Field Oriented Control (FOC) has proven to be a high performance and robust control strategy for electrical drives. However the states of the machine, namely speed and/or position, have to be measured in this control strategy. Since the use of encoders decreases the robustness of the system and increases cost, increasing interest has been focused on sensorless control schemes.  This control strategy aims to eliminate the encoder, and estimate the speed and/or position of the machine based only on the currents and voltages measurements. In this thesis, sensorless controll of a permanent magnet synchronous machine (PMSM) is studied. Two methods are introduced in this work. The Extended Kalman Filter for the high speed range and the High Frequency injection method for low speed range. In addition, these methods are implemented using an FPGA instead of a DSP solution. Simulations and emperimental results are presented. The two methods prove to be effective in their respective speed ranges, and provide a basis for hybrid full speed sensorless controller.

This thesis focus on time flexible demand of electrically heated buildings, suggesting that load can be manipulated to maintain balance between supply and demand of electricity, and reduce cost with no or small impact on temperature comfort. Taking off from a consumer perspective, associated values are discussed and energy management strategies of electrically heated buildings are evaluated.

The role of the hydraulic shock absorber is to damp oscillations and absorb energy which has a direct impact on the driving. Öhlins Racing has succeeded to produce a sophisticated semiactive technique; CES (Continuously Controlled Electronic Suspension), where the damper is controllable and therefore adaptable for various driving situations. With the knowledge of difficulties in detecting useful information about the damper-velocity at high frequencies, the aim of the thesis is to find a method which can improve the estimated velocity of a damper mounted on a motorcycle. Sensor fusion is a method which takes multiple measurements into account in an effort to reach an optimal estimate. The results showed that a Kalman filter which estimated the dampervelocity generated useful information about the sprung and the unsprung mass of the motorcycle. By measuring the position and acceleration of the sprung and the unsprung mass, time delays that are retarding the system could be reduced.

No description available.

Floor segmentation is a challenging problem in image processing. It has a wide range of applications in the engineering field. In mobile robot navigation systems, detecting which pixels belong to the floor is crucial for guiding the robot within an environment, defining the geometry of the scene, or avoiding obstacles.This report presents a floor segmentation algorithm for indoor scenarios that works with single grey-scale images. The portion of the floor closest to the camera is segmented by judiciously joining a set of horizontal and vertical lines, previously detected. Unlike similar methods in the literature, it does not rely on computing the vanishing point and, thus, it adapts faster to changes in camera motion and is not restricted to typical corridor scenes. A second contribution of this thesis project is the moving features detection for points within the segmented floor area. Based on the camera ego-motion, the expected motion of the points on the ground plane is computed and used for rejecting feature points that belong to movable obstacles. A key point of the designed method is its ability to deal with general motion of the camera. The implemented techniques are to be integrated in a visual-aided inertial navigation system (INS) that combines visual and inertial information. This INS requires a certain number of feature point correspondences on the groundplane to correct data from an inertial measurement unit (IMU) and estimate the ego-motion of the camera. Hence, segmenting the floor region and detecting movable features become relevant tasks in order to ensure that the considered features do belong to the ground.

Renewable generation is the fastest growing energy resources in the past decade. Renewable energy sources, particularly wind power, provide clean and environmentally friendly energy to meet the system demand, meanwhile introducing huge levels of uncertainty in the system. On the one hand the deregulated electric power industry and on the other hand the intermittent nature of renewable energy sources cause highly volatile and uncertain electricity prices in different market places. This will create challenges for economical operation and planning of the flexible energy sources, particularly hydropower, which being a flexible energy source is the best option to balance wind power variation. The main purpose of this work is to develop optimal short-term planning models for price taker hydropower producer working in the existing environment. Those models have to deal with the huge level of uncertainties the wind power introduces into the power system. An optimization tool known as stochastic optimization is used to plan hydropower production under uncertainties. The first model, which is used to make sensitivity analysis, is a twostage stochastic linear programming problem. The uncertainties are handled by generating scenarios based on historical data. Profound sensitivity analysis is provided, in terms of volatility in day-ahead market prices and water inflow level as well as in terms of water opportunity cost and initial volume of the reservoir. Based on the comparison of the stochastic and corresponding deterministic problems, the result aims to show the impact of modeling the uncertainties explicitly. The results show that for the short-term hydropower planning problems the effect of considering price uncertainty in the stochastic model is higher compared with considering inflow level uncertainty. The second model used in this work is a two-stage stochastic linear programming problem. The model generates optimal bids to day-ahead market considering real-time market price uncertainties. While simultaneously bidding to both markets, the results for most of the hours suggest two actions; either to bid the available amount of energy to upward regulation market or to bid the maximum capacity to day-ahead market and bring back the whole amount making down regulation. To make the bidding strategies more flexible and robust different approaches are modeled and assessed. Finally one of the approaches is suggested as the most applicable one. / <p>QC 20121109</p>

QC 20111205

<p>QC 20120208</p>

Society has become increasingly dependent on electricity, so power system reliability is of crucial importance. However, while underinvestment leads to an unacceptable number of power outages, overinvestment will result in costs that are too high for society. The challenge is to find a socioeconomically adequate level of risk. In this risk assessment, not only the probability of power outages, but also the severity of their consequences should be included.   A risk assessment can be performed from either the perspective of customers or the perspective of the grid owner, depending on whether the consequences faced by customers or the grid owner are considered. Consequences of power outages are usually measured through interruption costs. Examples of interruption costs for the grid owner are customer compensations and loss of goodwill. Examples of interruption costs for customers are retail losses for commercial customers and loss of heating and lighting for residential customers. The aim of this thesis is to develop methods for assessing risks in power distribution systems from the customer-oriented perspective. From this perspective realistic assessments of customer interruption costs are essential.   To perform a customer-oriented risk assessment of a distribution system three different models are required: a customer interruption cost model, a load model and a reliability model. The customer interruption cost model describes the consequences, or costs, of power outages that customers face. The load model predicts the loss of load and the energy not supplied due to power outages. The reliability model describes component failures, which are the root causes of power outages, and the restoration processes that follow. The three models can be used together in a cost-benefit analysis to investigate the consequences for customers due to different investment alternatives.   In this thesis a set of new models is developed that incorporates time dependencies in customer interruption costs, load and component failures. The timing of the outage has an impact on the consequences customers face. Severe weather, which is a main contributor to component failures, is generally more common during certain seasons. These facts imply that there may be a correlation between high customer interruption costs and an increased risk for power outages. In Sweden the frequency of storms is higher during the cold period of the year when the demanded load and customer interruption costs are also high. By taking time dependencies into account, the correlation between high interruption costs and elevated risk for power outages is captured.   Results from the risk assessments of two test distribution systems using the models developed in this thesis show that taking time dependencies into account has a considerable impact on the estimation of customer interruption costs and energy not supplied due to outages. To evaluate the risks of extreme costs, the tools Value-at-Risk and Conditional Value-at-Risk which are commonly used in the finance industry are applied. A conclusion that can be drawn from the simulation results is that taking time dependencies into account is especially important when considering extreme outage events that give rise to extreme costs. / Samhället blir allt mer elberoende och leveranssäkerhet av el är av yttersta vikt. Medan underinvesteringar leder till ett oacceptabelt antal elavbrott medför dock överinvesteringar för höga kostnader för samhället. Utmaningen är därför att hitta en samhällsekonomisk lönsam risknivå. I en riskanalys måste inte bara hänsyn tas till sannolikheten för elavbrott utan också avbrottens konsekvenser.   En riskanalys kan genomföras från antingen kundernas eller nätägarens perspektiv beroende på om det är kundernas konsekvenser eller nätägarnas konsekvenser av elavbrott som tas med i analysen. Konsekvenser av elavbrott mäts oftast i avbrottskostnader. Exempel på avbrottskostnader som drabbar nätägaren är goodwill-förluster och ersättning till kunder som har haft långa elavbrott. Exempel på avbrottskostnader som drabbar kunder är förlorade försäljningsintäkter för handel- och tjänsteföretag och uteblivna möjligheter till uppvärmning och belysning för hushåll. Avhandlingens syfte är att utveckla metoder för riskanalys av eldistributionsnät utifrån kundperspektivet. Centralt i detta perspektiv är realistiska uppskattningar av kundavbrottskostnader.   För att kunna genomföra en riskanalys från kundperspektivet krävs tre modeller: en kundavbrottskostnadsmodell, en belastningsmodell och en tillförlitlighetsmodell. Kundavbrottskostnadsmodellen beskriver konsekvenserna, eller kostnaderna, för kunderna av elavbrott. Belastningsmodellen modellerar icke-levererad energi och effekt på grund av elavbrott. Tillförlitlighetsmodellen beskriver fel- och lagningsprocessen för de olika komponenterna i elnätet. De tre modellerna kan kombineras i en kostnad/nytta-analys för att beskriva konsekvenserna för kunder av olika investeringsalternativ.   I denna avhandling utvecklas tre nya modeller som tar hänsyn till tidsberoenden i kundavbrottskostnader, belastning samt komponenters fel- och lagningsprocess. Tidpunkten för avbrottet har stor betydelse för vilka konsekvenserna blir för kunderna. Vidare är oväder, som ofta orsakar elavbrott, i regel mer koncentrerade till vissa årstider. Dessa fakta medför att det kan finnas en korrelation mellan höga kundavbrottskostnader och en ökad risk för elavbrott. I Sverige är vinterstormar vanligast och på vintern är även belastningen och avbrottskostnaden som högst. Genom att ta hänsyn till tidsberoenden fångas korrelationer mellan höga avbrottskostnader och en ökad haveririsk.   Med hjälp av de tre utvecklade modellerna genomförs riskanalyser av två fiktiva distributionsnät. Resultaten från analyserna visar att det ger en stor inverkan på den uppskattade kundavbrottskostnaden och den icke-levererade energin om hänsyn tas till tidsvariationer. För att utvärdera risken för extrema kostnader används två riskverktyg från finansbranschen: Value-at-risk och Conditional Value-at-risk. En slutsats från tillämpningen av riskverktygen är att tidsberoenden är speciellt viktiga att beakta om fokus ligger på de extrema händelser som ger upphov till extrema kostnader. / QC 20101102

In UWB communication sampling plays a key role in detection of the transmitted data. There are various methods of data transmission and detection at the receiver. Mostly, the detection methods are based on frequency domain methods. The popular method to lower the sampling rate is the sub-sampling technique, based on frequency of the transmitted signal. A special method like orthogonal frequency division multiplexing (OFDM) is needed to reduce inter symbol interference for a frequency based method. The power consumption associated with higher sampling rates is also a big challenge. Therefore some simple techniques are required to detect data on lower sampling rates without ISI in the multiple user environments and with lower power consumption. If selection of the sampling frequency would be flexible to detect data from multiple users then it could relax the UWB receiver design requirements. In this thesis we developed a transmission and reception methodology with reduced sampling frequency for data detection.   In the proposed work, transmitted data is distributed using TDMA frames for all users within fixed time slots for each user. The TDMA technique is being used to achieve low sampling rates and to avoid multiple access interference (MAI). The sampling rate to detect the data of each user can be selected according to number of users and transmission bandwidth. For this purpose each data bit of a user is arranged once in a transmission frame. The data can be detected on frame repetition rate depends on the total number of users. The data of each user can be accessed directly by calculating the total time of each user place within each frame. Since each data bit of one user occurs once in a frame therefore it could be claimed that ISI within the same user has been avoided. The proposed scheme has been tested with 50 MHz, 100 MHz and 500 MHz sampling frequencies for 50 users, 25 users and 5 users respectively by using 2.5 GHz bandwidth. 8-bits of data was transmitted and detected for different users using Matlab and Simulink Models. The results were analyzed in perfect synchronization condition and compared between integrated window energy detector UWB receiver and an UWB receiver using a matched filter. The performances are evaluated on the basis of BER. To observe the impact of synchronization, both receivers were evaluated with some timing mismatch. It is concluded that the scheme works well for the lower sampling rate for both types of UWB receivers stated above. It can also be concluded by observing the results that the UWB receiver using matched filter has better performance in noisy environment compared to energy detector UWB receiver with integrated window. The performance of energy detector UWB receiver with integrated window and UWB receiver with matched filter were also evaluated with timing mismatch. It can be concluded that the UWB receiver with integrated window has better performance compared to UWB receiver using matched filter if the synchronization is not achieved properly. The UWB receiver with matched filter is more vulnerable against timing mismatch compared to UWB receiver with integrated window. / QC 20120612