A system for autonomously validating the topology information of an electrical power distribution system is provided. For example, the system includes a group of meters previously determined to be connected to the same transformer of an electrical power distribution system. The group of meters is configured to perform family check periodically or upon request and to identify orphan meters in the group. The identified orphan meter can contact a community device communicatively connected to meters in more than one group to request a community check. The community device performs the community check by contacting meters in other groups of meters and obtain their family signature data. The community device further determines whether the orphan meter belongs to a new family based on the voltage data of the orphan meter and the family signature data of other groups. The orphan meter can report the community check results to a headend system.

A method for predicting the operation state of a power distribution network based on scene analysis is provided, comprising the following steps of step 10) obtaining the network structure and historical operation information of a power distribution system; step 20) extracting representative scene sequence fragments of output of the DGs according to historical output sequences of the DGs; step 30) obtaining a multi-scene prediction result of a future single-time section T.sub.0 through matching the historical similar scenes; step 40) establishing a future multi-time section operation scene tree; and step 50) deeply traversing all scenes in the future multi-time section operation scene tree, performing power distribution network load flow analysis for each scene, calculating the line current out-of-limit risk and the busbar voltage out-of-limit risk of the power distribution network, and obtaining a future operation state variation tendency of the power distribution network with the DGs.

A method and a system for evaluating inertia of a power system and a storage medium. The method includes: injecting a cosine active power disturbance into the power system by small-disturbance injection, and obtaining frequency response at a node where the disturbance is injected, where the active power disturbance can be an energy storage, wind power, or photovoltaic power; acquiring an evaluation framework of inertia and frequency regulation capability of the power system according to relative characteristics of a frequency response function; and constructing a mathematical relationship between the impedance and frequency response characteristics according to a relationship among active power disturbance, frequency fluctuation and impedance.

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.

A rapidly deployable modular microgrid including a plurality of renewable and other energy generation technologies, energy storage technologies, energy distribution networks, and intelligent control systems capable of managing the flow of electrical energy between one or more locations of energy generation, storage, and consumption are disclosed. The aforementioned microgrid may be delivered and rapidly deployed to provide primary or secondary electricity for a variety of purposes; including but not limited to household electrification, commercial or industrial productivity, grid resiliency, water pumping, telecommunication systems, medical facilities, and disaster relief efforts.

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.

A system and method are provided for controlling a power generating system having at least one power generating subsystem connected to a point of interconnection (POI). A first data signal is obtained corresponding to a feedback signal of an electrical parameter regulated at the POI, the first data signal having a first signal fidelity. A second data signal indicative of the electrical parameter generated at the power generating subsystem is obtained, the second data signal having a second signal fidelity that is higher than the first signal fidelity. A correlation value between the first and second data signals is obtained by filtering a value difference between the first and second data signals. The correlation value is applied to a setpoint value for the electrical parameter regulated at the POI. The modified setpoint value and the second data signal are combined to generate a setpoint command for the power generating subsystem that is used for controlling generation of power at the power generating subsystem to regulate the electrical parameter at the POI.

Systems and apparatuses include a circuit structured to: identify a first source object, a second source object, and a load bus object; determine locations of the first source object, the second source object, and the load bus object on a one-line topology; receive operational parameters of the first source object, the second source object, and the load bus object; define, using the one-line topology, a first route including objects electrically connected between the first source object and the load bus object; define, using the one-line topology, a second route including all objects electrically connected between the second source object and the load bus object; and control operation of the first route and the second route.

Systems and methods are directed to controlling components of a utility grid. The system can receive data samples including signals detected at one or more portions of a utility grid. The system can construct a matrix having a first dimension and a second dimension. The system can train a machine learning model based on the matrix to predict values for signals of the utility grid not provided in the matrix. The system can receive bounds for one or more input variables, constraints on one or more output variables, and a performance objective for the utility grid. The system can determine, based on the machine learning model and via an optimization technique, an adjustment to a component of the utility grid that satisfies the performance objective. The system can provide the adjustment to the component of the utility grid to satisfy the performance objective.

A modular system is described which can provide high frequency monitoring of power use and responsive control as well as enabling network connectivity for centralised monitoring and operation. One modular system consists of a communications bus, end caps, and a combination of the modules providing communications, power metering, relay control and battery backup. Each modular system can be configured with a combination of modular units as needed for the application. A combination of bus communication monitoring and tilt detection provides security against external tampering after installation.