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A key problem when using the derotator is to ensure the coaxial alignment between the optical axis of the derotator and the rotation axis of the measured object. Moreover, accurate measurement of the rotation axis is the prerequisite of achieving the coaxial alignment. In this paper, we propose a strategy for estimation of the rotation axis with the assistant of an auxiliary laser and a binocular stereo vision sensor. When a laser source is temporarily attached to the measured object or the rotor shaft, the rotation of the laser will generate a ruled surface. The binocular sensor can accurately measure the coordinates of laser dots in three-dimensional (3D) space. The pose vector of the laser in each certain rotation angle can be estimated with measured 3D coordinates of the laser dots. Finally, the rotation axis of the object can be estimated with multiple pose vectors considering the constraint of the fixed axis rotation. The validity and precision of this proposed strategy are demonstrated by means of experiments. © 2018 SPIE.

Increasing shares of fluctuating renewable energy, the integration of European electricity grids and markets as well as new technologies induce continuous change in the European energy system. Due to these changes, fundamental electricity system and market models that have been developed and applied in the past are dealing with an increasing number of details inducing correspondingly huge data needs. The complexity of these called parameter-rich models (cf. Weron, 2014) leads to limited transparency, also on the impact of data on results, and makes model backtesting rather cumbersome. At the same time, the validity of future scenarios based on non-validated models is dubious. To complement these highly complicated models, more reduced models may be helpful both for transparency and for backtesting. In this paper, we apply a parsimonious fundamental modelling approach to determine hourly German day-ahead power market prices and production volumes. The methodology approximates the supply stack by a piecewise linear function and considers fundamental information, e.g. power plant capacities and availabilities, fuel prices, must-run production and cross-border exchange. We reduce complexity by considering technology classes, uncoupled time periods and only one market area. Between 2011 and 2015, German day-ahead prices declined by 38% and various reasons have been identified in literature, namely a drop in emission certificate prices, the expansion of renewable energies (RES) or lower fuel prices. However, the decision of the German government to shut down nuclear power plants after the Fukushima nuclear disaster happened at the same time and received too little attention as it rather by itself could have led to an increase in prices. The parsimonious model is able to reproduce the hourly historical prices (2011-2015) with a MAE of 5.6 €/MWh and accurately reproduces the electricity production volumes for most thermal production units. In a case study, we investigate a counterfactual scenario without accelerated nuclear phase-out in Germany after the Fukushima nuclear disaster in 2011. The results indicate that German day-ahead power prices would have fallen by additional 3 €/MWh if the nuclear phase-out would have not occurred. Since coal- and gas-fired production as well as additional imports have substituted production from nuclear power plants, their usage would have dropped in the counterfactual scenario.

Practitioners in the electricity industry aim to assess the value of power plants or other real options several months or even years ahead of operation. Such a valuation is notably required for hedging purposes. The revenue streams to be earned in the spot market are thereby already secured on future markets. Yet the peculiarities of the electricity market, notably the limited storability of electricity and the incompleteness of the derivative markets, make this problem also theoretically challenging since they prevent the straightforward application of standard approaches for price modeling and for hedging. In this context, the contribution of this article is twofold: (1) We present a novel methodology to model electricity prices based on fundamental expectations and accounting for both short-term and long-term uncertainties. This requires the joint modeling of different commodity prices, namely electricity, fuel and CO2 prices. Moreover price distributions have to be modelled in order to assess the real option value adequately ex ante. Specifically, we compare two different modeling approaches to account for long-term variations in multi-commodity price dynamics. (2) We suggest a test procedure and introduce performance measures to analyze the accuracy of the proposed price modeling. We thereby focus on the practically relevant question, whether the price modeling provides ex ante estimates of the value of the real option that are in line with the ex post realized values. This approach is chosen since no derivative markets exist where the (extrinsic) values for the real options could be observed months or years ahead of actual operation. Nonetheless we show that under well-defined assumptions, the ex-ante values derived using the price model should provide unbiased estimates of the ex post values, which are computed as a sum of hedging and spot exercise revenues. The application part shows results for a state-of-the-art gas power plant. By applying the developed performance measures and test statistics, we find that neither of the two investigated price models clearly outperforms the other.

This work proposes a two-step phase-shifting algorithm as an improvement of fringe projection profilometry. Considering the working process of fringe projection, the captured fringe image is formulated with two variables, i.e. surface reflectivity and phase value. And a phase shift of 3π/2 is introduced to get the two-step phase-shifting. After appropriate variable substitution, expressions of two fringe images can be transformed into two equations corresponding to a line and a circle respectively. With this circle-line model, the characteristic of solution and the phase error due to non-zero ambient light are analyzed. Then the approach of error compensation is proposed based on estimation of the real fringe contrast and non-linear least square optimization. The validity of the proposed approach is demonstrated with both simulations and experiments.

Increasing requirements concerning the quality and lifetime of machine components in industrial and automotive applications require comprehensive investigations of the components in conditions close to the application. Irregularities in heating of mechanical parts reveal regions with increased loading of pressure, draft or friction. In the long run this leads to damage and total failure of the machine. Thermographic measurements of rotating objects, e.g., rolling bearings, brakes, and clutches provide an approach to investigate those defects. However, it is challenging to measure fast-rotating objects accurately. Currently one contact-free approach is performing stroboscopic measurements using an infrared sensor. The data acquisition is triggered so that the image is taken once per revolution. This leads to a huge loss of information on the majority of the movement and to motion blur. The objective of this research is showing the potential of using an optomechanical image derotator together with a thermographic camera. The derotator follows the rotation of the measurement object so that quasi-stationary thermal images during motion can be acquired by the infrared sensor. Unlike conventional derotators which use a glass prism to achieve this effect, the derotator within this work is equipped with a sophisticated reflector assembly. These reflectors are made of aluminum to transfer infrared radiation emitted by the rotating object. Because of the resulting stationary thermal image, the operation can be monitored continuously even for fast-rotating objects. The field of view can also be set to a small off-axis region of interest which then can be investigated with higher resolution or frame rate. To depict the potential of this approach, thermographic measurements on a rolling bearings in different operating states are presented. © 2017 SPIE.

Unstable movement in roller bearings like cage or roller slip can lead to damages or eventually even to an early break of the bearing. To prevent slip, inadequate operating states should be avoided. Therefore, it is necessary to study the dynamic behavior of the bearing. Unfortunately, there is only a limited range of measurement methods for the dynamic of bearing components. Two possible approaches are using solely a high-speed camera or the combination of an optomechanical image derotator and a high-speed camera. This work focuses on a proposal which is suitable for both. Initially, the influence of the rotational velocity in the images is eliminated. In the next step the measurement data is reduced to a region of interest which displays a particular rolling-element. A rolling element is equipped with a linear marker which, in the next stage, is segmented by a thresholding method to multiple regions. The region representing the marker is extracted from the background and the position is calculated by a Principle Component Analysis. Depending on the shift of the angular position and the lag time between two images, the rotational velocity of the rolling element is calculated. Thus, it is possible to determine whether the rolling element is operating under ideal conditions. In conclusion, it can be said that this approach enables a simple and flexible non-invasive method to depict the occurrence of roller slip in roller bearings. © 2017 SPIE.

Dissertation, Universität Duisburg-Essen, 2018 (Kumulative Dissertation)

An increasing share of variable renewable energy sources (VREs) basically affects the electricity price formation in two ways: (1) The so-called merit order effect tends to lower the base price level and challenges conventional plants to remain profitable. (2) Due to the variable nature of renewable energy infeed, the shortterm demand for flexibility increases and changes the volatility of electricity prices. The more variable prices offer opportunities for controllable electricity producers (CEPs) to provide up- and down-ramping flexibility to increase their revenues. In contrast, the VREs with high degrees of simultaneity tend to pay for this flexibility in the electricity spot market to reduce their imbalance exposure. The intraday market (IDM) for electricity has gained importance for the market value of different technologies lately and continues to expand due to the increasing efforts to balance within-day deviation from day-ahead schedules. This article presents a combination and extension of two existing models to capture the peculiarities of the intraday price formation and to analyse the impact of the IDM on the market value of VREs and CEPs. Doing so, the paper suggests an adjustment of the classical market value factor metric and to go beyond classical day-ahead market (DAM) information. The article shows that market value factors (MVFs) can be stabilized if the IDM delivers "marketbased" price signals for the costs of flexibility, that are sufficient to activate flexibilities prior to the usually more expensive imbalance mechanism (IBM). Yet, the MVFs from single VRE technologies will worsen if their market share is high enough to outweigh forecast errors from other technologies and if they become a permanent price maker in the IDM and the IBM.