Technologies for switching network traffic include a network switch. The network switch includes one or more processors and communication circuitry coupled to the one or more processors. The communication circuity is capable of switching network traffic of multiple link layer protocols. Additionally, the network switch includes one or more memory devices storing instructions that, when executed, cause the network switch to receive, with the communication circuitry through an optical connection, network traffic to be forwarded, and determine a link layer protocol of the received network traffic. The instructions additionally cause the network switch to forward the network traffic as a function of the determined link layer protocol. Other embodiments are also described and claimed.

A power load data prediction method and device, and a storage medium are disclosed. In an embodiment, the he method comprises: acquiring historical power load data of a one-dimensional time sequence, the historical power load data including values of corresponding time points; mapping the values of corresponding time points to a coordinate system in which a horizontal axis is a set time period, and a vertical axis is time points within the time period, and performing marking at each mapping point by using predetermined pixel values corresponding to the values to obtain a mapping image, wherein different values correspond to different pixel values; and inputting the pixel values of the mapping image to a trained data prediction model, and acquiring a power load data prediction value output by the data prediction model. The method and device and the storage medium can improve the prediction accuracy of the power load data.

Amendment to the Abstract:

Disclosed are an in-place supervision method and apparatus suitable for overhead transmission line maintenance operation, the method includes: geographic coordinate information of an overhead transmission line is, written into a risk management and control master station system of the whole electric power operation process, and an in-place supervision algorithm is written into the risk management and control master station system of the whole electric power operation process; geodetic coordinates A of a maintenance operation site and geodetic coordinates B of a supervisor are read; a distance is solved based on an elliptic spherical arc length approximate chord length algorithm; whether the distance S exceeds a threshold value of out of supervision or not is judged. In implementation of the invention, the execution level of in-place supervision of the overhead transmission line operation is improved, and the personal risk of the site of supervision operation is effectively controlled.

A reasoning engine is disclosed. Contemplated reasoning engines acquire data relating to one or more aspects of various environments. Inference engines within the reasoning engines review the acquire data, historical or current, to generate one or more hypotheses about how the aspects of the environments might be correlated, if at all. The reasoning engine can attempt to validate the hypotheses through controlling acquisition of the environment data.

A system and method that enables the ongoing communication, tracking, and management review of feedback among a population of workers and their management.

A computer-implemented process receives into memory, information designating a task to be performed on an industrial vehicle. The task has a metric associated therewith. The process also extracts vehicle operational data that is generated on the industrial vehicle in response to the industrial vehicle executing the task. The process further receives into memory, information identifying a set of target scores, each target score of the set of target scores defining a different measure of performance associated with the task. The process yet further computes a task evaluation score for each target score in the set of target scores based upon the corresponding measure of performance associated with the task, and creates an adjusted task evaluation indicative of industrial vehicle performance that takes into account an aggregation of the task evaluation score computed for each target score in the set of target scores.

A collaborative aggregation trading method for consuming clean energy includes: acquiring related data of clean energy power generation companies, the demand-side resources and energy storage service providers; acquiring a trading quotation and acquiring self-regulating ability data and regulating fees of shared energy storage service providers; performing trading of collaboratively consuming the clean energy through the demand-side resources and the shared energy storage: when the power generation output value exceeds the maximum regulating ability of user demands and the demand-side resources, storing the redundant power into shared energy storage systems for standby application; when the power generation output value is lower than the minimum operation load level of the user demands and the demand-side resources, calling the shared energy storage service providers participating in the trading according to energy storage ranking indexes, to acquire required power from the shared energy storage systems; and performing fees settlement.

Various embodiments for a connection topology reconfiguration technique for photovoltaic (PV) arrays to maximize power output under partial shading and fault conditions using neural networks are disclosed herein.

A system and method for use in environment with electrical equipment is provided. The system including a housing and at least one light source located on an exterior of the housing. The light source being activated when the system is in a switching mode of operation. At least one sensor is operably coupled to the housing and configured to measure at least one parameter associated with the electrical equipment. A computing device is disposed within the housing and coupled to communicate with the at least one light source and the at least one sensor.

The disclosure relates to a quantile probabilistic short-term power load ensemble forecasting method. The method includes: dividing historical power load data of a power system into a first data set and a second data set; performing bootstrap sampling on the first data set to generate multiple training data sets; training a neural network quantile regression model, a random forest quantile regression model and a gradient boosting regression tree regression model for the each training data set to obtain quantile forecasting models; establishing an optimization model with an objective function for minimizing the quantile loss for the second data set, and determining a weight for each of the quantile regression models, to calculate a power load ensemble forecasting model for predicting the power load in the power system.