arXiv subjects

Thiemo Pesch

Publications and source records attributed to Thiemo Pesch.

7 recordsLinked to original sources

arXiv2026

CHAMB-GA: A Containerized HPC Scalable Microservice-Based Framework for Genetic Algorithms

Metaheuristic-based global optimization with embedded, long-running simulations is a computationally expensive process. To support various stages of development and execution, a seamless transition from personal computers to distributed clusters is desired, enabling execution across all computational scales. However, existing tool chains are often characterized by rigidity and hardware-bound constraints, which impede scalability and the integration of complex simulations. Bridging this gap, we present a containerized HPC scalable microservice-based framework for genetic algorithms with embedded simulations (CHAMB-GA). The deployment of the framework scales consistently across cloud infrastructure via container orchestration and HPC clusters via batch-scheduled parallel execution. Users provide the GA operators and simulation backend separately. The framework is designed to run these components in a distributed and decoupled manner, mapped to separate hardware. This approach ensures that the fitness evaluation and genetic operations are not managed within the same process and are utilizing distinct parts of the compute infrastructure. A central message broker coordinates asynchronous manager-worker communication between microservices, thereby parallelizing evolutionary operations and fitness evaluations. We demonstrate CHAMB-GA's scalability, portability, and reproducibility, while facilitating the integration of external tools and complex simulations on benchmark and powerflow problems. The capabilities of CHAMB-GA are validated in a two-part approach: (i) a benchmark study demonstrating minimal overhead while scaling to over 3,500 CPU cores, and (ii) a dispatch optimization of High Voltage Direct Current (HVDC) lines in the German transmission grid, showing seamless migration from Kubernetes to SLURM, combined horizontal and vertical scaling, and integration of multi-stage workflows.

cs.DC↗

arXiv2026

Impact of Market Reforms on Deterministic Frequency Deviations in the European Power Grid

Deterministic frequency deviations (DFDs) are systematic and predictable excursions of grid frequency that arise from synchronized generation ramps induced by electricity market scheduling. In this paper, we analyze the impact of the European day-ahead market reform of 1 October 2025, which replaced hourly trading blocks with quarter-hourly blocks, on DFDs in the Central European synchronous area. Using publicly available frequency measurements, we compare periods before and after the reform based on daily frequency profiles, indicators characterizing frequency deviations, principal component analysis, Fourier-based functional data analysis, and power spectral density analysis. We show that the reform substantially reduces characteristic hourly frequency deviations and suppresses dominant spectral components at hourly and half-hourly time scales, while quarter-hourly structures gain relative importance. While the likelihood of large frequency deviations decreases overall, reductions for extreme events are less clear and depend on the metric used. Our results demonstrate that market design reforms can effectively mitigate systematic frequency deviations, but also highlight that complementary technical and regulatory measures are required to further reduce large frequency excursions in low-inertia power systems.

physics.soc-ph↗

arXiv2025

Towards Quantum Algorithms for the Optimization of Spanning Trees: The Power Distribution Grids Use Case

Optimizing the topology of networks is an important challenge across engineering disciplines. In energy systems, network reconfiguration can substantially reduce losses and costs and thus support the energy transition. Unfortunately, many related optimization problems are NP hard, restricting practical applications. In this article, we address the problem of minimizing losses in radial networks, a problem that routinely arises in distribution grid operation. We show that even the computation of approximate solutions is computationally hard and propose quantum optimization as a promising alternative. We derive two quantum algorithmic primitives based on the Quantum Alternating Operator Ansatz (QAOA) that differ in the sampling of network topologies: a tailored sampling of radial topologies and simple sampling with penalty terms to suppress non-radial topologies. We show how to apply these algorithmic primitives to distribution grid reconfiguration and quantify the necessary quantum resources.

eess.SY↗

arXiv2025

Cyber-Physical Systems on the Megawatt Scale: The impact of battery control on grid frequency stability

Electric power systems are undergoing fundamental change. The shift to inverter-based generation challenges frequency stability, while growing digitalisation heightens vulnerability to errors and attacks. Here we identify an emerging risk at the intersection of cyber-physical coupling and control system design. We show that grid frequency time series worldwide exhibit a persistent one-minute oscillatory pattern, whose origin has remained largely unexplained. We trace this pattern back to the energy management systems of battery electric storage systems and demonstrate that the pattern amplitude has increased substantially in the Nordic and British grids. We argue that this effect is a potential burden for stability in future grids with low inertia and an increasing penetration with batteries and smart devices, though it can be mitigated by a revision of battery control algorithms.

eess.SY↗

arXiv2025

Quantum Annealing based Power Grid Partitioning for Parallel Simulation

Graph partitioning has many applications in powersystems from decentralized state estimation to parallel simulation. Focusing on parallel simulation, optimal grid partitioning minimizes the idle time caused by different simulation times for the sub-networks and their components and reduces the overhead required to simulate the cuts. Partitioning a graph into two parts such that, for example, the cut is minimal and the subgraphs have equal size is an NP-hard problem. In this paper we show how optimal partitioning of a graph can be obtained using quantum annealing (QA). We show how to map the requirements for optimal splitting to a quadratic unconstrained binary optimization (QUBO) formulation and test the proposed formulation using a current D-Wave QPU. We show that the necessity to find an embedding of the QUBO on current D-Wave QPUs limits the problem size to under 200 buses and notably affects the time-to-solution. We finally discuss the implications on near-term implementation of QA in combination to traditional CPU or GPU based simulation.

eess.SY↗

arXiv2022

Understanding Braess' Paradox in power grids

The ongoing energy transition requires power grid extensions to connect renewable generators to consumers and to transfer power among distant areas. The process of grid extension requires a large investment of resources and is supposed to make grid operation more robust. Yet, counter-intuitively, increasing the capacity of existing lines or adding new lines may also reduce the overall system performance and even promote blackouts due to Braess' paradox. Braess' paradox was theoretically modeled but not yet proven in realistically scaled power grids. Here, we present an experimental setup demonstrating Braess' paradox in an AC power grid and show how it constrains ongoing large-scale grid extension projects. We present a topological theory that reveals the key mechanism and predicts Braessian grid extensions from the network structure. These results offer a theoretical method to understand and practical guidelines in support of preventing unsuitable infrastructures and the systemic planning of grid extensions.

eess.SY↗

arXiv2020

Economic Viability and Infrastructure Requirements for the Electrification of Highway Traffic

Battery electric vehicles are rapidly entering the market. Their success offers great opportunities for the decarbonization of the transport sector, but also pose new challenges to energy infrastructures. Public charging stations must be built and power grids may become congested. In this article, we analyze the optimal layout and operation of charging systems along highways using a high-resolution optimization model. We discuss the economic viability and identify potential roadblocks impeding a rapid build-up of electric mobility. We find that congestion of regional distribution grids becomes a serious issue already for a moderate market penetration of electric vehicles. While peak loads can be handled by battery electric storage systems, the grid connection fundamentally limits the total amount of cars that can be served per day. Our results further highlight the interdependency of different sectors and the importance of regional infrastructures during the transformation to a sustainable energy system. Given the long time period needed for the planning and realization of infrastructure measures, rapid decisions are imperative.

physics.soc-ph↗