Energy Digest

The Operational Technology Supervisor (OTSV) is a three-tier passive monitoring framework designed to capture security telemetry in deterministic industrial networks without degrading timing-sensitive grid-edge infrastructure. The framework utilizes a Layer-3-unconfigured passive ingestion mode, isolating the deep packet inspection engine from the production network, and achieves stable latency distributions with a latency delta of less than 0.12 milliseconds. This approach enables continuous high-fidelity security observation alongside stringent metering timing bounds.

Grid-informed maintenance optimization in offshore wind farms can reduce annual maintenance costs by up to 10% by leveraging both farm- and grid-level information to determine maintenance plans. The approach considers high generation curtailment or negative electricity pricing as opportunities for preventive maintenance. By jointly leveraging farm- and grid-level signals, the method enhances asset availability and resource utilization.

Non-physical traders' speculative imbalance positions in Great Britain reduced the total net balancing volume required by 3.1-3.9 TWh, lowered system imbalance standard deviation by 48-65 MWh, and reduced balancing costs by £347-396m. These actions decreased supplier imbalance costs by £193-325m, and if not present, consumer bills would likely be higher. SIP by NPTs had a positive impact on the electricity system's balancing mechanism.

This article proposes a framework for constructing explicit inner approximations of flexibility regions in radial networks, using the augmented relaxed optimal power flow (AR-OPF) method, which provides exact second-order cone relaxation and sufficient conditions for exactness and feasibility. The framework guarantees that the approximated flexibility regions are AC feasible under certain conditions. Numerical evaluations show that the proposed methods provide a reliable approach to constructing operationally admissible flexibility regions for TSO-DSO coordination.

Rising temperatures due to climate change will reduce power system transmission capacity, requiring a 1-5% increase in transmission investment to maintain existing capacity. However, adopting dynamic line ratings (DLR) or ambient-adjusted ratings (AAR) can eliminate most transmission capacity needs, reducing aggregate transmission investments by up to 31%. Planning with time-varying ratings does not increase investment variability for individual lines under climate uncertainty.

Large data centers pose a power-system stability challenge as rapidly varying computing demand can induce grid oscillations. A new controller is designed to simultaneously isolate oscillations and provide grid support, with a coupled closed-loop model revealing fundamental limits to its performance. The controller outperforms existing controls in isolating oscillations while meeting prescribed grid response across operating points.

The isolated four-quadrant single-stage X-Rectifier for EV on-board chargers uses GaN monolithic bidirectional power transistors to provide four-quadrant operation in three-phase and single-phase grids without power derating. A new phase-modular control method enables tracking of arbitrary and independent phase current references, supporting grid-tied and grid-forming operation. The system has been validated experimentally with a 5.5 kVA hardware demonstrator and demonstrated robust operation in various modes, including grid-tied and V2L modes.

A proposed runtime monitor assesses the validity of learned barrier certificates for stochastic systems by analyzing observed closed-loop trajectories, detecting potential loss of statistical support for the deployed barrier condition, and providing finite-sample false-alarm control under arbitrary stopping times. The monitor does not guarantee detection before unsafe entry or safety of a subsequent intervention. It is designed to detect statistical evidence that the safety certificate is no longer consistent with the observed dynamics.

The open-loop minimum-energy control problem for stochastic linear time-invariant systems can be formulated as a quadratic convex program (QCQP), with optimal solutions generalizing the Deterministic MEC problem. Incorporating structural information from the problem can lead to better performance, as demonstrated by bias-variance analysis. Finite-sample high-probability upper bounds on optimal-cost sub-optimality and constraint-violation probability are established, showing the dependence on system and estimation parameters.

A learned control variate can reduce the number of runs required for rare grid-outage estimation by a significant amount, with variance reduction rates of up to 60% even in rare-event regimes. The estimator can be applied to estimate small outage probabilities in grid design, reducing city-wide blackout days by a third. The use of learned control variates can help planners design more reliable distribution grids.