A5045772206- Smart Grid Security and Resilience
- Smart Grid Energy Management
- Blockchain Technology Applications and Security
- Simulation Techniques and Applications
- Electric Power System Optimization
- Distributed and Parallel Computing Systems
- Reinforcement Learning in Robotics
- Auction Theory and Applications
- Multi-Agent Systems and Negotiation
- Power Systems and Technologies
- Adversarial Robustness in Machine Learning
- Real-Time Systems Scheduling
- Islanding Detection in Power Systems
- Model Reduction and Neural Networks
- Real-time simulation and control systems
- Peer-to-Peer Network Technologies
- Distributed systems and fault tolerance
- Supply Chain and Inventory Management
- Modeling, Simulation, and Optimization
- Constraint Satisfaction and Optimization
- Advanced Battery Technologies Research
- Flexible and Reconfigurable Manufacturing Systems
- Integrated Energy Systems Optimization
- Network Security and Intrusion Detection
- Game Theory and Applications
Oldenburger Institut für Informatik
2009-2024
This paper presents the requirements and a concept for modular Smart Grid simulation framework based on an automatic composition of existing, heterogeneous models. The problem is broken down into different layers, each which first concepts solving are presented. A prototype showing feasibility presented has been developed. First results scenario including electric vehicles as well renewable energy sources Finally, limitations possible improvements discussed.
Transforming the existing power generation to renewable, distributed implicates an increase in complexity for control of overall system. We propose a method launch products self-organized coalitions small active units grid at markets trading as well ancillary services. Our concept combines integration restrictions into proactive scheduling with provision services, and additionally provides reactive power, e.g. case service activation.
Abstract Unlocking and managing flexibility is an important contribution to the integration of renewable energy efficient resilient operation power system. In this paper, we discuss how potential a fleet battery-electric transportation vehicles can be used provide frequency containment reserve. To end, first examine use case in detail then present system designed meet challenge. We give overview tasks individual sub-components, consisting (a) artificial neural network predict availability...
Principles of modern cyber-physical system (CPS) analysis are based on analytical methods that depend whether safety or liveness requirements considered. Complexity is abstracted through different techniques, ranging from stochastic modelling to contracts. However, both distributed heuristics and Artificial Intelligence (AI)-based approaches as well the user perspective unpredictable effects, such accidents weather, introduce enough uncertainty warrant reinforcement-learning-based...
Distributed algorithms and multi-agent systems have been studied in Smart Grid research for several years to address the problems arising from integration of a substantial amount distributed energy units. To change role these units an uncontrolled feed-in behavior actively contributing system stability, efficient control scalability are important requirements given domain. In this work, we present ISAAC, unit aggregation planning software based on principles controlled self-organization...
This paper introduces Adversarial Resilience Learning (ARL), a concept to model, train, and analyze artificial neural networks as representations of competitive agents in highly complex systems. In our examples, the normally take roles attackers or defenders that aim at worsening improving-or keeping, respectively-defined performance indicators system. Our provides adaptive, repeatable, actor-based testing with chance detecting previously unknown attack vectors. We provide constitutive...
Congestion management in distribution grids is an important task for grid operators, both from a financial and technological perspective. Whereas large generation units controllable loads might general be manual way, this no option small distributed generators loads. With flexibility control multiple owner scenarios, documentation, transparency automation are of crucial importance. In work, we present fully automated congestion approach based on combination ledger technology algorithms...
Abstract Surrogate models are used to reduce the computational effort required simulate complex systems. The power grid can be considered as such a system with large number of interdependent inputs. With artificial neural networks and deep learning, it is possible build high-dimensional approximation models. However, data set also for training process. This paper presents an approach sample input create learning surrogate model low voltage grid. Challenges discussed evaluated under different...
Intelligent and autonomous agents have gained increased recognition as a solution for the efficient reliable operation of distributed digitalised power systems. In multi-agent systems, use negotiation to coordinate their behaviour, letting them exchange information make informed control decisions according shared goal. However, systems are socio-technical too, agents' directly or indirectly impact welfare human beings. Thus, question moral agency arises: How can decision-making, resulting...
An active matching of supply and demand electric power contributes to an optimised utilisation grids. In this paper, we will outline the potential conjoint generation management load adaption measures especially regarding system balancing in low voltage
Modern cyber-physical systems (CPS), such as our energy infrastructure, are becoming increasingly complex: An ever-higher share of Artificial Intelligence (AI)-based technologies use the Information and Communication Technology (ICT) facet for operation optimization, cost efficiency, to reach CO2 goals worldwide. At same time, markets with increased flexibility ever shorter trade horizons enable multi-stakeholder situation that is emerging in this setting. These still form critical...
Principles of modern cyber-physical system (CPS) analysis are based on analytical methods that depend whether safety or liveness requirements considered. Complexity is abstracted through different techniques, ranging from stochastic modelling to contracts. However, both distributed heuristics and Artificial Intelligence (AI)-based approaches as well the user perspective unpredictable effects, such accidents weather, introduce enough uncertainty warrant reinforcement-learning-based...