The present invention relates to an optimal load curtailment calculating method based on Lagrange multiplier and an application thereof in power system reliability assessment, wherein the calculating method comprises the following steps: inputting all system states to be analyzed for reliability assessment and establishing corresponding optimal load curtailment models; classifying the optimal load curtailment models according to Lagrange multiplier to obtain several sets; and solving the optimal load curtailment models in each set by using Lagrange multipliers to obtain an optimal load curtailment corresponding to the system state. The core of the present invention is to establish Lagrange-multiplier-based linear functions between the optimal load curtailment and the system states, and the iterative optimization processes of the traditional optimal load curtailment calculating method are substituted with the simple matrix multiplications.

A method for associating geographic location information with a power system model. The method generally includes the steps of receiving known geographic information for a plurality of power system assets within the model and automatically calculating the geographic information for other power system assets with unknown geographic information based on the imported geographic information and architectural information available within the model. The step of calculating the geographic location information may be performed iteratively initially using only imported geographic information and subsequently using both imported and calculated geographic information. The geographic location of each power system asset with an unknown location may be determined through multilateration based on known locations and branch connection lengths of two or more connections with known geolocations.

Evaluating expected performance of a wind farm during a voltage event of a power grid, using a simulation tool. The tool initiates a simulated voltage event, at time, t.sub.0; initiates simulation of a subsequent response to the voltage event by the farm; retrieves information regarding an initial voltage state of a model of the farm, at t.sub.0, and predicts a final voltage state of the model of the wind farm, based on the retrieved information regarding the initial voltage state. At t.sub.0, a simulated output current, I, of the farm is lowered, based on the retrieved information and the predicted final voltage state, and a simulated output voltage, V, of the model of the farm, is monitored. The simulated output current, I, of the farm is subsequently adjusted, based on V, while monitoring V, I, and/or simulated output power of the model. Expected performance of the farm is then evaluated.

A computing device for distributed power system model calibration is provided. The computing device is programmed to receive event data and model response data associated with a model to simulate, wherein the model includes a plurality of parameters, divide the event data into a plurality of sets, wherein each set includes associated parameters, and transmit the plurality of sets of event data to a plurality of client nodes. Each client node of the plurality of client nodes is programmed to analyze a corresponding set of event data to determine updated parameters for the model. The computing device is further programmed to receive a plurality of updated parameters for the model from the plurality of client nodes and analyze the received plurality of updated parameters to determine at least one adjusted parameter.

Tools and techniques are described to attach a device to a controller, whereby the controller analyzes the device inputs, looks up information about the device in a database, and then determines which inputs on the device match the defined device inputs. It then may translate information received from the device into an intermediate language. It may also use the information received from the device, the location of the device, and information about the device to create a digital twin of the device.

Various implementations described herein are related to a device having logic that operates in multiple voltage domains. The device may include a backside power network with rows of segmented supply rails coupled to the logic. The rows of segmented supply rails may include alternating rail breaks that define an interchanging directional supply of power to the logic in the multiple voltage domains.

A module is described which is slidably attachable to a controller. Resource wires are connected to the module through resource connectors, The module has a circuit board that can perform actions. The module can modify the function of its resource connectors. These modifications may be to meet the requirements of resources that are to be connected to the module. The module may be able to monitor voltage, current, or power, or check for faults on the wire. The results of such monitoring may be displayed on a screen associated with the controller.

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.

A multiple objective optimization route selection method based on a step ring grid network for a power transmission line is configured to use multiple data for regional classification and to select virtual topological nodes to construct a virtual topology map. An overall route is planed according to the shortest and optimization route selection method. After selecting the virtual topology route, a semi annular domain of a step ring grid map is constructed through the connections of the topological nodes. After the segmentation of the semi-annular domain to form a plurality of grids, the grids are numbered. The grid attributes of the grids are used for optimizing the route. The multiple objective optimization function is constructed according to a distance function, a cost objective function and an angle cornering objective function, in order to collaboratively optimize the transmission line route.

Tools and techniques are described to attach a device to a controller, whereby the controller analyzes the device inputs, looks up information about the device in a database, and then determines which inputs on the device match the defined device inputs. It then may translate information received from the device into an intermediate language. It may also use the information received from the device, the location of the device, and information about the device to create a digital twin of the device.