The power system components connected to renewable energy sources, such as transformers, are often oversized and conservatively loaded. The design of transformers normally ignores the intermittent nature of the connected renewable energy sources (e.g. solar, wind). Due to the variations in weather conditions and operation states, the transformer load oscillates and the actual hot spot temperature is significantly lower than the designed thermal rating. For wind farms, the oversized transformer causes extra resourcematerial waste and a higher wind power price. Dynamic thermal rating can be applied to determine the rating of the transformers based on real-time environmental conditions (e.g. ambient temperature, wind speed). However, in order to optimize the operation of the transformers with dynamic thermal rating, the prediction of the load profile of transformers is an obstacle. The load of wind farm export transformers oscillates due to thechange of load conditions (e.g. turbine availability, power curtailment) and environmental conditions (e.g. wind speed, wind direction and ambient temperature). This thesis proposes a new methodology to improve the utilization of wind farm export transformers by estimating their load profile more accurately and assessing their aging rate. The estimation of the load profile takes the wake effect and turbine availability into account. Specifically, the variation in the wind turbine failure and repair rates, which is influenced by the wind, is considered in the evaluation of turbine availability. Additionally, a correction method is proposed to improve the accuracy of the wake loss computation. The results demonstrate that the estimation accuracy of the transformer load profile is improved after considering the influence of the wake effect and turbine availability. The wake effect and the turbine availability reduce the generated wind power and to some extent, reduce the load and the aging rate of transformers. However, the wake effect has limited influence when the wind farm reaches peak power production while turbine availability influences the load profile of transformers especially when the load is close to the installed capacity of the wind farm. After considering these two factors, the prediction accuracy of the hot spot temperature in the transformers can be enhanced and dynamic thermal rating can be applied to transformers with improved reliability. / Kraftsystemkomponenter som är anslutna till förnybara energikällor, såsom transformatorer, är ofta överdimensionerade och konservativt belastade. Konstruktionen av transformatorer ignorerar normalt sett den intermittenta naturen hos anslutna förnybara energikällor (t.ex. sol och vind). På grund av variationer i väderförhållanden och drifttillstånd, oscillerar transformatorbelastningen och den faktiska hotspottemperaturen är betydligt lägre än den designade termiska bedömningen. För vindkraftsparker orsakar den överdimensionerade transformatorn extra resursmaterialavfall och högre vindkraftspriser. Dynamisk termisk bedömning kan tillämpas för att bestämma transformatorernas betyg baserat på realtidsmiljöförhållanden (t.ex. omgivande temperatur, vindhastighet). Men för att optimera driften av transformatorer med dynamisk termisk bedömning är förutsägelsen av transformatorernas belastningsprofil ett hinder. Belastningen på transformatorer för export av vindkraftsparkeroscillerar på grund av ändringar i belastningsförhållanden (t.ex. tillgänglighet för turbiner, effektreglering) och miljöförhållanden (t.ex. vindhastighet, vindriktning och omgivande temperatur). Denna avhandling föreslår en ny metod för att förbättra användningen av transformatorer för export av vindkraftsparker genom att uppskatta deras belastningsprofil mer noggrant och bedöma deras åldrande takt. Uppskattningen av belastningsprofilen tar hänsyn till wake-effekten och turbinernas tillgänglighet. Specifikt beaktas variationen i felfrekvensen och reparationsfrekvensen för vindturbiner, som påverkas av vinden, vid utvärderingen av turbinernas tillgänglighet. Dessutom föreslås en korrektionsmetod för att förbättra noggrannheten i beräkningen av wake-förlusten. Resultaten visar att uppskattningen av transformatorns belastningsprofil förbättras efter att ha beaktat wake-effekten och turbinernas tillgänglighet. Wake-effekten och turbinernas tillgänglighet minskar den genererade vindkraften och minskar till viss del belastningen och åldringstakten hos transformatorer. Wake-effekten har emellertid begränsad påverkan när vindkraftsparken når maximal produktionsnivå medan turbinernas tillgänglighet påverkar belastningsprofilen hos transformatorer, särskilt när belastningen är nära installerad kapacitet för vindkraftsparken. Efter att ha beaktat dessa två faktorer kan förutsägelsens noggrannhet för hotspot-temperaturen i transformatorerna förbättras och dynamisk termisk bedömning kan tillämpas på transformatorer med förbättrad tillförlitlighet. / <p>QC 20230414</p>

Wind power installations have seen a significant rise all over the world in the past decade. Further significant growth is expected in the future. The UK’s ambitions for offshore wind installations are reflected through Round 1, 2 and 3 projects. It is expected that Round 3 alone will add at least 25 GW of offshore wind generation into the system. Current research knowledge is mostly limited to smaller wind farms, the aim of this research is to improve offline and online modelling techniques for large offshore wind farms. A critical part of offline modelling is the design of the wind farm. Design of large wind farms particularly requires careful consideration as high capital costs are involved. This thesis develops a novel methodology which leads to a cost-effective and reliable design of an offshore wind farm. A new industrial-grade software tool is also developed during this research. The tool enables multiple offshore wind farm design options to be built and tested quickly with minimal effort using a Graphical User Interface (GUI). The GUI is designed to facilitate data input and presentation of the results. This thesis also develops an improved method to estimate a wind farm’s energy yield. Countries with large-scale penetration of wind farms often carry out wind energy curtailments. Prior knowledge of estimated energy curtailments from a wind farm can be advantageous to the wind farm owner. An original method to calculate potential wind energy curtailment is proposed. In order to perform wind energy curtailments a network operator needs to decide which turbines to shut down. This thesis develops a novel method to identify turbines inside a wind farm that should be prioritised for shut down and given priority when scheduling preventive maintenance of the wind farm. Once the wind farm has been built and connected to the network, it operates as part of a power system. Real-time online simulation techniques are gaining popularity among system operators. These techniques allow operators to carry out simulations using short-term forecasted wind conditions. A novel method is proposed to probabilistically estimate the power production of a wind farm in real-time, taking into account variation in wind speed and effects of turbulence inside the wind farm. Furthermore, a new probabilistic aggregation technique is proposed to establish a dynamic equivalent model of a wind farm. It determines the equivalent number and parameters of wind turbines that can be used to simulate the dynamic response of the wind farm throughout the year.

Les travaux de thèse s’intéressent au réglage de la puissance active injectée dans le réseau, ce qui représente aujourd'hui l'une des problématiques principales du pilotage des parcs éoliens participant à la gestion du réseau. Dans le même temps, l'un des buts reste de maximiser la puissance extraite du vent en considérant les effets de couplage aérodynamique entre les éoliennes.La structure du contrôle-commande choisie est de type hiérarchisée et distribuée. Dans la première partie de la thèse, les travaux portent sur la commande de la turbine d'une éolienne autour des points de fonctionnement classiques mais également autour des points à puissance extraite réduite. En fait, cela relève d’une condition de fonctionnement nécessaire pour l'atteinte des objectifs imposés au pilotage d'un parc éolien.Dans la deuxième partie, le problème du contrôle à l'échelle d'un parc est posé sous la forme d'une optimisation distribuée parmi les turbines. Deux nouveaux algorithmes d'optimisation métaheuristique sont proposés et leur performance testée sur différents exemples de parcs éoliens. Les deux algorithmes s'appuient sur la méthode d'optimisation par essaim particulaire, qui est ici modifiée et adaptée pour les cas d'application aux systèmes multi agents. L'architecture de contrôlecommande globale est enfin évaluée en considérant les dynamiques des turbines contrôlées. Les simulations effectuées montrent des gains potentiels significatifs en puissance.Finalement, dans la troisième partie de la thèse, l'introduction d'une nouvelle étape de coopération au niveau des contrôleurs locaux des turbines, par l'utilisation de la technique de contrôle par consensus, permet d'améliorer les performances du système global. / In this PhD work we focus on the wind farm (WF) active power control since some of the new set grid requirements of interest can be expressed as specifications on its injection in the electric grid. Besides, one of our main objectives is related to the wind farm power maximization problem under the presence on non-negligible wake effect. The chosen WF control architecture has a two-layer hierarchical distributed structure. First of all, the wind turbine (WT) control is addressed. Here, a nonlinear controller lets a WT work in classic zones of functioning as well as track general deloaded power references. This last feature is a necessary condition to accomplish the WF control specifications. Secondly, the high level WF control problem is formulated as an optimization problem distributed among the WTs. Two novel distributed optimization algorithms are proposed, and their performance tested on different WF examples. Both are based on the well-known particle swarm optimization algorithm, which we modify and extend to be applicable in the multi-agent system framework. Finally, the overall WF control is evaluated by taking into account the WTs controlled dynamics. Simulations show potential significant power gains. Eventually, the introduction of a new control level in the hierarchical structure between the WF optimization and the WTs controllers is proposed. The idea is to let further cooperation among the WT local controllers, via a consensusbased technique, to enhance the overall system performance.

[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.