In this thesis, a research project is conducted to help technical service providers (TSP) that are active in the energy transition of the industrial sector implement Product Service System (PSS) business models. An analytical framework is created to identify success factors for the implementation of PSS business models.

The rise of the so called Insurtechs, leveraging digital technologies to offer superior and personalized offerings, has shaken the insurance industry leading to a new age of innovation and business models. In addition, the importance of a digital customer experience is increasing as the number of sales completed online are rising. Customers expect wide availability of personalized options and offerings tailored to their specific risk scenarios. Traditional insurers should react fast to face the threat of new players and remain competitive in this fast-paced market environment. A customer-centric approach to digitalization is required to meet demanding requests from customers while targeting benefits including financial flexibility, lower Total Cost of Ownership (TCO), speed to market, and availability of information anywhere and at any time. Concurrently, the rise of cloud computing technologies spark interests in traditional players that have an opportunity to tackle these challenges by transforming their IT infrastructure to generate value for clients while substantially improving the enterprise’s operations. The aim of this document is to inspire the management to perceive the need for innovation and structural change and provide them with the tools and key recommendations to tackle the challenge. Besides, the literature is lacking contents weighting the cloud computing advantages in the insurance industry and exploring the business model’s innovations necessary to welcome the use of the cloud. Hence, the additional goal of this research, is to address this gap and explore the barriers hindering cloud adoption in the financial services industry together with the mitigation strategies expected to reduce such risk factors.

In the Netherlands more wind farms are constructed and energy is contracted in long-term Power Purchase Agreemenats (PPA) to guarantee a steady revenue stream for the wind farm owners. However, until now only large corporates closed PPA contracts to obtain the Renewable Energy Credits (RECs) from a wind farm and claim to be renewable. A new type of PPA is designed that has a direct link between the corporate and wind farm and transfers both power and the RECs. This direct trade PPA is analysed by applying an economic theory, the property rights theory, on the energy sector and by modelling the financial consequences. The result is a framework with the transactions, the risk allocation and the economic incentives of the actors involved. It shows more incentives to invest in renewable energy, moreover the corporate takes more volume risk on the energy production in order to obtain benefit which can be reduced by contracting a service provider. Furthermore, the financial model shows a significant financial benefit for a direct trade PPA compared to a traditional contract and shows a positive eect on the match between supply and demand. Moreover, the match and benefit can be increased by 25% by adding solar capacity in combination with wind energy. The next step is to further investigate this direct trade PPA and to promote this PPA type to corporates that want to invest in renewables and use this as a preferred contract type.

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

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.

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.

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.

Currently in the energy system of the Netherlands, lower level consumer demand flexibility is rather obsolete due to sufficient capacity limits of the distribution network and supply of capacity mechanisms by large industrial actors. However, in the upcoming 10- 20 years, the power system is in transition to become decentralised with a higher share of renewable energy sources and significant increase in consumption. An operational control structure in the power system, where private consumers provide flexible capacity, is an effective and economical efficient approach to make sure the regulated process of electricity generation to supply at consumers is secure and reliable. Currently as a result of the EU Energy Efficiency Directive of 2012, an institutional base is presented for development initiatives of demand response in Europe [17]. Technical and regulatory standards now enable demand response flexibility to be offered on the wholesale and retail energy market and allow for consumer participation [34]. Demand response schemes are usually distinguished by the various motivation methods offered to the participating consumers. Programs include in general two control methods, centralised direct load control or time-based and incentive-based DR. Because these schemes rely on demand response decision-making by means of a centralised (multi) aggregator perspective, direct load control can be precisely adjusted to technical (local) grid constraints [69]. Practically, the objective of DR in this research is used to reduce congestion in distribution grids by moving part of BEV energy demand from (evening) peaks to the afternoon or night with direct control. By achieving these measures potential benefits arise, including the most profound in the distribution grid [29]: • Optimising local grid assets by increasing the utilisation factor, and thereby maximise asset efficiency and subsequently decrease costs, which is beneficial for the DSO • Scheduling of peak charging demand to aid congestion in distribution grids. The modelling of the demand response charging strategies in Amsterdam fills the knowledge gap towards handling congestion for the DSO. It also provides a new study that addresses the potential to postpone future distribution grid investments by using charging strategies specifically for Amsterdam. The main research question that this study addresses is therefore: What is the value of demand response management in a Vehicle-to-Grid network and does it provide increased benefits to smart charging for consumers and the distribution system operator in Amsterdam? In order to grasp the subject of congestion prevention within the time limits of graduation, the scope of this study is limited to assess the first mentioned item by modelling charging demand, and subsequently simulate optimal demand response charging strategies for a case study in Amsterdam’s local power grid. The motivation for this study is threefold. Firstly, providing insight and recommendations in Amsterdam’s BEV charging demand to compute the potential to provide demand flexibility by making use of a large-scale charging sessions data (2017-2018). Literature that uses such a vast data set for Amsterdam is scarce. Therefore, typical demand behaviour for daily and seasonal variation or periodicity is assessed by using a method of time series analysis and local regression analysis to derive time- and load-flexibility parameters. These parameters de- scribe the measures for which demand response is generally defined. Secondly, a linear programming model is developed that optimises charging demand of smart charging and V2G charging strategies for demand response purposes to aid congestion at local feeders in the distribution grid of Liander. Lastly, an information-task exchange protocol is de- scribed from the perspective of a multi-aggregator to perform coordinated DR. Further investigation about the usable amount of flexibility is simulated with linear programming for charging strategies (smart charging and V2G charging) to aid in local feeder congestion. In this research a case study is performed on data of a low-voltage feeder under different congestion situations, and a range of different number of BEVS connected to explore future distribution grid implications. Results show that the model’s performance works especially well during peak demand periods throughout the day. In addition, the V2G strategy outperforms charged prices per kWh in almost every simulation compared to the uncontrolled scenario, by both charging during periods of low prices and discharging during periods of high prices even though the LP model does not optimise on prices. Thus, the V2G strategy allows the DSO to postpone grid investments in a number of cases while simultaneously the consumer almost always receives remuneration for its delivered services. The V2G strategy therefore provides a significantly added value over a smart charging strategy, by allowing electric vehicles to be charged whenever the feeder exhibits congestion. Future work includes analysis towards the value of DR in a liberalised system regarding the subject of the split-incentives challenge. Who initiates demand response (consumer, retailer, aggregator, DSO) and how should the benefits be divided along the supply chain. Handling an optimisation problem of DR for holds strong requirements for an global system balance in which neither participating actors are discriminated and the whole system benefits. An assessment of relational dependencies between participators in DR should be incorporated in designing charging strategies.

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.

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.

The thesis identifies critical implementation barriers to collective battery storage on business parks in the Netherlands. Subsequently, using a mixed methods research approach, different assessment frameworks are applied to propose three policy interventions that can overcome the identified critical implementation barriers and stimulate the adoption of collective battery storage in the Netherlands.

In the last decade, Mergers and Acquisitions (M&A) activity steadily enlarged, where global deal making continues to rise. While the M&A activity is increasing, it is the technology sector with the fastest growing number of transitions. Even though M&A are widely used for financial research purposes, there is plenty yet to be uncovered, particularly on an aggregate level and privately held high-tech firms. Europe offer a natural lab- oratory to study the determinant and consequences of mergers and acquisitions given essential variations in laws and regulations, institutions, traditions, and economic environments across countries, continents and over time. Interestingly, novel data has become recently available meaning that we can see how privately held target firms in Europe behave before and after the takeover. This thesis report focuses on understanding whether M&A affect target firm’s performance. The analysis is conducted on 689 European high-tech target firms, in which 95.26% are privately held, that were acquired in the period from 2011 to 2017. Target firm performance changes are tested with the inclusion of four key accounting performance indicators (e.g., Return on Assets, Operating Margin, Sales Growth and Net Profit), the difference in Intellectual Property measured by the number of patent applications, and three prominent quantitative research methods (Ordinary Least Square model, the Intercept model, and the Difference-in- Difference model). Including several approaches enhances the findings, overcomes weaknesses of the individual methods and addresses endogeneity concerns. Overall, the results clearly shows that target firms do not benefit from the M&A in terms of performance. In other words, the synergies did not benefit the target firm, whereas multiple potential M&A motives, including diversification, strategic gains, and market power did not lead to a better performance of the target firm. Interestingly, the results indicate that target firms in general tend to under perform to the adjusted con- trol group or their peer firms. The latter implies that acquired firms failed to keep up with the competition and confirm the fact that targets were in need of a way to strategically improve. Further, distinguishing evidence is found between domestic versus cross-border takeovers, whereas domestic deals outperform cross- border deals. Which proves it is easier to transfer assets between parent and subsidiary operating in the same country. Large enterprises perform better after the M&A compared to small and medium enterprises. M&A between SME are more likely to be financed with equity over debt which better process the transaction of tangible and intangible asset what could be in favour of the synergy exploitation’s. Also, findings suggest that large firm are more capable to exploit economies of scope and economies of scale. Firms that enclose a medium or high cultural distance outperform low cultural distance deals an not vice versa. This suggests that, taking into account the fact that bordering countries have similar cultural characteristics, greater cultural dimension between firms expose significant growth opportunities. Precisely be- cause long-distance target firms tend to have benefited substantially from the diffusion of the acquiring firms’ know-how, while taking into account that management and organisational styles are obviously significantly different between the two firms. In addition, target firms from the Anglo-Saxon region outperform target firms from the Rhineland region. Firms with an Anglo-Saxon corporate governance orientated firms conversely, are more likely to adopt strategic innovate projects on exploitation and external development. Whereas Rhineland corporate governance are more likely to adopt internal growth and exploratory as strategic renewal trajectories. Further, no compelling differences in performance are found for M&A in the same industry than across industries. In general, the findings presented in this paper provide new insights, while it also complements existing evidence, and on the other hand it contradicts former claims.

Today, shipping industry is a complex system involving multiple actors, multiple interests and intricate interactions occurring at different levels.With any disruption to interaction occurring there would be multiple impacts and accumulation of costs on individual actors operating in the system.Unless these risks are well understood and prioritized based on the situational demands, the businesses will find it difficult operate in such complex actor-intensive system.In energy industry, Risk Based optimization (RBO) approach has been in use to manage the large infrastructures and multiple assets. RBO approach has been effective in identifying and prioritising the risks affecting the performance of the assets.Research was thus taken up to investigate this idea and thereby to develop a risk based decision making (RBDM) approach for international shipping domain. Further, to improve visibility in supply chain, development of a large scale Digital Trade Infrastructure (DTI) called Data Pipeline is in progress under the project called CORE. This research also tried to evaluate the extent to which both the concepts could reinforce each other and improve the supply chain quality.In the process, a prototype of RBDM Tool was developed and used to analyze the trade lane of JamboFresh, a fruit importing company in the Netherlands. By coping with the challenges posed by RBO approach of energy industry, by narrowing down the limitations offered by current risk management practices, and by incorporating the relevant multi-actor theories a RBDM Appraoch was developed. Based on the findings and discussions several reccomendations were laid down.

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.

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.

The European policy focus on smart grids implies their development as an indispensable part of the future power system. However, the definition of a smart grid is broad and vague, and the actual implementation of a smart grid can differ significantly depending on the stakeholders involved. Smart electricity grids can be defined as electricity networks that can intelligently integrate the behaviour and actions of all end users connected to them – generators, consumers and those that are both – in order to efficiently ensure a sustainable, economic and secure electricity supply. This integration of behaviour is achieved through a two-way information and power exchange between suppliers and consumers using information technology.@en