Risk-Averse Model Predictive Operation Control of Islanded Microgrids

In this paper we present a risk-averse model predictive control (MPC) scheme for the operation of islanded microgrids with very high share of renewable energy sources. The proposed scheme mitigates the effect of errors in the determination of the probability distribution of renewable infeed and load. This allows to use less complex and less accurate forecasting methods and to formulate low-dimensional scenario-based optimisation problems which are suitable for control applications. Additionally, the designer may trade performance for safety by interpolating between the conventional stochastic and worst-case MPC formulations. The presented risk-averse MPC problem is formulated as a mixed-integer quadratically-constrained quadratic problem and its favourable characteristics are demonstrated in a case study. This includes a sensitivity analysis that illustrates the robustness to load and renewable power prediction errors

Tracing Noble Gas Radionuclides in the Environment

Trace analysis of radionuclides is an essential and versatile tool in modern science and technology. Due to their ideal geophysical and geochemical properties, long-lived noble gas radionuclides, in particular, 39Ar (t1/2 = 269 yr), 81Kr (t1/2 = 2.3x10^5 yr) and 85Kr (t1/2 = 10.8 yr), have long been recognized to have a wide range of important applications in Earth sciences. In recent years, significant progress has been made in the development of practical analytical methods, and has led to applications of these isotopes in the hydrosphere (tracing the flow of groundwater and ocean water). In this article, we introduce the applications of these isotopes and review three leading analytical methods: Low-Level Counting (LLC), Accelerator Mass Spectrometry (AMS) and Atom Trap Trace Analysis (ATTA)

Karst simulation with Lindenmayer-systems and ODSIM

International audienceKarstic systems are geological structures that strongly impact underground flows. Despite intensive explorations by speleologists, they remain partially described as many conduits are not accessible to humans. Paleokarsts are buried karstic systems with a significant reservoir potential. But they are not easily identifiable on seismic images. In those contexts, a huge uncertainty subsists on the network location and the conduit geometry. Stochastic simulations help to better assess that uncertainty. The difficulty is to reproduce the system connectivity at different scales while integrating as much geological knowledge as possible without involving poorly constrained parameters (e.g. paleo-climate, boundary conditions...). In this paper we propose to work on two aspects and scales of karstic systems. At large scale, we stochastically simulate karst network skeletons with a new method based on a formal grammar, the Lindenmayer-system. Based on an alphabet, an axiom and user-defined rules, the method puts together segments to build the network skeleton. The definition of proper rules and the introduction of karst-dedicated parameters generate curves reproducing the complex architectures encountered in those systems, mixing branchwork and anastomotic patterns. At the conduit scale, we propose to build a 3D envelope around these skeletons with an enhanced Object Distance based Simulation Method. It uses a custom distance field from the skeleton which takes into account geological features influencing karstogenesis (horizons, faults or fractures). This controls the first-order shape of the conduits. It is then combined to a custom random threshold controlling finer-scale features of the conduits. This threshold is generated with several parameter values depending on the involved geological structures. This workflow is demonstrated on a synthetic case, showing the potentialities of the approach at both scales. Results are encouraging and various improvements are in focus. Data conditioning, both to karst observations and local shape information has to be enhanced. The network simulation has the advantage to be grid-free, meaning that no background grid is needed to perform the simulation. Thus, it avoids the stair-step effect that can be observed in other techniques. On the opposite, the method used to simulate the conduit shapes relies on a grid, necessary to compute the distance fields and to perform the threshold geostatistical simulation. For detailed conduit geometry, the grid requires a high resolution, which impacts directly the computational efficiency. Finally, it would be interesting to test the approach on a real dataset and to develop a coupling with a flow simulator to evaluate the impact of the shape and of the network connections on the flow response

Modelling the long-term evolution of groundwater's quality in a flooded iron-ore mine using a reactive transport pipe network model

International audienceOver the past 25 years, underground mine flooding in the lorraine iron Basin (France) has resulted in a high concentration of dissolved sulphate and have made the water unsuitable for human consumption. this problematic issue has led to the development of numerical tools to support waterresource management in mining contexts. as water flows mainly in galleries and collapsed zones, we consider the flooded mine as a network of pipes and tanks. the software used for simulating flow andreactive transport in this network is the ePanet 2 code. a simplified sulphate dissolution-precipitation model, based on previous works, is included as source/sink in the tanks. Flow rates are calculated by processing data records with a rainfall-discharge model. the simulator gives good agreement between the calculated and observed sulphate concentrations