The thesis project outlined in this report aims to comprehensively assess and optimize methods for long-term power production estimation of hybrid PV-wind energy systems. Through practical case studies, this approach seeks to exemplify the challenges and opportunities inherent in such systems. The research is conducted within the Wind Technical Team of Akuo Energy, an independent French renewable energy producer, leveraging their extensive expertise in technologies, industry practices, and data processing. The primary objective is to evaluate the relevance of two key parameters used in Akuo’s internal estimation methods, focusing on their impact on long-term production and revenues within the context of hybrid PV-wind energy systems. These parameters include unavailability losses, modeled on an hourly basis using Markovian transition matrices, and interannual variability of resources, statistically modeled by randomly shuffling yearly production profiles of individual wind and solar plants. Python will be employed to generate hybrid production time series, incorporating the models for unavailability losses and interannual variability. This approach facilitates the creation of multiple scenarios for sensitivity analysis, allowing for the variation of parameters to compare the productivity and profitability of different scenarios. The study sheds light on the importance of employing realistic models to account for unavailability losses, revealing that simpler models tend to overestimate revenues from hybrid power plants systematically. Moreover, the research shows the impact of interannual variability of resources on both production and revenues, emphasizing the necessity of generating multiple scenarios to anticipate best and worst-case outcomes. Ultimately, the results of this study aim to assist the company on the necessity and relevance of using such models for calculating long-term production and revenues in future hybrid PV-wind projects, as opposed to current simpler methods. / Det avhandlingsprojekt som beskrivs i denna rapport syftar till att heltäckande utvärdera och optimera metoder för långsiktig kraftproduktionsestimering av hybrid PV-vindenergisystem. Genom praktiska fallstudier söker detta tillvägagångssätt att exemplifiera de utmaningar och möjligheter som är inneboende i sådana system. Forskningen utförs inom vindtekniska teamet på Akuo Energy, en oberoende fransk producent av förnybar energi, där man dra nytta av deras omfattande expertis inom teknik, branschpraxis och datahantering. Det primära målet är att utvärdera relevansen av två viktiga parametrar som används i Akuos interna estimeringsmetoder och fokuserar på deras påverkan på långsiktig produktion och intäkter inom ramen för hybrid PV-vindenergisystem. Dessa parametrar inkluderar otillgänglighetsförluster, modellerade på timbasis med hjälp av Markovska övergångsmatriser, och årlig variabilitet av resurser, statistiskt modellerade genom att slumpmässigt ordna årliga produktionsprofiler för enskilda vind- och solanläggningar. Python kommer att användas för att generera hybridproduktionsserier och inkludera modeller för otillgänglighetsförluster och årlig variabilitet. Detta tillvägagångssätt möjliggör skapandet av flera scenarier för känslighetsanalys, vilket gör det möjligt att variera parametrar för att jämföra produktiviteten och lönsamheten för olika scenarier. Studien belyser vikten av att använda realistiska modeller för att ta hänsyn till otillgänglighetsförluster och visar att enklare modeller tenderar att systematiskt överskatta intäkter från hybridkraftverk. Dessutom visar forskningen påverkan av årlig variabilitet av resurser på både produktion och intäkter och betonar nödvändigheten av att generera flera scenarier för att förutse bästa och sämsta fall. Slutligen syftar resultaten av denna studie till att bistå företaget när det gäller nödvändigheten och relevansen av att använda sådana modeller för att beräkna långsiktig produktion och intäkter i framtida hybrid PV-vindprojekt, jämfört med nuvarande enklare metoder.

<p>The purpose of this study is to develop a flexible computer tool to predict the power produced by a photovoltaic (PV) panel. The performance of the PV panel is dependent on the incident solar radiation and the cell temperature. The computer tool predicts voltage-current curves, power-voltage curves, and maximum power point values. Five different models are implemented to predict the temperature of the panel, and comparison between the different thermal models is good. A thermal capacitance approach that uses a simple relationship for the forced convection heat transfer coefficient is used to predict the cell temperature. Both the electrical and temperature models are verified through comparisons using PVWatts and validated by comparisons to measured values. The model is flexible in the sense that it can be applied to PV arrays of any size, at any location, and of different cell types. After being verified and validated, the model is used to investigate the effects of cooling on the photovoltaic panel to improve the panel efficiency and increase its power output. Typical results show that for every degree Celsius rise in temperature, the efficiency of the solar panel is reduced by 0.5%. The effect of cooling and the resulting increase in energy production in two different climatic zones are studied and discussed. </p>

The pandemic scenario caused by COVID-19 is an event with no precedent. Therefore, it<br>is a phenomenon that can be studied to observe how electricity loads have changed during the stayat-home order weeks. The data collection process was done through online surveys and using<br>publicly available data. This study is focusing on analyzing household energy units such as<br>appliances, HVAC, lighting systems. However, collecting this data is expensive and timeconsuming since dwellings would have to be studied individually. As a solution, previous studies<br>have shown success in characterizing residential electricity using surveys with stochastic models.<br>This characterized electricity consumption data allows the researchers to generate a predictive<br>model, make a regression and understand the data. In that way, the data collection process will not<br>be as costly as installing measuring instruments or smart meters. The input data will be the<br>behavioral characteristics of each participant; meanwhile, the output of the analysis will be the<br>estimated electricity consumption "kWh." After generating the "kWh" target, a sensitivity analysis<br>will be done to observe the electricity consumption through time and examine how people evolved<br>their load during and after the stay-at-home order.<br>This research can help understand the change in electricity consumption of people who<br>worked at home during the pandemic and generate energy indicators and costs such as home office<br>electricity cost kWh/year. In addition to utilities and energy, managers can benefit from having a<br>clear understanding of domestic consumers during emergency scenarios as pandemics. <br>

<div>In this paper various applications of axial tensile load, bending load, and rolling loading has been applied to a Copper Indium Gallium Diselenide (CIGS) Solar Cell to lean how it would affect the solar cell parameters of: Open circuit voltage (Voc), Short circuit current, (Isc), Maximum power (Pmax), and Efficiency (EFF), and Fill Factor (FF). These Relationships were found for with three different experiments. The first experiment the applies axial tensile stress is to a CIGS solar cell ranging from 0 to 200 psi with various strain rates: 0.0001, 0.001, 0.01, and 0.1 in/sec as well as various relaxation time: 1min, 5min, and 10 min while the performance of solar cell is measured. The results of this gave several trends couple pertaining the Voc . The first is that open circuit voltage increases slightly with increasing stress. The second is the rate of increase (the slope) increases with longer relaxation times. The second set of trend pertains to the Isc. The first is that short circuit current generally is larger with larger stress. The second is there seems to be a general increase in the Isc up to a given threshold of stress. After that threshold the Isc seems to decrease. The threshold stress varies depending on strain rate and relaxation time. The second set of experiments consisted of holding a CIGS solar cell in a fixed curved position while it was in operational use. The radii of the curved cells were: 0.41, 0.20, 0.16, 0.13, 0.11, 0.094, and 0.082 m. The radii were performed for both concave and convex cell curvature. The trends for this show a slight decrease in all cell parameters with decreasing radii, the exception being Voc which is not effecting, the convex curvature causing a slightly faster decrease than the concave. This set of experiments were also processed to find the trends of the single diode model parameters of series resistance (Rs), shunt resistance (Rsh), dark current (I0), and saturation current (IL), which agreed with the experimental results. The second experiment consisted of rolling a CIGS solar cell in tensile (cells towards dowel.) and compression (cells away from dowel) around a dowel to create internal damage. The diameter of the dowels decreased. The dowel diameters were: 2. 1.75, 1.25, 1, 0.75, 0.5, and 0.25 inches. This experiment showed similar trends as the bending one but also had a critical diameter of 1.75 in where beyond that damage much greater. Finally a parametric study was done in COMSOL Multiphysics® to examine how changes in the CIGS material properties of electron mobility (EM), electron life time, (EL), hole mobility 15 (HM), and Hole life time (HL) effect the cell parameters. The trends are of an exponential manner that converges to a given value as the material properties increase. When EL, EM, HL are very small, on the order of 10-4 times smaller than their accepted values, a transient like responses occurs.<br></div>

<p>The potential use of enzymes in industrial synthesis of epoxidized soybean oil has been limited through the high cost of the enzyme catalyst, in this work we evaluate the effectiveness of chemo enzymatic epoxidation of high oleic soybean oil (HOSBO) using lipase B from <i>Candida antarctica </i>(CALB) on immobilization support Immobead 150 and H₂O₂in a solvent-free system. Additionally, we evaluated the production decay rates for hydrolytic activity and epoxide product formation over consecutive batches to determine half-life of the enzyme catalyst. </p> <p> Batch epoxidation of HOSBO using CALB on 4wt% loading shows yields higher than 90% after 12 hrs. of reaction, and with a correlation to the consumption of double bonds suggesting that the reaction is selective and limiting side product reactions. Non-selective hydrolysis of oil was not found beyond the initial hydrolysis degree of raw HOSBO. Evaluations of decay given by epoxide product formation and released free fatty acids shows a half-life of the enzyme catalyst on these activities is of 22 ad 25 hrs. respectively. Finally, we evaluated the physical parameters influencing this decay, and found that H₂O₂ presence is the most important parameter of enzyme inactivation with no significant effect from its slowed addition. We propose a new reactor configuration for the analysis of the specific steps on epoxide formation through peracid intermediates. </p>

The transportation sector consumes around 70% of all petroleum in the US. In recent years, there have been improvements in the efficiency of the vehicles, and hybrid techniques that have been used to improve efficiency for conventional combustion vehicles. Hydraulic systems have been used as an alternative to conventional electric regenerative systems with good results. It has been proven that hydraulic systems can improve energy consumption in conventional combustion vehicles and in refuse collection vehicles. The control strategy has a large impact on the performance of the system and studies have shown the control strategy selection should be optimized and selected based on application. The performance of a hydraulic accumulator was compared with the performance of a set of ultracapacitors with the same energy storage capacity. The energy efficiency for the ultracapacitor was around 79% and the energy efficiency of the hydraulic accumulator was 87.7%. The power/mass ratio in the set of ultracapacitors was 2.21 kW/kg and 2.69 kW/kg in the hydraulic accumulator. The cost/power ratio is 217 US$/kW in the ultracapacitors and 75 US$/kW in the hydraulic accumulator. Based on these results, the hydraulic accumulator was selected as the energy storage device for the system. A testbench was designed, modeled, implemented to test the energy storage system in different conditions of operation. The experimental results of the testbench show how system can be actively controlled for different operating conditions. The operating conditions in the system can be adjusted by changing the number of rheostats connected to the electric generator. Different variables in the system were measured such as the angular shaft speed in the hydraulic pump, the torque and speed in the hydraulic motor, the pressure in the system, the flow rate, and the current and voltage in the electric generator. The control algorithm was successfully implemented, the results for the pressure in the system and the angular speed in the electric generator show how the control system can follow a desired reference value. Two different controllers were implemented: one controller for the pressure in the system, and one controller for the speed.

<p>In the US, seven regional transmission organizations (RTOs) operate wholesale electricity markets within three largely independent transmission systems, the largest of which includes five RTO regions and many vertically integrated utilities.</p> <p>RTOs operate a day-ahead and a real-time market. In the day-ahead market, generation and demand-side resources are optimally scheduled based on bids and offers for the next day. Those schedules are adjusted according to actual operating conditions in the real-time market. Both markets involve a unit commitment calculation, a mixed integer program that determines which generators will be online, and an economic dispatch calculation, an optimization determines the output of each online generator for every interval and calculates locational marginal prices (LMPs).</p> <p>The use of LMPs for the management of congestion in RTO transmission systems has brought efficiency and transparency to the operation of electric power systems and provides price signals that highlight the need for investment in transmission and generation. Through this work, we aim to extend these efficiency and transparency gains to the coordination across RTOs. Existing market-based inter-regional coordination schemes are limited to incremental changes in real-time markets. </p> <p>We propose a multi-regional unit-commitment that enables coordination in the day-ahead timeframe by applying a distributed approach to approximate a system-wide optimal commitment and dispatch while allowing each region to largely maintain their own rules, model only internal transmission up to the boundary, and keep sensitive financial information confidential. A heuristic algorithm based on an extension of the alternating directions method of multipliers (ADMM) for the mixed integer program is applied to the unit commitment. </p> The proposed coordinated solution was simulated and compared to the ideal single-market scenario and to a representation of the current uncoordinated solution, achieving at least 58% of the maximum potential savings, which, in terms of the annual cost of electric generation in the US, could add up to nearly $7 billion per year. In addition to the coordinated day-ahead solution, we develop a distributed solution for financial transmission rights (FTR) auctions with minimal information sharing across RTOs that constitutes the first known work to provide a viable option for market participants to seamlessly hedge price variability exposure on cross-border transactions.

<p>The purpose of this research was to determine what components of a complex centrifugal  compression system inlet needed to be modelled to accurately predict the swirl and total pressure  distortions at the compressor face. Two computational models were developed. A full-fidelity case  where all the inlet geometry was modelled and a reduced model where a small portion of the inlet  was considered. Both the numerical cases were compared with experimental data from a research  compressor rig developed by Honeywell Aerospace. The test apparatus was designed with a  modular inlet system to develop swirl distortion patterns. The modular inlet system utilized  transposable baffles within the radial-to-axial section of the inlet and blockage plates of varying  sizes and geometries at the inlet to this section.  Discerning the dominant inlet component that dictates distortion behavior at the compressor  face would allow the reduced modelling of inlet components for compression systems and would  allow coupling with more tortuous systems. Furthermore, it would reduce the design iteration and  simulation time of the inlet systems. Several investigations utilizing a reduced model only  considering a radial-to-axial inlet are available in literature, but no comprehensive justification has  been presented as to the impact this has on the distortion behavior.   Experimental surveys of flow conditions just upstream of the inducer of the centrifugal  compressor were conducted at several operating conditions. The highest and lowest mass flow  rates of these operating points were simulated using ANSYS CFX 2020R1 for both the  computational models. Multiple inlet configurations were simulated to test the robustness of the  reduced model in comparison to the full fidelity. The numerical simulations highlighted  shortcomings of the instrumentation used to characterize the experimental flow field at the inducer,  particularly with respect to total pressure distortion. Furthermore, transient pressure data were  measured in experiment and indicated unsteady fluctuations in the inlet that would not be captured  by steady computational fluid dynamic simulations. These data matched locations of disagreement  with swirl distortion behavior at high mass flow rates. This suggested that transient vortex  movement occured at the aerodynamic interface plane in certain configurations.   The total pressure distortion metrics between the two models were remarkably comparable.  Furthermore, the simplified model accurately predicted the mixing losses associated with the  blockage plates at the inlet to the radial-to-axial inlet using a simple inlet extension. Swirl  18  distortion was dictated by the radial-to-axial inlet. The reduced model data trends were comparable  with experiment for both the baffle and blocker plate configurations. The swirl intensities for all  configurations were comparable between the two models. The reduced model swirl directivity  trends matched those of experiment. The most notable deviations between the full-fidelity model  and the reduced model were observed with swirl directivity numerics. </p>

<div> Porous lithium ion battery (LIB) electrodes are comprised of electrochemically active material particles that store lithium and a surrounding conductive binder, liquid electrolyte, carbon black mixture that facilitates ionic and electronic transport. Typically, lithium diffusivity is several orders of magnitude smaller in the active material as compared to the surrounding electrolyte, making the electrode microstructure a governing factor in determining the balance between its lithium storage capacity and transport rate. Here, the effects of microstructure on the performance of LIBs are systematically analyzed at three length scales - the single particle length scale, the spatially resolved multiple particle length scale, and the porous electrode layer (homogenized) length scale. At the single particle length scale, a thermodynamically consistent variational framework is presented to examine the effects of crystallographic anisotropy, crystallographic texture, grain size, and grain morphology on the LiNi_1/3Mn_1/3Co_1/3O₂ (NMC111) chemistry. The theory was extended to the spatially resolved multiple particle length scale and the porous electrode layer length scale to explain the microstructural origin of experimentally observed instances of apparent phase separation in NMC111. At the electrode length scale, a data driven framework is presented to evaluate the electrochemical performance of a wide range of particle morphologies and battery architectures. Specifically, microstructural characteristics of 53 356 microstructures are assessed, and strategies to optimize electrode design parameters such as active particle morphology, spatial orientation, electrode porosity, and cell thickness are presented.</div><p></p>

<div>The manufacturing cost of solar cells along with their efficiency and reliability define the levelized cost of electricity (LCOE). One needs to reduce LCOE to make solar cells cost competitive compared to other sources of electricity. After a sustained decrease since 2001 the manufacturing cost of the dominant photovoltaic technology based on c-Si solar cells has recently reached a plateau. Further reduction in LCOE is only possible by increasing the efficiency and/or reliability of c-Si cells. Among alternate technologies, organic photovoltaics (OPV) has reduced manufacturing cost, but they do not offer any LCOE gain because their lifetime and efficiency are significantly lower than c-Si. Recently, perovskite solar cells have showed promising results in terms of both cost and efficiency, but their reliability/stability is still a concern and the physical origin of the efficiency gain is not fully understood.</div><div><br></div>In this work, we have collaborated with scientists industry and academia to explain the origin of the increased cell efficiency of bulk solution-processed perovskite cells. We also explored the possibility of enhancing the efficiency of the c-Si and perovskite cells by using them in a tandem configuration. To improve the intrinsic reliability, we have investigated 2D-perovskite cells with slightly lower efficiency but longer lifetime. We interpreted the behavior of the 2D-perovskite cells using randomly stacked quantum wells in the absorber region. We studied the reliability issues of c-Si modules and correlated series resistance of the modules directly to the solder bond failure. We also found out that finger thinning of the contacts at cell level manifests as a fake shunt resistance but is distinguishable from real shunt resistance by exploring the reverse bias or efficiency vs. irradiance. Then we proposed a physics-based model to predict the energy yield and lifetime of a module that suffers from solder bond failure using real field data by considering the statistical nature of the failure at module level. This model is part of a more comprehensive model that can predict the lifetime of a module that suffers from more degradation mechanisms such as yellowing, potential induced degradation, corrosion, soiling, delamination, etc. simultaneously. This method is called forward modeling since we start from environmental data and initial information of the module, and then predict the lifetime and time-dependent energy yield of a solar cell technology. As the future work, we will use our experience in forward modeling to deconvolve the reliability issues of a module that is fielded since each mechanism has a different electrical signature. Then by calibrating the forward model, we can predict the remaining lifetime of the fielded module. This work opens new pathways to achieve 2030 Sunshot goals of LCOE below 3c/kWh by predicting the lifetime that the product can be guaranteed, helping financial institutions regarding the risk of their investment, or national laboratories to redefine the qualification and reliability protocols.<br>