The invention relates to managing electrical power consumption in the home. Claimed is a system which includes the electric power grid in a home, means for measuring power, and means for controlling load. The home grid is fed by an external grid and is configured in the form of individual lines having individual shutoff devices on supply lines for low priority, medium priority, high priority and extra high priority consumers. The medium priority consumers are connected to a supply line such as to allow phase switching, deactivation and deferral of the operation of a consumer to a different designated time. Sensors for monitoring and transmitting instantaneous current and voltage values to a microcontroller are installed on the supply line of said consumers. A group of high priority consumers is connected to a supply line via a phase switcher, allowing both forward and reverse phase switching. The extra high priority consumers are optionally connected to a guaranteed voltage unit. The microcontroller receives monitoring information about instantaneous current and voltage values, and also receives information about the weather, the microclimate, open doors and windows, movement in the home, the status of a home microgeneration source, and air conditioning, heating and ventilation system parameters.

Embodiments implement non-intrusive load monitoring using a novel learning scheme. A trained machine learning model configured to disaggregate device energy usage from household energy usage can be stored, where the machine learning model is trained to predict energy usage for a target device from household energy usage. Household energy usage over a period of time can be received, where the household energy usage includes energy consumed by the target device and energy consumed by a plurality of other devices. Using the trained machine learning model, energy usage for the target device over the period of time can be predicted based on the received household energy usage.

A charging processes for an electric vehicle is planned depending on a future energy requirement of the electric vehicle, and a sequence of historical journeys and historical parking processes of the electric vehicle is taken into account when the future energy requirement is determined.

A method is provided for obtaining information for operating an accumulator, and for obtaining periods of time for charging different accumulators using the method. An electrical gardening and/or forestry apparatus system with at least one accumulator for carrying out such a method is provided.

A system operator side computer includes: a supply amount acquirer configured to acquire a maximum suppliable power amount from a power generation operator at a predetermined time later; a demand specifier configured to specify a power demand at the predetermined time later; and a shortage amount calculator configured to calculate a power shortage amount based on the power demand and the maximum suppliable power amount.

It is intended to reduce errors related to an energy supply plan to be formulated. An energy supply plan formulation device includes an acquisition unit for acquiring a change of a base load of energy equipment, a determination unit for determining whether to need correction of at least one of an equipment model and a load model on the basis of the change of the base load, a correction unit for correcting at least one of the equipment model and the load model on the basis of a determination result, a demand forecasting unit for forecasting the amount of energy demand, and a supply plan formulation unit for formulating an energy supply plan on the basis of the equipment model and the amount of energy demand.

The energy management system performs forecast of power consumption of the load of each of the first consumer and the second consumer; calculates a self-sufficiency rate of entirety of both the first consumer and the second consumer, based on self-sufficient electric power supplied to the load in accordance with the forecast of power consumption and on purchase electric power supplied from the electric power system to the load; and provides interchange control of energy so that at least a part of electric power generated by the renewable energy power generator of the second consumer is accumulated in the energy accumulator of the first consumer so that the self-sufficiency rate exceeds a threshold value.

In order to suppress frequency fluctuation caused by a load frequency, an AR calculating section calculates an AR using system frequency deviation and tie-line power flow deviation as inputs. An output distribution ratio determining section determines a ratio of output distribution according to merit order based on the AR calculated by the AR calculating section. An output distributing section determines output distribution according to an output change speed based on the output distribution ratio determined by the output distribution ratio determining section according to the output change speed. An output distributing section determines output distribution according to the merit order based on the output distribution ratio determined by the output distribution ratio determining section according to the merit order. An output distribution instruction value determining section determines an output distribution instruction value to each regulated power source using, as inputs, output distribution values determined by the output distributing sections.

An AI-based platform for enabling intelligent orchestration and management of power and energy is disclosed. The platform includes a digital twin system having a digital twin of a mining environment. The digital twin includes at least one parameter that is detected by a sensor of the mining environment. In some disclosed embodiments, the at least one parameter is associated with one or more of an unmined portion of the mining environment a mining of materials from the mining environment, a smart container event involving a smart container associated with the mining environment, a physiological status of a miner associated with the mining environment, a transaction-related event associated with the mining environment, and a compliance of the mining environment with one or more contractual, regulatory, and/or legal policies.

A control system for an energy storage system located behind a utility meter uses a unique, feedback-based, communication and control method to reliably and efficiently maximize economic return of the energy storage system. Operating parameters for the energy storage system are calculated at an external, centralized data center, and are selected to prevent electrical power demand of an electric load location from exceeding a specified set-point by discharging energy storage devices, such as DC batteries, through a bidirectional energy converter during peak demand events. The control system can operate autonomously in the case of a communications failure.