A system and method to join distributed energy resources (DER) to achieve common objectives is provided. The present technology organizes and/or aggregates DERs by routing a (DER) program request for resources to DER contributors capable of responding to and performing the request using a routing system. The system accesses a plurality of DER profiles, each profile associated with a DER contributor capable of contributing a resource to the request, and calculates an initial value for each DER profile based on request attributes and scoring metrics associated with the profile. The system then calculates a fitness metric for each DER profile based on the initial value using a neural network having weights based on the plurality of performance indicators and selects the DER profile and contributors to whom to route the request.

A system includes a first subsystem configured to produce a resource by consuming electricity, a second subsystem configured to produce the resource by consuming a fuel, and a controller. The controller is configured to determine an allocation of a predicted demand for the resource over a future time period between the first subsystem and the second subsystem based on a first carbon emissions rate associated with off-site production of the electricity and a second carbon emissions rate associated with on-site consumption of the fuel. The controller is also configured to control the first subsystem and the second subsystem to produce the resource in accordance with the allocation during the future time period.

The actual performance information classify part derives a classification result of an actual performance information on electric power demand, by a classification setting information, from an environment information and a date attribute information which is correlated with each of the electric power demands which is included in an actual performance information on electric power demand. The prediction information calculate part derives a classification result of a prediction target day, using the date attribute information of the prediction target day, which is a day to conduct a prediction, and the environment information which is measured before a start of the prediction of a prediction target day, and in addition, predicts an electric power demand of a prediction target day, based on the electric power demand of the actual performance information on electric power demand, which corresponds to the classification result of the prediction target day.

Devices and methods of allocating distributed energy resources (DERs) to loads connected to a microgrid based on the cost of the DERs are provided. The devices and methods may determine one or more microgrid measurements. The devices and methods may determine one or more real-time electricity prices associated with utility generation sources. The devices and methods may determine one or more forecasts. The devices and methods may determine a cost associated with one or more renewable energy sources within the microgrid. The devices and methods may determine an allocation of the renewable sources to one or more loads in the microgrid.

A site monitoring method uses an electrical socket device to collect current data of an electrical appliance that is electrically connected to the electrical socket device. Based on the current data, a management server can derive a user behavior in connection with using the electrical appliance, and send out a warning message when the user behavior thus derived is abnormal.

A method for managing an electric utility power grid including a utility power line route may include generating an infrastructure model including utility assets and image information; receiving power line imaging data collected on the route and including utility asset imaging data; receiving geospatial topological model information; and generating a navigable simulated virtual environment model including an integrated visualization of infrastructure model image information with geospatial topological model image information and power line imaging data. A trained classification algorithm categorizes the condition of utility assets on the route from virtual views.

A behavioral load shaping (BLS) system can be implemented to encourage consumer reductions in resource consumption. To accomplish this, consumption reports detailing resource consumption can be generated and transmitted to consumers to encourage resource consumption. A series of resource consumption reports can be generated and transmitted to consumers at regular time intervals throughout a calendar year informing the consumer of the rates the consumer is being charged for peak hour and non-peak hour resource consumption. To encourage the consumer to reduce their resource consumption, especially during peak hours, the resource consumption report can include information or insights as to how the consumer can reduce his/her resource consumption especially during peak hours. The resource reports can also include information regarding changes in the peak hours and non-peak hours. The resource reports can also inform the consumer that the consumer is about to exceed a high resource bill threshold.

Embodiments provide techniques for datacenter power management using variable power sources. Power from the variable power sources is stored in a power cache. An optimization engine receives input criteria such as power availability from non-variable and variable power sources, as well as one or more power management goals. The optimization engine implements a dispatch strategy that dispatches stored energy from the power cache and feeds it to the datacenter, resulting in a mixture of non-variable and variable power sources used to achieve the power management goals, such as reduced power cost, increased power availability, and lowered carbon footprint for the datacenter.

An electronic device and a method for management of power supply in enclosed space is provided. The electronic device determines first information indicating a disruption in a main power supply of a first enclosed space. The electronic device determines second information which indicates a power consumption of one or more electrical appliances in the first enclosed space based on the determined first information. The electronic device further determines third information associated with one or more secondary power supplies in the first enclosed space. The electronic device further applies a trained ML model on the determined first information, the second information, and the third information and determines scheduling information based on the application of the ML model. The electronic device further controls the one or more secondary power supplies to power the one or more electrical appliances, based on the determined scheduling information.

A charging processing system includes: a power supply facility that supplies CO.sub.2 free power generated using renewable energy; a vehicle in which CO.sub.2 free charging is able to be performed to charge an onboard power storage device using the CO.sub.2 free power supplied from the power supply facility; a mobile terminal portable by a user of the vehicle; and a server. The server issues, when the CO.sub.2 free charging is performed in the vehicle, a coupon to the user of the vehicle in which the CO.sub.2 free charging is performed, the coupon being usable at a shop located around the power supply facility. When a timing to perform the CO.sub.2 free charging is included in a specific time period, the server increases the number of issued coupons and a usage value of each coupon.