The present disclosure provides techniques for estimating network states using asynchronous measurements by leveraging network inertia. For example, a device configured in accordance with the techniques of the present disclosure may receive electrical parameter values corresponding to at least one first location within a power network and determine, based on the electrical parameter values and a previous estimated state of the power network, an estimated value of unknown electrical parameters that correspond to a second location within the power network. The device may further cause at least one device within the power network to modify operation based on the estimated value of the unknown electrical parameters. The leveraging of network inertia may obviate the need for probabilistic models or pseudo-measurements.

The present disclosure provides techniques for estimating network states using asynchronous measurements by leveraging network inertia. For example, a device configured in accordance with the techniques of the present disclosure may receive electrical parameter values corresponding to at least one first location within a power network and determine, based on the electrical parameter values and a previous estimated state of the power network, an estimated value of unknown electrical parameters that correspond to a second location within the power network. The device may further cause at least one device within the power network to modify operation based on the estimated value of the unknown electrical parameters. The leveraging of network inertia may obviate the need for probabilistic models or pseudo-measurements.

The present invention provides a method, system and storage medium for load dispatch optimization for residential microgrid. The method includes collecting environmental data and time data of residential microgrid in preset future time period; obtaining power load data of residential microgrid in future time period by inputting environmental data and time data into pre-trained load forecasting model; obtaining photovoltaic output power data of residential microgrid in future time period by inputting environmental data and time data into pre-trained photovoltaic output power forecasting model; determining objective function and corresponding constraint condition of residential microgrid in future time period, where optimization objective of objective function is to minimize total cost of residential microgrid; obtaining load dispatch scheme of residential microgrid in future time period by solving objective function with particle swarm algorithm. The invention can provide load dispatch scheme suitable for current microgrid and reduce operating cost of residential microgrid.

The present invention provides a method, system and storage medium for load dispatch optimization for residential microgrid. The method includes collecting environmental data and time data of residential microgrid in preset future time period; obtaining power load data of residential microgrid in future time period by inputting environmental data and time data into pre-trained load forecasting model; obtaining photovoltaic output power data of residential microgrid in future time period by inputting environmental data and time data into pre-trained photovoltaic output power forecasting model; determining objective function and corresponding constraint condition of residential microgrid in future time period, where optimization objective of objective function is to minimize total cost of residential microgrid; obtaining load dispatch scheme of residential microgrid in future time period by solving objective function with particle swarm algorithm. The invention can provide load dispatch scheme suitable for current microgrid and reduce operating cost of residential microgrid.

Methods, systems, and apparatus, including computer programs encoded on a storage device, for electric grid asset detection are enclosed. An electric grid asset detection method includes: obtaining overhead imagery of a geographic region that includes electric grid wires; identifying the electric grid wires within the overhead imagery; and generating a polyline graph of the identified electric grid wires. The method includes replacing curves in polylines within the polyline graph with a series of fixed lines and endpoints; identifying, based on characteristics of the fixed lines and endpoints, a location of a utility pole that supports the electric grid wires; detecting an electric grid asset from street level imagery at the location of the utility pole; and generating a representation of the electric grid asset for use in a model of the electric grid.

Transaction-enabled systems and methods for royalty apportionment and stacking are disclosed. An example system may include a plurality of royalty generating elements (a royalty stack) each related to a corresponding one or more of a plurality of intellectual property (IP) assets (an aggregate stack of IP). The system may further include a royalty apportionment wrapper to interpret IP licensing terms and apportion royalties to a plurality of owning entities corresponding to the aggregate stack of IP in response to the IP licensing terms and a smart contract wrapper. The smart contract wrapper is configured to access a distributed ledger, interpret an IP description value and IP addition request, to add an IP asset to the aggregate stack of IP, and to adjust the royalty stack.

Transaction-enabled systems and methods for royalty apportionment and stacking are disclosed. An example system may include a plurality of royalty generating elements (a royalty stack) each related to a corresponding one or more of a plurality of intellectual property (IP) assets (an aggregate stack of IP). The system may further include a royalty apportionment wrapper to interpret IP licensing terms and apportion royalties to a plurality of owning entities corresponding to the aggregate stack of IP in response to the IP licensing terms and a smart contract wrapper. The smart contract wrapper is configured to access a distributed ledger, interpret an IP description value and IP addition request, to add an IP asset to the aggregate stack of IP, and to adjust the royalty stack.

Methods, systems, and apparatus are disclosed for electrical power grid visualization. A computer-implemented method includes: obtaining power grid data including different temporal and spatially dependent characteristics of a power grid, the characteristics including a first characteristic, a second characteristic, and a third characteristic; and generating a graphical user interface (GUI) representing a visualization of the power grid data. The GUI includes a line-diagram representation of power lines in the power grid overlaid on a map of a geographic region in which the power grid is located, the line-diagram including a plurality of line segments, wherein attributes of each line segment represent the power grid data at a particular spatial location of the power grid. The attributes include a time-changing thickness of the line segment representing the first characteristic; a plurality of time-changing directional arrows on the line segment representing the second characteristic; and a color shading representing the third characteristic.

Methods, systems, and apparatus are disclosed for electrical power grid visualization. A computer-implemented method includes: obtaining power grid data including different temporal and spatially dependent characteristics of a power grid, the characteristics including a first characteristic, a second characteristic, and a third characteristic; and generating a graphical user interface (GUI) representing a visualization of the power grid data. The GUI includes a line-diagram representation of power lines in the power grid overlaid on a map of a geographic region in which the power grid is located, the line-diagram including a plurality of line segments, wherein attributes of each line segment represent the power grid data at a particular spatial location of the power grid. The attributes include a time-changing thickness of the line segment representing the first characteristic; a plurality of time-changing directional arrows on the line segment representing the second characteristic; and a color shading representing the third characteristic.

Embodiments herein relate to fuel monitoring systems and related methods. In an embodiment, a fuel monitoring system for a vehicle is included having a fuel filter sensor device configured to generate data reflecting a filter restriction value of a fuel filter, a geolocation circuit configured to generate or receive geolocation data, and a system control circuit configured to evaluate the sensor data to determine changes in the filter restriction value. The control circuit can receive fuel level data, cross-reference geolocation data and fuel level data to identify refueling locations utilized, and correlate refueling locations with subsequent changes in filter restriction to identify an effect of specific refueling locations on fuel filter loading. In some embodiments, a refueling guidance system for a vehicle is included that can provide route and/or refueling site recommendations based on fuel filter loading rate data. Other embodiments are also included herein.