for both a Dutch and British perspective regarding the construction. The first scenario on which the effects were simulated, describes a situation in which a connection to a foreign market is introduced to the reference case. The results of these simulations show no substantial changes in the cash flow of theoffshore wind farms. However, large amounts of costs imposed on society were identified under this scenario. When the offshore bidding zone was introduced as a new market setups in a cross-border connection various results were found. First, for a Dutch wind farm in this connection and under this market setup, the revenues tent to increase with respect to the reference case. However, for a British wind farm a clear decline in the collected revenues by the wind farm developers was observed. Nevertheless, due to the regulatory conflicts thatwere identified in the cross-border connection scenario under the current home market setup, a change to the offshore bidding zone market setup seems desirable. This implies that under current regulation, the offshore bidding zone market setup shows no issues being compliant with EU legislation and National regulation.An additional step was performed in this master thesis project, that adopts the objective to identify instruments that could mitigate these declines in revenues under an offshore bidding zone market setup. These instruments are regarded as mitigation options or mitigation schemes. The academic method of a policy scorecard was adopted, and additional desk research was performed to identify current proposals for mitigation schemes in the literature. Eight mitigation schemes were found from which seven were applicable to an offshore biddingzone market setup. These could be distinguished into support through operations and through regulatory changes. It was found that, within the scope of this research, which is looking into the economic effects and the feasibility of the identified mitigation schemes, the Contract for Difference scheme seems to be the best choice as it provides stability for the wind farm developers, and is the most cost-efficient option with respect to society. Good alternatives were identified to be the redistribution of congestion income and granting windfarm developers a so-called "Transmission System Operator -light" certificate that allows for a share in the congestion income. However, there is a broader political impact, in terms of financial budget requirements on a member state level, general public support for support schemes and overall effectiveness of support schemes in broader policy objectives. As a consequence, it is recommended for future research to further investigate different domains than the economically and feasibility domains that have been presented in this research. In order to solve the current issue, thesedomains require additional investigated to obtain this broader perspective and to eventually be able to make political decisions.

With increased awareness of anthropogenic emissions, industries and sectors worldwide are changing rapidly. One of those sectors is the transport sector which has seen immense change with the increase of electric vehicles in recent years. Although these electric vehicles reduce emissions and are a welcoming sign of change, they greatly increase electrical demand, especially on the residential distribution grids. Case studies and research on demand response with EVs has been increasing over the last years in an attempt to reduce this load impact. This thesis aims to explore how the charging load of a large EV fleet impacts the distribution grid of the capital region in Iceland and how it can be minimised with demand response strategies. A load model was created for the distribution grid and the results indicate that large-scale EV penetration can have a huge load impact. Furthermore, the results showed that demand response strategies can greatly reduce that impact and offer significant peak reductions. However, based on a bottom-up approach, the lower levels of the distribution grid seem to be worst affected, with and without demand response strategies. Future research should be focused on mapping these local grid effects and conducting more in-depth analyses on that level.

Germany aims to compose 65 % of its electricity mix with renewable energy by
2030. Thus, it relies on onshore wind energy as a source. This industry has experienced a significant turmoil from 2017 to 2019 as the newly installed capacity dropped by 80 % within these two years. The public discussion sees an increase in lawsuits caused by low public acceptance as the reason for this behaviour. Action is demanded in form of a simplification of the permitting process of the wind energy projects and an increase in public support mainly by involvement of the community adjacent to the planned wind park or increased distance between projects and habitants. Even though these are noble requests, calling public acceptance as the only reason for the decrease in installed capacity does not seem plausible. Interestingly, 2017 coincides with the adoption of a new subsidization scheme which includes a bidding process. Since wind energy projects are private investment projects, their finances are key to success. The aim of this study is to gain understanding about the reasons of the slump and develop an alternative hypothesis. A literature review summarizes the legal, political, social, and technological landscape for onshore wind energy. A detailed synthesis of public acceptance literature is performed and understanding of the financial dependencies and influences related to wind energy projects is gained. To support the reasoning, a model is constructed which simulates the income and expenses of wind energy projects. A participation in the bidding process is simulated including a detailed calculation of interest rates, an approximation of the impact of an increasing wind turbine population and an estimation of the development of the turbine maintenance sector. The findings of this study are threefold. First, it summarizes in detail all financial aspects of onshore
wind energy projects. As a result, it is concluded that the maximum bid is set too low and the subsidization scheme is not adapted to the financial needs of a project. As a consequence, not enough sites are built even though they could technically be available, resulting in the slump. Secondly, with the current constrains of the bidding process, the onshore wind energy sector will remain in a slump and the 2030 goal set by the German government cannot be reached as projected technological advancements have a small effect. The slump also forces the wind energy sector into a recession. Since any scenario of technological development cannot be relied on to counteract the slump, an adjustment of the subsidization scheme is needed. The most effective way to reach the objectives
is to increase the maximum bid. Thirdly, it is argued that the public acceptance
would have limited to no effect on the situation. The German government has three options. Either, (I) the maximum bid is raised or (II) reversed to the old subsidization both implying higher costs than desired or (III) other renewable energy sources have to be supported and the onshore wind energy sector will undergo major restructuring including possible job losses.

In 2017, Hurricane Maria proved how fragile Puerto Rico’s grid is to natural disasters. The consequence of this fragility was the longest power blackout in the history of the U.S., which affected 3.3 million people, lasted for 3.4 billion customer-hours, and resulted in economic losses estimated in 95 billion USD. The solution, then, is energy resilience, defined here as the overall ability of an electricity system to prevent, mitigate, and recover from wide-area, long-duration outages. Accordingly, the aim of this study is to quantify the value of the energy resilience that solar microgrids can provide to electricity users in Puerto Rico.

On the 22nd of April 2016, now also known as the ”Earth day”, the Paris Agreement has been brought to live. This agreement is constructed by all nations to fight together against a common enemy, namely climate change. Over the past few years it has become more difficult then ever before to ignore the effects of global warming. While species which have lived on the face of earth for over a thousand years are dying out, while natural disasters such as typhoons, tsunamis, extreme droughts and floods are drastically increasing in occurrence and while we measure new record years of climate change perceiving every year over the past decade it finally becomes inevitable to start taking measures to fight against climate change in order to allow humans and all other species living on this planet to survive. The Paris Agreement is one of the leading most respected agreement combating this cause, it bring together all the nations to sum up their efforts in order to try and mitigate and adapt the effects of climate change. The main goal of this act is to enforce the global response to the danger coming from the change in climate. To achieve this goal a target has been placed which states, the global temperature rise this century should stay well below 2 degrees Celsius. Every country has made its own individual pledge to help achieve the goal set by the Paris Agreement. Indonesia the 4th most populated country in the world is one of them. Indonesia is not only one of the most populous countries, but also one of the most polluting countries, with emissions coming from deforestation and enormous coal-fired power generation pipelines. Next to this, Indonesia’s location makes it highly vulnerable to the consequences of climate change. Therefore, Indonesia pledged to reduce it’s greenhouse gases, however up until now their targets have been rated as “Highly Insufficient”, meaning that they only show modest signs of improvement. The cause of this, is their development of coal fired plants, as they plan to build further 6 GW of such power plants by 2022 and around 27 GW by 2028. Therefore, it becomes inevitable to star moving the investments in coal for the next years towards renewable energy sources, such zero-carbon methods are for Indonesia to start the right pathway to attain the Paris Agreement and sustainable development. This is the reasoning behind the development of this research. However, since entire Indonesia seems like a too big of a challenge for one research. Therefore, this research aims at picking one of it’s islands and hoping that by designing an effective road map for the energy transition on this island will lead for others to follow. The island of choice has been Bali, a well knows and highly visited island in the archipelago. The target set by Indonesia are taken over for the case of the energy sector in Bali. These targets are the following, first a foremost a total greenhouse gas reduction of 11% by the energy sector compared to the reference scenario should be achieved by 2030. Second, to help meeting the first target a 23% penetration of renewable energy in the total electricity mix should be achieved by 2025. Last, these two targets should not hinder the expansion of the total capacity to satisfy the growing electricity demand at all time. From these targets and a literature review about energy transition on islands and renewable energy technology on islands the following main research question as been constructed: What plausible road map can ESDM follow, in order to accelerate the energy transition in Bali, while assuring that the demand is covered, to help Indonesia achieve their targets? In order to find the solution to this question four sub research question have been set up. These require the implementation of a system dynamics model. From the literature study and research done on similar islands which have already achieved a successful transition towards renewable energy, a total of 15 different scenarios have been constructed. These scenarios are possible outcomes of particular applications of 8 different policies, which the Ministry of Energy and Mineral Resources (MERM) or in Indonesian Energi dan Sumber Daya Minera (ESDM) has the power off to apply. First, a system analysis is given, which introduces all of the information required of the system, which is in this case the island of Bali and its electricity network. This analysis also demonstrates the current structure of the electricity network and explains why the transition of renewable energy is happening at such a slow pace. There are multiple reasons for this, ranging from cultural barriers to overcome as also geographical difficulties for the construction of renewable energy sources. In addition, there is also the issue that the balinese people are used to coal and oil powered electricity and see renewable technologies as methods coming along with a high risk. After the system analysis setting the boundaries of the complex system a road map development is introduced. In this chapter, it is explained how the different policies have to be applied, in order to construct the 15 different simulations of the future. This is followed by a chapter describing the model setup. First a conceptual model is designed including all of the mechanisms in work at the electricity network transition. The implementation of these feedback loops and of the policies into the system dynamics model is explained in great detail. Next to this, a table can be found in this chapter including all of the main input variables with the sources and assumption taken to determine their values. Before running the simulation with the final input variables, a verification and validation of the system dynamics model is demonstrated. This chapter verifies that the computerised model represents the conceptual model introduced before. Next, a validation testing if the simulation can support what it stands for is carried out. This has been done by investigating whether the main theories and assumptions elemental for the conceptual model are valid. In addition to this, the model is checked on errors and whether all of the units included in all of the equations are valid. At the end of this chapter a sensitivity analysis is executed. In this sensitivity analysis the different input variables are modified, in order to see the response on the output variables. This ensures that the system dynamics model representing the electricity network of Bali is indeed valid and can be use for further analysis. In the follow up chapter, the results of the different simulations are given and they are being compared to the main targets introduced at the beginning. From the total of 15 scenarios there are only 5 which meet the most important requirements. Therefore only these 5 scenarios are deployed into a trade-off table. The conclusion of this chapter is that the scenario S12+TE is the best choice for ESDM. This scenario represents a 24% growth rate of the solar PV sector stimulated by ESDM. Next to this, it requires a modification of the onsite oil fired power plants, so that they can run on cleaner fuel, namely liquefied natural gas. In addition to this, this scenario also requires to raise the taxes on fossil fuels, give out subsidies for solar PV projects, fix the land cost of farmland which has potential for solar farms and it includes an evolution of efficiency of photo voltaic cells from 17% to 30% within the next 10 years. This scenario would have a total cost of 2,050 million US dollars, to ensure them that they would achieve all of their targets by 2030. This result is then being reflected on in the final chapter, where some concluding remarks are given on the different results and methods. Next to this, several ideas are given to help improve any future follow up work on this research.

Electricity is a basic need in today`s society, being present in almost every aspect of life. The extensive infrastructure that transports electricity to the consumers, is expected to always work. At the same time there is a growing realism that the energy sector needs to modernise and ‘greenify’, in order to become more climate friendly. This is realised in the Netherlands by increasing the electricity produced by rooftop solar panels and wind parks.

Electricity produced by solar and wind depends on weather circumstances. Their production pattern is much more variable and uncertain than conventional fossil power plants. In order to maintain the balance on the electricity grid, an increased amount of balancing power is needed. For the Netherlands this is estimated to reach 15.2 TWh in the year 2050.

New sources of balancing power are also established by becoming more climate friendly. In the Netherlands the electrification of demand, results in gas fired boilers being replaced by heat pumps. Not just the established ground water based variant, but also the air based heat pump.
The heat pumps capability of providing balancing power is based on two aspects. First are the well-insulated houses in which they are installed. This reduces the cooling rate. Secondly is that residents generally do not experience any discomfort when the room temperature slightly deviates from their comfort temperature. And when they are absent, the room temperature may take any value.

Among the houses and residents where a heat pump is installed, differences can be found. Not everyone lives in a detached house, and not everyone is absent during the day. The effect of these differences on the demand response from a pool of heat pumps, is not known. This leads to the main research question:
“To what extent can a distinction in different residents and houses, increase the accuracy of demand response calculations for a Dutch heat pump pool?”

In order to answer the research question, a model based approach is chosen. The ISO 13790 modelling approach is selected, as it includes the following requirements:
1.Includes the comfort temperature of the resident
2.Includes the 4 MW participation requirement of the secondary reserve market
3.Allows the comfort temperature to change on an hourly basis
4.Allows for a distinction between different houses and residents
5.Includes the room temperature
6.Includes the air based heat pump`s dependency on the outside temperature
As a result of the 4 MW participation requirement, heat pumps need to be combined into a pool. An aggregator is tasked with controlling this pool, and offering the demand response to the market. It is the aggregator that must predict the demand response available from each heat pump. Distinguishing between the different houses and residents, should increase the accuracy of predictions.

The distinction between the different houses and residents programmed into the model, depends strongly on the information available about the region. The region chosen in this research is the Netherlands. For this region four different categories of houses have been identified, each with a different cooling rate.
•Detached house
•Semi-detached house
•Terraced house middle
•Terraced house corner

In case of the residents three different types have been identified. Each having a different comfort temperature and a different daily routine.
•The single
•The couple
•The family

Each of the three types of residents could live in any of the four categories of houses. All of the possible combinations have been included in the experiments. In the experiments the demand response available from the two types of heat pump has been calculated, in both the up- and downward direction. The demand response is here defined as the intentional deviation in the electric load, compared to the normal use of the heat pump.

The results of the experiments show that both types of heat pump are capable of keeping the house near to the comfort temperature. Between the two types of heat pump a significant difference was found. The air based variant is capable of providing more demand response, especially during the winter.

A significant difference was also found between the three different types of residents, and almost all of the four different categories of houses. With the exception of the semi-detached house and the terraced house middle, where no significant difference was found in the upward direction.

The conclusion is that by making a distinction between residents, houses and heat pumps the accuracy of calculations will increase.

The differences in the demand response available from each combination, effect the number of heat pumps needed for the 4 MW participation requirement. Depending on the time of day, the size of the pool would range between less than 10.000, and more than 180.000. It can be stated that it is not about finding the size of the pool that allows an aggregator to always participate. But it is about determining when an aggregator is capable of participating, based upon the pool he controls.

With the growing balancing power needed by 2050, heat pumps will be capable of providing part of the needed capacity. However, the balancing power offered fluctuates strongly depending on the time of day and season. Next to that, it will require large numbers of heat pumps in order to participate.

Uprising innovative technologies like blockchain and the Internet of Things are increasingly changing the energy domain. These disruptive technologies are becoming more mainstream as a result of media attention and are supported by large multinationals like Tesla and Google. This combined with the enormous CO2 emissions due to fossil fuels and increased number of black-outs has resulted in a growing societal need for self-owned and self-generated renewable energy. More and more communities are forming intending to produce their own energy and to sell their excess energy to their neighbours via local energy markets. This concept of local energy markets can theoretically be realised via the use of a blockchain. However, the manner in which and by whom this ideally shall be done is inconclusive. This research aimed to identify how the proposed business models are impacted by the blockchain facilitating local energy markets. This was done by stress testing the innovated business models against the identified uncertainties and scenarios that the blockchain and the transitioning energy domain bring forth. It was found that the business models of the Distribution System Operator and Supplier are despite several challenges feasible whereas the business model for the commercial/industrial prosumer is not and is advised to make a market entry at a later stage.