Heat pump integration in non-continuous industrial processes by Dynamic Pinch Analysis Targeting

A key strategy for the transition towards a low-carbon economy is the electrification of industrial heat. Heat pumps can recover and upgrade excess or waste heat. They present a highly efficient component to decarbonize process heating. In Pinch Analysis, most approaches to design the heat recovery system as well as the utility system are based on a single operating point or a couple of operating point. In the past, this was due to the lack of temporally detailed process data. However, the available process data is expected to increase drastically by the use of transient process simulation models. Thus, a method is needed which interprets the data correctly and assists with design choices. This study proposes a methodology for the design and sizing of a heat pump based on the simulated annual process data of an industrial process. Three approaches are explored: (1) the conventional approach for heat pump integration by application of the Time Average Model (TAM), (2) an approach that investigates the optimal heat pump parameters for each data point by the principles of Pinch Analysis and mathematical optimization and (3) an optimization method, which considers the entire annual process data as well as thermo-economic objectives such as net present value (NPV) and internal rate of return (IRR). The new methodology compared to the conventional TAM approach is able to design a 33 % smaller heat pump, which reduces the annual operating cost by an additional 2.2 %. The NPV and IRR are more than tripled

A detailed review on current status of energy efficiency improvement in the Swiss industry sector

While quantitative methods for tracking the evolution of energy efficiency (EE) in industry do exist, these cannot always be directly applied, mainly due to lack of data on physical activity levels, as encountered in Switzerland. Therefore, a bottom-up method is developed and tested for estimating the sectoral physical activity levels in Switzerland. On this basis, sector-specific EE indices are determined. The results show that during the period 2009–2016, EE improved most in the paper sector (3.3% p.a.), followed by minerals (2.3% p.a.) and food (1.6% p.a.) sectors while the levels have remained approximately unchanged in chemical and metal sectors. Furthermore, the annual change in final energy demand was decomposed into changes of physical production, price levels and EE. The analysis concluded that only the food sector performed well according to all performance indicators. The detailed analysis of the Swiss target agreements’ data has revealed major final energy savings in chemical and food sectors during the period 2000–2016. Among the different categories of EE measures, process related measures have proven to yield the highest energy savings across all sectors. The results indicate the successful implementation of EE measures in Swiss industry, favored by the relatively strict Swiss regulatory framework and its target agreement mechanism

Cloud detection and visibility estimation using thermal camera images during night time

Reduced visibility and adverse cloud cover is a major issue for aviation, road traffic, and military activities. Synoptic meteorological stations and LIDAR measurements are common tools to detect meteorological conditions. However, a low density of meteorological stations and LIDAR measurements may limit a detailed spatial analysis. While geostationary satellite data is a valuable source of information for analyzing the spatio-temporal variability of fog and clouds on a global scale, considerable effort is still required to improve the detection of atmospheric variables on a local scale, especially during the night. In this study we propose to use thermal camera images to (1) improve cloud detection and (2) to study visibility conditions during nighttime. For this purpose, we leverage FLIR A320 and FLIR A655sc Stationary Thermal Imagers installed in the city of Bern, Switzerland. We find that the proposed data provides detailed information about low clouds and the cloud base height that is usually not seen by satellites. However, clouds with a small optical depth such as thin cirrus clouds are difficult to detect as the noise level of the captured thermal images is high. The second part of this study focuses on the detection of structural features. Predefined targets such as roof windows, an antenna, or a small church tower are selected at distances of 140m to 1210m from the camera. We distinguish between active targets (heated targets or targets with insufficient thermal insulation) and passive structural features to analyze the sensor’s visibility range. We have found that a successful detection of some passive structural features highly depends on incident solar radiation. Therefore, the detection of such features is often hindered during the night. On the other hand, active targets can be detected without difficulty during the night due to major differences in temperature between the heated target and its surrounding non-heated objects. We retrieve response values by the cross-correlation of master edge signatures of the targets and the actual edge-detected thermal camera image. These response values are a precise indicator of the atmospheric conditions and allows us to detect restricted visibility conditions

Near-Infrared High-Resolution Real-Time Omnidirectional Imaging Platform for Drone Detection

Recent technological advancements in hardware systems have made higher quality cameras. State of the art panoramic systems use them to produce videos with a resolution of 9000 x 2400 pixels at a rate of 30 frames per second (fps).(1) Many modern applications use object tracking to determine the speed and the path taken by each object moving through a scene. The detection requires detailed pixel analysis between two frames. In fields like surveillance systems or crowd analysis, this must be achieved in real time.(2) In this paper, we focus on the system-level design of multi-camera sensor acquiring near-infrared (NIR) spectrum and its ability to detect mini-UAVs in a representative rural Swiss environment. The presented results show the UAV detection from the trial that we conducted during a field trial in August 2015

Synthesis of real world drone signals based on lab recordings

There is a great interest in the generation of plausible drone signals in various applications, e.g. for auralization purposes or the compilation of training data for detection algorithms. Here, a methodology is presented which synthesises realistic immission signals based on laboratory recordings and subsequent signal processing. The transformation of a lab drone signal into a virtual field microphone signal has to consider a constant pitch shift to adjust for the manoeuvre specific rotational speed and the corresponding frequency dependent emission strength correction, a random pitch shift variation to account for turbulence induced rotational speed variations in the field, Doppler frequency shift and time and frequency dependent amplitude adjustments according to the different propagation effects. By evaluation of lab and field measurements, the relevant synthesizer parameters were determined. It was found that for the investigated set of drone types, the vertical radiation characteristics can be successfully described by a generic frequency dependent directivity pattern. The proposed method is applied to different drone models with a total weight between 800 g and 3.4 kg and is discussed with respect to its abilities and limitations comparing both, recordings taken in the lab and the field

Synthesis of real world drone signals based on lab recordings

There is a great interest in the generation of plausible drone signals in various applications, e.g. for auralization purposes or the compilation of training data for detection algorithms. Here, a methodology is presented which synthesises realistic immission signals based on laboratory recordings and subsequent signal processing. The transformation of a lab drone signal into a virtual field microphone signal has to consider a constant pitch shift to adjust for the manoeuvre specific rotational speed and the corresponding frequency dependent emission strength correction, a random pitch shift variation to account for turbulence induced rotational speed variations in the field, Doppler frequency shift and time and frequency dependent amplitude adjustments according to the different propagation effects. By evaluation of lab and field measurements, the relevant synthesizer parameters were determined. It was found that for the investigated set of drone types, the vertical radiation characteristics can be successfully described by a generic frequency dependent directivity pattern. The proposed method is applied to different drone models with a total weight between 800 g and 3.4 kg and is discussed with respect to its abilities and limitations comparing both, recordings taken in the lab and the field