The present invention discloses a method for modeling sequence impedance of a modular multilevel converter (MMC) under phase locked loop (PLL) coupling. The method includes the following steps: S1, establishing a circuit topology model; S2, establishing a PLL output characteristic model; S3, establishing a PI controller output control small signal model under a dq axis; S4, deducing a modulation small signal; and S5, calculating MMC port impedance. According to the method, a precise MMC port impedance model is established by analyzing a double mirror frequency coupling effect in the output of a modulation signal in a control link caused by a phase angle disturbance and comprehensively considering the combination of the multi-harmonic coupling effect of an MMC. On one hand, the proposed modeling method aims at a common MMC adopting current closed-loop control, in which a half-bridge sub-module is adopted, a circuit topological structure and a control structure are both more common, and a mathematical model is easy to establish. On the other hand, the physical significance of an impedance analysis method is clear, the modeling process is modular and is easy to understand and implement, and the inverter port impedance can be measured on site, so that the correctness of theoretical modeling can be conveniently verified.

Tools and techniques are described to automate line testing when wiring devices (such as equipment and sensors) to controllers. Controllers have access to databases of the devices that are controlled by them, including wiring diagrams and protocols, such that the controller can automatically check that each wire responds correctly to stimulus from the controller. After testing, a reporting device rapidly shows the results of the line testing.

In some embodiments, a low-resistance path between an active cell and a power supply layer in an integrated circuit device includes at least one layer of a plurality of conductive lines commonly connected to at least one conductive line through a plurality of respective conductive pillars, the at least one conductive line being in the power supply layer or intervening the active cell and the power supply layer. In some embodiments, the integrated circuit device includes a conductive layer that includes the plurality of conductive lines and additional conductive portions, where the plurality of conductive lines are isolated from the additional conductive portions.

The present disclosure provides an optimization method, a unit, and an electronic device of a shifted frequency (SF)-based electromagnetic transient simulation, comprising: determining a current amplitude and a voltage frequency based on a node voltage and a branch current calculated from a shifted frequency on a basis of a current time step; determining an optimal shifted frequency of the current time step based on the current amplitude and the voltage frequency; and updating the shifted frequency by adopting the optimal shifted frequency of the current time step for calculating a node voltage and a branch current of the next time step. The method, the unit, and the electronic device provided in the present disclosure may gradually update and optimize the shifted frequency in the simulation process so to enable the shifted frequency to reach the best, thus ensuring the accuracy of output current and voltage simulation results.

Embodiments of the present disclosure are directed to a solar calculator which can calculate a layout for a set of solar panels to be installed on a roof of a building. Generally speaking, the solar calculator can receive as input a roof type for the building, system requirements, site information, specifications for mounting hardware to be used, specifications for the solar panels to be used, wind data for the location of the building, etc. From this data, the solar calculator can then calculate the number of solar panels needed, a layout for the panels on the roof, the hardware required to mount the panels, locations for the hardware to be installed, and/or other information. A graphical and/or textual report can then be generated that describes the layout of the solar panels and hardware, a bill of materials for the installation, and other information.

One embodiment provides a system and method for predicting network power usage associated with workloads. During operation, the system configures a simulator to simulate operations of a plurality of network components, which comprises embedding one or more event counters in each simulated network component. A respective event counter is configured to count a number of network-power-related events. The system collects, based on values of the event counters, network-power-related performance data associated with one or more sample workloads applied to the simulator; and trains a machine-learning model with the collected network-power-related performance data and characteristics of the sample workloads as training data 1, thereby facilitating prediction of network-power-related performance associated with a to-be-evaluated workload.

A power grid reactive voltage control model training method. The method comprises: establishing a power grid simulation model; establishing a reactive voltage optimization model, according to a power grid reactive voltage control target; building interactive training environment based on Adversarial Markov Decision Process, in combination with the power grid simulation model and the reactive voltage optimization model; training the power grid reactive voltage control model through a joint adversarial training algorithm; and transferring the trained power grid reactive voltage control model to an online system. The power grid reactive voltage control model trained by using the method according to the present disclosure has transferability as compared with the traditional method, and may be directly used for online power grid reactive voltage control.

The present invention discloses a method for modeling sequence impedance of a modular multilevel converter (MMC) under phase locked loop (PLL) coupling. The method includes the following steps: S1, establishing a circuit topology model; S2, establishing a PLL output characteristic model; S3, establishing a PI controller output control small signal model under a dq axis; S4, deducing a modulation small signal; and S5, calculating MMC port impedance. According to the method, a precise MMC port impedance model is established by analyzing a double mirror frequency coupling effect in the output of a modulation signal in a control link caused by a phase angle disturbance and comprehensively considering the combination of the multi-harmonic coupling effect of an MMC. On one hand, the proposed modeling method aims at a common MMC adopting current closed-loop control, in which a half-bridge sub-module is adopted, a circuit topological structure and a control structure are both more common, and a mathematical model is easy to establish. On the other hand, the physical significance of an impedance analysis method is clear, the modeling process is modular and is easy to understand and implement, and the inverter port impedance can be measured on site, so that the correctness of theoretical modeling can be conveniently verified.

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating a load adjustment simulation and a capacity forecast. In one aspect, a method comprises: generating, using a simulation system, a load adjustment simulation that characterizes predicted energy consumption by a population of energy consuming devices based on performance of a current load adjustment event; generating, using the simulation system, a baseline load simulation that characterizes predicted energy consumption by the population of energy consuming devices based on non-performance of the current load adjustment event; determining, using the baseline load simulation, a load adjustment simulation error that is an estimate of an error between: (i) the load adjustment simulation, and (ii) actual energy consumption by the population of energy consuming devices based on performance of the current load adjustment event; and updating the load adjustment simulation using the load adjustment simulation error.

Aspects of the present disclosure describe distributed fiber optic sensing (DFOS) systems, methods, and structures that advantageously enable and/or facilitate the continuous monitoring and identification of damaged utility poles by employing a DFOS distributed acoustic sensing (DAS) methodology in conjunction with a finite element analysis and operational modal analysis. Of particular advantage and in further contrast to the prior art, systems, methods, and structures according to aspects of the present disclosure utilize existing optical fiber supported/suspended by the utility poles as a sensing medium for the DFOS/DAS operation.