European Commission (2011) aims to reduce the greenhouse gas emission sby 85-95% by 2050 in comparison to 1990’s levels. Wave energy could be an important step to archiving this goal. This report aims to develop a quantitative risk assessment for the Uppsala University's wave energy converter. Failure rates have been collected from various databases and reports and have been processed accordingly in order to implement them in the risk analysis. CAPEX, OPEX and possible downtime windows have been estimated. A fault tree analysis (FTA) has estimated the total unavailability, unreliability and downtime. Furthermore an economical assessment model using Monte Carlo and the unreliability data from the FTA has been developed, estimating the expected LCOE and OPEX/WEC for parks consisting of 20, 100, and 200 WECs (wave energy converters). The result show that the O-ring seal has the largest impact on both the unavailability, and the economy of the OPEX/WEC. Second biggest contributor is the translator bearing failure. The study also shows that the CAPEX cost has to be reduced to make the LCOE competitive in comparison to other renewable sources. A comparison between the system unavailability and unreliability has also been done in terms of different component parameters.

Alltmer intermittent elkraft byggs idag i Sverige för att öka andelen förnybar el i energisystemet. Detta leder till mer ojämn elproduktion, vilket skapar problem i form av mer volatila och oförutsägbara elpriser. Ett sätt att dämpa effekten av den ökande intermittenta kraften är att använda förnybar vätgasproduktion som lastutjämning. På detta sätt kan vätgasen potentiellt bli en viktig del i den fossilfria energimixen. Att använda vätgas som energilager i en Power-to-Power-applikation (P2P) möjliggör även utnyttjandet av prisarbitrage på elmarknaden. Ett ökat klimatfokus har återuppväckt intresset för hur vätgasproduktion kan göras lönsamt. Några tecken på att satsningar sker är att flera länder satsar stora pengar på vätgastekniker och infrastruktur, där flertalet samarbeten över nationella gränser har etablerats.Denna studie syftar till att undersöka de tekno-ekonomiska förutsättningarna för produktion av förnybar vätgas där lönsamheten av arbitragehandel på elmarknaden Elspot bedöms. Detta innefattar en gedigen granskning av kommersiella tekniker lämpade för Linköpings energisystem, däribland elektrolys, ångreformering och bränslecell. Tre fall konstruerades med olika uppsättningar av ingående komponenter. Sedan utfördes en driftoptimering som tog fram övre och undre prisgränser för produktion respektive konvertering av vätgas mot spotpriset. Optimeringsverktyget Problemlösaren i Excel användes för att få fram dessa gränser. Visual Basic (VBA) användes sedan för att genomföra en lagersimulering som visualiserar lagersaldot för alla årets timmar. För att få fram kostnaden för varje kilogram producerad vätgas användes nuvärdesberäkningen Levelised Cost of Energy (LCOE), vilket även underlättade jämförelsen av de tre fallen. Vilka effekter i form av växthusgasutsläpp de olika anläggningarna medför utvärderades också genom beräkningssättet konsekvensanalys. Där jämfördes effekten i form av nettoutsläpp i koldioxidekvivalenter för integrering av respektive anläggning. Resultaten visar på att det finns kommersiella tekniker som kan integreras med det befintliga energisystemet på ett resurseffektivt sätt, däremot är de ekonomiska förutsättningarna inte lika bra och P2P-lösningarna är idag långt ifrån lönsamma. Anledningen tros vara en kombination av otillräckliga elprisfluktuationer samt låg total systemverkningsgrad (som högst 14%) för samtliga konstruerade fall. De årliga intäkterna från elförsäljningen motsvarar cirka 1 procent av de årliga kostnaderna för anläggningen, och LCOE landade på cirka 1500 kronor. Resultaten från investeringskalkyleringen visar på att en högre utnyttjandegrad leder till en lägre LCOE. Lagersimuleringen visar på att säsongslagring krävs för denna typ av anläggning då fluktuationerna inte är tillräcklig stora på en daglig, veckovis eller månatlig basis. Känslighetsanalys på LCOE och driftoptimeringen visar inte heller på lönsamhetsmöjligheter i P2P-fallen även vid gynnsamma justeringar på parametrarna investeringskostnad, elpris och verkningsgrad. Ur ett klimatperspektiv visar samtliga fall, med ett undantag, på en minskade växthusgasutsläpp i regionen.  Slutsatsen som dras av resultaten från fallstudien är att, trots goda tekniska förutsättningar och positiv inverkan på lokala växthusgasutsläpp, kan en P2P-applikation med vätgaslagring inte göras lönsam i en svensk kontext inom en nära framtid. Däremot visar ett Power-to-Gas-fall potential för lönsamhet, då dess investeringskostnad är mindre samt att systemverkningsgraden är högre. / More and more intermittent electric power is being built in Sweden today to increase the share of renewable electricity in the energy system. This leads to more uneven electricity generation, which creates problems in terms of more volatile and unpredictable electricity prices. One way to dampen the effect of the increasing intermittent power is to use renewable hydrogen production as load shedding. In this way, the hydrogen gas can potentially become an important part of the fossil-free energy mix. Using hydrogen as energy storage in a Power-to-Power application (P2P) also enables the use of price arbitrage in the electricity market. An increased climate focus has rekindled interest in how hydrogen production can be made profitable. Some signs that investments are taking place are that several countries are investing big money on hydrogen technologies and infrastructure, and collaborations across national borders have been established. This study aims to investigate the techno-economic prerequisites for renewable hydrogen production where the profitability of arbitrage on the Elspot market is explored. This comprises a thorough investigation of commercial technologies suited for Linköping’s energy system. Three cases where constructed with different component constellations. Then the operational strategy was optimised which generated a lower and upper price limit for production and conversion of hydrogen with input price data from Elspot. The optimisation tool in Excel was used in order to obtain these price limits. Visual Basic (VBA) was then used for storage simulation in order to get a perception of the storage development through all the hours of the year. The cost of every kilogram of hydrogen produced was then calculated through Levelized Cost of Energy (LCOE), which made the comparison of the three cases easier. The resulting greenhouse gas emissions when integrating the facilities in each case were also evaluated with a so-called impact analysis. The effect was compared in net emissions in carbon dioxide equivalents for an integration of each facility.     The results show that there are commercial technologies that can be integrated with the existing energy system in a resource efficient manner, whereas the economic prerequisites are not as good, where today’s Power-to-Power (P2P) solutions are not profitable. The reason seems to be the combination of insufficient spot price fluctuations and a low system efficiency (14% at best) for each case. The annual revenues correspond to 1 percent of the annual costs and that LCOE lands at about 1500 SEK. A higher utilization percentage of the plant shows a lower LCOE in the investment calculation. The storage simulation indicates that a seasonal storage is needed for this type of facility because of that the spot price fluctuations are not big enough on a daily, weekly or monthly basis. The sensitivity analysis made on the investment calculation and operational strategy also shows that there is no profitability in the P2P cases where parameters regarding investment cost, efficiency and electricity price were set optimistically. The Power-to-Gas case on the other hand shows potential for profitability, all because of lower total investment costs and higher efficiency. All cases except the case with steam methane reforming shows reductions in greenhouse gas emissions when integrated in the regional energy system.   The conclusion that can be drawn from the results in the case study is that, in spite of good technological prerequisites and a positive effect on local greenhouse gas emissions, a P2P-application with hydrogen storage cannot be made profitable in a Swedish context in the near future. However, a Power-to-Gas case shows potential for profitability because of its lesser investment cost and that the system efficiency is higher.

As part of Nigeria’s drive to increase electricity production capacity and shift to renewable sources, a new 50 MW photovoltaic (PV) plant is proposed for a town in north-west Nigeria. Rather than using conventional monofacial modules and fixed mounting, it is of interest to consider a selection of new technologies which are attracting growing attention in the global utility PV market. These can increase energy output, and could be used to advantage in this 50 MW plant. However, the technologies, namely bifacial modules and solar tracking, are more expensive than their conventional counterparts, while their relative performance depends on the latitude and climate of the plant location. Thus their economic benefit cannot be taken for granted. The aim of this study is to propose multiple designs for the 50 MW plant using different combinations of module and mounting technologies, finding their economic order of merit by estimating their respective levelised costs of electricity (LCOEs).Using the simulation software PVsyst, the electricity production of different plant layouts and component configurations was estimated. Key parameters such as tilt angle and pitch distance were varied in order to optimise each configuration of technologies. Having sourced economic data from the industry and literature, lifetime plant costs were calculated, which in combination with lifetime electricity production, were used to estimate the LCOE.As expected, results indicated that the optimum configuration was bifacial modules mounted on horizontal single-axis tracking (SAT), followed by monofacial modules on horizontal SAT. Fixed installations had greater LCOEs by a reasonable margin, while the LCOE difference between monofacial and bifacial modules on fixed mounting was within the error of the calculation, meaning this choice relies on more accurate input data. A sensitivity analysis allowed uncertainty in the results to be gauged, and highlighted the factors which most influence LCOE, so that efforts to increase profitability can be focussed in the right places. Finally, suggestions are offered to help optimise bifacial and tracking installations by comparison with conventional plants.The conclusions drawn herein will be specifically relevant to the Swedish developer and EPC contractor Svenska Solenergigruppen which, in due course, will submit a plant design proposal to the project developer of the 50 MW plant. However, it is hoped that this work will act as a guide for any EPC contractor or developer working on a utility PV plant in sub-Saharan Africa, allowing efficient design of an optimal system.

To meet the energy targets and improve the lack of power and higher prices in southern Sweden, the amount of electricity must increase, and alternative fuel sources be introduced. This thesis examines the techno-economic feasibility of offshore wind-hydrogen production in southern Sweden, depending on whether an onshore- or offshore hydrogen system is used, and how grid connection subsidies would affect this. New research and development regarding the subjects were analyzed and reviewed. A project that has currently applied for a permit in southern Sweden, Skåne Offshore Wind Park, was used as a case study where the information from the review and data from similar parks were used to determine the cost and production for the two different systems. The costs were then adjusted according to the three different subsidy scenarios: current with no subsidies, partial with sea cable and transformer costs removed, or a full subsidy scenario where only the internal grid cost remained to achieve feasible levelized costs for electricity and hydrogen based on a discount rate of 6% and a lifetime of 25 years. Finally, a sensitivity analysis was performed.   The results showed that market competitive electricity prices are only achieved with an onshore hydrogen system- and only if a full subsidy is introduced or if a best-case scenario is applied. In a worst-case scenario, no competitive electricity prices were achieved. For the offshore hydrogen system, the extra fuel system is too inefficient for electricity production. For hydrogen, prices were achieved within a reasonable price range of green hydrogen for all scenarios, where the onshore hydrogen system was 4% more advantageous. In a best-case scenario, competitive values ​​even against blue hydrogen were achieved for the offshore hydrogen systems and for the full subsidy onshore hydrogen system. For hydrogen, the offshore hydrogen system's hydrogen prices were competitive regardless of subsidies, however this system had the highest CAPEX and OPEX costs.   The results of the study underline the need for fixed conditions but also the necessity of introducing a full subsidy for the grid connection cost - or best-case scenario conditions - to encourage further offshore wind power development.

Floating offshore wind turbines show great potential within the energy industry, especially for deeper waters where traditional fixed-bottom turbines cannot be used. Offshore locations also offer stronger and more stable winds compared to onshore locations. The study explores the impact of the secondary machine efficiency on the electricity production in a Counter Rotating Axis Floating Tilting (CRAFT) wind turbine. The counter-rotating design holds promise for achieving high overall system efficiency.  MATLAB simulations show that it is possible to maintain a lower secondary machine efficiency without compromising stability. Reviewing two control systems confirms that using a robust control algorithm with optimized TSR ensures system stability in both high and low winds. A decrease in secondary electric machine efficiency from 97% to 93% resulted in a 0.03% reduction in annually generated electricity, whereas a similar decrease in primary electric generator efficiency led to a 1% reduction instead. Decreasing the secondary machine efficiency further to 83% resulted in a 0.1% reduction in annual generated electricity. Thus, the secondary machine's efficiency is shown to be less critical for the electricity production than the primary generator’s efficiency.  Choosing an asynchronous over a synchronous option as the secondary machine is economically advantageous since its lower efficiency of 83% instead of 97% does not significantly affect the electricity production. Moreover, the lower magnet cost for the asynchronous machines positively impacts economic metrics like LCoE, NPVI and payback period, making the asynchronous generator a more favourable economic choice. Further research areas to obtain higher accuracy include integrating differences in maintenance costs and conducting a more in-depth assessment of the investment costs associated with the two types of generators. Additionally, considering airflow losses around turbine blades and airflow interaction amongst the turbines could further enhance the model accuracy.

Wind energy technologies are considered to be among the most promising types of renewable energy sources, which have since attracted broad considerations through recent years due to the soaring oil prices and the growing concerns over climate change and energy security. In Kuwait, rapid industrialisation, population growth and increasing water desalination are resulting in high energy demand growth, increasing the concern of oil diminishing as a main source of energy and the climate change caused by CO2 emissions from fossil fuel based energy. These demands and challenges compelled governments to embark on a diversification strategy to meet growing energy demand and support continued economic growth. Kuwait looked for alternative forms of energy by assessing potential renewable energy resources, including wind and sun. Kuwait is attempting to use and invest in renewable energy due to the fluctuating price of oil, diminishing reserves, the rapid increase in population, the high consumption of electricity and the environment protection. In this research, wind energy will be investigated as an attractive source of energy in Kuwait.

Today’s carbon constrained world with its increasing demand for cheap energy and a fossil fuel intensive fleet of power producers is making carbon capture and storage (CCS) desirable. Several CCS technologies are under investigation by various research and development groups globally. One of the more promising technologies is oxy-fuel combustion, since it produces a CO2 rich flue gas which requires minor processing to meet storage condition requirements. In this study the economics of an advanced super critical oxy-coal power plant burning lignite, simulated in-house was assessed. A robust and user-friendly financial tool box has been developed with commonly acceptable default parameter settings. Capital, operation and maintenance costs were estimated along with corresponding levelized cost of electricity and CO2 avoidance costs calculated using the detailed financial model developed. A levelized cost of electricity of 131 $/MWhrnet along with a levelized CO2 avoidance cost of 64 $/tonne was estimated for an ASC oxy-coal power plant with CO2 capture. Also a levelized cost of electricity of 83 $/MWhrnet was estimated for an ASC air-fired coal power plant without CO2 capture capabilities as the base plant. The price of electricity was observed to increase from 83 $/MWhrnet to 131 $/MWhrnet translating into a 57% increase. The sensitivity of the overall economics of the process was assessed to several parameters. The overall economics was found sensitive to the choice chemical engineering plant cost index (CEPCI), capacity factor, size of power plant, debt ratio, fuel price, interest rate, and construction duration.

Today???s carbon constrained world with its increasing demand for cheap energy and a fossil fuel intensive fleet of power producers is making carbon capture and storage (CCS) desirable. Several CCS technologies are under investigation by various research and development groups globally. One of the more promising technologies is oxy-fuel combustion, since it produces a CO2 rich flue gas which requires minor processing to meet storage condition requirements. In this study the economics of an advanced super critical oxy-coal power plant burning lignite, simulated in-house was assessed. A robust and user-friendly financial tool box has been developed with commonly acceptable default parameter settings. Capital, operation and maintenance costs were estimated along with corresponding levelized cost of electricity and CO2 avoidance costs calculated using the detailed financial model developed. A levelized cost of electricity of 131 $/MWhrnet along with a levelized CO2 avoidance cost of 64 $/tonne was estimated for an ASC oxy-coal power plant with CO2 capture. Also a levelized cost of electricity of 83 $/MWhrnet was estimated for an ASC air-fired coal power plant without CO2 capture capabilities as the base plant. The price of electricity was observed to increase from 83 $/MWhrnet to 131 $/MWhrnet translating into a 57% increase. The sensitivity of the overall economics of the process was assessed to several parameters. The overall economics was found sensitive to the choice chemical engineering plant cost index (CEPCI), capacity factor, size of power plant, debt ratio, fuel price, interest rate, and construction duration.

Floating offshore wind power is a relatively new technology that enables wind turbines to float above the sea level, tied by anchors at the seabed. The purpose of this work is to develop an economic model for the technology in order to calculate the total cost of a planned wind farm. Cost data are retrieved from reports and academic journals available online. Based on these data, a model in Microsoft Excel is developed which calculates the Levelized cost of energy (LCOE) for floating wind power plants as a function of several input values. As an addition to this model, financing offshore projects are described using literature study and by doing interviews with three major companies, currently investing in offshore wind. As a result, the model allows the user to calculate Capital expenditures, Operating expenditures and LCOE for projects at any given size and at any given site. The current LCOE for a large floating offshore wind farm is indicated to be in the range of 138-147 £/MWh. The outline from interviews was that today there is no shortage of capital for funding wind projects. However, in order to attract capital, the governmental regulatory of that market has to be suitable since it has a crucial impact on price risks of a project.

<div>In a world of ever-increasing demand for energy while preventing adverse effects of climate</div><div>change, renewable energy has been sought after as a sustainable solution. To this end,</div><div>the last couple of decades have seen an advancement in research and development of solar</div><div>photovoltaic (PV) technology by leaps and bounds. This has led to a steady improvement</div><div>in the cost-effectiveness of solar PV as compared to the traditional sources of energy, e.g.,</div><div>fossil fuels as well as contemporary renewable energy sources such as wind and hydropower.</div><div>To further decrease the levelized cost of energy (LCOE) of solar PV, new materials and</div><div>technologies are being investigated and subsequently deployed as residential, commercial, and</div><div>utility-scale systems. One such innovation is called bifacial PV, which allows collection of</div><div>light from the front as well as rear surfaces of a flat PV panel.</div><div><br></div><div>In this thesis, we present a detailed investigation of bifacial solar PV farms analyzed across</div><div>the globe. We define the problem, explore the challenges, and collaborate with researchers</div><div>from academia and the PV industry to find a novel solution.</div><div><br></div><div>First, we begin by developing a multi-module computational framework to numerically</div><div>model a utility-scale bifacial solar PV farm. This requires integrating optical, electrical,</div><div>thermal, and economic models in order to estimate the energy yield and LCOE of a bifacial</div><div>PV system. The first hurdle is to re-formulate the LCOE so that the economist and the</div><div>technologist can collaborate seamlessly. Thus, we re-parameterize the LCOE expression</div><div>and validate our economic model with economists at the National Renewable Energy Lab</div><div>(NREL).</div><div><br></div><div>Second, we extend the existing optical and electrical models created for stand-alone</div><div>bifacial PV panels to models that can simulate a large-scale bifacial solar PV farm. This</div><div>brings the challenge of mathematically modeling solar farms and light collection on the rows</div><div>of PV panels elevated from the ground by taking into account the mutual shading between</div><div>the rows, reflections from the ground, and elevation-dependent light absorption on the rear</div><div>surface of the PV panels from several neighboring rows. Next, we integrate temperaturedependent</div><div>efficiency models to take into account the effects of location-dependent ambient</div><div>temperature, wind speed, and technology-varying temperature coefficients of the solar PV</div><div>system in consideration.</div><div><br></div><div>Third, we complete the comprehensive modeling of bifacial solar PV farms by including</div><div>two types of single-axis tracking algorithms viz. sun-tracking and power tracking. Using these</div><div>algorithms, we explore the best tracking orientation of solar farms i.e., East-West tracking</div><div>vs. North-South tracking for locations around the world. We further find the best land type</div><div>suitable for installation of these E/W or N/S tracking bifacial solar PV farms.</div><div><br></div><div>Fourth, we reduce the computation time of numerical modeling by utilizing the advantages</div><div>of machine learning algorithms. We train neural networks using data from the alreadybuilt</div><div>models to emulate the numerical modeling of a solar farm. Amazingly, we find the</div><div>computation time reduces by orders of magnitude while accurately estimating the energy</div><div>yield and LCOE of PV farms.</div><div><br></div><div>Fifth, we derive, compare, and experimentally validate the thermodynamic efficiency</div><div>limits of photovoltaic-to-electrochemical energy conversion for the purpose of storing solar</div><div>energy for future needs.</div><div><br></div><div>Finally, we present some new ideas and guidelines for future extensions of this thesis as</div><div>well as new challenges and problems that need further exploration.</div>