A power source fault prediction and control system includes a plurality of power sources, such as generator sets connected in parallel, a controller, and a data acquisition and analysis module. The data acquisition and analysis module is configured to receive sensor data from a sensor, analyze the sensor data, predict a future fault scenario at a first time, and optionally send an instruction to the controller to change an operational parameter of a respective power source, such as the generator set. The instruction is configured to delay the fault scenario to a second time after the first time.

A technological solution for controlling generation or distribution of electric power in a power generation and distribution network. The solution includes modeling and forecasting electricity demand in the power generation and distribution network, which includes a plurality of nodes each having cooling appliances, heating appliances, or both cooling and heating appliances. The solution includes, among other things, building a per-capita parametric model of an electric demand curve for a geographic region, modeling residual intraday variations in electric demand, determining an average residual variation in demand, iteratively optimizing the residual intraday variations in demand and the average residual variation in demand, and determining electricity demand per-capita for the geographic region.

A grid power configuration may provide a reliable, efficient, inexpensive and environmentally conscious power source to a site, for example, a remote site such as a well services environment. Grid power may be provided for one or more operations at the site by coupling a main breaker to a switchgear unit coupled to one or more loads. The switchgear unit may be coupled to the main breaker via a main power distribution unit and may also be coupled to one or more loads. At least one of a grid power unit and a switchgear unit may be coupled to the main breaker via the main power distribution unit and may also be coupled to one or more additional loads. A control center may be communicatively coupled to the main breaker or any one or more other components to control one or more operations of the grid power configuration.

A building automation system that is comprised of a plurality of network connected electrical modules contained in standard receptacle gang boxes for outlets and switches is described. The system includes an AC to DC power supply, a bidirectional solid state dimmer switch, a microprocessor, and, interconnected sensors that are powered and controlled by microprocessors within the electrical modules. The electrical modules include a user interface for programming and control. The system provides enhanced safety and security, power metering, power control, and home diagnostics. The apparatus replaces existing outlet receptacles and switches with a familiar flush but elegantly updated and seamlessly integrated faceplate.

In one aspect, a method to determine a capacity of a microgrid includes applying a current test load to the microgrid and measuring a current through an energy storage device, the current indicating a charging status of the energy storage device based on a current load being applied to the microgrid through activated power outlets being served by the microgrid and the current test load, the energy storage device being integrated with the microgrid. The method also includes, responsive to a determination that the measured current based on the current load being applied to the microgrid and the current test load indicates that the energy storage device is discharging, determining the capacity of the microgrid, wherein the capacity is the current load being applied to the microgrid through activated power outlets and a test load applied to the microgrid immediately preceding the current test load.

An example system includes an aggregator configured to receive a service collaboration request and iteratively determine, based on minimum and maximum power values for DERs under its management, an optimized operation schedule. The aggregator may also be configured to iteratively determine, based on the optimized operation schedule, an estimated flexibility range for devices under its management and output an indication thereof. The system may also include a power management unit (PMU) configured to iteratively receive the indication and determine, based on a network model that includes the estimated flexibility range, a reconfiguration plan and an overall optimized operation schedule for the network. The PMU may also be configured to iteratively cause reconfiguration of the network based on the plan. The PMU and aggregator may also be configured to iteratively, at a fast timescale, cause energy resources under their management to modify operation based on the overall optimized operation schedule.

Disclosed are systems and methods of generating electrical power utilizing a mining bank of individual blockchain miners. The blockchain miners operate as a revenue generating heat source that provides thermal energy into a power plant's Rankine or Brayton cycle turbines.

A dynamic charging demand side response method and a dynamic charging demand side management method based on a consumer order, and a demand side management control system for performing the methods. In favor of a consumer, a controllable reduction capacity may be increased by securing a number of flexible blocking measures suitable for characteristics of target load, thereby performing efficient demand management.

A system and method for creating and making use of customer profiles, including energy consumption patterns. Devices within a service point, using the active load director, may be subject to control events, often based on customer preferences. These control events cause the service point to use less power. Data associated with these control events, as well as related environment data, are used to create an energy consumption profile for each service point. This can be used by the utility to determine which service points are the best targets for energy consumption. In addition, an intelligent load rotation algorithm determines how to prevent the same service points from being picked first each time the utility wants to conserve power.

A system and method for creating and making use of customer profiles, including energy consumption patterns. Devices within a service point, using the active load director, may be subject to control events, often based on customer preferences. These control events cause the service point to use less power. Data associated with these control events, as well as related environment data, are used to create an energy consumption profile for each service point. This can be used by the utility to determine which service points are the best targets for energy consumption. In addition, an intelligent load rotation algorithm determines how to prevent the same service points from being picked first each time the utility wants to conserve power.