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ALADIN-α - An open-source MATLAB toolbox for distributed non-convex optimization

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arXiv 2020年

作者： Engelmann, Alexander Jiang, Yuning Benner, Henrieke Ou, Ruchuan Houska, Boris Faulwasser, Timm Institute for Automation and Applied Informatics Karlsruhe Institute of Technology Karlsruhe Germany School of Information Science and Technology ShanghaiTech University Shanghai China

This paper introduces an open-source software for distributed and decentralized non-convex optimization named ALADIN-α. ALADIN-α is a MATLAB implementation of tailored variants of the Augmented Lagrangian Alternating Direction Inexact Newton (ALADIN) algorithm. Its user interface is convenient for rapid prototyping of non-convex distributed optimization algorithms. An improved version of the recently proposed bi-level variant of ALADIN is included enabling decentralized non-convex optimization with reduced information exchange. A collection of examples from different applications fields including chemical engineering, robotics, and power systems underpins the potential of ALADIN-α. Copyright © 2020, The Authors. All rights reserved.

关键词： Constrained optimization

Robust adaptive state-feedback control of linear time-varying systems under both potentially unbounded system's modeling uncertainty and external disturbance

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arXiv 2020年

作者： Vrabel, R. Slovak University of Technology in Bratislava Institute of Applied Informatics Automation and Mechatronics Bottova 25 Trnava917 01 Slovakia

The conceptually new approach based on the logarithmic norm to design of robust adaptive state-feedback controller for linear time-varying (LTV) systems under system's modeling uncertainty and nonlinear external disturbance is proposed. This controller, consisting of two independent parts - adaptive and robust ones - globally asymptotically stabilizes every LTV system regardless how large the disturbance *** Codes 93D09 93D21 34M03. Copyright © 2020, The Authors. All rights reserved.

关键词： Robust control

Smart data representations: Impact on the accuracy of deep neural networks

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arXiv 2021年

作者： Neumann, Oliver Ludwig, Nicole Turowski, Marian Heidrich, Benedikt Hagenmeyer, Veit Mikut, Ralf Institute for Automation and Applied Informatics Karlsruhe Institute of Technology Hermann-von-Helmholtz-Platz 1 Eggenstein-Leopoldshafen76344 Germany Cluster of Excellence Machine Learning University of Tübingen Maria-von-Linden Str. 6 Tübingen72076 Germany

Deep Neural Networks (DNNs) are able to solve many complex tasks with less engineering effort and better performance. However, these networks often use data for training and evaluation without investigating its representation, i.e. the form of the used data. In the present paper, we analyze the impact of data representations on the performance of DNNs using energy time series forecasting. Based on an overview of exemplary data representations, we select four exemplary data representations and evaluate them using two different DNN architectures and three forecasting horizons on real-world energy time series. The results show that, depending on the forecast horizon, the same data representations can have a positive or negative impact on the accuracy of DNNs. © 2021, CC BY.

关键词： Deep neural networks

Mixed-Integer vs. Real-Valued Formulations of Battery Scheduling Problems

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IFAC-PapersOnLine 2018年第28期51卷 350-355页

作者： Murray, Alexander Faulwasser, Timm Hagenmeyer, Veit Institute for Automation and Applied Informatics Karlsruhe Institute of Technology Karlsruhe Germany

Coordinating the charging and discharging of a population of batteries with respect to load and generation forecasts decreases operating costs. However, in the case of asymmetric charging and discharging efficiencies the mathematical formulation of this problem is not straightforward. This paper compares the scheduling problem for a population of batteries in two formulations: mixed-integer (MINLP) and non-convex real-valued (NLP). In the case of the latter, the resulting separable NLP is solved using the Augmented Lagrangian based Alternating Direction Inexact Newton (ALADIN). In the case of the latter, the resulting MINLP is solved in hierarchical distributed fashion, we propose a mixed-integer extension of ALADIN. Real load and generation data is used to create an example of 54 batteries demonstrating improved performance for the MINLP formulation. © 2018

关键词： Charging (batteries) Constrained optimization Natural language processing systems Operating costs Scheduling Secondary batteries Standby power systems ALADIN Alternating directions Augmented Lagrangians Distributed optimization Generation forecast Mathematical formulation MINLP Scheduling problem

Turnpike properties in discrete-time mixed-integer optimal control

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arXiv 2020年

作者： Faulwasser, Timm Murray, Alexander Institute for Energy Systems Energy Efficiency and Energy Economics TU Dortmund University Germany Institute for Automation and Applied Informatics Karlsruhe Institute of Technology Germany

This note discusses properties of parametric discrete-time Mixed-Integer Optimal Control Problems (MIOCPs) as they often arise in mixed-integer NMPC. We argue that in want for a handle on similarity properties of parametric MIOCPs the classical turnpike notion from optimal control is helpful. We provide sufficient turnpike conditions based on a dissipativity notion of MIOCPs, and we show that the turnpike property allows specific and accurate guesses for the integer-valued controls. Moreover, we show how the turnpike property can be used to derive efficient node-weighted branch-and-bound schemes tailored to parametric MIOCPs. We draw upon numerical examples to illustrate our findings. Copyright © 2020, The Authors. All rights reserved.

关键词： Optimal control systems

Hierarchical Distributed Mixed-Integer Optimization for Reactive Power Dispatch

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IFAC-PapersOnLine 2018年第28期51卷 368-373页

作者： Murray, Alexander Engelmann, Alexander Hagenmeyer, Veit Faulwasser, Timm Institute for Automation and Applied Informatics Karlsruhe Institute of Technology Karlsruhe Germany

One key aspect of power system operation is the minimization of line losses while maintaining voltages within certain limits. Doing so can be achieved through the use of voltage regulators, tap changing transformers, and shunt capacitors. However, both tap changing transformers and/or shunt capacitors are operated in a discrete manner, i.e. the inputs can only take finitely many discrete values. Thus, the problem of minimizing line losses while maintaining voltage stability can be cast as a mixed-integer optimization problem. For large grids or cases where independent entities have concurrent control of the system, distributed optimization provides a solution. The present paper discusses a hierarchically distributed approach; i.e. the problem is partitioned into local subproblems and solved using a mixed-integer extension of the Augmented Lagrangian based Alternating Direction Inexact Newton (ALADIN) algorithm. We present results for the IEEE 14- and 30-bus systems and compare them with previous approaches, such as particle swarm optimization and genetic algorithms. © 2018

关键词： Electric load dispatching Concurrency control Constrained optimization Electric load flow Genetic algorithms Integer programming Particle swarm optimization (PSO) Reactive power Voltage regulators Alternating directions Distributed approaches Distributed optimization Mixed integer optimization Mixed integer problems Optimal power flows Power system operations Reactive power dispatch

Import options for chemical energy carriers from renewable sources to Germany

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arXiv 2021年

作者： Hampp, Johannes Düren, Michael Brown, Tom Center for International Development and Environmental Research Justus Liebig University Gießen Hesse Germany Department of Digital Transformation in Energy Systems Technische Universität Berlin Berlin Germany Institute for Automation and Applied Informatics Karlsruhe Institute of Technology Baden-Württemberg Germany

Import and export of fossil energy carriers are cornerstones of energy systems world-wide. If energy systems are to become climate neutral and sustainable, fossil carriers need to be substituted with carbon neutral alternatives or electrified if possible. We investigate synthetic chemical energy carriers, hydrogen, methane, methanol, ammonia and Fischer-Tropsch fuels, produced using electricity from Renewable Energy Source (RES) as fossil substitutes. RES potentials are obtained from GIS-analysis and hourly resolved time-series are derived using reanalysis weather data. We model the sourcing of feedstock chemicals, synthesis and transport along nine different Energy Supply Chains to Germany and compare import options for seven locations around the world against each other and with domestically sourced alternatives on the basis of their respective cost per unit of hydrogen and energy delivered. We find that for each type of chemical energy carrier, there is an import option with lower costs compared to domestic production in Germany. No single exporting country or energy carrier has a unique cost advantage, since for each energy carrier and country there are cost-competitive alternatives. This allows exporter and infrastructure decisions to be made based on other criteria than energy and cost. The lowest cost means for importing of energy and hydrogen are by hydrogen pipeline from Denmark, Spain and Western Asia and Northern Africa starting at 36EUR/MWhLHVto 42EUR/MWhLHVor 1.0EUR/kgH2to 1.3EUR/kgH2(in 2050, assuming 5% p.a. capital cost). For complex energy carriers derived from hydrogen like methane, ammonia, methanol or Fischer-Tropsch fuels, imports from Argentina by ship to Germany are lower cost than closer exporters in the European Union or Western Asia and Northern Africa. For meeting hydrogen demand, direct hydrogen imports are more attractive than indirect routes using methane, methanol or ammonia imports and subsequent decomposition to hydrogen because of h

关键词： Methanol

On (local) analysis of multifunctions via subspaces contained in graphs of generalized derivatives

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arXiv 2021年

作者： Gfrerer, Helmut Outrata, Jiri V. Institute of Computational Mathematics Johannes Kepler University Linz LinzA-4040 Austria Institute of Information Theory and Automation Czech Academy of Sciences Prague18208 Czech Republic Centre for Informatics and Applied Optimization Federation University of Australia POB 663 BallaratVIC3350 Australia

The paper deals with a comprehensive theory of mappings, whose local behavior can be described by means of linear subspaces, contained in the graphs of two (primal and dual) generalized derivatives. This class of mappings includes the graphically Lipschitzian mappings and thus a number of multifunctions, frequently arising in optimization and equilibrium problems. The developed theory makes use of new generalized derivatives, provides us with some calculus rules and reveals a number of interesting connections. In particular, it enables us to construct a modification of the semismooth∗ Newton method with improved convergence properties and to derive a generalization of Clarke's Inverse Function Theorem to multifunctions together with new efficient characterizations of strong metric (sub)regularity and tilt *** Codes 65K10, 65K15, 90C33 © 2021, CC BY.

关键词： Mapping

Assessment of a scheduling strategy for dispatching prosumption of an industrial campus

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Assessment of a scheduling strategy for dispatching prosumpt...

Internationaler ETG-Kongress 2019: Das Gesamtsystem im Fokusder Energiewende - International ETG Congress 2019: The Overall System in the Focus of the Energy Turnaround

作者： Appino, Riccardo Remo González Ordiano, Jorge Ángel Munzke, Nina Mikut, Ralf Faulwasser, Timm Hagenmeyer, Veit Institute for Automation and Applied Informatics Karlsruhe Institute of Technology Eggenstein-Leopoldshafen76344 Germany Institute of Electrotechnical Engineering Karlsruhe Institute of Technology Eggenstein-Leopoldshafen76344 Germany

ISBN: (纸本)9783800749553

Effective scheduling of the power exchange with an external grid is of interest for clusters of devices (including consumption, generation and storage) that aim to participate in energy markets. Scheduling is often performed by means of optimization-based algorithms considering uncertain forecasts of inflexible generation and consumption. In this paper, we assess the performance of a previously proposed scheduling algorithm—based on non-parametric probabilistic forecasts both in terms of power and energy—in a realistic industrial campus setting. Simulation results using real data from the KIT north campus underpin the applicability of the proposed algorithm. © VDE VERLAG GMBH Â Berlin Â Offenbach

关键词： Scheduling algorithms