Abstract: Methods for detecting network model data errors are disclosed. In some examples, methods for detecting network model data errors may include splitting a network model into a first plurality of portions, executing an algorithm on each of the portions, identifying a portion for which the algorithm is determined to be non-converged, splitting the identified portion into a second plurality of portions, repeating the executing, identifying and splitting the identified portion until a resulting identified portion is smaller than a predefined threshold, and examining the resulting identified portion to identify plausible data errors therein. In some examples, examining the resulting identified portion to identify plausible data errors therein may include executing a modified algorithm, which may include an augmented measurement set, on the identified portion.

Abstract: The teachings herein disclose an advantageous method and apparatus for performing Security Constrained Economic Dispatch (SCED) for a hybrid power system that includes one or more AC grids interconnected with one or more multi-terminal High Voltage DC (HVDC) grids. The teachings include optimizing a non-linear objective function, subject to a set of constraints that include AC and DC grid constraints, for determining the SCED solution using successive linear approximation. The linear programming model used in the linear approximations is advantageously augmented with a DC grid portion in a manner that accounts for the effects of the DC grid on the AC grid, but which does not require exposing proprietary DC grid modeling details, and which conforms the resultant SCED solution to all applicable AC and DC grid constraints, including AC grid line flow constraints, AC grid power balance constraints, DC grid line flow constraints, and DC grid power balance constraints.

Abstract: A power system grid is decomposed into several parts and decomposed state estimation steps are executed separately, on each part, using coordinated feedback regarding a boundary state. The achieved solution is the same that would be achieved with a simultaneous state estimation approach. With the disclosed approach, the state estimation problem can be distributed among decomposed estimation operations for each subsystem and a coordinating operation that yields the complete state estimate. The approach is particularly suited for estimating the state of power systems that are naturally decomposed into separate subsystems, such as separate AC and HVDC systems, and/or into separate transmission and distribution systems.

Abstract: Techniques are disclosed for performing the estimation and/or prediction of the dynamic system state of large power system networks, using a multi-processor approach. More particularly, a large power system network is divided into smaller sub-systems, each sub-system having associated dynamic state variables. Each sub-system is assigned to one or more of a plurality of processing elements, and dynamic state variables for each sub-system are estimated or predicted independently, using the processing elements and sensor measurements. In several embodiments, the dynamic state of each sub-system is computed through the construction of a set of dedicated observers, such as linear parameter-varying (LPV) observers, which are designed to reduce the effects of other sub-systems on the state estimation problem.

Abstract: The teachings herein disclose an advantageous method and apparatus for performing Security Constrained Economic Dispatch (SCED) for a hybrid power system that includes one or more AC grids interconnected with one or more multi-terminal High Voltage DC (HVDC) grids. The teachings include optimizing a non-linear objective function, subject to a set of constraints that include AC and DC grid constraints, for determining the SCED solution using successive linear approximation. The linear programming model used in the linear approximations is advantageously augmented with a DC grid portion in a manner that accounts for the effects of the DC grid on the AC grid, but which does not require exposing proprietary DC grid modeling details, and which conforms the resultant SCED solution to all applicable AC and DC grid constraints, including AC grid line flow constraints, AC grid power balance constraints, DC grid line flow constraints, and DC grid power balance constraints.

Abstract: A power system grid is decomposed into several parts and decomposed state estimation steps are executed separately, on each part, using coordinated feedback regarding a boundary state. The achieved solution is the same that would be achieved with a simultaneous state estimation approach. With the disclosed approach, the state estimation problem can be distributed among decomposed estimation operations for each subsystem and a coordinating operation that yields the complete state estimate. The approach is particularly suited for estimating the state of power systems that are naturally decomposed into separate subsystems, such as separate AC and HVDC systems, and/or into separate transmission and distribution systems.

Abstract: Techniques are disclosed for performing the estimation and/or prediction of the dynamic system state of large power system networks, using a multi-processor approach. More particularly, a large power system network is divided into smaller sub-systems, each sub-system having associated dynamic state variables. Each sub-system is assigned to one or more of a plurality of processing elements, and dynamic state variables for each sub-system are estimated or predicted independently, using the processing elements and sensor measurements. In several embodiments, the dynamic state of each sub-system is computed through the construction of a set of dedicated observers, such as linear parameter-varying (LPV) observers, which are designed to reduce the effects of other sub-systems on the state estimation problem.

Abstract: Methods for detecting network model data errors are disclosed. In some examples, methods for detecting network model data errors may include splitting a network model into a first plurality of portions, executing an algorithm on each of the portions, identifying a portion for which the algorithm is determined to be non-converged, splitting the identified portion into a second plurality of portions, repeating the executing, identifying and splitting the identified portion until a resulting identified portion is smaller than a predefined threshold, and examining the resulting identified portion to identify plausible data errors therein. In some examples, examining the resulting identified portion to identify plausible data errors therein may include executing a modified algorithm, which may include an augmented measurement set, on the identified portion.

Abstract: A system and method for monitoring the power damping compliance of a power generation unit comprises a measurement unit that is configured to be coupled to a power generation unit to identify the voltage, current, and frequency values associated with power output therefrom. A processing system maintaining a model-based filter processes the voltage, current, and, frequency values to estimate the total amount of damping provided by the power generation unit. The estimated total damping is compared to prior historical values maintained in a database using various statistical techniques to determine if a power system stabilizer (PSS) provided by the power generation unit is being operated in a manner complying with predetermined guidelines.

Abstract: A wireless secondary assembly is disclosed for use in an electrical distribution network. The secondary assembly may include a wireless source electrically connected to a first electric cable and adapted to emit an electromagnetic power signal. A wireless receiver is electrically connected to a secondary device and adapted to receive the electromagnetic power signal and convert the electromagnetic power signal to electricity to power to secondary device.

Abstract: A protection setting determiner (118) adaptively updates settings of protection functions in memory of a protection device (106) that protects a machine (102) that provides power to a power system (104), wherein the settings are updated based at least in part upon sensed data acquired during operation of the machine (102). A physical parameter determiner (110) receives the sensed data, which includes three-phase voltage and three-phase current values at the terminals of the machine (102), and uses any suitable real-time or off-line parameter estimation technique (such as Kalman Filtering for an augmented state) to determine physical parameters of the machine (102) and the power system (104). The protection setting determiner (118) uses the physical parameters to update the protection settings.

Abstract: A system and method for monitoring the power damping compliance of a power generation unit comprises a measurement unit that is configured to be coupled to a power generation unit to identify the voltage, current, and frequency values associated with power output therefrom. A processing system maintaining a model-based filter processes the voltage, current, and, frequency values to estimate the total amount of damping provided by the power generation unit. The estimated total damping is compared to prior historical values maintained in a database using various statistical techniques to determine if a power system stabilizer (PSS) provided by the power generation unit is being operated in a manner complying with predetermined guidelines.

Abstract: A sag calculator (112) computes sag for a span of a line section based at least in part upon an average temperature of the conductors in the line section. A temperature calculator (110) determines the temperature by ascertaining an ohmic resistance of the conductor lines based at least in part upon time-synchronized power system voltage and current measurements such as (but not limited to) phasor measurements generated by phasor measurement units (104, 106). The temperature calculator (110) determines the temperature as a function of the ohmic resistance.

Abstract: A wireless secondary assembly is disclosed for use in an electrical distribution network. The secondary assembly may include a wireless source electrically connected to a first electric cable and adapted to emit an electromagnetic power signal. A wireless receiver is electrically connected to a secondary device and adapted to receive the electromagnetic power signal and convert the electromagnetic power signal to electricity to power to secondary device.

Abstract: Phasor measurement units (108) provide phasor data from various locations (102) in an electrical power system. The phasor data is referenced to a common timing signal. Non-phasor measurement data is also obtained at various locations in the power system. A phasor assisted state estimator (120) uses the phasor data and the non-phasor data to determine the power system state.

Abstract: A sag calculator (122) computes sag for a span of a section of a power line based at least in part upon a temperature of conductor lines in the line section. A temperature calculator (120) determines the temperature by computing a resistance ascertained through augmented state estimation techniques performed by a state estimator (118). A Supervisory Control and Data Acquisition (SCADA) system (104) acquires data used by the state estimator (118) to compute the resistance.

Abstract: A protection setting determiner (118) adaptively updates settings of protection functions in memory of a protection device (106) that protects a machine (102) that provides power to a power system (104), wherein the settings are updated based at least in part upon sensed data acquired during operation of the machine (102). A physical parameter determiner (110) receives the sensed data, which includes three-phase voltage and three-phase current values at the terminals of the machine (102), and uses any suitable real-time or off-line parameter estimation technique (such as Kalman Filtering for an augmented state) to determine physical parameters of the machine (102) and the power system (104). The protection setting determiner (118) uses the physical parameters to update the protection settings.

Abstract: A sag calculator (112) computes sag for a span of a line section based at least in part upon an average temperature of the conductors in the line section. A temperature calculator (110) determines the temperature by ascertaining an ohmic resistance of the conductor lines based at least in part upon time-synchronized power system voltage and current measurements such as (but not limited to) phasor measurements generated by phasor measurement units (104, 106). The temperature calculator (110) determines the temperature as a function of the ohmic resistance.

Abstract: A sag calculator (122) computes sag for a span of a section of a power line based at least in part upon a temperature of conductor lines in the line section. A temperature calculator (120) determines the temperature by computing a resistance ascertained through augmented state estimation techniques performed by a state estimator (118). A Supervisory Control and Data Acquisition (SCADA) system (104) acquires data used by the state estimator (118) to compute the resistance.

Abstract: Phasor measurement units (108) provide phasor data from various locations (102) in an electrical power system. The phasor data is referenced to a common timing signal. Non-phasor measurement data is also obtained at various locations in the power system. A phasor assisted state estimator (120) uses the phasor data and the non-phasor data to determine the power system state.