Today's power systems are seeing a paradigm shift under the energy transition, sparkled by electrification of demand, digitalisation systems, and an increasing share decarbonated generation. Most these changes have direct impact on their control centers, forcing them to handle weather-based resources, new interconnections with neighbouring transmission networks, more markets, active distribution micro-grids, greater amounts available data. Unfortunately, translated during past decade small,...

Power networks, responsible for transporting electricity across large geographical regions, are complex infrastructures on which modern life critically depend. Variations in demand and production profiles, with increasing renewable energy integration, as well the high voltage network technology, constitute a real challenge human operators when optimizing transportation while avoiding blackouts. Motivated to investigate potential of AI methods enabling adaptability power operation, we have...

Abstract A 250 year simulation of a strongly eddying global version the Parallel Ocean Program (POP) model reveals new mode intrinsic multidecadal variability, Southern Mode (SOM), with period 40–50 year. The peak‐to‐peak difference in ocean heat content within cycle is up to 60 ZJ. This change results from surface flux variations South Atlantic and propagation temperature anomalies along Antarctic Circumpolar Current into Weddell gyre around 30°E. propagate as deep 5000 m isopycnals between...

We present a massively parallel solver that accelerates DC loadflow computations for power grid topology optimization tasks. Our approach leverages low-rank updates of the Power Transfer Distribution Factors (PTDFs) to represent substation splits, line outages, and reconfigurations without ever refactorizing system. Furthermore, we implement core routines on Graphics Processing Units (GPUs), thereby exploiting their high-throughput architecture linear algebra. A two-level decomposition...

Transmission grid congestion increases as the electrification of various sectors requires transmitting more power. Topology control, through substation reconfiguration, can reduce but its potential remains under-exploited in operations. A challenge is modeling topology control problem to align well with objectives and constraints operators. Addressing this challenge, paper investigates application multi-objective reinforcement learning (MORL) integrate multiple conflicting for power control....

Power grid operators face increasing difficulties in the control room as increase energy demand and shift to renewable introduce new complexities managing congestion maintaining a stable supply. Effective topology requires advanced tools capable of handling multi-objective trade-offs. While Reinforcement Learning (RL) offers promising framework for tackling such challenges, existing Multi-Objective (MORL) approaches fail scale large state action spaces inherent real-world operations. Here we...

Power grid operation is becoming more complex due to the increase in generation of renewable energy. The recent series Learning To Run a Network (L2RPN) competitions have encouraged use artificial agents assist human dispatchers operating power grids. However, combinatorial nature action space poses challenge both conventional optimizers and learned controllers. Action factorization, which breaks down decision-making into smaller sub-tasks, one approach tackle curse dimensionality. In this...

The climate impact of ocean gateway openings during the Eocene-Oligocene transition is still under debate. Previous model studies employed grid resolutions at which mesoscale eddies has to be parameterized. We present results a state-of-the-art eddy-resolving global with closed Drake Passage and compare same noneddying resolution. An analysis pathways heat by decomposing meridional transport into eddy, horizontal, overturning circulation components indicates that behavior on large scale...

The operation of electricity grids has become increasingly complex due to the current upheaval and increase in renewable energy production. As a consequence, active grid management is reaching its limits with conventional approaches. In context Learning Run Power Network (L2RPN) challenge, it been shown that Reinforcement (RL) an efficient reliable approach considerable potential for automatic operation. this article, we analyse submitted agent from Binbinchen provide novel strategies...

The Atlantic Meridional Overturning Circulation (MOC) is a crucial part of the climate system because its associated northward heat transport. present-day MOC sensitive to freshwater anomalies and may collapse state with strongly reduced A future has been identified as one most dangerous tipping points in system. It therefore develop early warning indicators for such potential based on relatively short time series. So far, attempts use critical slowdown have marginally successful. Based...

Abstract The role of standing eddies for the meridional overturning circulation (MOC) is discussed. time-mean isopycnal streamfunction decomposed into a time- and zonal-mean part, standing-eddy transient-eddy part. It turns out that construction an MOC with exactly vanishing part has to be performed by zonal integration along depth-dependent horizontal isolines density. In contrast, geostrophic streamlines generally only leads reduced A generalized approach constructing transport...

Abstract Recently, multidecadal variability in the Southern Ocean has been found a strongly eddying global ocean circulation model. In this paper, we study Lorenz energy cycle of so‐called Mode (SOM). The analysis provides details on pathways associated with SOM. It shows that eddies and baroclinic pathway together variations kinetic input by wind are crucial aspects variability. is also shown how convective mixing, which induced SOM particular Weddell Gyre, responsible for large‐scale...

System operators are faced with increasingly volatile operating conditions. In order to manage system reliability in a cost-effective manner, control room turning computerised decision support tools based on AI and machine learning. Specifically, Reinforcement Learning (RL) is promising technique train agents that suggest grid actions operators. this paper, simple baseline approach presented using RL represent an artificial operator can operate IEEE 14-bus test case for duration of 1 week....

Abstract. In this paper we present the Oceanographic Multipurpose Software Environment (OMUSE). OMUSE aims to provide a homogeneous environment for existing or newly developed numerical ocean simulation codes, simplifying their use and deployment. way, experiments that combine models representing different physics spanning ranges of physical scales can be easily designed. Rapid development is made possible through creation simple high-level scripts. The low-level core abstraction in designed...

A new method for constructing complex networks from fluid flow fields is proposed. The approach focuses on spatial properties of the field, namely, topology streamline field. network applied to a model wind-driven ocean circulation, which exhibits prototype critical transition, that is, back-to-back saddle-node bifurcation related two separate dynamical regimes. analysis enables structural characterization of, one hand, viscous regime as weakly-connected and highly-assortative regime, and,...

Abstract In this study we investigate a covariate-based stochastic approach to parameterize unresolved turbulent processes within standard model of the idealised, wind-driven ocean circulation. We focus on vertical instead horizontal coarse-graining, such that avoid subtle difficulties coarsegraining. The corresponding eddy forcing is uniquely defined and has clear physical interpretation related baroclinic instability.We propose emulate by sampling from conditional probability distribution...

Dynamical systems methodology is a mature complementary approach to forward simulation which can be used investigate many aspects of climate dynamics. With this paper, review given on the methods analyse deterministic and stochastic models show that these are not restricted low-dimensional toy models, but they applied formulated by partial differential equations. We sketch numerical implementation illustrate showing results for two canonical problems in

Abstract A new approach to parameterizing subgrid-scale processes is proposed: The impact of the unresolved dynamics on resolved (i.e., eddy forcing) represented by a series expansion in dynamical spatial modes that stem from energy budget dynamics. It demonstrated convergence these so-called faster orders magnitude than Fourier-type modes. Moreover, novel way test parameterizations models explored. and corresponding instantaneous forcing are defined via filtering accounts for representation...