A method and apparatus for controlling a reactive power of a generator in a power plant are provided. The method includes: S1, dividing a plurality of power plants into a plurality of plant-plant coordination groups; S2, dividing generators into a first generator and a second generator set; S3, calculating a deviation between a measured voltage and a preset voltage of a central bus; S4, comparing the deviation with a control dead band threshold; S5, establishing a reactive power tracking model if the deviation is greater than the control dead band threshold; S6, establishing a reactive power keeping model; and S7, obtaining sum reactive power adjustments of the generators according to the first reactive power adjustments and the second reactive power adjustments, and obtaining voltage adjustments of buses according to the sum reactive power adjustments.

A system architecture and method for enabling hierarchical intelligent control with appropriate-speed communication and coordination of control using intelligent distributed impedance/voltage injection modules, local intelligence centers, other actuator devices and miscellaneous FACTS coupled actuator devices is disclosed. Information transfer to a supervisory utility control is enabled for responding to integral power system disturbances, system modelling and optimization. By extending the control and communication capability to the edge of the HV power grid, control of the distribution network through FACTS based Demand response units is also enabled. Hence an integrated and hierarchical total power system control is established with distributed impedance/voltage injection modules, local intelligence centers, connected other actuator devices, miscellaneous FACTS coupled devices and utility supervisory all networked at appropriate speeds allowing optimization of the total power system from generation to distribution.

A micro-grid dynamic stability control system includes: a micro-grid dynamic stability control device, configured to calculate a power factor based on a real-time voltage and current of a bus; a central control device, configured to transmit a reactive power control instruction if the power factor is lower than a predefined threshold; and at least one local control device, configured to transmit a control signal to the micro-grid dynamic stability control device and at least one distributed power supply controlled by the at least one local control device. In response to the control signal, the micro-grid dynamic stability control device compensates the voltage of the bus with droop control, and the at least one distributed power supply outputs a reactive power to the bus to increase the power factor of the bus.

A power management apparatus manages power consumptions of a plurality of equipments provided in a facility. The power management apparatus comprises: an acquisition unit configured to acquire power amount information which is information related to power consumption of the plurality of equipments; and a controller configured to calculate, based on the power amount information, a predicted value of a power consumption amount which is an accumulated value of power consumptions of the plurality of equipments in a predetermined time period. The plurality of equipments includes an automatically-controlled equipment to which automatic control of automatically controlling power consumptions by the controller is applicable, and a non-automatically-controlled equipment to which the automatic control is not applied. The controller notifies a user of information for identifying the non-automatically-controlled equipment from among the plurality of equipments, in a case in which the predicted value exceeds a threshold value.

The present innovations control and improve operation of one or more microgrids optionally and/or intermittently coupled to an Electric Power System(s).

Devcies 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 method for controlling power in a microgrid that includes power sources, loads and at least one connection to a main grid where a transformer is arranged to transfer electric power between the microgrid and the main grid is disclosed. The method includes: monitoring the power balance within the microgrid; monitoring the transformer, including monitoring the transformer temperature; and detecting a need for overloading the transformer based on the power balance within the microgrid. Especially, the method includes: determining a load profile for the transformer based on the power balance within the microgrid; determining a prognosis of the transformer temperature based on the load profile; and determining a schedule for power control of the microgrid, which determining of a schedule for power control includes analyzing the prognosis of the transformer temperature.

There is provided air-conditioning control in a low power operation so as not to exceed a target demand power amount in a predetermined measurement period while preventing deterioration of comfortableness of a living space. There include a reducible-power-amount estimation unit configured to calculate, for each group, a reducible power amount by making indoor units perform, for each group, a shut-off operation for a minimum shut-off time in the first half of a demand time limit, and a reduced-power-amount determination unit configured to distribute, when a power consumption amount predicted by a power consumption amount prediction unit exceeds a target demand power amount after the first half of the demand time limit passes, the exceeding power amount to each zone, evenly distribute, in each zone, the distributed power amount to each group, and calculate, based on the reducible power amount of each group, a shut-off time of each group when each group performs the shut-off operation to reduce the distributed power amount.

A monitoring system for recognizing a contingency in a power supply network including in-field measurement devices adapted to generate measurement data of the power supply network and a processing unit adapted to process the measurement data generated by the in-field measurement devices of the power supply network by using a local network state estimation model to calculate local network state profiles used to generate a global network state profile, wherein the processing unit is further adapted to process the measurement data generated by the in-field measurement devices of the power supply network to provide a relevance profile including for the in-field measurement devices a relevance distribution indicating a probability where the origin of a contingency within the power supply network.

A method for designing feedforward and feedback controllers for integration of stochastic sources and loads into a nonlinear networked AC/DC microgrid system is provided. A reduced order model for general networked AC/DC microgrid systems is suitable for HSSPFC control design. A simple feedforward steady state solution is utilized for the feedforward controls block. Feedback control laws are provided for the energy storage systems. A HSSPFC controller design is implemented that incorporates energy storage systems that provides static and dynamic stability conditions for both the DC random stochastic input side and the AC random stochastic load side. Transient performance was investigated for the feedforward/feedback control case. Numerical simulations were performed and provided power and energy storage profile requirements for the networked AC/DC microgrid system overall performance. The HSSPFC design can be implemented in the Matlab/Simulink environment that is compatible with real time simulation/controllers.