Fraunhofer-Institut für Optronik, Systemtechnik und Bildauswertung IOSB

Filters

Reset filters

Settings
Now showing 1 - 10 of 25
  • Publication
    Intelligent Information Management in Aquaponics to Increase Mutual Benefits
    ( 2021)
    Karimanzira, Divas
    ;
    Na, Chai
    ;
    Hong, Mu
    ;
    Wei, Yaoguang
    Aquaponics are feedback and two player systems, in which fish and crops mutually benefit from one another and, therefore require close monitoring, management and control. Vast amount of data and information flow from the aquaponics plant itself with its huge amount of smart sensors for water quality, fish and plant growth, system state etc. and from the stakeholder, e.g., farmers, retailers and end consumers. The intelligent management of aquaponics is only possible if this data and information are managed and used in an intelligent way. Therefore, the main focus of this paper is to introduce an intelligent information management (IIM) for aquaponics. It will be shown how the information can be used to create services such as predictive analytics, system optimization and anomaly detection to improve the aquaponics system. The results show that the system enabled full traceability and transparency in the aquaponics processes (customers can follow what is going on at the farm), reduced water and energy use and increased revenue through early fault detection. In this, paper the information management approach will be introduced and the key benefits of the digitized aquaponics system will be given.
  • Publication
    A LSTM-based Model Predictive Control for a Reverse Osmosis Desalination Plant
    ( 2020)
    Karimanzira, Divas
    ;
    Rauschenbach, Thomas
    Reverse Osmosis (RO) desalination plants are highly nonlinear multi-input-multioutput systems that affected by uncertainties, constraints and some physical phenomenon such as membrane fouling that are mathematically difficult to describe. Such systems require effective control strategies that take these effects into account. Such a control strategy is the nonlinear model predictive (NMPC) controller. However, a NMPC depends very much on the accuracy of the internal model used for prediction in order to maintain feasible operating conditions of the RO desalination plant. Recurrent Neural Networks (RNNs), especially the Long-Short-Term Memory (LSTM) can capture complex nonlinear dynamic behavior and provide long-range predictions even in the presence of disturbances. Therefore, in this paper a NMPC for a RO desalination plant that utilizes a LSTM as the predictive model will be presented. It will be tested to maintain a given permeate flow rate and keep the permeate concentration under a certain limit by manipulating the feed pressure. Results show a good performance of the system.
  • Publication
    Object Detection in Sonar Images
    ( 2020)
    Karimanzira, Divas
    ;
    Renkewitz, Helge
    ;
    Shea, David
    ;
    Albiez, Jan
    The scope of the project described in this paper is the development of a generalized underwater object detection solution based on Automated Machine Learning (AutoML) principles. Multiple scales, dual priorities, speed, limited data, and class imbalance make object detection a very challenging task. In underwater object detection, further complications come in to play due to acoustic image problems such as non-homogeneous resolution, non-uniform intensity, speckle noise, acoustic shadowing, acoustic reverberation, and multipath problems. Therefore, we focus on finding solutions to the problems along the underwater object detection pipeline. A pipeline for realizing a robust generic object detector will be described and demonstrated on a case study of detection of an underwater docking station in sonar images. The system shows an overall detection and classification performance average precision (AP) score of 0.98392 for a test set of 5000 underwater sonar frames.
  • Publication
    A novel framework for synchrophasor based online recognition and efficient post-mortem analysis of disturbances in power systems
    ( 2020)
    Kummerow, André
    ;
    Monsalve, Cristian
    ;
    Brosinsky, Christoph
    ;
    Nicolai, Steffen
    ;
    Westermann, Dirk
    Synchrophasor based applications become more and more popular in today's control centers to monitor and control transient system events. This can ensure secure system operation when dealing with bidirectional power flows, diminishing reserves and an increased number of active grid components. Today's synchrophasor applications provide a lot of additional information about the dynamic system behavior but without significant improvement of the system operation due to the lack of interpretable and condensed results as well as missing integration into existing decision-making processes. This study presents a holistic framework for novel machine learning based applications analyzing both historical as well as online synchrophasor data streams. Different methods from dimension reduction, anomaly detection as well as time series classification are used to automatically detect disturbances combined with a web-based online visualization tool. This enables automated decision-making processes in control centers to mitigate critical system states and to ensure secure system operations (e.g., by activating curate actions). Measurement and simulation-based results are presented to evaluate the proposed synchrophasor application modules for different use cases at the transmission and distribution level.
  • Publication
    Hardware/Software architecture to investigate resilience in energy management for smart grids*
    ( 2020)
    Lenk, Steve
    ;
    Arnoldt, Alexander
    ;
    Rösch, Dennis
    ;
    Bretschneider, Peter
    In the age of digitization, for critical infrastructures arises new challenges due to the amount of data to handle, the increasing automation level and threats to cybersecurity. Resilience of critical systems, i. e., to be prepared for and to prevent threats, to protect systems against them, to respond to threats and to recover from them, rises in priority. Here, we present a hardware-software architecture design for energy management systems as part of critical energy infrastructures, which is scalable, distributable, parallelizable and adaptable. Therefore, it is capable to handle the increasing amount of data but it also allows an in-depth monitoring. This enables the investigation of the impact of diverse threat scenarios like technical errors, human failure and cyber attacks. Thus, it is the basis for developing resilient algorithms, improved communications channels and monitoring mechanisms for energy management systems.
  • Publication
    Simulation of Coupled Components within Power-Hardware-in-the-Loop (PHiL) Test Bench
    ( 2020)
    Ruhe, Stephan
    ;
    Fechner, Max
    ;
    Nicolai, Steffen
    ;
    Bretschneider, Peter
    Power Hardware-in-the-Loop (PHiL) becomes more and more an important part at the investigation of dynamics and stability issues of the electrical grids. As derived from Hardware-in-the-Loop (HiL) approach, one of the central PHiL requirements is to feedback measurement signals into the simulation. In PHIL applications, the operational behavior of a connected device is integrated within real-time simulations. With the integration of the Hardware under Test (HuT) into a PHiL test bench, stability issues may arise. Therefore, this paper focuses on the stability investigation and the description of typical PHiL setup and condititions. The frequency domain modelling reveals phenomenon of instability as well as concepts of Interface Algorithm (IA) and Compensation Methods (CM). To investigate the behavior of different devices as HuT, also the HuT is modelled and simulated in the real time environment. In the next step, the analog loopback integrates HuT models into PHiL simulation by using HYPERSIM from OPAL-RT as simulation software (time domain). Analog loopback introduces time delay into the PHiL simulation that would also occur in real PHiL applications with connected devices to build a more realistic environment. The simulation with analog loopback consists of implemented IAs which feedback operational behavior of HuT models into PHiL test bench. In selected simulation approaches, the mentioned technique loops back currents of various loads and inverters. Therefore it is possible to evaluate the feedback of devices with different described methods and their impact on stability and signal fidelity.
  • Publication
    How to Use Wind Power Efficiently for Seawater Reverse Osmosis Desalination
    ( 2020)
    Karimanzira, Divas
    Due to water scarcity and the global trends in climate change, winning drinking water through desalination is increasingly becoming an option, especially using reverse osmosis (RO) membrane technology. Operating a reverse osmosis desalination plant is associated with several expenses and energy consumption that take a very large share. Several studies have shown that wind power incurs lower energy costs compared to other renewable energy sources, therefore, should be the first choice to be coupled to an RO desalination system to clean water using sustainable energy. Therefore, in this paper, we investigate the feasibility of driving an RO desalination system using wind power with and without pressure vessel energy storage and small scale energy recovery using Clark pump based on simulation models. The performance of both variants was compared with several scenarios of wind patterns. As expected buffering and energy recovery delivered higher water production and better water quality demonstrating the importance of an energy storage/recovery system for a wind-power-supplied desalination plant.
  • Publication
    Cyber-physical data stream assessment incorporating Digital Twins in future power systems
    ( 2020)
    Kummerow, André
    ;
    Monsalve, Christian
    ;
    Rösch, Dennis
    ;
    Schäfer, Kevin
    ;
    Nicolai, Steffen
    Reliable and secure grid operations become more and more challenging in context of increasing IT/OT convergence and decreasing dynamic margins in today's power systems. To ensure the correct operation of monitoring and control functions in control centres, an intelligent assessment of the different information sources is necessary to provide a robust data source in case of critical physical events as well as cyber-attacks. Within this paper, a holistic data stream assessment methodology is proposed using an expert knowledge based cyber-physical situational awareness for different steady and transient system states. This approach goes beyond existing techniques by combining high-resolution PMU data with SCADA information as well as Digital Twin and AI based anomaly detection functionalities.
  • Publication
    Angewandtes Quantencomputing
    ( 2020)
    Lässig, Jörg
    Quantencomputing ist als Konzept mittlerweile zwar mehrere Jahrzehnte alt und hat von der Idee bis zu den heutigen Noisy Intermediate-Scale Quantum Maschinen verschiedene Phasen stetiger Entwicklung durchlaufen, jedoch insbesondere in den letzten Jahren deutlich an Dynamik gewonnen. Im aktuellen Stadium stehen Quantenrechner zur Verfügung, die zwar noch immer stark limitiert sind, jedoch die Ausführung maßgeschneiderter Algorithmen unterstützen, die bestehende Schwächen dieser Maschinen mit ihrem speziellen Design zu umgehen versuchen. Diese Algorithmen adressieren dabei mit Maschinellem Lernen, kombinatorischer Optimierung und Simulationsanwendungen sowie weiteren potenziellen Anwendungsfeldern Problemstellungen, die praktisch vielfältig relevant und deshalb von breitem, allgemeinen Interesse sind. Das prinzipielle Potenzial des Quantencomputers, in bestimmten Anwendungsfeldern deutlich leistungsfähiger zu sein als klassische Rechner, ruft viel Aufmerksamkeit hervor. Außerdem stellt bereits eine ganze Reihe von prinzipiell für jedermann zugänglichen Softwareframeworks Implementierungen aktueller Quantenalgorithmen zum Test und zur Evaluierung bereit. Der Artikel stellt die bisherige Entwicklung, aktuelle Verfahren sowie weitere Perspektiven der Technologie in Grundzügen dar und informiert über mögliche Anwendungsgebiete aber auch bekannte Grenzen des Quantencomputing-Paradigmas.
  • Publication
    Application of blockchain technology for electricity supplier change
    ( 2020)
    Pemsel, Jonas
    ;
    Warweg, Oliver
    ;
    Bretschneider, Peter
    In the course of digitalization various technologies which could deeply transform present processes are put forth. As such an innovation, blockchain is attributed to have potential to make energy industry procedures more efficient and to simplify them. The aim of this paper is to examine the applicability of this technology using the change of power supplier as an example. Based on Ethereum a proper blockchain solution for the use-case is developed using smart contracts to handle all processes of the example. Beside qualitative evaluation of manipulation security and privacy, a test scenario is built to measure the speed in which the developed solution allows supplier changes.