Oberschwingungen als ein Merkmal der Elektroenergiequalität gewinnen durch die starke Netzintegration leistungselektronisch geregelter Anlagen wie Windenergieanlagen und nichtlineare Lasten zunehmend an Bedeutung. Bestehende Normen entsprechen nicht den zukünftigen Erfordernissen des Elektroenergiesystems und bedürfen diesbezüglich einer Überarbeitung. In der Arbeit werden wesentliche Einflussfaktoren auf das Oberschwingungsverhalten von Windparks identifiziert, beschrieben und modelliert. Dabei wird der stochastische Charakter der Oberschwingungen mithilfe von probabilistischen Ansätzen erfasst. Des Weiteren wird ein neuer Ansatz zur Untersuchung der Wechselwirkung zwischen dem Windpark und dem vorgelagerten Netz entwickelt. Der Ansatz ermöglicht, die vom Windpark verursachte Änderung der Oberschwingungsspannung am Netzanschlusspunkt zu ermitteln. Diese Arbeit liefert einen Beitrag zur Verbesserung bestehender Normen für die Anbindung von Windparks. / Harmonics, as one of the power quality criteria, are increasingly gaining attention due to the progressive contribution of renewable energy resources and the application of the nonlinear load in the power system. Current standards do not conform to the future requirements of the power system, thus requiring a revision. In this work, main influence factors on the harmonic behavior of wind farms are identified, explained, and modelled. Thereby, the stochastic nature of harmonics is taken into account using probabilistic approaches. Moreover, a novel approach is developed to investigate the interaction between the wind farm and the upstream grid. With the aid of this approach, it is possible to determine the voltage change caused by the wind farm at the point of connection. This work contributes to improve the existing standards for the connection of wind farms.

風力発電システムは、現在世界中で普及しているが、その地上高と立地条件からしばしば落雷の被害を受け、稼働率の低下が問題視されている。本論文は、垂直導体である風力発電タワーにおける雷サージ解析の高精度化、高速化を目的とした垂直導体回路解析モデルの提案、およびその有用性のについて述べるとともに、風力発電所や洋上風車への拡張性についてまとめたものである。 / 博士(工学) / Doctor of Philosophy in Engineering / 同志社大学 / Doshisha University

[pt] À medida que o mundo enfrenta a urgente questão das mudanças climáticas, a energia eólica se destaca como uma fonte crítica de energia limpa. No entanto, realizar seu pleno potencial depende da otimização dos layouts de parques eólicos, especialmente à luz do complexo efeito de esteira. Esta dissertação adentra na Otimização de Layout de Parques Eólicos (WFLO, na sigla em inglês) usando o Modelo de Efeito de Esteira de Bastankhah. O escopo deste estudo vai além do design de layout; abrange a intrincada tarefa de mitigar o impacto do efeito de esteira, juntamente com a busca por uma estratégia de negociação com aversão ao risco e maximização de valor. Para contabilizar a aversão ao risco, uma combinação entre o Valor Esperado e os funcionais de medida de risco baseados no quantil esquerdo, a medida de Valor em Risco Condicional (CVaR). Para apoiar esta pesquisa, um pacote de código aberto OptimalLayout.jl foi desenvolvido. Este pacote co-otimiza o posicionamento das turbinas eólicas para mitigar o impacto do efeito de esteira e a estratégia de contratação de um agente/gerador avesso ao risco. Através de uma série de estudos de casos práticos em diversos ambientes dinâmicos, esta pesquisa ilustra a aplicabilidade do WFLO no mundo real. Estas investigações examinam detalhadamente a sua influência na produção de energia e na dinâmica das receitas, oferecendo informações valiosas sobre soluções energéticas sustentáveis. / [en] As the world confronts the pressing issue of climate change, wind power stands out as a critical source of clean energy. However, realizing its full potential relies on the optimization of wind farm layouts, particularly in light of the complex wake effect. This dissertation delves into Wind Farm Layout Optimization (WFLO) using the Bastankhah Wake Model. The scope of this study goes beyond layout design; it encompasses the intricate task of mitigating the wake effect s impact along with the seek for a risk-averse-value maximizing trading strategy. To account for risk-averseness, a combination between Expected Value and the left-side-quantile-based risk-measure functionals, the Conditional Value-at-Risk (CVaR) measure. To support this research, an opensource package OptimalLayout.jl was developed. This package co-optimizes the positioning of wind turbines to mitigate wake effect impact,and the contracting strategy of a Risk-Averse agent/generator. Through a series of practical case studies across diverse dynamic environments, this research illustrates the real-world applicability of WFLO. These investigations intricately examine its influence on power production and revenue dynamics, offering valuable insights into sustainable energy solutions.

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.

It is well known that the layout of a large wind turbine cluster aects the energyoutput of the wind farm. The individual placement and distances betweenturbines will in uence the wake spreading and the wind velocity decit. Manyanalytical models and simulations have been made trying to calculate this, butstill there is a lack of experimental data to conrm the models. This thesis isdescribing the preparations and the execution of an experiment that has beenconducted using about 250 small rotating turbine models in a wind tunnel. Theturbine models were developed before the experiment and the characteristicswere investigated. The main focus was laid on special eects occurring in largewind turbine clusters, which were named Global Turbine Array Eects.It was shown that the upstream wind was little aected by a large windfarm downstream, even though there existed a small dierence in wind speedbetween the undisturbed free stream and the wind that arrived to the rstturbines in the wind farm. The dierence in wind speed was shown to beunder 1% of the undisturbed free stream. It was also shown that the densityof the wind farm was related to the reduced wind velocity, with a more densefarm the reduction could get up to 2.5% of the undisturbed free stream at theupstream center turbine. Less velocity decit was observed at the upstreamcorner turbines in the wind farm.When using small rotating turbine models some scaling requirements hadto be considered to make the experiment adaptable to reality. It was concludedthat the thrust coecient of the turbine models was the most important parameterwhen analysing the eects. One problem discussed was the low Reynoldsnumber, an eect always present in wind tunnel studies on small wind turbinemodels.A preliminary investigation of a photo measuring technique was also performed,but the technique was not fully developed. The idea was to take oneor a few photos instantaneously and then calculate the individual rotationalspeed of all the turbine models. It was dicult to apply the technique becauseof uctuations in rotational speed during the experiment, therefore thecalculated values could not represent the mean value over a longer time period.

Due to the increase in electrical demand and renewable penetration, electrical utilities need to improve and optimize the grid infrastructure. Fundamental components in this grid infrastructure are transformers, which are designed conservatively on the base of a static rated power. However, load and weather change continuously and hence, transformers are not used in the most efficient way. For this reason a new technology has been developed: Dynamic transformer rating (DTR). By applying DTR, it is possible to load transformers above the nameplate rating without affecting their life time expectancy. This project goes one step further and uses DTR for the short term and long term wind farm planning. The optimal wind farm is designed by applying DTR to the power transformer of the farm. The optimization is carried out using a Mixed-Integer Linear Programming (MILP) model. In respect of the transformer thermal analysis, the linearized top oil model of IEEE Clause 7 is selected. The model is executed for 4 different types of power transformers: 63 MVA, 100 MVA, 200 MVA and 400 MVA. As result, it is obtained that the net present value for the investment and the capacity of the wind farm increase linearly with respect to the size of the transformer. Then, a sensitivity analysis is carried out by modifying the wind speed, the electricity price, the lifetime of the transformer and the selected weather data. From this sensitivity analysis, it is possible to conclude that wind resources and electricity price are key parameters for the feasibility of the wind farm. / På grund av ökningen av efterfrågan av elektricitet och förnybara energin, elförsörgingsföretag måste förbättras och elnätets infrastruktur måste optimeras. Grundläggande komponenter i elnätet är transformatorer, som är designade konservativt efter en statisk märkeffekt. Laster och vädret ändras dock kontinuerligt, detta betyder att transformatorer inte används på de mest effektiva sätten. Av denna anledning har en ny teknik utvecklats: Dynamisk lastbarhet hos transformatorer (DTR). Genom att applicera DTR, gör det möjligt att belasta en transformator högre än märkdata utan att påverka den förväntade livslängden. Detta projekt går ett steg längre och använder DTR för kort och lång sikts vindkraftparkplaneringar. Den optimala vindkraftparken är designad genom att använda DLT på krafttransformatorn för vindkraftsparken. Optimeringen utförst med hjälp av Mixed-Integer Linear programming (MILP) modell. Gällande transformatorns termiska analys, så valdes den linjäriserade toppoljemodellen av IEEE Clause 7. Modellen var utförd för fyra olika krafttransformatorer: 63 MVA, 100 MVA, 200 MVA och 400 MVA. Resultatet blev att nettonuvärdet för investeringen och kapaciteten av vindkraftsparken ökade linjärt med avseende på storleken på transformatorn. En känslighetsanalys var utförd genom att ändra vindhastigheten, elpriset, livstiden av transformatorn och de valda väderdata. Från känslighetsanalysen så var det möjligt att dra slutsatsen att vindresurser och elpriset är nyckelparametrar för vindkraftsparkens genomförbarhet.

This research delves into the complex interplay between wind turbine operations and bat conservation efforts, focusing on mitigating bat mortality caused by wind turbines in France. Despite comprehensive legal safeguards and conservation measures, bat fatalities remain a pressing concern, necessitating innovative solutions to reconcile environmental protection with energy production. The problem statement revolves around the challenge of optimising bat curtailment plans to minimise bat mortality while mitigating energy losses. With over 80% of bat species in France affected by wind turbine collisions, the urgency of this issue is underscored by the significant ecological implications and regulatory imperatives. Despite the existence of curtailment plans, there is a lack of comprehensive understanding regarding their effectiveness and potential trade-offs. This problem warrants a Master’s thesis project due to its multifaceted nature and practical implications. It requires a nuanced understanding of bat behaviours, wind turbine operations, and regulatory frameworks, making it both intellectually stimulating and socially relevant. Previous efforts have largely focused on static curtailment plans, leaving room for exploration of dynamic approaches and optimisation strategies. The methodology employed in this study involves the development of a Power BI tool and key performance indicators (KPIs) to evaluate different curtailment plans. Through comparative analysis, insights are gained into the efficacy of static versus dynamic curtailment plans, as well as the influence of weather conditions, such as rain, on curtailment decisions. Additionally, sensitivityanalysis is conducted to identify the most influential parameters and optimise curtailment plans accordingly. The key results of this study demonstrate the superiority of dynamic curtailment plans in reducing energy losses while maintaining sufficient protection for bat activity (higher than the 90% protection rate required by law) compared to static approaches (50% reduction in losses over an entire curtailment season). Insights gleaned from sensitivity analysis highlight the critical parameters influencing energy losses, informing targeted modifications to curtailment plans. Furthermore, the study underscores the importance of considering continuous variables, such as humidity, and site-specific factors, such as sunrise and sunset times, for more precise conservation strategies. The implications of this research extend beyond academia, informing policy-making and industry practices in wind energy and biodiversity conservation. By optimizing curtailment plans, stakeholders can achieve a balance between environmental protection and renewable energy generation, paving the way for sustainable development. Future research avenues include refining curtailment strategies based on continuous variables and conducting field studies to validate findings across diverse wind farm locations. / Denna forskning utforskar det komplexa samspel mellan vindkraftverkens drift och fladdermusbevarande insatser, med fokus på att mildra fladdermusdödlighet orsakad av vindkraftverk i Frankrike. Trots omfattande lagliga skydd och bevarandeåtgärder förblir fladdermusdödsfall ett påtagligt bekymmer, vilket kräver innovativa lösningar för att förena miljöskydd med energiproduktion. Problemformuleringen kretsar kring utmaningen att optimera fladdermusbegränsningsplaner för att minimera fladdermusdödlighet samtidigt som energiförluster mildras. Med över 80% av fladdermusarterna i Frankrike påverkade av kollisioner med vindkraftverk, understryks brådskan i detta ärende av dess betydande ekologiska konsekvenser och reglerande krav. Trots att begränsningsplaner existerar, finns det en brist på en heltäckande förståelse för deras effektivitet och potentiella avvägningar. Detta problem motiverar ett magisterprojekt på grund av dess mångfacetterade natur och praktiska konsekvenser. Det kräver en nyanserad förståelse för fladdermusars beteenden, vindkraftverks drift och reglerande ramar, vilket gör det både intellektuellt stimulerande och socialt relevant. Tidigare insatser har i stor utsträckning fokuserat på statiska begränsningsplaner och lämnat utrymme för utforskning av dynamiska tillvägagångssätt och optimeringsstrategier. Metoden som används i denna studie innefattar utvecklingen av ett Power BI-verktyg och nyckelprestationsindikatorer för att utvärdera olika begränsningsplaner. Genom jämförande analys får man insikter om effektiviteten hos statiska jämfört med dynamiska begränsningsplaner, samt påverkan av väderförhållanden, såsom regn, på begränsningsbeslut. Dessutom genomförs känslighetsanalys för att identifiera de mest inflytelserika parametrarna och optimera begränsningsplanerna därefter. De viktigaste resultaten av denna studie visar överlägsenheten hos dynamiska begränsningsplaner när det gäller att minska energiförluster samtidigt som tillräckligt skydd för fladdermusaktivitet bibehålls (högre än den 90% skyddsnivå som krävs enligt lag) jämfört med statiska metoder (50% minskning av förluster under en hel begränsningssäsong). Insikter från känslighetsanalysen belyser de kritiska parametrarna som påverkar energiförluster och ger vägledning för målinriktade modifieringar av begränsningsplaner. Dessutom betonar studien vikten av att beakta kontinuerliga variabler, såsom luftfuktighet, och platsspecifika faktorer, såsom soluppgångs- och solnedgångstider, för mer precisa bevarandestrategier. Denna forsknings betydelse sträcker sig bortom akademin och informerar beslutsfattande inom politik och branschpraxis inom vindenergi och biologisk mångfaldsbevarande. Genom att optimera begränsningsplaner kan intressenter uppnå en balans mellan miljöskydd och förnybar energiproduktion, vilket banar väg för hållbar utveckling. Framtida forskningsvägar inkluderar att förädla begränsningsstrategier baserade på kontinuerliga variabler och att genomföra fältstudier för att validera resultat på olika vindkraftsplatser.

The research is motivated by the need to address two major challenges in wind power integration: how to mitigate wind power fluctuation and how to ensure stability of the farm and host grid. It is envisaged that wind farm power output fluctuation can be reduced by using a specific type of buffer, such as an energy storage system (ESS), to absorb its negative impact. The proposed solution, therefore, employs ESS to solve the problems. The key research findings include a new technique for calculating the desired power output profile, an ESS charge-discharge scheme, a novel direct-calculation (optimization-based) method for determining ESS optimal rating, and an ESS operation scheme for improving wind farm transient stability. Analysis with 14 wind farms and a compressed-air energy storage system (CAES) shows that the charge-discharge scheme and the desired output calculation technique are appropriate for ESS operation. The optimal ESSs for the 14 wind farms perform four or less switching operations daily (73.2%-85.5% of the 365 days) while regulating the farms output variation. On average, the ESSs carry out 2.5 to 3.1 switching operations per day. By using the direct-calculation method, an optimal ESS rating can be found for any wind farm with a high degree of accuracy. The method has a considerable advantage over traditional differential-based methods because it does not require knowledge of the analytical form of the objective function. For ESSs optimal rating, the improvement in wind energy integration is between 1.7% and 8%. In addition, a net increase in grid steady-state voltage stability of 8.3%-18.3% is achieved by 13 of the 14 evaluated ESSs. For improving wind farm transient stability, the proposed ESS operation scheme is effective. It exploits the use of a synchronous-machine-based ESS as a synchronous condenser to dynamically supply a wind farm with reactive power during faults. Analysis with an ESS and a 60-MW wind farm consisting of stall-regulated wind turbines shows that the ESS increases the farm critical clearing time (CCT) by 1 cycle for worst-case bolted three-phase-to-ground faults. For bolted single-phase-to-ground faults, the CCT is improved by 23.1%-52.2%. / text

Species distribution maps can provide important information to focus conservation efforts and enable spatial management of human activities. Two sympatric marine predators, grey seals (Halichoerus grypus) and harbour seals (Phoca vitulina), have overlapping ranges but contrasting population dynamics around the UK; whilst grey seals have generally increased, harbour seals have shown significant regional declines. A robust analytical methodology was developed to produce maps of grey and harbour seal usage estimates with corresponding uncertainty, and scales of spatial partitioning between the species were found. Throughout their range, both grey and harbour seals spend the majority of their time within 50 km of the coast. The scalability of the analytical approach was enhanced and environmental information to enable spatial predictions was included. The resultant maps have been applied to inform consent and licensing of marine renewable developments of wind farms and tidal turbines. For harbour seals around Orkney, northern Scotland, distance from haul out, proportion of sand in seabed sediment, and annual mean power were important predictors of space-use. Utilising seal usage maps, a framework was produced to allow shipping noise, an important marine anthropogenic stressor, to be explicitly incorporated into spatial planning. Potentially sensitive areas were identified through quantifying risk of exposure of shipping traffic to marine species. Individual noise exposure was predicted with associated uncertainty in an area with varying rates of co-occurrence. Across the UK, spatial overlap was highest within 50 km of the coast, close to seal haul outs. Areas identified with high risk of exposure included 11 Special Areas of Conservation (from a possible 25). Risk to harbour seal populations was highest, affecting half of all SACs associated with the species. For 20 of 28 animals in the acoustic exposure study, 95% CI for M-weighted cumulative Sound Exposure Levels had upper bounds above levels known to induce Temporary Threshold Shift. Predictions of broadband received sound pressure levels were underestimated on average by 0.7 dB re 1μPa (± 3.3). An analytical methodology was derived to allow ecological maps to be quantitatively compared. The Structural Similarity (SSIM) index was enhanced to incorporate uncertainty from underlying spatial models, and a software algorithm was developed to correct for internal edge effects so that loss of spatial information from the map comparison was limited. The application of the approach was demonstrated using a case study of sperm whales (Physeter macrocephalus, Linneaus 1758) in the Mediterranean Sea to identify areas where local-scale differences in space-use between groups and singleton whales occurred. SSIM is applicable to a broad range of spatial ecological data, providing a novel tool for map comparison.

L’énergie éolienne, l’une des énergies renouvelables les plus compétitives, est considérée comme une solution qui remédie aux inconvénients de l’énergie fossile. Pour une meilleure gestion et exploitation de cette énergie, des prévisions de sa production s’avèrent nécessaires. Les méthodes de prévisions utilisées dans la littérature permettent uniquement une prévision de la moyenne annuelle de cette production. Certains travaux récents proposent l’utilisation du Théorème Central Limite (TCL), sous des hypothèses non classiques, pour l’estimation de la production annuelle moyenne de l’énergie éolienne ainsi que sa variance pour une seule turbine. Nous proposons dans cette thèse une extension de ces travaux à un parc éolien par relaxation de l’hypothèse de stationnarité la vitesse du vent et la production d’énergie, en supposant que ces dernières sont saisonnières. Sous cette hypothèse la qualité de la prévision annuelle s’améliore considérablement. Nous proposons aussi de prévoir la production d’énergie éolienne au cours des quatre saisons de l’année. L’utilisation du modèle fractal, nous permet de trouver une division ”naturelle” de la série de la vitesse du vent afin d’affiner l’estimation de la production éolienne en détectant les points de ruptures. Dans les deux derniers chapitres, nous donnons des outils statistiques de la détection des points de ruptures et d’estimation des modèles fractals. / The wind energy, one of the most competitive renewable energies, is considered as a solution which remedies the inconveniences of the fossil energy. For a better management and an exploitation of this energy, forecasts of its production turn out to be necessary. The methods of forecasts used in the literature allow only a forecast of the annual mean of this production. Certain recent works propose the use of the Central Limit Theorem (CLT), under not classic hypotheses, for the estimation of the mean annual production of the wind energy as well as its variance for a single turbine. We propose in this thesis, an extension of these works in a wind farm by relaxation of the hypothesis of stationarity the wind speed and the power production, supposing that the latter are seasonal. Under this hypothesis the quality of the annual forecast improves considerably. We also suggest planning the wind power production during four seasons of the year. The use of the fractal model, allows us to find a "natural" division of the series of the wind speed to refine the estimation of the wind production by detecting abrupt change points. Statistical tools of the change points detection and the estimation of fractal models are presented in the last two chapters.