A dispatchable datacentre energy system is provided. The system comprises a power conditioning system for providing conditioned power to a datacentre; wherein the power conditioning system includes a primary battery system for providing a primary energy reserve to the datacentre and being available to supply power to a grid operably connected to the datacentre in response to a dispatch request from a grid operator. A secondary battery system provides a secondary energy reserve to the datacentre and being available to supply power to the grid in response to the dispatch request. A power generation system provides a third energy reserve to the datacentre and being available to supply power to the grid in response to the dispatch request. A controller is provided for predicting grid conditions and being configured for selectively controlling at least one of the primary battery system; the secondary battery system and the power generation system in response to the predicted grid conditions; and wherein the controller is responsive to the dispatch request to adjust power consumption of the datacentre from the grid or power supply from at least one of the primary battery system, the secondary battery system and the power generation to the grid.

Technologies are provided for reporting, monitoring, analyzing performance of distributed energy resources (DERs). The monitoring and analysis of a DER can be performed in real-time or essentially real-time. The monitoring also can include health monitoring of a DER. The reporting of performance of a DER is configurable. The monitoring and analysis of performance of the DER also is configurable. Attributes that control the reporting, monitoring, and analysis can be interactively configured via user interfaces having one multiple control elements. Performance of a DER can be reported, monitored, and analyzed irrespective of manufacturer of the DER.

A load management system integrates comparator-based neutral sensing, machine learning prediction, and relay control into a single integrated AC board requiring no additional wiring. A highspeed comparator circuit detects grid failures in sub millisecond timeframes, providing clean data to a temporal convolutional network that predicts load requirements 24 hours in advance with integration of external data sources such as weather and time of use pricing. The system automatically manages 120V and 240V circuits during grid transitions, learning from user override patterns to continuously improve performance. A mobile application provides real-time monitoring and control. The integration of low-latency sensing with predictive machine learning enables performance improvements exceeding 40% in battery runtime compared to conventional systems, while reducing installation time and cost.

A method for optimising the consumption of an installation includes, carried out before a specified period, implementing a disaggregation method, so as to predict, for each appliance, an expected individual consumption profile, predicting an expected renewable production profile by the renewable energy source, defining first optimised individual consumption profiles for the appliances, making it possible to maximise a use of renewable electrical energy, and the second step of controlling the appliances during the specified period, by using the first optimised individual consumption profiles.

An AI-based platform for enabling intelligent orchestration and management of at least one operating process is provided herein. The AI-based platform includes an artificial intelligence system that is configured to generate a prediction of an energy pattern associated with the at least one operating process. The AI-based platform is also configured to manage the at least one operating process based on the prediction of the energy pattern.

A phase swapping system is provided for swapping phases in a power distribution system. The system includes an interface circuitry configured to receive, from sensors arranged at buses in the power distribution system, real-time states at current time step, wherein each of the real-time states are associated with a complex power flowing from an upstream bus to a downstream bus, one or more processors and a non-transitory computer-readable storage medium having stored thereon executable instructions that, when executed by the one or more processors, cause the phase swapping system to perform steps of determining a multi-step phase swapping action by using the real-time states and a trained optimal policy generating phase swapping commands based on the multi-step phase swapping action, and transmitting, via the interface circuitry, the phase swapping commands to phase swapping devices arranged at around the sensors, wherein the phase swapping devices are configured to perform the multi-step phase swapping action based on the phase swapping commands.

A pool automation system is connectable with one or more pieces of equipment associated with a swimming pool or spa. The pool automation system may receive a demand event with a requested load reduction, and the pool automation system may determine a demand response for the one or more pieces of equipment associated with the swimming pool or spa based on the demand event and based on information gathered by the pool automation system about the at least one piece of equipment. The demand response may be based on a prioritization of the one or more pieces of equipment associated with the swimming pool or spa. The pool automation system may implement control of the one or more pieces of equipment associated with the swimming pool or spa responsive to the demand event.

A system for dynamic rating of a power grid may include a plurality of terminal units, and a controller. The terminal units may detect a voltage phasor and a current phasor at nodes of the power grid. The controller may, based on the voltage phasors and the current phasors of the plurality of nodes, determine a dynamic thermal stability power rating for each line, a dynamic angular stability power rating for each node, and a dynamic voltage stability power rating for each node. The controller may, based on the dynamic thermal stability power rating, the dynamic angular stability power rating, and the dynamic voltage stability power rating, determine a dynamic system rating for the power grid. The controller may control the power grid in response to the dynamic system rating.

Provided is a method for load transfer for an open-loop power grid. The method includes: constructing a tree graph for the power grid based on power transmission among devices in the power grid; determining a target node representing a target device which triggers load transfer in the open-loop power grid; determining one or more target graphs; enumerating all transfer schemes for the target graphs based on the target graphs, and prioritizing the transfer schemes; and performing load transfer based on the prioritized transfer schemes.

The disclosure relates to systems and methods for managing data generated by connected systems and/or devices in connection with energy usage and/or management decisions. In certain embodiments, a gateway device in communication with one or more connected devices may be configured to receive energy management signal information and apply one or more policies in connection with the management of the connected devices. Responses generated in connection with such energy management decisions may be reported securely in a manner that respects various stakeholder concerns relating to transparency, confidentiality, privacy, auditability, and/or affirmation of data provenance.