In the following Master’s degree research main information and communication aspects in wind power plant farm analyzed and demonstrated by constructing basic prototype. The wind energy market in Europe is growing and needs have arisen to develop standard-based information systems to support future expansion of wind energy in Lithuania. Introduction and first chapter overview the background for modeling such system. Requirements for data structures representing main measurements and information exchange inside and outside of the system are defined on the base of IEC 61400-25 standard “Wind Turbine Generator Systems - Part 25: Communications for monitoring and control of wind power plants”. Models, comprising such system are described and possible communication topologies enumerated. From several existing communication profiles, defined in above mentioned standard, SOAP / XML based web services for communication architecture are chosen and prototype built. Article based on this work was written together with coauthor professor A. Nemura and presented in international KTU conference “Automation and Control technologies – 2005���� and LEI conference “Application of information and management technologies in electricity energetics“. The purpose of article is to form and refine the wind farm information system problem introducing IEC 61400-25 standard.

The major achievements of this work are based on two categories: (A) introduction of an advanced simulation technique in both time domain and frequency domain, and (B) realistic and reliable models for converters applicable to analysis of alternative transmission systems. The proposed modeling-methodology using a combination of model quadratization and quadratic integration (QMQI) is demonstrated as a more robust, stable, and accurate method than previous modeling methodologies for power system analyses. The quadratic-integration method is free of artificial numerical-oscillations exhibited by trapezoidal integration (which is the most popularly used method in power system analyses). Artificial numerical oscillations can be the direct reason for switching malfunction of switching systems. However, the quadratic-integration method has a natural characteristic to eliminate fictitious oscillations with great simulation accuracy. Also, model quadratization permits nonlinear equations to be solved without simplification or approximation, leading to realistic models of nonlinearities. Therefore, the QMQI method is suitable for simulations of network systems with nonlinear components and switching subsystems. Realistic and reliable converter models by the application of the QMQI method can be used for advanced designs and optimization studies for alternative transmission systems; they can also be used to perform a comprehensive evaluation of the technical performance and economics of alternative transmission systems. For example, the converters can be used for comprehensive methodology for determining the optimal topology, kV-levels, etc. of alternative transmission systems for wind farms, for given distances of wind farms from major power grid substations. In this case, a comprehensive evaluation may help make more-informed decisions for the type of transmission (HVAC, HVDC, and LFAC) for wind farms.

Mathematical modeling and simulations of a submerged renewable storage system integrated to a wind farm, chosen based on the geographical and wind conditions at the Baltic Sea, gives insight on the feasibility of the submerged renewable storage and an approximation of the payback period and profits that could be generated. Genetic Algorithms were used to obtain the optimal number of spheres for a certain depth, based on 2 objective functions I.e. Minimum Life Cycle Cost (LCC) and maximum reduction in wind curtailment. The new arrangement concept shows that the Initial Capital Cost (ICC) could be decreased by 25% to 60% depending upon the number of sphere employed. Based on the inputs considered in the study, the results prove that the submerged renewable storage system would be feasible, and the profits ranging from 15 Million Euro to 29 Million Euro can be achieved at the chosen location, towards the Swedish side of the Baltic sea. Although, in a real life scenario it is assumed that only up to half of the profits obtained in the results would be achievable. The results also show that, the Pump/Turbine with a high turbine efficiency and lower pump efficiency, generated better profits, compared to a Pump/Turbine running with a higher pump efficiency and lower turbine efficiency. An attempt to increase the round-trip efficiency by adding a multi stage submersible pump, resulted in additional ICC and LCC, which saw a decrease in profits.

Recently wind resource assessment studies have become an important research tool to identify the possible wind farm locations.  In this thesis work technical analysis was carried out to determine the wind resource potential of two candidate sites in Eritrea with help of suitable software tools. The first site is located along the Red Sea cost which is well known for its wind resource potential, whereas the second site is located in the central highlands of Eritrea with significant wind resource potential. Detailed wind resource assessment, for one year hourly weather data including wind speed and wind direction, was performed for the two candidate sites using MS Excel and MATLAB. The measured wind data at Assab wind site showed that the mean wind speed and power density was 7.54 m/s and 402.57 W/m2 , whereas the mean wind speed and mean power density from Weibull distribution was 7.51 m/s and 423.71 W/m2 respectively at 80m height. Similarly, the measured mean wind speed and mean power density at Dekemahre wind site was obtained to be 5.498 m/s and 141.45 W/m2, whereas the mean wind speed and mean power density from Weibull distribution was 5.4859m/s and 141.057W/m2 respectively. Based on the analysis results Assab wind site classified as wind class-III and Dekemhare as wind class-I.  Wind farm modeling and Annual Energy Production (AEP) estimation was performed for E-82 & E-53 model turbines from Enercon Company with the help of MATLAB and Windpro software. The analysis revealed that Assab wind farm was an ideal site for wind energy production with capacity factor (CF) 53.4% and 55% for E-82 and E-53 turbines respectively. The gross and net AEP for turbine E-82 at Assab wind farm was 469.5 GWh and 446.025 GWh respectively with 95% park efficiency. Similarly, the analysis showed that the CF in Dekemhare site was very low with typical value 14.2% and 15.26% for E-82 and E-53 turbines respectively. The gross and net AEP of that site for model turbine E-53 was 53.5 GWh and 50.825 GWh respectively with 5% wake loss. Finally, a simplified economic analysis was carried out to determine the economic feasibility of possible wind power projects in both sites by assuming investment cost 1600 €/kW for E-82 turbine and 2000 €/kW for E-53 turbine. The total wind farm investment cost was found to be 215.85 and 107.93 Million Euro for E-82 and E-53 model turbines respectively. The levelized cost of energy at Assab and Dekemhare wind farm for E-82 model turbine was 0.0307 €/kWh and 0.5526 €/kWh respectively. The analysis result show that the levelized cost of energy in Dekemhare wind fasrm was much higher than that of Assab wind farm.

Distance relays due to their selectivity and operating speed are used in HV/EHV line protection. The dynamic nature of Mho characteristic, which happens to be most primitive technique in line protection implemented with distance relaying, is built by using the measurement of local voltage and current signals. These signals have been influenced substantially by fault resistance and the source impedance feeding the line. In case of different generation sources, the source impedance and fault characteristic also change accordingly. Environmental benefit of wind turbine technology is making it a potential source of energy. These wind turbine-generating units (WTGU) use rugged induction/synchronous machines along with power electronics converters as controlling equipment. This gives a new challenge to distance relays, as the fault current contribution of these sources depends on the converter operational principle. In this thesis a typical wind farm of Indian systems are modeled in an IN-HOUSE tool developed as part of fault analysis on wind farm system. Directly connected and front-end converter based wind turbines with their interconnections are modeled in this simulation tool. Fault voltage and current waveforms are obtained for all types of wind turbine-generating units with both radial and LILO (Loop in Loop out) connection. PSCAD based modeling has been done for DFIG type of wind turbines. The fault waveforms are generated to evaluate relay performance. Five case studies having both Radial and Loop in Loop out (LILO) connection of wind farms are simulated. These case studies generate approximately 20000 cases, which are analyzed for distance relay performance studies. In addition, the analysis is further verified on relay hardware having three characteristics, namely Self Polarized Mho (SPM), Quadrature Polarized Mho (QPM) and Quadrilateral (QUAD) characteristics. The detailed studies are carried out in this thesis to ensure and suggest the system operators with appropriate relay characteristics to be used for transmission line protection in the case of wind farms interconnected to Grid. Based on the studies carried out in the thesis, LILO connection has no impact on distance relay characteristic. In radially connected wind farms, grid side relay will operate reliably for all types of faults. It has been recommended in the thesis that wind farm side distance relay characteristics should be adjusted based on the types of wind turbines (Type-1, Type-2, Type-3 and Type-4). Based on the investigations carried out in the thesis, voltage based phase selector has been recommended for Type-4 WTGU based wind farms.

L’intégration massive de la production d’énergie éolienne intermittente au niveau des réseaux électriques pose un problème de stabilité du système électrique. En effet les caractéristiques sont très différentes de celles de sources conventionnelles maîtrisées par les gestionnaires de réseau. Par conséquent, l’injection de cette énergie induit de nouveaux challenges pour les gestionnaires de réseaux électriques. De plus, les conditions de raccordement évoluent et tendent à ce que toutes les sources participent aux services rendus aux systèmes électriques. Les travaux de cette thèse sont focalisés sur la proposition d’une nouvelle stratégie de commande non-linéaire basée sur la commande par « platitude à une boucle » d’un système de conversion d’énergie éolienne. Cette stratégie de contrôle vise la gestion des interactions au point de connexion par la génération et le suivi de trajectoires de références. De par le fait que toutes les variables du système sont liées à la « sortie plate » de ce système, cette commande procure une rapidité de réponse et une bonne maitrise des régimes transitoires. La mise en œuvre de cette nouvelle stratégie de contrôle pour la constitution d’un parc éolien offshore, capable de satisfaire différentes conditions de raccordement a été simulée avec succès. Plus particulièrement, l’évaluation de l’impact de différents défauts du réseau sur les services proposés (Régulation de fréquence et de tension, la tenue aux creux de tension.) a été réalisée. / The massive integration of intermittent production of wind energy in electrical networks creates an electrical system stability problem. Indeed, its characteristics are very different from those of conventional sources controlled by Grid managers. Therefore, the injection of this energy makes new challenges for power Grid operators. Moreover, the connection conditions are evolving and go towards the situations that all different sources participate into services of electrical systems. This thesis proposes a new nonlinear control strategy based on a « one loop flatness control » of a wind energy conversion system. This control strategy has aim of energy interactions management at the connection point through generation and tracking of reference trajectories. As all system variables are functions of the « flat output » of the system, this control provides fast response and good control in transient state. The application of this new control strategy into an offshore wind farm which is able to satisfy different connection conditions was simulated successfully. Specifically, effects of various grid faults on the proposed ancillary services (frequency and voltage regulation, and low-voltage ride through capabilities) were performed.

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.

Aujourd’hui, la conception de réseaux est une problématique cruciale qui se pose dans beaucoup de domaines tels que le transport ou l’énergie. En particulier, il est devenu nécessaire d’optimiser la façon dont sont conçus les réseaux permettant de produire de l’énergie. On se concentre ici sur la production électrique produite à travers des parcs éoliens. Cette énergie apparait plus que jamais comme une bonne alternative à la production d’électricité via des centrales thermiques ou nucléaires.Nous nous intéressons dans cette thèse à la conception du câblage collectant l’énergie dans les parcs éoliens. On connaît alors la position de l’ensemble des éoliennes appartenant au parc ainsi que celle du site central collecteur vers laquelle l’énergie doit être acheminée. On connaît également la position des câbles que l’on peut construire, leurs capacités, et la position des nœuds d’interconnexion possibles. Il s’agit de déterminer un câblage de coût minimal permettant de relier l’ensemble des éoliennes à la sous-station, tel que celui-ci soit résistant à un certain nombre de pannes sur le réseau. / Nowadays, the design of networks has become a decisive problematic which appears in many fields such as transport or energy. In particular, it has become necessary and important to optimize the way in which networks used to produce, collect or transport energy are designed. We focus in this thesis on electricity produced through wind farms. The production of energy by wind turbines appears more than ever like a good alternative to the electrical production of thermal or nuclear power plants.We focus in this thesis on the design of the cabling network which allows to collect and route the energy from the wind turbines to a sub-station, linking the wind farm to the electrical network. In this problem, we know the location of each wind turbine of the farm and the one of the sub-station. We also know the location of possible inter-connection nodes which allow to connect different cables between them. Each wind turbine produces a known quantity of energy and with each cable are associated a cost and a capacity (the maximum amount of energy that can be routed through this cable). The optimizationproblem that we consider is to select a set of cables of minimum cost such that the energy produced from the wind turbines can be routed to the sub-station in the network induced by this set of cables, without exceeding the capacity of each cable. We focus on cabling networks resilient to breakdowns.

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.

In recent years, machine learning applications have gained great attention in the wind power industry. Among these, artificial neural networks have been utilized to predict the fatigue loads of wind turbine components such as rotor blades. However, the limited number of contributions and differences in the used databases give rise to several questions which this study has aimed to answer. Therefore, in this study, 5-min SCADA data from the Lillgrund wind farm has been used to train two feed-forward neural networks to predict the fatigue loads at the blade root in flapwise and edgewise directions in the shape of damage equivalent loads.The contribution of different features to the model’s performance is evaluated. In the absence of met mast measurements, mesoscale NEWA data are utilized to present the free flow condition. Also, the effect of wake condition on the model’s accuracy is examined. Besides, the generalization ability of the model trained on data points from one or multiple turbines on other turbines within the farm is investigated. The results show that the best accuracy was achieved for a model with 34 features, 5 hidden layers with 100 neurons in each hidden layer for the flapwise direction. For the edgewise direction, the best model has 54 features, 6 hidden layers, and 125 neurons in each hidden layer.For a model trained and tested on the same turbine, mean absolute percentage errors (MAPE) of 0.78% and 9.31% are achieved for the flapwise and edgewise directions, respectively. The seen difference is argued to be a result of not having enough data points throughout the range of edgewise moments. The use of NEWA data has been shown to improve the model’s accuracy by 10% for MAPE values, relatively. Training the model under different wake conditions did not improve the model showing that the wake effects are captured through the input features to some extent. Generalization of the model trained on data points from one turbine resulted in poor results in the flapwise direction. It was shown that using data points from multiple turbines can improve the model’s accuracy to predict loading on other turbines.