Réseau de Transport d' Electricité

Model Based System Engineering is widely used for the development of Cyber Physical Systems and in particular Smart Grids (SG). SysML/UML are used for several years to develop Domain Specific Modeling Languages (DSML) each one tackling one or several aspects/viewpoints of the SG. In this Paper we will not just present yet another DSML for SG control design, but we will discuss different modeling patterns adopted to define the DSML and discuss the added value/gain of next generation languages/tools mainly SysML v2 and web tools in the developing of DSML. Our DSML is the first building blocks of a Modeling tool integrated in the new RTE (French Energy Transmission company) platform to design, simulate and evaluate the new control architectures of the French electrical transmission network.

Motivated by the increasing need to hedge against load and generation uncertainty in the operation of power grids, we propose flexibility maximization during operation. We consider flexibility explicitly as the amount of uncertainty that can be handled while still ensuring nominal grid operation in the worst case. We apply the proposed flexibility optimization in the context of a DC flow approximation. By using a corresponding parameterization, we can find the maximal range of uncertainty and a range for the manageable power transfer between two parts of a network subject to uncertainty. We formulate the corresponding optimization problem as an (existence-constrained) semi-infinite optimization problem and specialize an existing algorithm for its solution.

Power systems worldwide are going through unprecedented changes. Power generators have become much smaller and power systems much more complex. Thirty years ago, each country had only a few large power plants ( Figure 1 ) that could be controlled to the exact megawatt. Today though, power systems are much more different and include millions of devices, solar photovoltaic installations, onshore and offshore wind turbines, batteries, and electric vehicles inject or withdraw power when they can or when they want. Still, every consumer expects that when they plug in their devices there will be enough electricity.

Numerous High‐Voltage Direct Current (HVDC) interconnections in a bipolar configuration are currently in the design phase and set to become operational in the next decade. In the meantime, the shift from Synchronous Generators (SGs) to converter‐interfaced units is raising concerns over the stability of power systems. Grid‐Forming (GFM) control in converters, as opposed to Grid‐Following (GFL) mode, is anticipated to replicate, to some extent, the stabilizing behaviour of SGs. An open research question is whether mimicking the behaviour of SGs with GFM converters would, in turn, induce sub‐synchronous oscillations similar to those present in power systems dominated by SGs. This paper investigates sub‐synchronous interactions between converters and asynchronous AC systems at the terminals of a bipolar HVDC connection. A modal analysis based on a state‐space approach reveals the participation of converters as well as the influence of control modes and system parameters on these low‐frequency oscillations. Time‐domain simulations of a non‐linear model in EMTP software support the findings of the modal analysis.

fn fn-type="other" id="fn3" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> This paper highlights the importance of proper initialization techniques for simulation model stability and computational efficiency. A generic initialization method called Decoupling Interface (DI) is proposed. It is applicable to any MTDC grid component. The method is tested on the CIGRE BM1 and BM7 benchmarks in a tool for the simulation of electromagnetic transients (EMTs). Compared to an existing load-flow initialization technique, DI reduces the initialization time by 41 and 16 times for CIGRE BM1 and BM7 test cases, respectively. Furthermore, the paper demonstrates DI's ability to prevent initialization failures in the CIGRE BM7 system.

Linear transportation infrastructures (LTIs) are established drivers of habitat fragmentation and barrier effects. Yet, they represent an increasing surface of managed seminatural habitats where increased consideration of biodiversity outputs is needed in an era of global biodiversity decline. A combined effort by both scientists and stakeholders is, therefore, needed to evaluate the promises and limits of these alternatives so that they best achieve their conservation potential. Our study explores the effects of forest powerline clearings on biodiversity, as well as the potential benefits of integrated vegetation management (IVM) as alternatives to clear‐cuts. We recorded the acoustic activity at 35 pairs of forest/clearing stations in two forested regions of France in 2021. Our results suggest that powerline clearings represent increased movement opportunities for bats and, most particularly, edge‐foraging species. They also provide suitable habitats for bush‐cricket species, particularly species requiring thermophilic conditions. We detected no direct benefit from IVM on bat communities. However, bush‐cricket communities appeared richer, more acoustically active, and statistically different from adjacent forests in clearings favoring secondary vegetation compared with clear‐cut ones. This collaborative study provides data on understudied taxa in the context of LTIs and sheds light on conservation promises and limits associated with their management.

Since substation automations systems were introduced in the 1990s to protect, control, and automate high-voltage and medium voltage substations, several new technologies have been applied to improve the functionality, performance, and efficiency of the design and architecture. Digital substations are beginning to replace substation automations systems, benefitting from new architectures that are based on digital interfaces provided by intelligent primary devices and related sensors. This transition was prompted by the intensive work in standardization of communication protocols and data models dedicated for power system automation, as defined in the International Electrotechnical Commission (IEC) 61850 series of standards. The evolution of technologies and performances driven by microelectronics enabled the functional integration of previously separated devices onto common hardware over the last three decades. Still, the functional integration was limited by requirements concerning reliability, resilience, testability, and life-cycle perspectives. In a substation, any device, such as a protection relay, was allocated to a bay, a feeder, or a zone. Applying concepts of IEC 61850 concerning the separation of physical signals, their conversion into digital information, and allocation of application functions using this information from any physical device, makes it possible to think about the next generation of digital substations. Based on virtualization technologies developed in the world of information technology (IT) to dramatically improve the design, operation, and maintenance of IT systems, centralized protection and control systems (CPCs) would allow an even more flexible and economic way to protect, control, and automate substations.

The shift to net zero energy systems has changed the face of our power grid. Traditional large-scale synchronous generators found inside coal and natural gas plants are being replaced with inverter-based resource (IBR) technologies. This transition to an IBR-dominant power grid introduces new characteristics, altering how our grid operates. Therefore, the role of IBRs has expanded, requiring them to provide a range of essential services to keep our grid reliable, resilient, and secure.

Buildings are key in supporting human activities and well-being by providing shelter and other important services to their users. Buildings are, however, also responsible for major energy use and greenhouse gas (GHG) emissions during their life cycle. Improving the quality of services provided by buildings while reaching low energy demand (LED) levels is crucial for climate and sustainability targets. Building sector models have become essential tools for decision support on strategies to reduce energy demand and GHG emissions. Yet current models have significant limitations in their ability to assess the transformations required for LED. We review building sector models ranging from the subnational to the global scale to identify best practices and critical gaps in representing transformations toward LED futures. We focus on three key dimensions of intervention (socio-behavioral, infrastructural, and technological), three megatrends (digitalization, sharing economy, and circular economy), and decent living standards. This review recommends the model developments needed to better assess LED transformations in buildings and support decision-making toward sustainability targets.

Thanks to their extensive use in Internet-based applications, ontologies have gained significant popularity and recognition within the semantic web domain. They are widely regarded as valuable sources of semantics and interoperability in artificial intelligence systems. With the exponential growth of unstructured data on the web, there is a pressing need for automated acquisition of ontologies from unstructured text. This research area has seen the emergence of various methodologies that leverage techniques from machine learning, text mining, knowledge representation and reasoning, information retrieval, and high level natural language processing. These new techniques represent an opportunity to introduce automation into the process of ontology acquisition from unstructured text. To this end, this contribution offers a semi-automatic framework with a concrete usage of a tooled NLP-based approach to design an application ontology in a real-world industrial context. We discuss the state of the art analysis, the challenges met and the technological choices for the realization of this approach. Specifically, we explore its application in the real-world scenario of RTE’s power grid event management.

The energy transition of power grids has spawned a large spectrum of new technical challenges at the design, deployment, and operation levels. From a control standpoint, the integration of renewable-energy-based power generation sources into the power grid translates into emerging uncertainties which compromise the system’s safety, stability, and performance. This article proposes a model-based predictive controller (MPC) that incorporates the stochastic nature of these sources into its feedback decision-making policy. The overarching objective is to balance upholding operational constraints of power lines with smart power generation curtailment and energy storage strategies. The proposed method introduces a novel characterization of disturbance trajectory scenarios, and their incorporation into the optimization problem is detailed leading to a robust congestion management strategy. Simulation results are discussed with respect to a baseline of a trend-based disturbance estimation.

This paper performs a study on three-way subsynchronous torsional interactions (SSTI) between a hybrid dual-in-feed high-voltage direct current (HVDC) system and a nuclear generator. The test case is based on the French IFA2000 line commutated converter (LCC) HVDC (2 GW) and the new Eleclink modular multilevel converter (MMC) HVDC (1 GW) interacting with the Gravelines generator (1 GW). The analysis is performed by the means of the eigenvalue stability assessment on an analytical model, while the accuracy of the conclusions is verified using the detailed non-linear electromegnetic transient program (EMTP) model. The study shows that the dual-infeed system may introduce higher risk of the SSTI compared with the point-to-point HVDC systems. It shows that MMC operating as static synchronous compensator (STATCOM) may further reduce the torsional damping at 6.3 Hz mode. This conclusion may be unexpected since it is known fact from literature that STATCOM has a beneficial impact on the transient performance of LCC. Further studies show that in a sequential HVDC loading, it may be beneficial to load the MMC HVDC first. Also, the risk of the SSTI may be minimized by changing HVDC controller gains, in particular, by increasing phase-locked-loop (PLL) gains on the LCC rectifier.

Legacy Protection and Control (P&C) Systems are vulnerable to misoperations due to a variety of reasons: miscoordination, complexity, human error, and hidden failures. Adding to these, the characteristics of the power system are changing due to the addition of inverter-interfaced generation. Inverters have different characteristics than synchronous machines when responding to faults or disturbances, and the logic of commonly applied P&C systems may fail to operate as expected. Some recent relay misoperations have been attributed to inverter-interfaced resources.

AC-OPF (Alternative Current Optimal Power Flow) aims at minimizing the operating costs of a power grid under physical constraints on voltages and power injections. Its mathematical formulation results in a nonconvex polynomial optimization problem which is hard to solve in general, but that can be tackled by a sequence of SDP (Semidefinite Programming) relaxations corresponding to the steps of the moment-SOS (Sum-Of-Squares) hierarchy. Unfortunately, the size of these SDPs grows drastically in the hierarchy, so that even second-order relaxations exploiting the correlative sparsity pattern of AC-OPF are hardly numerically tractable for large instances — with thousands of power buses. Our contribution lies in a new sparsity framework, termed minimal sparsity, inspired from the specific structure of power flow equations. Despite its heuristic nature, numerical examples show that minimal sparsity allows the computation of highly accurate second-order moment-SOS relaxations of AC-OPF, while requiring far less computing time and memory resources than the standard correlative sparsity pattern. Thus, we manage to compute second-order relaxations on test cases with thousands of power buses, which we believe to be unprecedented.

We propose a new method for improving the bound tightness of the popular semidefinite programming (SDP) relaxation for the ACOPF introduced in Lavaei and Low (2012), Molzahn and Hiskens (2019). First, we reformulate the ACOPF Lagrangian dual as an unconstrained concave maximization problem with a clique decomposition induced sparse structure. We prove that this new formulation has the same optimal value as the SDP relaxation. We then use the solution of the SDP relaxation as a starting point for a tailored structure-aware bundle method. This post-processing technique significantly improves the tightness of the SDP bounds computed by the state-of-the-art solver MOSEK, as shown by our computational experiments on large-scale instances from PGLib-OPF v21.07. For ten of the tested instances, our post-processing decreases by more than 50% the optimality gap obtained with MOSEK.