’Netto-noll utsläpp’ i EU vid 2050 är ett av målen för att påskynda övergången från fossila bränslen till mer förnyelsebara och hållbara alternativ. Detta har däremot introducerat mer turbulens på elnäten. Ett av verktygen för att reglera och förbättra eldistributionen är stor-skaliga batterier, där litium-jon är den mest förekommande kemin. Men på grund av oro kring resursutbud och hopp om teknologidiversifiering har det påbörjat en sökning efter alternativ som kan användas i stället eller tillsammans med litium-jon batterier. Från en lång lista så har tre alternativ med hög potential identifierats. Dessa är nickel-vätgasbatteri, zink-brom flödesbatteri och järn-luftbatteri. Deras lämplighet undersöktes och diskuterades för flertalet användningsområden och för ett speciellt användarfall av Vattenfall. Slutsatsen var att utav de tre, så är det endast nickel-vätgas som kan förväntas vara ett bra alternativ för specifika fall, att zink-brom har få möjligheter att konkurrera och att järn-luft har väldigt hög potential men också många oklarheter som gör det svårt att förutspå dess utveckling. / With net-zero emissions set to be achieved in the EU by 2050, the transition from fossil-based energy sources to more renewable and green options are ever expanding. This puts a strain on the electricity grids because of the intermittent nature from these energy sources. To mitigate this battery systems are used, of which the lithium-ion battery is the most prevalent, and expected to only increase in use. However, material resource concerns and possible danger of over-reliance on one technology has opened for a search to find other alternatives that could be used instead or in conjunction with the battery. Out of a long list of batteries, the nickel-hydrogen battery, zinc-bromide flow battery and iron-air battery are three alternatives that have been identified to have potential. Their suitability was researched and discussed for various grid-applications. The result show that out of the three, it is only believed that the nickel-hydrogen battery have a definitive competitiveness, that the zinc bromide flow battery has few things going for it, and that the iron-air battery has large potential but just as large uncertainty surrounding its future. Lastly, a specific off-shore wind park case was investigated to see the practicality and competitiveness of the nickel-hydrogen battery compared to a specific lithium-ion chemistry.

The execution of the scientific applications on the Cloud comes with great flexibility, scalability, cost-effectiveness, and substantial computing power. Market-leading Cloud service providers such as Amazon Web service (AWS), Azure, Google Cloud Platform (GCP) offer various general purposes, memory-intensive, and compute-intensive Cloud instances for the execution of scientific applications. The scientific community, especially small research institutions and undergraduate universities, face many hurdles while conducting high-performance computing research in the absence of large dedicated clusters. The Cloud provides a lucrative alternative to dedicated clusters, however a wide range of Cloud computing choices makes the instance selection for the end-users. This thesis aims to simplify Cloud instance selection for end-users by proposing a probabilistic machine learning framework to allow to users select a suitable Cloud instance for their scientific applications. This research builds on the previously proposed A2Cloud-RF framework that recommends high-performing Cloud instances by profiling the application and the selected Cloud instances. The framework produces a set of objective scores called the A2Cloud scores, which denote the compatibility level between the application and the selected Cloud instances. When used alone, the A2Cloud scores become increasingly unwieldy with an increasing number of tested Cloud instances. Additionally, the framework only examines the raw application performance and does not consider the execution cost to guide resource selection. To improve the usability of the framework and assist with economical instance selection, this research adds two Naïve Bayes (NB) classifiers that consider both the application’s performance and execution cost. These NB classifiers include: 1) NB with a Random Forest Classifier (RFC) and 2) a standalone NB module. Naïve Bayes with a Random Forest Classifier (RFC) augments the A2Cloud-RF framework's final instance ratings with the execution cost metric. In the training phase, the classifier builds the frequency and probability tables. The classifier recommends a Cloud instance based on the highest posterior probability for the selected application. The standalone NB classifier uses the generated A2Cloud score (an intermediate result from the A2Cloud-RF framework) and execution cost metric to construct an NB classifier. The NB classifier forms a frequency table and probability (prior and likelihood) tables. For recommending a Cloud instance for a test application, the classifier calculates the highest posterior probability for all of the Cloud instances. The classifier recommends a Cloud instance with the highest posterior probability. This study performs the execution of eight real-world applications on 20 Cloud instances from AWS, Azure, GCP, and Linode. We train the NB classifiers using 80% of this dataset and employ the remaining 20% for testing. The testing yields more than 90% recommendation accuracy for the chosen applications and Cloud instances. Because of the imbalanced nature of the dataset and multi-class nature of classification, we consider the confusion matrix (true positive, false positive, true negative, and false negative) and F1 score with above 0.9 scores to describe the model performance. The final goal of this research is to make Cloud computing an accessible resource for conducting high-performance scientific executions by enabling users to select an effective Cloud instance from across multiple providers.

The unpredictability and variability of wind power generation can pose an economical risk to the wind power producer when participating in the day-ahead market and delivering the committed generation. These risks come from the creation of imbalances due to a mismatch between the sold and real generation fed to the grid. Energy Storage System (ESS) are a good solution for the wind power producer to plan the operation of the wind farm once the day-ahead market prices are cleared. However, depending on the price forecasts and wind generation, one type of storage technology might be more optimal than others. This is due to the fact that lithium-ion batteries have costs, power and energy ratings and limits that differ from other ESS (vanadium redox flow batteries, supercapacitors, pumped hydro or even other lithium-ion batteries with different chemistries). Hence, a multi-energy storage system technology solution can be proposed to be combined with a wind farm in order to both optimise the bids in the day-ahead market and to take part in current and emerging electricity markets. For this purpose, a mathematical model has been developed, and it provides the optimal bidding strategy to the day-ahead market and the most convenient operational planning for the energy storage systems. Based on the expected daily profits, a yearly stream of revenues is obtained and an overall techno-economical assessment is provided. The results show that, with the current capital costs of energy storage systems, the multi-ESS hybrid wind farm would recover the initial investment after 2-5 years depending on the ESS combinations. Moreover, the wind power producer would need an extra stream of revenues in order for it to be more profitable than the wind farm operating without storage blocks. / Den oförutsägbara och varierande vindkraftsproduktionen kan utgöra en teknisk och ekonomisk risk för vindkraftsproducenten när denne deltar i dayahead-marknaden och levererar den sålda energin. Dessa risker beror på att det uppstår obalanser på grund av bristande överensstämmelse mellan den sålda och den verkliga produktionen som matas in i nätet. Energilagringssystem (ESS på engelska) är en bra lösning för vindkraftsproducenten för att planera driften av vindkraftparken när priserna på dagen före marknaden är klara. Beroende på prisprognoserna och vindkraftsproduktionen kan dock en typ av lagringsteknik vara mer optimal än andra. Detta beror på att litiumjonbatterier har kostnader, effekt- och energimärkningar och gränser som skiljer sig från dem som gäller för vanadiumredoxflödesbatterier, superkondensatorer, pumpad vattenkraft eller till och med andra litiumjonbatterier med olika kemiska sammansättningar. Därför kan man använda en teknisk lösning med olika typer av energilager som kombineras för att både optimera budgivningen på day-ahead-marknaden och för att delta i nuvarande och nya elmarknader. För detta ändamål har en matematisk modell utvecklats som ger den optimala budstrategin för day-ahead-marknadenochdenmestpraktiskadriftsplaneringen för energilagringssystemen. På grundval av de förväntade dagliga vinsterna erhålls en årlig intäktsström och en övergripande teknisk-ekonomisk bedömning görs. Resultaten visar att med de nuvarande kapitalkostnaderna för energilagringssystem skulle återbetalningstiden för en vindkraftpark med flera olika energilager vara 2-5 år beroende på vilka energilager som kombinerats. Dessutom skulle vindkraftsproducenten behöva en extra intäktsström för att bli mer lönsam än en vindkraftpark som drivs utan lagringsblock.

Renewable energy for energy production, like Solar, is turning out to be very pertinent in today's world [1]. It is very clear that Solar Energy is going to emerge as one of the key sources of energy in future. Moreover, the storage option is going to play an essential role to the future deployment of solar power plants. Concentrated solar power plants with thermal storage, photovoltaic plants integrated with battery energy storage, and hybrid plants are attractive solutions to obtain a stable and dispatchable energy production. Investors or policymakers usually find it challenging to come up with the most feasible solar storage technology because they need to consider techno-economic feasibility, and at the same time, from a market or administrative perspective as well. So, this thesis study will address the key problem which is aimed at investors or policymakers since there is a need to choose the best solar storage technology at a utility level in future based on so many attributes. The thesis project was carried out in two phases which includes forecast modelling & estimations and techno-economic assessment of virtual plants. These two phases helped to address various questions in relation to the problem statement of this study. The entire thesis study broadly covered seven countries spanning across four major regions around the world. The first phase of the thesis, forecast modelling estimations shows how the seven countries will look in future (2020 – 2050) with respect to installed capacity and costs for PV, CSP, and BESS technologies. Some major results from phase 1 include, in low-cost estimates, China will remain to be the market leader in PV & CSP by 2050. In U.S.A and India, the installed costs of PV are projected to decline by 70% by 2050. By 2050, the installed costs of Solar Tower technology are estimated to drop by about 65% in China and Spain. In U.S.A, the prices of BESS technology are likely to fall by around 58 – 60 % by 2050. In the second phase of thesis study, a techno-economic evaluation of virtual plants addressed the aspects which are to be considered for a solar project if it is deployed in future across seven specific countries. Results from this analysis helps investors or policymakers to choose the cheapest solar storage technology at a utility level across seven specific countries in future (2020 – 2050). Key results from this analysis show that, in the U.S.A, by 2050, PV+BESS will be the cheapest storage technology for 4 – 10 storage hours. Addition of another renewable technology will add up more viability to the comparison. In China, Hybrid will be the cheapest storage technology for 4 – 8 hrs by 2050. There is huge potential for deployment of CSP & hybrid plants in future than PV. In South Africa, CSP will be the cheapest storage technology by 2050 for 4 – 10 hours of storage. It is assumed that deployment of BESS projects at utility level starts from 2025 in South Africa. Beyond this, market forces analysis was carried out which offers insights especially for the policymakers of how various drivers and constraints are influencing each solar technology across the specific countries in future. Overall, the entire thesis study provides guidelines/insights to investors or policy makers for choosing the best solar storage technology in future at a utility scale for a particular country. / Förnybar energi för energiproduktion, liksom Solar, visar sig vara mycket relevant i dagens värld [1]. Det är mycket tydligt att solenergi kommer att framstå som en av de viktigaste energikällorna i framtiden. Dessutom kommer lagringsalternativet att spela en väsentlig roll för den framtida distributionen av solkraftverk. Koncentrerade solkraftverk med värmelagring, solcellsanläggningar integrerade med batterilagring och hybridanläggningar är attraktiva lösningar för att få en stabil och skickbar energiproduktion. Investerare eller beslutsfattare brukar tycka att det är utmanande att komma på den mest genomförbara solcellstekniken eftersom de måste överväga teknikekonomisk genomförbarhet, och samtidigt, ur ett marknads- eller administrativt perspektiv också. Så denna avhandlingsstudie kommer att ta itu med nyckelproblemet som riktar sig till investerare eller beslutsfattare eftersom det finns ett behov av att välja den bästa solenergilagringstekniken på en användningsnivå i framtiden baserat på så många attribut. Avhandlingsprojektet genomfördes i två faser som inkluderar prognosmodellering och uppskattningar och teknikekonomisk bedömning av virtuella anläggningar. Dessa två faser hjälpte till att ta itu med olika frågor i samband med problemstudien i denna studie. Hela avhandlingsstudien omfattade i stort sju länder som sträcker sig över fyra stora regioner runt om i världen. Den första fasen i avhandlingen, prognosmodelleringsuppskattningar visar hur de sju länderna kommer att se ut i framtiden (2020 - 2050) med avseende på installerad kapacitet och kostnader för PV-, CSP- och BESS -teknik. Några viktiga resultat från fas 1 inkluderar, i lågkostnadsuppskattningar, att Kina kommer att vara marknadsledande inom PV och CSP år 2050. I USA och Indien beräknas de installerade kostnaderna för PV minska med 70% år 2050. Av 2050 beräknas de installerade kostnaderna för Solar Tower -teknik sjunka med cirka 65% i Kina och Spanien. I USA kommer priserna på BESS -teknik sannolikt att sjunka med cirka 58 - 60 % år 2050. I den andra fasen av avhandlingsstudien behandlade en teknikekonomisk utvärdering av virtuella anläggningar de aspekter som ska övervägas för ett solprojekt om det används i framtiden i sju specifika länder. Resultaten från denna analys hjälper investerare eller beslutsfattare att välja den billigaste solenergilagringstekniken på en användningsnivå i sju specifika länder i framtiden (2020 - 2050). Viktiga resultat från denna analys visar att i USA, år 2050, kommer PV+BESS att vara den billigaste lagringstekniken på 4 - 10 lagringstimmar. Tillägg av en annan förnybar teknik kommer att öka jämförbarheten. I Kina kommer Hybrid att vara den billigaste lagringstekniken i 4-8 timmar fram till 2050. Det finns en enorm potential för distribution av CSP & hybridanläggningar i framtiden än PV. I Sydafrika kommer CSP att vara den billigaste lagringstekniken år 2050 för 4 - 10 timmars lagring. Det antas att distributionen av BESS -projekt på verktygsnivå börjar från 2025 i Sydafrika. Utöver detta genomfördes marknadskravsanalys som ger insikter speciellt för beslutsfattarna om hur olika drivkrafter och begränsningar påverkar varje solteknik i de specifika länderna i framtiden. Sammantaget ger hela avhandlingsstudien riktlinjer/insikter till investerare eller beslutsfattare för att välja den bästa solenergitekniken i framtiden i en nyttoskala för ett visst land.

The integration of renewable energy sources (RES) into local energy distribution networks becomes increasingly important. Renewable energy highly depends on weather conditions, making it difficult to maintain stability in such networks. To still enable efficient planning and balancing, forecasts of energy supply are essential. However, typical distribution networks contain a variety of heterogeneous RES installations (e.g. wind, solar, water), each providing different characteristics and weather dependencies. Additionally, advanced meters, which allow the communication of final-granular production curves to the network operator, are not available at all RES sites. Despite these heterogeneities and missing measurements, reliable forecasts over the whole local distribution network have to be provided. This poses high challenges on choosing the right input parameters, statistical models and forecasting granularity (e.g. single RES installations vs. aggregated data). In this paper, we will discuss such problems in energy supply forecasting using a real-world scenario. Subsequently, we introduce our idea of a generalized optimization approach that determines the best forecasting strategy for a given scenario and sketch research challenges we are planning to investigate in future work.

In this thesis, we explore the potential of financing a fast charging system with energy storage by delivering ancillary services from the energy storage in an optimal way. Specifically, a system delivering frequency regulation services FCR-D Up and FCR-D Down in combination with energy arbitrage trading is considered. An optimization model is developed that could be implemented operationally and then used in a Monte-Carlo simulation to estimate the net present value of the system for four identified cases at three different energy market price scenarios. The main modeling approach is to formulate the system as a state-space model serving as the foundation for model predictive control, with the delay between decision and delivery of the frequency regulation services incorporated as a part of the system state. The optimization of the system is implemented using a dynamic programming approach with a time horizon of 48h, where the choice of admissible controls is optimized for computational efficiency. The result shows that the system could profitable under optimal operation, but it is heavily dependent on the size of the grid connection, future price levels for ancillary services, and the nature of fast-charging demand. As such, the business case and profitability should be evaluated with a specific use case in mind. The developed model showed relatively good computational efficiency for operational implementations with a run time for one iteration of the optimization problem of 15 seconds. The model could therefore be used as the foundation for future research within the specific field and for similar control problems considering delayed controls and stochastic demand. Several proposed improvements and suggested areas of future research are proposed. / I den här uppsatsen utforskar vi huruvida det är finansiellt lönsamt att leverera snabbladdning från ett energilager samtidigt som energilagret används för att leverera systemtjänster på ett optimalt sätt. Mer specifikt undersöks ett potentiellt system som levererar frekvensregleringstjänsterna FCR-D Up och FCR-D Down samt energiarbitragehandel. Vi utvecklar en optimeringsmodell som kan implementeras i ett fysiskt system och använder sedan modellen i en Monte-Carlo-simulering för att estimera nuvärdet av fyra olika systemkonfigurationer för tre olika prisscenarion. Den huvudsakliga modelleringsmetoden är att formulera systemet som en tillstånds-rum modell, som sedan används som grund för modellprediktiv styrning, där fördröjningen mellan beslut och leverans av frekvensregleringstjänster inkluderas som en del av systemets tillstånd. Optimeringen av systemet implementeras med en dynamisk programmeringsmetodik med en tidsram på 48 timmar, där valet av tillåtna kontroller optimeras för beräkningseffektivitet. Resultatet visar att systemet kan vara lönsamt under optimal drift, men det är starkt beroende av storleken på nätanslutningen, framtida prisnivåer för systemtjänster och typen av snabbladdningsbehovet. Därför bör lönsamheten utvärderas för varje specifikt fall. Den utvecklade modellen visade relativt god beräkningseffektivitet för praktiskt implementation med en körtid för en enskilt iteration på 15 sekunder. Modellen kan därför användas som grund för framtida forskning inom området och för liknande problem inom optimal styrteori som involverar fördröjda kontroller och stokastisk efterfrågan. Flera föreslagna förbättringar och områden för framtida forskning föreslås.

The electric power supply industry has evolved into one of the largest industries. Even though secure and reliable operation of the electric power system is fundamental to economy, social security and quality of modern life, the complicated power grid is now facing severe challenges to meet the high-level secure and reliable operation requirements. New technologies will play a major role in helping today's electric power industry to meet the above challenges. This dissertation has focused on some key technologies among them, including the emerging technologies of energy storage, controlled power electronics and wide area measurement technologies. Those technologies offer an opportunity to develop the appropriate objectives for power system control. The use of power electronics based devices with energy storage system integrated into them, such as FACTS/ESS, can provide valuable added benefits to improve stability, power quality, and reliability of power systems. The study in this dissertation has provided several guidelines for the implementation of FACTS/ESS in bulk power systems. The interest of this study lies in a wide range of FACTS/ESS technology applications in bulk power system to solve some special problems that were not solved well without the application of FACTS/ESS. The special problems we select to solve by using FACTS/ESS technology in this study include power quality problem solution by active power compensation, electrical arc furnace (EAF) induced problems solution, inter-area mode low frequency oscillation suppression, coordination of under frequency load shedding (UFLS) and under frequency governor control (UFGC), wide area voltage control. From this study, the author of this dissertation reveals the unique role that FACTS/ESS technology can play in the bulk power system stability control and power quality enhancement in power system. In this dissertation, almost all the studies are based on the real system problems, which means that the study results are special valuable to certain utilities that have those problems. The study in this dissertation can assist power industry choose the right FACTS/ESS technology for their intended functions, which will improve the survivability, minimize blackouts, and reduce interruption costs through the use of energy storage systems. / Ph. D.

This master thesis investigates the risks associated with Battery Energy Storage (BESS) projects to improve the insurance process for BESS projects in Sweden, aligning with the global shift towards renewable energy as mandated by the Paris Agreement. The primary objective of this report is to develop guidelines for small enterprises entering the BESS market, focusing on risk identification and stakeholder objectives to improve the insurance process. Some risks identified were a lack of knowledge and experience, unsatisfactory suppliers, and policy and regulatory uncertainties. Utilizing a system engineering approach, the study investigates the interactions and communication between stakeholders, including project developers, insurance brokers, and insurers. The research is conducted through interviews with these stakeholders and a comprehensive literature review. The findings highlight challenges in communication during the insurance process and identify key factors that project developers should consider to ensure smoother interactions, such as providing more detailed information about the requirements to receive insurance. The study reveals the unique challenges posed by the novelty of BESS technology in Sweden. It suggests that a standardized and improved insurance process for BESS projects can accelerate the adoption of renewable energy technologies. The study is delimited to the Swedish context, acknowledging that insurance market mechanisms and BESS technology implementations vary across different countries. The theoretical contributions include an analysis of insurance for BESS projects and an overview of the current insurance products available in the Swedish market. The practical contributions include a guideline for new BESS project developers with considerations they can take to ensure a smoother insurance process for their projects. / Denna masteruppsats undersöker de risker som är förknippade med projekt för batterienergilagringssystem (BESS) för att förbättra försäkrings processen för BESS-projekt i Sverige, i linje med den globala övergången till förnybar energi enligt Parisavtalet. Huvudmålet med denna rapport är att utveckla riktlinjer för småföretag som går in på BESS-marknaden, med fokus på riskidentifiering och intressenternas mål för att förbättra försäkrings processen. Några identifierade risker var bristande kunskap och erfarenhet, otillfredsställande leverantörer och osäkerheter i policy och regelverk. Genom att använda Systems Engineering undersöker denna studie interaktionerna och kommunikationen mellan intressenter, inklusive projektutvecklare, försäkringsmäklare och försäkringsbolag. Forskningen genomförs genom intervjuer med dessa intressenter och en omfattande litteraturstudie. Resultaten belyser utmaningar i kommunikationen under försäkrings processen och identifierar viktiga faktorer som projektutvecklare bör beakta för att säkerställa smidigare interaktioner, såsom att tillhandahålla mer detaljerad information om kraven för att få försäkring. Studien avslöjar de unika utmaningar som den nya BESS-tekniken medför i Sverige. Den föreslår att en standardiserad och förbättrad försäkrings process för BESS-projekt kan påskynda införandet av förnybar energiteknik. Studien är begränsad till den svenska kontexten och erkänner att försäkringsmarknadens mekanismer och BESS-teknikens tillämpningar varierar mellan olika länder. De teoretiska bidragen inkluderar en analys av försäkringar för BESS-projekt och en översikt över de nuvarande försäkringsprodukterna som finns tillgängliga på den svenska marknaden. De praktiska bidragen inkluderar riktlinjer för nya BESS-projektutvecklare med överväganden dekan ta för att säkerställa en smidigare försäkrings process för sina projekt.

Relational databases are the most popular databases used by enterprise applications to store persistent data to this day. It gives a lot of flexibility and efficiency. A process called database normalization helps make sure that the database is free from redundancies and update anomalies. In a Database-First approach to software development, the database is designed first, and then an Object-Relational Mapping (ORM) tool is used to generate the programming classes (data layer) to interact with the database. Finally, the business logic code is written to interact with the data layer to persist the business data to the database. However, in modern application development, a process called Code-First approach evolved where the domain classes and the business logic that interacts with the domain classes are written first. Then an Object Relational Mapping (ORM) tool is used to generate the database from the domain classes. In this approach, since database design is not a concern, software programmers may ignore the process of database normalization altogether. To help software programmers in this process, this thesis takes the theory behind the five database normal forms (1NF - 5NF) and proposes Five Class Normal Forms (1CNF - 5CNF) that software programmers may use to normalize their domain classes. This thesis demonstrates that when the Five Class Normal Forms are applied manually to a class by a programmer, the resulting database that is generated from the Code-First approach is also normalized according to the rules of relational theory.

Approved for public release; distribution in unlimited. / Future sea bases, such as the Maritime Prepositioning Force (Future), will serve as key distribution nodes and must be able to sustain forces ashore and selectively offload supplies from storerooms quickly and efficiently. Current MPF ships maximize the available cargo storage onboard and have little ability to selectively offload supplies. To make selective offload a reality, MPF(F) requires lower stowage densities and new technologies to efficiently move items, especially for those supplies needed in direct support of forces ashore. The difficult questions are how dense and in what configurations MPF(F) storerooms can be packed, and how items should be retrieved in order to selectively offload supplies and provide acceptable response time. We analyze the trade-off between storage density and mean retrieval time in a dynamic environment for different storage densities and configurations in notional storerooms aboard a future sea base. We examine two demand scenarios and two different retrieval rules to determine how each storage configuration responds to retrieval requests over time. Our results provide insight into the types of storeroom configurations that provide the best mean retrieval times and how a simple retrieval rule can significantly reduce mean retrieval time under certain demand conditions. / Lieutenant Commander, United States Navy