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.

Dynamic Rating (DR) is usually associated with unlocking the capacity of power lines and transformers using available information on weather conditions. Our studies show that Dynamic Rating is a broad concept that requires further study and development. The capacity of the majority of power devices is highly dependent on the heat transfer properties of the materials which the devices are made of. To ensure correct power limits of the equipment, one must take into consideration not only the power load, but also ambient conditions, such as: temperature, wind speed, wind direction, solar irradiation, humidity, pressure, radiation into the atmosphere and magnetic losses. Dynamic rating is created as an alternative to standard constant rating that is designed with reference to extreme weather and load conditions. Some areas are more likely than others to experience extreme weather conditions, which have a chance of occurring only a few days per year for short periods of time. Such a distribution of weather parameters gives an opportunity to embed existing material properties of the power equipment and achieve a better utilization of the grid. The following thesis is divided into two simultaneous topics: Dynamic line rating and Dynamic transformer rating. The division is motivated by the importance of analysing the operation of the above-mentioned parts of the power network in greater detail. Power lines and transformers play a significant part in grid planning and have a potential to result in economic benefits when used with DR. The main focus of the doctoral project "Dynamic rating of power lines and transformers for wind energy integration" is on exploring potential ways to connect power generated from wind to the grid with the help of dynamic rating technologies. Therefore, great focus of the work lies on the analysis of DR connection of variable energy sources such as wind farms. The thesis presents the comparison of different line rating methods and proposes a new way of their classification. Evaluation of dynamic line rating application has shown the possibility to expand the power grid with additional capacity from wind power generation. Literature analysis and detailed evaluation of the conductor heat balance models have led to experimental evaluation of the convective cooling effect. The dynamic transformer rating application has shown a possibility to decrease the size of the power transformer without shortcoming in component availability. / <p>QC 20180423</p> / Dynamic Rating for Wind Power

This study selects several new advanced topics in power systems, and verifies their usefulness using the simulation. In the study on ratio of the equivalent reactance and resistance of the bulk power systems, the simulation results give us the more correct value of X/R of the bulk power system, which can explain why the active power compensation is also important in voltage flicker mitigation. In the application study of the Energy Storage System(ESS) to the wind power, the new model implementation of the ESS connected to the wind power is proposed, and the control effect of ESS to the intermittency of the wind power is verified. Also this study conducts the intensive simulations for clarifying the behavior of the wide-area power system frequency as well as the possibility of the on-line instability detection. In our POWER IT Laboratory, since 2003, the U.S. national frequency monitoring network (FNET) has been being continuously operated to monitor the wide-area power system frequency in the U.S. Using the measured frequency data, the event of the power system is triggered, and its location and scale are estimated. This study also looks for the possibility of using the simulation technologies to contribute the applications of FNET, finds similarity of the event detection orders between the frequency measurements and the simulations in the U.S. Eastern power grid, and develops the new methodology for estimating the event location based on the simulated N-1 contingencies using the frequency measurement. It has been pointed out that the simulation results can not represent the actual response of the power systems due to the inevitable limit of modeling power systems and different operating conditions of the systems at every second. However, in the circumstances that we need to test such an important infrastructure supplying the electric energy without taking any risk of it, the software based simulation will be the best solution to verify the new technologies in power system engineering and, for doing this, new models and better application of the simulation should be proposed. Conducting extensive simulation studies, this dissertation verified that the actual X/R ratio of the bulk power systems is much lower than what has been known as its typical value, showed the effectiveness of the ESS control to mitigate the intermittence of the wind power from the perspective of the power grid using the newly proposed simulation model of ESS connected to the wind power, and found many characteristics of the wide-area frequency wave propagation. Also the possibility of using the simulated responses of the power system for replacing the measured data could be confirmed and this is very promising to the future application of the simulation to the on-line analysis of the power systems based on the FNET measurements. / Ph. D.

The energy sector represents the biggest contributor to global climate change. The concurring efforts to decarbonise electricity and heat generation contribute to the ongoing expansion of renewable energy systems.  The European wind power (WP) capacity is expected to triple by the year 2030, with onshore wind farms accounting for over 80% of new installations. This upswing entails critical demands for construction materials, shifting environmental burdens to the construction phase, compared to the use-phase hotspot of fossil resources. To counteract these magnified impacts, emerging innovations are disrupting conventional wind turbine (WT) technologies. To assess these developments, this study evaluates the future environmental impacts of WP production in Sweden using the emerging prospective life cycle assessment (pLCA) methodology. Six explorative foreground scenarios are developed for a generic Swedish WP plant in the year 2050. The scenarios build on projected national capacity developments, as well as identified key processes of hydrogen-based steel and concrete, as well as wooden WT towers. In addition, the application and propagation of the integrated assessment model REMIND-SSP2-NDC-2050 is deployed to project socio-economic changes in the background system.   Compared to the reference year 2020, all six scenarios show clear improvements of the climate change contribution. Especially “green” materials and wood towers promise significant future potential to accelerate a sustainable transition of Swedish WP production. The combined introduction of green steel, concrete, and hydrogen results in the overall best environmental performance, reducing the global warming potential by 47% from 6,3 g CO2eq per kWh in 2020 to 3,34 g CO2eq per kWh in 2050. However, burden-shifting occurs in particular for cancerous human toxicity and the occupation of agricultural land. While inheriting only 8% higher GWP, the wood tower scenario avoids the shifted effect on human toxicity but increases land occupation and terrestrial acidification even further. For all six scenarios, critical pressures emerge for non-fossil elements resulting from the growing demand for permanent magnet materials. The study’s results highlight a promising outlook for Swedish WP production by 2050 and the corresponding importance of pLCA to facilitate a sustainable transition of the energy sector. / Energisektorn är den sektor som bidrar mest till den globala klimatförändringen. De samtidiga insatserna för att minska koldioxidutsläppen från el- och värmeproduktion bidrar till den pågående utbyggnaden av förnybara energisystem.  Den europeiska vindkraftskapaciteten (WP) förväntas tredubblas fram till år 2030, och vindkraftsparker på land står för över 80% av de nya installationerna. Detta uppsving medför en kritisk efterfrågan på byggmaterial, vilket innebär att miljöbelastningen flyttas från användnings- till byggfasen. För att motverka dessa ökade effekter finns det nya innovationer som förändrar den konventionella tekniken för vindkraftverk (WT). För att bedöma denna utveckling utvärderas i denna studie den framtida miljöpåverkan från produktionen av vindkraftverk i Sverige med hjälp av den nya prospektiva livscykelanalysmetoden (pLCA). Sex explorativa förgrundsscenarier utvecklas för en generisk svensk WP-anläggning år 2050. Scenarierna bygger på förväntad nationell kapacitetsutveckling, samt identifierade nyckelprocesser för vätgasbaserat stål och betong, samt WT-torn av trä. Dessutom används tillämpningen och spridningen av den integrerade utvärderingsmodellen REMIND-SSP2-NDC-2050 för att projicera socioekonomiska förändringar i bakgrundssystemet.   Jämfört med referensåret 2020 visar alla sex scenarierna tydliga förbättringar av bidraget till klimatförändringarna. Särskilt ”gröna” material och trätorn har en betydande framtida potential för att påskynda en hållbar omställning av svensk WPproduktion. Det kombinerade införandet av grönt stål, betong och vätgas resulterar i den övergripande bästa miljöprestandan, vilket minskar den globala uppvärmningspotentialen med 47% från 6,3 g CO2eq per kWh 2020 till 3,34 g CO2eq per kWh 2050. Det sker dock en omfördelning av bördorna, särskilt när det gäller cancerframkallande toxicitet för människor och ianspråktagande av jordbruksmark. Trätornsscenariot, som endast har 8 % högre GWP, undviker rebound-effekten för humantoxicitet men ökar markanvändningen och försurningen av marken ytterligare. För alla sex scenarierna uppstår ett kritiskt tryck på icke-fossila grundämnen till följd av den växande efterfrågan på permanentmagnetmaterial. Studiens resultat belyser en lovande utsikt för svensk WP produktion fram till 2050 och den motsvarande betydelsen av pLCA för att underlätta en hållbar övergång av energisektorn.

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

Die Bundesregierung plant im Rahmen der Energiewende den Anteil von erneuerbaren Energien an der Stromerzeugung in Deutschland von heute rund 25% auf 80% bis zum Jahr 2050 auszubauen. Damit stehen auch dem Stromsektor in Sachsen grundlegende Veränderungen bevor. Derzeit leistet im Freistaat Sachsen die Braunkohle den größten Beitrag zur Elektrizitätsbereitstellung. Mit dem zunehmenden Ausbau an erneuerbaren Energien steigt der Anteil dargebotsabhängiger Energieträger. Daraus resultieren technische und wirtschaftliche Herausforderungen für das bestehende Energiesystem, wie z.B. die künftige Bereitstellung von Systemdienstleistungen. Mit diesen und weiteren Fragestellungen zur Transformation des Elektrizitätssystems haben sich Nachwuchswissenschaftler der TU Dresden in den vergangenen zwei Jahren im Rahmen des vom Europäischen Sozialfonds – ESF geförderten Projekts EnerSAX auseinander gesetzt. Neben der Erstellung einer Potenzialanalyse für Sachsen wurden sowohl technische Fragestellungen,wie z.B. die Auswirkungen der Integration erneuerbarer Energien auf die Übertragungs-, Verteilungs-und Niederspannungsnetze, als auch ökonomische Fragestellung, wie z.B. die künftige Ausgestaltung der Regelenergiemärkte, untersucht. Durch die Zusammenarbeit der Nachwuchsforscher aus den Bereichen der Elektrotechnik und Energiewirtschaft konnten so integrierte Lösungsansätze zur Ausgestaltung einer weitgehend auf erneuerbaren Energien beruhenden Energieversorgung mit dem Fokus auf Sachsen im transnationalen Kontext erarbeitet werden. Die wesentlichen Ergebnisse aus dem Projekt werden in diesem Buch vorgestellt.

Cette thèse s’intéresse à la problématique de la prédiction dans le cadre du design de systèmes énergétiques et des problèmes d’opération, et en particulier, à l’évaluation de l’adéquation de systèmes de production d’énergie renouvelables. L’objectif général est de développer une approche empirique pour générer des prédictions avec les incertitudes associées. En ce qui concerne cette direction de la recherche, une approche non paramétrique et empirique pour estimer les intervalles de prédiction (PIs) basés sur les réseaux de neurones (NNs) a été développée, quantifiant l’incertitude dans les prédictions due à la variabilité des données d’entrée et du comportement du système (i.e. due au comportement stochastique des sources renouvelables et de la demande d'énergie électrique), et des erreurs liées aux approximations faites pour établir le modèle de prédiction. Une nouvelle méthode basée sur l'optimisation multi-objectif pour estimer les PIs basée sur les réseaux de neurones et optimale à la fois en termes de précision (probabilité de couverture) et d’information (largeur d’intervalle) est proposée. L’ensemble de NN individuels par deux nouvelles approches est enfin présenté comme un moyen d’augmenter la performance des modèles. Des applications sur des études de cas réels démontrent la puissance de la méthode développée. / This Ph.D. work addresses the problem of prediction within energy systems design and operation problems, and particularly the adequacy assessment of renewable power generation systems. The general aim is to develop an empirical modeling framework for providing predictions with the associated uncertainties. Along this research direction, a non-parametric, empirical approach to estimate neural network (NN)-based prediction intervals (PIs) has been developed, accounting for the uncertainty in the predictions due to the variability in the input data and the system behavior (e.g. due to the stochastic behavior of the renewable sources and of the energy demand by the loads), and to model approximation errors. A novel multi-objective framework for estimating NN-based PIs, optimal in terms of both accuracy (coverage probability) and informativeness (interval width) is proposed. Ensembling of individual NNs via two novel approaches is proposed as a way to increase the performance of the models. Applications on real case studies demonstrate the power of the proposed framework.

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.

Wind power presently plays a minor role in Western Canada as compared to hydroelectric power in British Columbia and coal and natural gas thermal power generation in Alberta. However, ongoing reductions in the cost of wind power generation facilities and the increasing costs of conventional power generation, particularly if the cost to the environment is included, suggest that assessment of the present and future wind field in Western Canada is of some importance. To assess present wind power, raw hourly wind speeds and homogenized monthly mean wind speeds from 30 stations in Western Canada were analyzed over the period 1971-2000 (past). The hourly data were adjusted using the homogenized monthly means to attempt to compensate for differences in anemometer height from the standard height of 10m and changes in observing equipment at stations. A regional reanalysis product, the North American Regional Reanalysis (NARR), and simulations conducted with the Canadian Regional Climate Model (CRCM) driven with global reanalysis boundary forcing, were compared to the adjusted station wind-speed time-series and probability distributions. The NARR had a better temporal correlation with the observations, than the CRCM. We posit this is due to the NARR assimilating regional observations, whereas the CRCM did not. The NARR was generally worse than the CRCM in reproducing the observed speed distribution, possibly due to the crude representation of the regional topography in NARR. While the CRCM was run at both standard (45 km) and fine (15 km) resolution, the fine grid spacing does not always provide better results: the character of the surrounding topography appears to be an important factor for determining the level of agreement. Multiple simulations of the CRCM at the 45 km resolution were also driven by two global climate models (GCMs) over the periods 1971-2000 (using only historic emissions) and 2031-2060 (using the A2 emissions scenario). In light of the CRCM biases relative to the observations, these simulations were calibrated using quantile-quantile matching to the adjusted station observations to obtain ensembles of 9 and 25 projected wind speed distributions for the 2031-2060 period (future) at the station locations. Both bias correction and change factor techniques were used for calibration. At most station locations modest increases in mean wind speed were found for most of the projected distributions, but with a large variance. Estimates of wind power density for the projected speed distributions were made using a relationship between wind speed and power from a CRCM simulation for both time periods using the 15km grid. As would be expected from the wind speed results and the proportionality of wind power to the cube of wind speed, wind power at the station locations is more likely than not to increase in the 2031-2060 period from the 1971-2000 period. Relative changes in mean wind speeds at station locations were found to be insensitive to the station observations and choice of calibration technique, suggesting that we estimate relative change at all 45km grid points using all pairs of past/future mean wind speeds from the CRCM simulations. Overall, our results suggest that wind energy resources in Western Canada are reasonably likely to increase at least modestly in the future. / Graduate / 0725 / 0608 / jtdaines@uvic.ca

Die Bundesregierung plant im Rahmen der Energiewende den Anteil von erneuerbaren Energien an der Stromerzeugung in Deutschland von heute rund 25% auf 80% bis zum Jahr 2050 auszubauen. Damit stehen auch dem Stromsektor in Sachsen grundlegende Veränderungen bevor. Derzeit leistet im Freistaat Sachsen die Braunkohle den größten Beitrag zur Elektrizitätsbereitstellung. Mit dem zunehmenden Ausbau an erneuerbaren Energien steigt der Anteil dargebotsabhängiger Energieträger. Daraus resultieren technische und wirtschaftliche Herausforderungen für das bestehende Energiesystem, wie z.B. die künftige Bereitstellung von Systemdienstleistungen. Mit diesen und weiteren Fragestellungen zur Transformation des Elektrizitätssystems haben sich Nachwuchswissenschaftler der TU Dresden in den vergangenen zwei Jahren im Rahmen des vom Europäischen Sozialfonds – ESF geförderten Projekts EnerSAX auseinander gesetzt. Neben der Erstellung einer Potenzialanalyse für Sachsen wurden sowohl technische Fragestellungen,wie z.B. die Auswirkungen der Integration erneuerbarer Energien auf die Übertragungs-, Verteilungs-und Niederspannungsnetze, als auch ökonomische Fragestellung, wie z.B. die künftige Ausgestaltung der Regelenergiemärkte, untersucht. Durch die Zusammenarbeit der Nachwuchsforscher aus den Bereichen der Elektrotechnik und Energiewirtschaft konnten so integrierte Lösungsansätze zur Ausgestaltung einer weitgehend auf erneuerbaren Energien beruhenden Energieversorgung mit dem Fokus auf Sachsen im transnationalen Kontext erarbeitet werden. Die wesentlichen Ergebnisse aus dem Projekt werden in diesem Buch vorgestellt.