Abb Research Ltd.

Abb Schweiz Ag

Abb Technology Ag

Vaibhav Deepak Donde

James Stoupis

Zhenyuan Wang

Fang Yang

Ernst Scholtz

David Lubkeman

Jean-Charles Albert Tournier

William Peterson

Wenping Li

Mirrasoul Mousavi

Mats Larsson

Xiaoming Feng

John McGowan

Mohamed Maharsi

Yan Zhang

Mani Subramanian

John Finney

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.

Detecting state estimation network model data errors

A method and system restores power in a power distribution network. The network includes a plurality of power sources, a plurality of loading zones, a plurality of switching devices interconnected between the plurality of power sources and the plurality of loading zones, and an intelligent electronic device associated with each of the plurality of switching devices to control the switching devices. A base network state is defined and a power restoration logic is created for the base network state. A simulation is run for the power restoration logic and then the power restoration logic is transmitted to a power restoration controller which thereafter monitors and controls the intelligent electronic devices.

Load restoration for feeder automation in electric power distribution systems

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.

Power system state estimation using a two-level solution

Among other things, one or more techniques and/or systems are provided for leasing electrical network computational services to one or more network control centers. A power grid may comprise one or more substations. Network control centers disposed within the power grid may be configured to manage the substations within the power grid. A remote centralized network control center may be configured to lease electrical network computational services to the network control centers (e.g., which may mitigate costs associated with including computational hardware and/or software within respective network control centers for performing such electrical network computational services). In this way, substation data received from a network control center may be processed by the remote centralized network control center according to a level of service subscribed to by the network control center. Computational results may be provided back to the network control center (e.g., in real-time).

Centralized control center for electrical network computational services

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.

Parallel computation of dynamic state estimation for power system

The method of determining back-feed paths is capable of efficiently solving multi-layer restoration problems by minimizing a fitness function using an iterative genetic algorithm. The method optimizes back-feeding of out-of-service areas by minimizing power loss, switching, unserved loads and voltage/current violations. The efficiency of the algorithm is further increased through the use of a reactive Tabu search to prevent duplicate candidate systems.

Restoration switching analysis with modified genetic algorithm

A power outage restoration system manages a power network including a plurality of switching devices. The power outage restoration system includes an outage management system having a network model of said power network. A plurality of local restoration controllers are in communication with the outage management system and each said local restoration controller includes a trimmed network model correlating to a respective area of responsibility.

Hybrid distribution network power restoration control

A method and a protective device operable to perform the method are provided, wherein the method is for detecting and analyzing faults in a first cable and one or more other cables, which convey power in a three phase feeder system. Current magnitude in the first cable is compared to a threshold level. If the current magnitude exceeds the threshold level, the duration of the condition is measured. If the duration falls within a predetermined duration range, a predetermined time interval is allowed to pass and then a determination is made whether a fault is detected in the one or more other cables. If a fault is not detected in the one or more other cables, then a determination is made that a single phase fault has occurred in the feeder system.

Apparatus and method for adaptive fault detection in MV distribution circuits

A soft PLC technology based computer-implemented method includes updating a system configuration incidence matrix for an electric power distribution system based on both a depth-first search of a connectivity matrix for the electric power distribution system and information about the electric power distribution system, wherein the information includes at least status information about one or more switches of the electric power distribution system. The method further includes detecting a fault in the system based on the incidence matrix. The method further includes generating isolation control logic based on the incidence matrix and isolating the fault based on isolation control logic. The method further includes generating restoration control logic based on a breadth-first search of the incidence matrix and restoring the system based on the restoration control logic.

Feeder automation for an electric power distribution system

A method of forecasting loads on a distribution network is disclosed. The method employs load profiles in combination with short-term load estimations to forecast expected loads on a distribution network. The predicted loads may then be used by power restoration controllers when performing back-feed capacity checks.

Growing community of inventors

Cary, NC, United States of America

Vaibhav Deepak Donde