Electric current is dynamically distributed to vehicles, which each is connected to a respective consumer node in a distribution network receiving a total amount of incoming electric current via a root interface. Current is allotted to each node in the distribution network according to a stepwise procedure, wherein amounts of current is gradually allotted to the nodes until all of the total amount of electric current has been allotted, or at least one threshold criterion is fulfilled. A respective amount of current requested by each consumer node is repeatedly reassessed, and if for a particular consumer node, a requested amount of current is lower than an amount of current allotted to the node, the amount of electric current allotted to the particular consumer node is decreased to the amount of current requested by that node.

A building load management device includes a processor and a memory configured to store one or more programs executed by the processor. The processor includes a first processing unit configured to perform clustering, a second processing unit configured to predict a load of a first building at a future time using the previous building load data, a third processing unit configured to predict a load of a first cluster at the future time, and a fourth processing unit configured to assign a weight to a load prediction value of the first building and a load prediction value of the first cluster using a distance value between a centroid of the first cluster and the first building and calculate a final load prediction value of the first building using the weighted load prediction value of the first building and the weighted load prediction value of the first cluster.

A method for managing a virtual power plant on a user interface includes displaying, in a first portion of the user interface, a calendar grid of cells, the calendar grid including multiple columns each corresponding to available dates and including rows each corresponding to time slots. The method further includes receiving a first user input in a second portion of the user interface to create a power generation offer from a particular distributed energy resource at a particular time slot and a particular date, and in response to receiving the first user input, displaying the power generation offer on the calendar grid within a particular cell corresponding to the particular time slot and the particular date. The method further includes, in response to receiving the first user input, submitting the power generation offer to a distributed energy resource market.

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.

The present invention discloses a method and system for participating in grid frequency regulation within full range of charging and discharging of energy storage, comprising: collecting grid operation power and frequency data, and constructing a full-range droop coefficient; setting constraints of upper and lower limits of a frequency deadband, obtaining an actual output power command value based on the constraint function constructed from a theoretical power command value and a rated charging and generating power value, and controlling operation of the grid; and setting a hysteresis interval on the power command of an energy storage system, wherein when the demand of the grid exceeds the upper threshold, the energy storage system switches from the charging mode to the discharging mode; and when the demand of the grid falls below the lower threshold, the energy storage system switches from the discharging mode to the charging mode.

Systems, methods and apparatuses for power systems and energy storage systems are disclosed herein. The system, or part thereof, may be configured to determine an operational plan for controlling device(s) (e.g., an energy storage device and/or a load device) such that the device(s) may increase their power consumption in response to an increasing voltage at a grid connection point thus reducing the probability that the voltage level at the grid connection point rises to or above an upper limit. The system, or part thereof, may identify external conditions that may cause harm to one or more energy storage devices (e.g., a battery pack). A controller (e.g., battery management system, or part thereof) may be used to determine critical external conditions or high-risk conditions based on sensor data, and/or to determine mitigation actions or send alerts. The system may comprise one or more energy storage devices that may be stacked together.

A device, method, and non-transitory computer readable medium for controlling a power distribution system includes an islanded microgrid and a control system. The islanded microgrid includes battery energy storage systems (BESSs) that operate as a primary energy source, and a decentralized consensus-based virtual synchronous generator (VSG). The control system simultaneously, emulates inertial response of a synchronous generator by the virtual synchronous generator during grid disruptions to regulate and stabilizes frequency of the islanded microgrid, and maintain consensus among the plurality of battery energy storage systems (BESSs).

A method and system for tracking the oscillation path of a direct drive wind farm involve: collecting the port current, the current and state variables of the current inner loop, the dynamic angle and state component of the phase-locked loop and the phase and amplitude of the fault point voltage of each wind turbine generator in a dominant oscillation mode period which is used as acquisition period, and then obtaining corresponding instantaneous value of each oscillation component of the direct drive wind turbine generator; obtaining energy flow of coupling energy transfer path of direct drive wind farm in each acquisition period based on the instantaneous value; tracking the key energy transfer path of the direct drive wind farm according to the energy flow, so as to realize the stability control of the direct drive wind farm.

A method includes: receiving, by an apparatus or system, a first set of values for an electric grid, a second set for a first electricity supply, and a third set for a second electricity supply; receiving data from electricity controllers, wherein all the received data form a fourth set of values, wherein each electricity controller of the controllers is associated with a household of multiple households and controls electricity supplied to the electric grid, stored and requested from the electric grid at the different time periods within the PT, wherein each household includes at least one renewable electrical energy production device and the fourth set of values is indicative of electrical energy producible by each device of the at least one renewable energy production device at the different time periods within the PT; solving, by the apparatus or system based on the four sets of values, an optimization problem.

A predictive control method of a grid-connected converter based on a structurally adaptive extended state observer (ESO) is provided. The method includes: obtaining data of a grid current and a grid voltage and converting the data to data in a dq coordinate system; calculating a selected voltage vector based on a voltage in the dq coordinate system; adaptively inputting the current in the dq coordinate system to a parallel ESO, a cascade ESO, or a hybrid cascade-parallel ESO, so as to obtain a current predicted current value and estimated total disturbance; carrying out a two-step grid current prediction based on the current predicted current value, the estimated total disturbance and the selected voltage vector; and taking minimizing a cost function as a control target, so as to obtain an optimal voltage vector based on a two-step grid current prediction result, and carrying out switching control of the grid-connected converter.