Performance and scalability of isolated DC-DC converter topologies in low voltage, high current applications

Fuel cells are a promising alternative for clean and efficient energy production. A fuel cell is probably the most demanding of all distributed generation power sources. It resembles a solar cell in many ways, but sets strict limits to current ripple, common mode voltages and load variations. The typically low output voltage from the fuel cell stack needs to be boosted to a higher voltage level for grid interfacing. Due to the high electrical efficiency of the fuel cell, there is a need for high efficiency power converters, and in the case of low voltage, high current and galvanic isolation, the implementation of such converters is not a trivial task. This thesis presents galvanically isolated DC-DC converter topologies that have favorable characteristics for fuel cell usage and reviews the topologies from the viewpoint of electrical efficiency and cost efficiency. The focus is on evaluating the design issues when considering a single converter module having large current stresses. The dominating loss mechanism in low voltage, high current applications is conduction losses. In the case of MOSFETs, the conduction losses can be efficiently reduced by paralleling, but in the case of diodes, the effectiveness of paralleling depends strongly on the semiconductor material, diode parameters and output configuration. The transformer winding losses can be a major source of losses if the windings are not optimized according to the topology and the operating conditions. Transformer prototyping can be expensive and time consuming, and thus it is preferable to utilize various calculation methods during the design process in order to evaluate the performance of the transformer. This thesis reviews calculation methods for solid wire, litz wire and copper foil winding losses, and in order to evaluate the applicability of the methods, the calculations are compared against measurements and FEM simulations. By selecting a proper calculation method for each winding type, the winding losses can be predicted quite accurately before actually constructing the transformer. The transformer leakage inductance, the amount of which can also be calculated with reasonable accuracy, has a significant impact on the semiconductor switching losses. Therefore, the leakage inductance effects should also be taken into account when considering the overall efficiency of the converter. It is demonstrated in this thesis that although there are some distinctive differences in the loss distributions between the converter topologies, the differences in the overall efficiency can remain within a range of a few percentage points. However, the optimization effort required in order to achieve the high efficiencies is quite different in each topology. In the presence of practical constraints such as manufacturing complexity or cost, the question of topology selection can become crucial.

Kaivoslastauskoneen hybridisointianalyysi virtuaali- ja in-loop -simuloinnin avulla

Työssä tutkitaan raskaiden työkoneiden hybridisointimitoitusta simuloimalla. Työssä esitetään simulation-in-the-loop-simulointiin perustuva järjestelmä, jolla esimerkkitapauksena oleva kaivoslastauskone työympäristöineen voidaan mallintaa mekaaniselta osaltaan monikappaledynamiikkaan perustuvalla ohjelmistolla ja hybridijärjestelmän osalta Simulinkissa. Yhdistetty simulointi mahdollistaa hybridityökoneen virtuaalimallin ohjaamisen käyttäjän toimesta reaaliajassa. Simuloinnista saadaan tuloksena mm. työsykli, jota voidaan käyttää hybridisointimitoitukseen. Hybridisointi toteutetaan kahdella erilaisella kokoonpanolla, joista analysoidaan suorituskykyä sekä polttoaineen kulutusta. Tuloksia verrataan pelkästään dieselmoottoria voimanlähteenä käyttävään lastauskoneeseen. Työssä tehty tutkimus osoittaa, että (sarja-) hybridisoinnilla voidaan saavuttaa merkittäviä etuja raskaiden työkoneiden polttoainetehokkuudessa. Dieselmoottoria voidaan ajaa sellaisessa staattisessa toimintapisteessä, jonka hyötysuhde on korkea riippumatta työkoneen kuormituksesta. Saavutettu hyöty on toteutetussa tutkimuksessa parhaimmillaan jopa 56 % vähennys polttoaineenkulutuksessa. Lisäksi tarvittava dieselin nimellisteho pienenee huomattavasti. Tutkimuksen osana esitellään myös Hardware-in-the-Loop -laitteisto, jonka avulla voidaan liittää oikea sähkömoottori ja taajuudenmuuttaja osaksi virtuaalisesti simuloitua työkonetta.

Electrical Machine Product Development; Transmission to Lean Approach

The requirements set by the market for electrical machines become increasingly demanding requiring more sophisticated technological solutions. Companies producing electrical ma-chines are challenged to develop machines that provide competitive edge for the customer for example through increased efficiency, reliability or some customer specific special requirement. The objective of this thesis is to derive a proposal for the first steps to transform the electrical machine product development process of a manufacturing company towards lean product development. The current product development process in the company is presented together with the processes of four other companies interviewed for the thesis. On the basis of current processes of the electrical machine industry and the related literature, a generalized electrical machine product development process is derived. The management isms and –tools utilized by the companies are analyzed. Adoption of lean Pull-Event –reviews, Oobeya –management and Knowledge based product development are suggested as the initial steps of implementing lean product development paradigm in the manufacturing company. Proposals for refining the cur-rent product development process and increasing the stakeholder involvement in the development projects are made. Lean product development is finding its way to Finnish electrical machine industry, but the results will be available only after the methods have been implemented and adopted by the companies. There is some enthusiasm about the benefits of lean approach and if executed successfully it will provide competitive edge for the Finnish electrical machine industry.

Designing a Demand Forecasting Process in the Fast Moving Consumer Goods Context

The purpose of this thesis was to study the design of demand forecasting processes. A literature review in the field of forecasting was conducted, including general forecasting process design, forecasting methods and techniques, the role of human judgment in forecasting and forecasting performance measurement. The purpose of the literature review was to identify the important design choices that an organization aiming to design or re-design their demand forecasting process would have to make. In the empirical part of the study, these choices and the existing knowledge behind them was assessed in a case study where a demand forecasting process was re-designed for a company in the fast moving consumer goods business. The new target process is described, as well as the reasoning behind the design choices made during the re-design process. As a result, the most important design choices are highlighted, as well as their immediate effect on other processes directly tied to the demand forecasting process. Additionally, some new insights on the organizational aspects of demand forecasting processes are explored. The preliminary results indicate that in this case the new process did improve forecasting accuracy, although organizational issues related to the process proved to be more challenging than anticipated.

Price spike forecasting in a competitive day-ahead energy market

Electricity price forecasting has become an important area of research in the aftermath of the worldwide deregulation of the power industry that launched competitive electricity markets now embracing all market participants including generation and retail companies, transmission network providers, and market managers. Based on the needs of the market, a variety of approaches forecasting day-ahead electricity prices have been proposed over the last decades. However, most of the existing approaches are reasonably effective for normal range prices but disregard price spike events, which are caused by a number of complex factors and occur during periods of market stress. In the early research, price spikes were truncated before application of the forecasting model to reduce the influence of such observations on the estimation of the model parameters; otherwise, a very large forecast error would be generated on price spike occasions. Electricity price spikes, however, are significant for energy market participants to stay competitive in a market. Accurate price spike forecasting is important for generation companies to strategically bid into the market and to optimally manage their assets; for retailer companies, since they cannot pass the spikes onto final customers, and finally, for market managers to provide better management and planning for the energy market. This doctoral thesis aims at deriving a methodology able to accurately predict not only the day-ahead electricity prices within the normal range but also the price spikes. The Finnish day-ahead energy market of Nord Pool Spot is selected as the case market, and its structure is studied in detail. It is almost universally agreed in the forecasting literature that no single method is best in every situation. Since the real-world problems are often complex in nature, no single model is able to capture different patterns equally well. Therefore, a hybrid methodology that enhances the modeling capabilities appears to be a possibly productive strategy for practical use when electricity prices are predicted. The price forecasting methodology is proposed through a hybrid model applied to the price forecasting in the Finnish day-ahead energy market. The iterative search procedure employed within the methodology is developed to tune the model parameters and select the optimal input set of the explanatory variables. The numerical studies show that the proposed methodology has more accurate behavior than all other examined methods most recently applied to case studies of energy markets in different countries. The obtained results can be considered as providing extensive and useful information for participants of the day-ahead energy market, who have limited and uncertain information for price prediction to set up an optimal short-term operation portfolio. Although the focus of this work is primarily on the Finnish price area of Nord Pool Spot, given the result of this work, it is very likely that the same methodology will give good results when forecasting the prices on energy markets of other countries.

Long-term nutrient load management and lake restoration: Case of Säkylän Pyhäjärvi (SW Finland)

Eutrophication caused by anthropogenic nutrient pollution has become one of the most severe threats to water bodies. Nutrients enter water bodies from atmospheric precipitation, industrial and domestic wastewaters and surface runoff from agricultural and forest areas. As point pollution has been significantly reduced in developed countries in recent decades, agricultural non-point sources have been increasingly identified as the largest source of nutrient loading in water bodies. In this study, Lake Säkylän Pyhäjärvi and its catchment are studied as an example of a long-term, voluntary-based, co-operative model of lake and catchment management. Lake Pyhäjärvi is located in the centre of an intensive agricultural area in southwestern Finland. More than 20 professional fishermen operate in the lake area, and the lake is used as a drinking water source and for various recreational activities. Lake Pyhäjärvi is a good example of a large and shallow lake that suffers from eutrophication and is subject to measures to improve this undesired state under changing conditions. Climate change is one of the most important challenges faced by Lake Pyhäjärvi and other water bodies. The results show that climatic variation affects the amounts of runoff and nutrient loading and their timing during the year. The findings from the study area concerning warm winters and their influences on nutrient loading are in accordance with the IPCC scenarios of future climate change. In addition to nutrient reduction measures, the restoration of food chains (biomanipulation) is a key method in water quality management. The food-web structure in Lake Pyhäjärvi has, however, become disturbed due to mild winters, short ice cover and low fish catch. Ice cover that enables winter seining is extremely important to the water quality and ecosystem of Lake Pyhäjärvi, as the vendace stock is one of the key factors affecting the food web and the state of the lake. New methods for the reduction of nutrient loading and the treatment of runoff waters from agriculture, such as sand filters, were tested in field conditions. The results confirm that the filter technique is an applicable method for nutrient reduction, but further development is needed. The ability of sand filters to absorb nutrients can be improved with nutrient binding compounds, such as lime. Long-term hydrological, chemical and biological research and monitoring data on Lake Pyhäjärvi and its catchment provide a basis for water protection measures and improve our understanding of the complicated physical, chemical and biological interactions between the terrestrial and aquatic realms. In addition to measurements carried out in field conditions, Lake Pyhäjärvi and its catchment were studied using various modelling methods. In the calibration and validation of models, long-term and wide-ranging time series data proved to be valuable. Collaboration between researchers, modellers and local water managers further improves the reliability and usefulness of models. Lake Pyhäjärvi and its catchment can also be regarded as a good research laboratory from the point of view of the Baltic Sea. The main problem in both of them is eutrophication caused by excess nutrients, and nutrient loading has to be reduced – especially from agriculture. Mitigation measures are also similar in both cases.

Ison tuuligeneraattorin roottorin ja staattorin rakennetarkastelu

Maailmanlaajuinen ilmastopolitiikka asettaa vaativia tavoitteita hiilidioksidipäästöjen vähentämiselle. Suurin haaste on tuottaa energiaa mahdollisimman alhaisin kustannuksin käyttäen uusiutuvia ja ympäristöä säästäviä energiamuotoja. Tuulivoimasta on tullut nopeimmin kehittyvä sähköntuotantotapa, ja tuuliturbiinien koon kasvun myötä on myös generaattorien koko kasvanut merkittävästi 1990-luvulta lähtien. Generaattorin massiivisuus suoravetoisessa tuuliturbiinin voimansiirrossa vaatii tarkkoja kuormitustarkasteluja, jotta rakenne kestäisi tuuliturbiinin eliniän. Tuuliturbiinin kuormitukset ovat stokastisia ja toisinaan erittäin suuria, mikä vaikeuttaa kuormitusten määrittämistä. Tuulen kuormitusten lisäksi generaattori altistuu eri toimintojen kautta muillekin kuormituksille, ja tästä syystä on otettava huomioon jarrutuksen, dynaamisen tasapainon ja ohjauksen sekä verkkovikojen aiheuttamat rasitukset tuuliturbiinin voimansiirrolle. Edellisten lisäksi työssä on tarkasteltu erilaisia rakenneratkaisuja sekä pyritty kiinnittämään huomio niiden kuormankantokykyyn ja jäykkyyteen sekä generaattorin keventämismahdollisuuksiin verrattuna perinteisiin radiaalivuogeneraattoreihin. Työssä on pyritty selvittämään rakenteen kuormitukset siten, että pystyttäisiin optimoimaan mahdollisimman kevyt rakenne. Optimoinnin kohteena on pinnarakenteisen generaattorin rakenteen massa puolien, puolan kulmien sekä tukirenkaan ja niistä aiheutuvien erilaisten rakenneyhdistelmien suhteen tarkasteltuna.

Forecasting of wind speeds and directions with artificial neural networks

In this master’s thesis, wind speeds and directions were modeled with the aim of developing suitable models for hourly, daily, weekly and monthly forecasting. Artificial Neural Networks implemented in MATLAB software were used to perform the forecasts. Three main types of artificial neural network were built, namely: Feed forward neural networks, Jordan Elman neural networks and Cascade forward neural networks. Four sub models of each of these neural networks were also built, corresponding to the four forecast horizons, for both wind speeds and directions. A single neural network topology was used for each of the forecast horizons, regardless of the model type. All the models were then trained with real data of wind speeds and directions collected over a period of two years in the municipal region of Puumala in Finland. Only 70% of the data was used for training, validation and testing of the models, while the second last 15% of the data was presented to the trained models for verification. The model outputs were then compared to the last 15% of the original data, by measuring the mean square errors and sum square errors between them. Based on the results, the feed forward networks returned the lowest generalization errors for hourly, weekly and monthly forecasts of wind speeds; Jordan Elman networks returned the lowest errors when used for forecasting of daily wind speeds. Cascade forward networks gave the lowest errors when used for forecasting daily, weekly and monthly wind directions; Jordan Elman networks returned the lowest errors when used for hourly forecasting. The errors were relatively low during training of the models, but shot up upon simulation with new inputs. In addition, a combination of hyperbolic tangent transfer functions for both hidden and output layers returned better results compared to other combinations of transfer functions. In general, wind speeds were more predictable as compared to wind directions, opening up opportunities for further research into building better models for wind direction forecasting.

Electrical status epilepticus during sleep. Continuous spikes and waves during sleep

ABSTRACT Maria Peltola Electrical status epilepticus during sleep – Continuous spikes and waves during sleep Department of Clinical Neurophysiology, University of Turku Department of Clinical Neurophysiology and Department of Pediatric Neurology, Children’s Hospital, Helsinki University Central Hospital Annales Universitatis Turkuensis, Medica-Odontologica, Turku, Finland, 2014 Background: Electrical status epilepticus during sleep (ESES) is an EEG phenomenon of frequent spikes and waves occurring in slow sleep. ESES relates to cognitive deterioration in heterogeneous childhood epilepsies. Validated methods to quantitate ESES are missing. The clinical syndrome, called epileptic encephalopathy with continuous spikes and waves during sleep (CSWS) is pharmacoresistant in half of the patients. Limited data exists on surgical treatment of CSWS. Aims and methods: The effects of surgical treatment were studied by investigating electroclinical outcomes in 13 operated patients (nine callosotomies, four resections) with pharmacoresistant CSWS and cognitive decline. Secondly, an objective paradigm was searched for assessing ESES by the semiautomatic quantification of spike index (SI) and measuring spike strength from EEG. Results: Postoperatively, cognitive deterioration was stopped in 12 (92%) patients. Three out of four patients became seizure-free after resective surgery. Callosotomy resulted in greater than 90% reduction of atypical absences in six out of eight patients. The preoperative propagation of ESES from one hemisphere to the other was associated with a good response. Semiautomatic quantification of SI was a robust method when the maximal interspike interval of three seconds was used to determine the “continuous” discharge in ten EEGs. SI of the first hour of sleep appeared representative of the whole night SI. Furthermore, the spikes’ root mean square was found to be a stable measure of spike strength when spatially integrated over multiple electrodes during steady NREM sleep. Conclusions: Patients with pharmacoresistant CSWS, based on structural etiology, may benefit from resective surgery or corpus callosotomy regarding both seizure outcome and cognitive prognosis. The semiautomated SI quantification, with proper userdefined settings and the new spatially integrated measure of spike strength, are robust and promising tools for quantifying ESES. Keywords: Electrical status epilepticus during sleep, ESES, continuous spikes and waves during sleep, CSWS, epilepsy surgery, spike index, spike strength, RMS TIIVISTELMÄ Maria Peltola Unenaikainen sähköinen status epilepticus Kliininen neurofysiologia, Turun yliopisto Kliininen neurofysiologia ja lastenneurologia, Lasten ja nuorten sairaala, Helsingin yliopistollinen keskussairaala Annales Universitatis Turkuensis, Medica-Odontologica, Turku, Suomi, 2014 Tausta: Sähköinen status epilepticus unessa (ESES) on aivosähkökäyrä (EEG)-ilmiö, jossa hidasaaltounen aikana esiintyy tiheä piikkihidasaaltopurkaus. ESES:n kvantifioimiseen ei ole olemassa validoituja menetelmiä. ESES on liitetty kognitiivisen tason laskuun ja tällöin puhutaan CSWS (continuous spikes and waves during sleep) - oireyhtymästä. CSWS ei vastaa lääkehoitoon puolella potilaista ja sen epilepsiakirurgisesta hoidosta on olemassa vain vähän tietoa. Tavoitteet ja menetelmät: Selvitimme retrospektiivisesti epilepsiakirurgian vaikusta elektrokliinisiin löydöksiin 13:lla lääkeresistenttiä CSWS-oireyhtymää sairastavalla lapsella, joilla oli rakenteellinen aivojen poikkeavuus. Toinen tavoite oli löytää objektiivinen puoliautomaattinen tapa mitata purkauksen määrää ja piikkien voimakkuutta EEG:stä. Tulokset: Kognitiivisen tason jatkuva heikentyminen loppui 12 (92 %) potilaalla leikkauksen jälkeen. Kolme neljästä resektiopotilaasta tuli kohtauksettomaksi. Kallosotomian jälkeen kuudella kahdeksasta potilaasta päivittäiset kohtaukset vähenivät yli 90 %:lla. Purkauksen leviäminen leikkausta edeltävästi vain yhdestä hemisfääristä toiseen liittyi hyvään leikkaushoitovasteeseen. Piikki-indeksi, jossa käytetään jatkuvan purkauksen määritelmänä maksimissaan kolmea sekuntia piikkien välillä, osoittautui luotettavaksi menetelmäksi ESES:n kvantifioimiseen. Useammasta elektrodista integroitu piikkien neliöllinen keskiarvo oli piikin voimakkuuden vakaa mitta häiriintymättömässä NREM-unessa. Päätelmät: Lääkehoidolle vastaamatonta CSWS:ää sairastavat potilaat, joilla on rakenteellinen aivopoikkeavuus ja yhdensuuntainen purkauksen leviämismalli, näyttävät kohtausten vähenemisen lisäksi hyötyvän epilepsiakirurgiasta kognitiivisesti. Puoliautomaattinen piikki-indeksin kvantifiointi sopivilla käyttäjäasetuksilla ja uusi spatiaalisesti integroitu piikin voimakkuuden mittari ovat stabiileja ja lupaavia ESES:n kvantitatiivisia mittareita. Avainsanat: Unenaikainen sähköinen status epilepticus, ESES, CSWS, epilepsiakirurgia, piikki-indeksi, piikin voimakkuus, neliöllinen keskiarvo

Application of Carbon Nanotubes in Rotating Electrical Machines

Demand for increased energy efficiency has put an immense need for novel energy efficient systems. Electrical machines are considered as a much matured technology. Further improvement in this technology needs of finding new material to incorporate in electrical machines. Progress of carbon nanotubes research over the latest decade can open a new horizon in this aspect. Commonly known as ‘magic material’, carbon nanotubes (CNTs) have promising material properties that can change considerably the course of electrical machine design. It is believed that winding material based on carbon nanotubes create the biggest hope for a giant leap of modern technology and energy efficient systems. Though carbon nanotubes (CNTs) have shown amazing properties theoretically and practically during the latest 20 years, to the best knowledge of the author, no research has been carried out to find the future possibilities of utilizing carbon nanotubes as conductors in rotating electrical machines. In this thesis, the possibilities of utilizing carbon nanotubes in electrical machines have been studied. The design changes of electrical machine upon using carbon nanotubes instead of copper have been discussed vividly. A roadmap for this carbon nanotube winding machine has been discussed from synthesis, manufacturing and operational points of view.

Demand forecasting process design and methods in medium sized enterprise

The purpose of this thesis was to study the design of demand forecasting processes and management of demand. In literature review were different processes found and forecasting methods and techniques interviewed. Also role of bullwhip effect in supply chain was identified and how to manage it with information sharing operations. In the empirical part of study is at first described current situation and challenges in case company. After that will new way to handle demand introduced with target budget creation and how information sharing with 5 products and a few customers would bring benefits to company. Also the new S&OP process created within this study and organization for it.

The Impact of Electrical Capacity Market Mechanisms on Capacity Mobility and End Use Customer Pricing

Potential impacts of electrical capacity market design on capacity mobility and end use customer pricing are analyzed. Market rules and historical evolution are summarized to provide a background for the analysis. The summarized rules are then examined for impacts on capacity mobility. A summary of the aspects of successful capacity markets is provided. Two United States market regions are chosen for analysis based upon their market history and proximity to each other. The MISO region is chosen due to recent developments in capacity market mechanisms. The PJM region neighbors the MISO region and is similar in size and makeup. The PJM region has had a capacity market mechanism for over a decade and allows for a controlled comparison of the MISO region’s developments. Capacity rules are found to have an impact on the mobility of capacity between regions. Regulatory restrictions and financial penalties for the movement of capacity between regions are found which effectively hinder such mobility. Capacity market evolution timelines are formed from the historical evolution previously summarized and compared to historical pricing to inspect for a correlation. No direct and immediate impact on end use customer pricing was found due to capacity market design. The components of end use customer pricing are briefly examined.

Forecasting financial weather - can we foresee market sentiment? Spectrum of stock price behavior - NYSE case study

The desire to create a statistical or mathematical model, which would allow predicting the future changes in stock prices, was born many years ago. Economists and mathematicians are trying to solve this task by applying statistical analysis and physical laws, but there are still no satisfactory results. The main reason for this is that a stock exchange is a non-stationary, unstable and complex system, which is influenced by many factors. In this thesis the New York Stock Exchange was considered as the system to be explored. A topological analysis, basic statistical tools and singular value decomposition were conducted for understanding the behavior of the market. Two methods for normalization of initial daily closure prices by Dow Jones and S&P500 were introduced and applied for further analysis. As a result, some unexpected features were identified, such as a shape of distribution of correlation matrix, a bulk of which is shifted to the right hand side with respect to zero. Also non-ergodicity of NYSE was confirmed graphically. It was shown, that singular vectors differ from each other by a constant factor. There are for certain results no clear conclusions from this work, but it creates a good basis for the further analysis of market topology.

Forecasting financial weather - can we foresee market sentiment? Quantitative analysis of nodal prices in the New Zealand Electricity Spot Market

Time series of hourly electricity spot prices have peculiar properties. Electricity is by its nature difficult to store and has to be available on demand. There are many reasons for wanting to understand correlations in price movements, e.g. risk management purposes. The entire analysis carried out in this thesis has been applied to the New Zealand nodal electricity prices: offer prices (from 29 May 2002 to 31 March 2009) and final prices (from 1 January 1999 to 31 March 2009). In this paper, such natural factors as location of the node and generation type in the node that effects the correlation between nodal prices have been reviewed. It was noticed that the geographical factor affects the correlation between nodes more than others. Therefore, the visualisation of correlated nodes was done. However, for the offer prices the clear separation of correlated and not correlated nodes was not obtained. Finally, it was concluded that location factor most strongly affects correlation of electricity nodal prices; problems in visualisation probably associated with power losses when the power is transmitted over long distance.

Lightweight, liquid-cooled, direct-drive generator for highpower wind turbines: motivation, concept, and performance

Thesis: A liquid-cooled, direct-drive, permanent-magnet, synchronous generator with helical, double-layer, non-overlapping windings formed from a copper conductor with a coaxial internal coolant conduit offers an excellent combination of attributes to reliably provide economic wind power for the coming generation of wind turbines with power ratings between 5 and 20MW. A generator based on the liquid-cooled architecture proposed here will be reliable and cost effective. Its smaller size and mass will reduce build, transport, and installation costs. Summary: Converting wind energy into electricity and transmitting it to an electrical power grid to supply consumers is a relatively new and rapidly developing method of electricity generation. In the most recent decade, the increase in wind energy’s share of overall energy production has been remarkable. Thousands of land-based and offshore wind turbines have been commissioned around the globe, and thousands more are being planned. The technologies have evolved rapidly and are continuing to evolve, and wind turbine sizes and power ratings are continually increasing. Many of the newer wind turbine designs feature drivetrains based on Direct-Drive, Permanent-Magnet, Synchronous Generators (DD-PMSGs). Being low-speed high-torque machines, the diameters of air-cooled DD-PMSGs become very large to generate higher levels of power. The largest direct-drive wind turbine generator in operation today, rated just below 8MW, is 12m in diameter and approximately 220 tonne. To generate higher powers, traditional DD-PMSGs would need to become extraordinarily large. A 15MW air-cooled direct-drive generator would be of colossal size and tremendous mass and no longer economically viable. One alternative to increasing diameter is instead to increase torque density. In a permanent magnet machine, this is best done by increasing the linear current density of the stator windings. However, greater linear current density results in more Joule heating, and the additional heat cannot be removed practically using a traditional air-cooling approach. Direct liquid cooling is more effective, and when applied directly to the stator windings, higher linear current densities can be sustained leading to substantial increases in torque density. The higher torque density, in turn, makes possible significant reductions in DD-PMSG size. Over the past five years, a multidisciplinary team of researchers has applied a holistic approach to explore the application of liquid cooling to permanent-magnet wind turbine generator design. The approach has considered wind energy markets and the economics of wind power, system reliability, electromagnetic behaviors and design, thermal design and performance, mechanical architecture and behaviors, and the performance modeling of installed wind turbines. This dissertation is based on seven publications that chronicle the work. The primary outcomes are the proposal of a novel generator architecture, a multidisciplinary set of analyses to predict the behaviors, and experimentation to demonstrate some of the key principles and validate the analyses. The proposed generator concept is a direct-drive, surface-magnet, synchronous generator with fractional-slot, duplex-helical, double-layer, non-overlapping windings formed from a copper conductor with a coaxial internal coolant conduit to accommodate liquid coolant flow. The novel liquid-cooling architecture is referred to as LC DD-PMSG. The first of the seven publications summarized in this dissertation discusses the technological and economic benefits and limitations of DD-PMSGs as applied to wind energy. The second publication addresses the long-term reliability of the proposed LC DD-PMSG design. Publication 3 examines the machine’s electromagnetic design, and Publication 4 introduces an optimization tool developed to quickly define basic machine parameters. The static and harmonic behaviors of the stator and rotor wheel structures are the subject of Publication 5. And finally, Publications 6 and 7 examine steady-state and transient thermal behaviors. There have been a number of ancillary concrete outcomes associated with the work including the following. X Intellectual Property (IP) for direct liquid cooling of stator windings via an embedded coaxial coolant conduit, IP for a lightweight wheel structure for lowspeed, high-torque electrical machinery, and IP for numerous other details of the LC DD-PMSG design X Analytical demonstrations of the equivalent reliability of the LC DD-PMSG; validated electromagnetic, thermal, structural, and dynamic prediction models; and an analytical demonstration of the superior partial load efficiency and annual energy output of an LC DD-PMSG design X A set of LC DD-PMSG design guidelines and an analytical tool to establish optimal geometries quickly and early on X Proposed 8 MW LC DD-PMSG concepts for both inner and outer rotor configurations Furthermore, three technologies introduced could be relevant across a broader spectrum of applications. 1) The cost optimization methodology developed as part of this work could be further improved to produce a simple tool to establish base geometries for various electromagnetic machine types. 2) The layered sheet-steel element construction technology used for the LC DD-PMSG stator and rotor wheel structures has potential for a wide range of applications. And finally, 3) the direct liquid-cooling technology could be beneficial in higher speed electromotive applications such as vehicular electric drives.