Electrical circuit control techniques in power systems are disclosed herein. In one embodiment, a supervisory computer in the power system can be configured to fit phasor measurement data from phasor measurement units into a Gaussian distribution with a corresponding Gaussian confidence level. When the Gaussian confidence level of the fitted Gaussian distribution is above a Gaussian confidence threshold, the supervisory computer can be configured to perform an ambient analysis on the received phasor measurement data to determine an operating characteristic of the power system. The supervisory computer can then automatically applying at least one electrical circuit control action to the power system in response to the determined operating characteristic.

The present application relates generally to Volt-VAR optimization for power distribution systems having advanced metering infrastructure (AMI). Distributed energy resources (DER) such as photovoltaic arrays are becoming prevalent in distribution systems. These DER systems inject power into the distribution system which can cause unfavorable changes, such as a rise in voltage across the feeder lines of the distribution system. Existing control proposals suffer from a number of shortcomings, drawbacks and disadvantages. In some instances, traditional controllers for distribution systems with DER systems may require information related to the arrangement of the distribution system which is unknown and cannot be provided by the advanced metering infrastructure. There remains a significant need for the apparatuses, methods, systems and techniques disclosed herein.

A system and method for estimating the magnitude and phase of magnetic and electrical currents in a power line comprising at least one processor operating to create a model of the power line and derive expected complex magnetic and electric-field values; at least one memory; at least one sensor positioned proximate to the at least one power line for sensing and providing measurements of the magnetic and electric fields of the at least one power line; the at least one processor operating to compute a set of complex magnetic and electric field values based upon the measurements provided by the at least one sensor and to estimate parameters related to the complex voltage and/or current of the at least one power line based upon the measured field values and the set of expected complex electric current and voltage values derived from a model of at least one power line.

Certain embodiments may generally relate to a smart fault detection device for power grids, and a method of fault detection for power grids. A method may include receiving raw data samples of currents in grounding conductors and line conductors. The method may also include processing the raw data samples under at least one of a plurality of system operating modes. The method may also include monitoring normal operation and anticipating an impending fault while operating under at least one of the system operating modes. The method may further include extracting fault information based on the monitoring. The method may also include reporting the fault information to a supervisory control and data acquisition system human-machine interface. The method may further include anticipating faults based on an analysis of the raw data samples.

The present disclosure provides a system-level protection system and method for sub/super-synchronous resonance/oscillation. The system includes a centralized protection coordinator arranged in a control center and a plurality of distributed protection relays arranged in a plurality of transformer substations or wind farms. Each distributed protection relay is configured to acquire a sub/super-synchronous impedance of the wind farm. The centralized protection coordinator is configured to acquire the sub/super-synchronous impedances measured by the plurality of distributed protection relays, to obtain a sub/super-synchronous aggregate impedance of the system according to a preset circuit topology and the sub/super-synchronous impedances, and to generate a system-level protection signal when the sub/super-synchronous aggregate impedance does not meet a stable condition. Each distributed protection relay is further configured to initiate a system-level protection according to the system-level protection signal.

Example implementations described herein are directed to detection of historical anomalous events that are similar to currently occurring events in a transmission power system based on phasor management unit (PMU) data to provide information to grid operators with online decision support. From the high-resolution time synchronized PMU data, the historical events can be quickly retrieved and compared to the currently occurring event so that operators can be provided with remedy actions that were attempted in response to the historical events. Utilization of PMU information for such decision support may compliment operation practices relying on supervisory control and data acquisition (SCADA) measurements by allowing a much fast response to the currently occurring event. Accurate identification of similar, historical events can advise grid operators of the cause of disturbances and provide ideas for response. Implementations of the proposed technology may improve the resilience and reliability of the transmission power systems.

The setting range of the voltage and the reactive power of a power system is maintained during variations of voltage and power flow due to the output variation of renewable energy of a large number of power supplies which fluctuate due to weather. A voltage/reactive power operation assisting device is provided with a first database for storing the data to be evaluated, target value data, individual control device control method data, and individual control device data of an individual control device for adjusting the voltage/reactive power of a power system. A second database stores the device operation data of the individual control device; and the operation of the individual control device is predicted from the data stored in the first database to obtain individual control device operation prediction data. A display unit displays the individual control device operation prediction data and the device operation data in a contrastive manner.

Data quality of Phasor Measurement Unit (PMU) is receiving increasing attention as it has been identified as one of the limiting factors that affect many wide-area measurement system (WAMS) based applications. In general, existing PMU calibration methods include offline testing and model based approaches. However, in practice, the effectiveness of both is limited due to the very strong assumptions employed. This invention presents a novel framework for online error detection and calibration of PMU measurement using density-based spatial clustering of applications with noise (DBSCAN) based on much relaxed assumptions. With a new problem formulation, the proposed data mining based methodology is applicable across a wide spectrum of practical conditions and one side-product of it is more accurate transmission line parameters for the energy management system (EMS) database and protective relay settings. Case studies are presented to demonstrate the effectiveness of the proposed method.

The method for determining mutual voltage sensitivity coefficients between a plurality of measuring nodes of an electric power network does not rely on knowledge of the network parameters (for example: series conductance and susceptance of the branches, shunt conductance and susceptance of the nodes, etc.). The method uses a monitoring infrastructure including metering units at each one of the measuring nodes, and includes a step of measuring at the same time, at each one of the measuring nodes, repeatedly over a time window, sets of data including values of the current, the voltage, and the phase difference, a step of computing active power, reactive power and values from each set of measured data, and a step of performing multiple parametric regression analysis of the variations of the voltage at each one of the measuring nodes.

Certain embodiments may generally relate to a smart fault detection device for power grids, and a method of fault detection for power grids. A method may include receiving raw data samples of currents in grounding conductors and line conductors. The method may also include processing the raw data samples under at least one of a plurality of system operating modes. The method may also include monitoring normal operation and anticipating an impending fault while operating under at least one of the system operating modes. The method may further include extracting fault information based on the monitoring. The method may also include reporting the fault information to a supervisory control and data acquisition system human-machine interface. The method may further include anticipating faults based on an analysis of the raw data samples.