This power management device: receives, at predetermined intervals for each certain time period, an integrated value that is obtained by totaling power flowing between a power system and a consumer facility within the certain time period from a smart meter that measures the amount of the power flowing between the power system and the consumer facility; receives, at shorter intervals than the predetermined intervals, the measured value of the power flowing in the consumer facility from a power sensor provided separately from the smart meter; and calculates complementary information that complements the integrated value on the basis of the measured value.

The present disclosure presents a system, method, and apparatus for capacity determination in a micro grid, and a tangible computer readable medium. The micro grid comprises multi-type energy supply devices to provide both electricity and thermal energy, In embodiments of the present disclosure, a capacity determination process for minimizing both annual integrated cost for the micro grid and annual energy outage cost, is performed under constraints on electricity supply/demand balance and thermal energy supply/demand balance, and operation constraints on the multi-type energy supply devices, to determine respective numbers or energy supply capacity of the multi-type energy supply device. With embodiments of the present disclosure, it may achieve an optimal capacity termination which could provide a significant cost saving and at the same time guarantees the operation reliability of the micro grid.

Systems and methods for minimizing demand charges, including determining one or more optimal monthly demand charge thresholds based on historical load data, time of use charges, demand charges, and energy storage unit size for one or more end users. A grid power dispatch setpoint is calculated for a particular time step based on a daily load forecast and a daily economic dispatch solution based on the determined optimal monthly demand charge thresholds. A grid power dispatch setpoint for a subsequent time step is determined by iteratively solving the daily energy dispatch for the subsequent time step to determine an optimal grid power dispatch setpoint. Energy and demand charges are minimized by controlling charging and discharging operations for the energy storage unit in real-time based on the determined optimal grid power dispatch setpoint.

An energy planning system that proposes an appropriate energy plan for a home includes: a sensor that senses a state of an energy facility in a home; a predictor that predicts a future lifestyle of a resident of the home; and a proposer that determines information about an energy plan for the home based on a result of the sensing by the sensor and the lifestyle predicted by the predictor, and outputs the information.

Systems and methods for distributed control and energy management of one or more communities of energy-consuming units may include aggregation of consumption data from units, and determining per-unit electricity consumption based thereon, including consumption of backup power provided by a community during periods of time of poor quality (brownouts) or blackouts of a utility. A system may calculate and assess to respective units per-unit costs for such backup power. A system may also issue a command or alert to units to carry out one or both of community electricity usage objectives and electricity quotas required by the utility, which may be determined through execution of rules.

A power system for a vehicle parking structure is disclosed. The power system comprises: a DC voltage bus arranged throughout the vehicle parking structure and configured to distribute DC power throughout the vehicle parking structure; at least one DC power source operably connected to the DC voltage bus and configured to provide DC power to the DC voltage bus; a plurality of DC loads arranged throughout the vehicle parking structure and operably connected to the DC voltage bus, the plurality of DC loads being configured to operate using DC power from the DC voltage bus; and a control system operably connected to the DC voltage bus and configured to communicate with at least one DC load in the plurality of DC loads using data signals transmitted via the DC voltage bus.

The disclosure includes a system and method for providing charging services to mobile client devices. The system includes a processor and a memory storing instructions that, when executed, cause the system to: receive demand response event data associated with a geographic region; determine a last-mile distribution network that includes a first endpoint in the geographic region, the first endpoint associated with a mobile client device; estimate one or more last-mile power usage factors describing power usage of a set of endpoints in the last-mile distribution network, the set of endpoints including the first endpoint associated with the mobile client device; and determine a charge schedule for the mobile client device based on the demand response event data and the one or more last-mile power usage factors.

According to an embodiment, energy management system includes client and server. Server includes acquisition unit, estimation unit, calculator and controller. Acquisition unit acquires data concerning electrical equipment in a building including a storage battery from client. Estimation unit estimates energy demand and energy generation amount in building based on the data. Calculator calculates, based on the energy demand and the energy generation amount, operation schedule of the electrical equipment to optimize energy balance in building under a constraint that minimizes dump power to be discarded after storage battery is fully charged. Controller creates control information to control electrical equipment based on operation schedule.

A household appliance includes a controller operating on an energy supply network having a data network for exchanging data via the energy supply network, wherein the network may include smart metering. The controller has a first control component embodies as a computer, a second control component for settings data, a third control component for operating data, and a fourth control component connected with the first control component and including a graph algorithm. The first control component determines data for controlling actuators from the settings data and the operating data. Through cooperation of the first control component, the fourth control component and the graph algorithm, the data from the data network for the household appliance are taken into account so as to allow operation of the household appliance always to continue. A corresponding method for operating such household appliance is also described.

A method for reducing aggregate power cost that includes determining an end device power consumption profile for each of a plurality of end devices, storing the end device power consumption profiles in a switching device configured to determine a desired power flow timing for each of the plurality of end devices, determining an optimal rate period with the switching device, determining, with the switching device, the desired power flow timing for each of the plurality of end devices such that a power consumption of the plurality of end devices is preferably within the optimal rate period, and controlling, via the control device, the plurality of end devices such that the desired power flow timing is substantially obtained, thereby reducing aggregate cost per kWhr of the plurality of end devices.