Cloud-based mixed state estimation

Abstract

Systems, methods, techniques, and apparatus for power network state estimation are disclosed. An exemplary embodiment is a method for state estimation in a power network, the method comprising: receiving a set of Supervisory Control and Data Acquisition (SCADA) information including a power network topology; generating a SCADA state estimate using the set of SCADA information; receiving a set of PMU phasors using a cloud computing architecture; aligning the timestamps of the SCADA estimate with the timestamps of the set of PMU phasors using the cloud computing architecture; updating the power network topology using the set of PMU phasors using the cloud computing architecture; generating a hybrid state estimate using the updated power network topology, the set of PMU phasors, and the SCADA state estimate using the cloud computing architecture; and transmitting the hybrid state estimate to a local control system.

Description

Background Technology

[0001] This disclosure generally relates to power network state estimation. Energy management systems use state estimation to control and protect power networks. Routine state estimation involves generating SCADA state estimates periodically (e.g., at 5-15 minute intervals) using Supervisory Control and Data Acquisition (SCADA) measurements and network topology data. Control and protection applications use the generated SCADA state estimates until a new SCADA state estimate is generated during the next interval. Existing power network state estimation suffers from several shortcomings and drawbacks. Unmet needs remain, including improving the accuracy of state estimates and increasing the state estimate response to significant changes in the power network. Waiting several minutes for a new state estimate can jeopardize the health and efficiency of the power network. As more low-inertia generation systems are added to the power network, the likelihood of sudden changes in generation increases. For example, changes in cloud cover or wind speed will alter the actual state of the power network, making the current SCADA state estimate no longer an accurate representation of the power network. Furthermore, circuit breaker disconnections or other changes in network topology will also cause the actual state of the power network to deviate from the current SCADA state estimate. In view of these and other shortcomings in the art, there is a great need for the unique devices, methods, systems, and techniques disclosed herein.

[0002] Disclosure of illustrated embodiments

[0003] To clearly, concisely, and accurately describe the non-limiting exemplary embodiments of this disclosure, the ways and processes of making and using it, and to enable its practice, making, and use, reference will now be made to certain exemplary embodiments (including those illustrated in the figures), and they will be described using specific language. However, it should be understood that this does not constitute a limitation on the scope of this disclosure, and that this disclosure includes and protects such variations, modifications, and further applications of the exemplary embodiments as would be conceived by those skilled in the art benefiting from this disclosure. Summary of the Invention

[0004] Exemplary embodiments of this disclosure include unique systems, methods, techniques, and apparatus for power network state estimation. Further embodiments, forms, objects, features, advantages, aspects, and benefits of this disclosure will become apparent from the following description and accompanying drawings. Attached Figure Description

[0005] Figure 1 This is a block diagram illustrating an exemplary state estimation system.

[0006] Figure 2 This is a flowchart illustrating an exemplary state estimation process. Detailed Implementation

[0007] refer to Figure 1 The illustration shows an exemplary state estimation system 100 for power networks. System 100 is configured to generate new state estimates and network topologies in near real-time. For example, to name just a few, system 100 can generate new state estimates at least every second or half a second. It should be understood that system 100 can be implemented in a variety of power networks (to name just a few, including power transmission systems and power distribution systems).

[0008] System 100 includes multiple remote terminal units (RTUs) 110, multiple phasor measurement units (PMUs) 130, multiple phasor data concentrators (PDCs) 120, a local control system (LCS) 170, and a cloud computing architecture 180. It should be understood that the topology of system 100 is illustrated for illustrative purposes and is not intended to be a limitation of this disclosure. For example, to name just a few, exemplary state estimation systems may include more or fewer RTUs, PDCs, or PMUs.

[0009] Each of the plurality of RTUs 110 is configured to receive SCADA information corresponding to characteristics of the power network from a plurality of sensors or meters and transmit the SCADA information to a local control system 170. The SCADA information may be continuously transmitted to the plurality of RTUs and transmitted to the local control system 170 in response to polling by the local control system 170. SCADA information may be received from intelligent electronic devices (IEDs), relays, sensors, or other devices configured to monitor the power network. SCADA information may include measurements such as voltage measurements, current measurements, or power measurements. For example, measurements may include bus voltage, active power injection, reactive power injection, and line flow. The SCADA information may also include the network topology within the power network, which includes various on / off states of controllable switches (including circuit breakers). In some embodiments, the plurality of RTUs 110 are configured to receive instructions from the local control system 170 and, in response to receiving these instructions, operate controllable devices of the power network. To name just a few examples, controllable devices may include controllable switches, such as circuit breakers or disconnectors.

[0010] Multiple RTUs 110 and local control systems 170 communicate via an RTU / LCS communication network 160 using a communication protocol. For example, the multiple RTUs 110 and local control systems 170 may use communication protocols based on the Distributed Network Protocol (DNP3), the IEC 60870-5-101 standard, or the IEC 60870-5-104 standard.

[0011] The plurality of PMUs 130 are configured to synchronize the measured electrical characteristics of the power network using a common time source and output synchronized phasors (also called synchronization phasors) corresponding to the measured electrical characteristics. The phasors may correspond to voltage amplitude and voltage phase angle or current amplitude and current phase angle. For example, the PMU may output voltage phasors based on bus measurements or current phasors based on measurements of current flowing through distribution lines. In some embodiments, some of the PMUs may be replaced with other devices having the PMU functionality described above, such as IEDs or protective relays. Each of the plurality of PMUs 130 transmits phasors to one of the plurality of PDCs 120.

[0012] Each of the plurality of PDCs 120 is configured to communicate with a plurality of PMUs 130. In the illustrated embodiment, each of the plurality of PDCs 120 aggregates phasors from the plurality of PMUs, aligns the phasors into groups of PMU phasors based on the timestamp of each phasor, and transmits the aligned groups of PMU phasors to the local control system 170. In some embodiments, one or more of the plurality of PDCs 120 transmit the aligned groups of PMU phasors directly to a cloud PDC application 183 of a cloud computing architecture 180. In some embodiments, each PDC transmits groups of PMU phasors at the same frequency as it receives these phasors. For example, to name just a few, each PDC transmits groups of PMU phasors at a rate of 60 groups of PMU phasors per second or 30 groups of PMU phasors per second.

[0013] The plurality of PMUs 130 and the plurality of PDCs 120 communicate via the PMU / PDC communication network 140 using a communication protocol. For example, by way of example only, the plurality of PMUs 130 and the plurality of PDCs 120 may use a communication protocol based on the IEEE c37.118 standard.

[0014] The plurality of PDCs 120 and the local control system 170 communicate via the PDC / LCS communication network 150 using a communication protocol. For example, by way of example only, the plurality of PDCs 120 and the local control system 170 may use a communication protocol based on the IEEE c37.118 standard.

[0015] The local control system 170 includes an input / output device 179, a processing device 177, and a memory device 171. The local control system 170 can be a standalone device, an embedded system, or a plurality of devices configured to perform the functions described herein. For example, the local control system 170 can be an energy management system (EMS).

[0016] Input / output device 179 enables local control system 170 to communicate with multiple external devices, including multiple RTUs 110, multiple PDCs 120, and cloud computing architecture 180. To name just a few, input / output device 179 may include network adapters, network credentials, interfaces, or ports (e.g., USB ports, serial ports, parallel ports, analog ports, digital ports, VGA, DVI, HDMI, FireWire, CAT 5, Ethernet, fiber optic, or any other type of port or interface). Input / output device 179 may include hardware, software, and / or firmware. It is envisioned that input / output device 179 includes more than one of these adapters, credentials, or ports, such as a first port for receiving data and a second port for transmitting data.

[0017] Processing device 177 is configured to execute an application program stored on memory device 171. Processing device 177 may be a programmable state machine, a dedicated state machine, a hardwired state machine, or a combination thereof. To name just a few examples, processing device 177 may include multiple processors, arithmetic logic units (ALUs), central processing units (CPUs), digital signal processors (DSPs), or field-programmable gate arrays (FPGAs). For the form of processing device 177 with multiple processing units, distributed, pipelined, or parallel processing may be used. Processing device 177 may be dedicated solely to performing the operations described herein or may be used in one or more additional applications. In the illustrated form, processing device 177 is programmable, executing processes and process data according to an application program that includes a set of instructions stored in memory device 171. Alternatively or additionally, the programming instructions are defined at least in part by hardwired logic or other hardware. Processing device 177 may include one or more components of any type suitable for processing signals received from input / output device 179 or elsewhere and providing output signals. Such components may include digital circuitry, analog circuitry, or a combination of both.

[0018] The memory device 171 is configured to store Supervisory Control and Data Acquisition (SCADA) information, phasor data, and multiple applications, including a SCADA main application 175, a data storage application 172, a state estimation application 173, and a super PDC application 174. The memory device 171 can be one or more types, such as solid-state, electromagnetic, optical, or combinations thereof, to name just a few. Furthermore, to name just a few, the memory device 171 can be volatile, non-volatile, transient, or a combination thereof, and some or all of the memory devices 171 can be portable types, such as disks, magnetic tapes, memory sticks, or cassette tapes.

[0019] The SCADA master application 175 includes instructions executable by the processing device 177, which are effective for polling the plurality of RTUs 110, receiving SCADA information including measurement values ​​and network topology from the plurality of RTUs 110, timestamping the SCADA information, and transmitting the received SCADA information to the state estimation application 173 and the data storage application 172. In some embodiments, the SCADA master application 175 transmits SCADA information to the state estimation application 173 every 5-15 minutes.

[0020] The state estimation application 173 includes instructions executable by the processing device 177, which are effective for generating SCADA state estimates of the power network using SCADA information received from the SCADA master application 175. To name just a few examples, the state estimation application 173 may use weighted least squares, weighted least absolute value, or extended Kalman filters to generate the SCADA state estimate. Once the SCADA state estimate is generated, the application 173 timestamps it. In some embodiments, the state estimation application 173 generates SCADA state estimates every 5-15 minutes.

[0021] The Super PDC application 174 includes instructions executable by the processing device 177, which are effective for receiving phasors from each of the plurality of PDCs 120, aligning the phasors using their timestamps, and transmitting the group of aligned phasors to the cloud PDC application 183 and the data storage application 172 of the cloud computing architecture 180. In some embodiments, the Super PDC application 174 receives phasors from the plurality of PDCs 120 at a rate of 30-120 times per second.

[0022] The data storage application 172 includes instructions executable by the processing device 177, which are effective for archiving phasors received by the super PDC application 174, archiving SCADA state estimates generated by the state estimation application 173, and archiving SCADA information received by the SCADA master application 175. For example, to cite just one example, the data storage application 172 can retain six months of historical values.

[0023] Cloud computing architecture 180 is a system with scalable system resources available on demand. Cloud computing architecture 180 includes input / output devices 189, processing devices 187, and storage devices 181. In some embodiments, cloud computing architecture 180 is a virtualization platform with a cloud broker, configured to allocate scalable computing resources.

[0024] Input / output device 189 enables cloud computing architecture 180 to communicate with local control system 170. For example, to name just a few, input / output device 189 may include network adapters, network credentials, interfaces, or ports (e.g., USB ports, serial ports, parallel ports, analog ports, digital ports, VGA, DVI, HDMI, FireWire, CAT5, Ethernet, fiber optic, or any other type of port or interface). Input / output device 189 may include hardware, software, and / or firmware. It is envisioned that input / output device 189 includes more than one of these adapters, credentials, or ports, such as a first port for receiving data and a second port for transmitting data.

[0025] Processing device 187 includes multiple processing units using distributed, pipelined, or parallel processing. In the illustrated form, processing device 187 is programmable, executing an application program according to programming instructions (such as software or firmware) stored in memory device 181. Processing device 187 may include one or more components of any type suitable for processing signals received from input / output device 189 or elsewhere and providing output signals. Such components may include digital circuitry, analog circuitry, or a combination of both.

[0026] Memory device 181 is configured to store SCADA information, PMU phasors, and multiple applications, including a cloud PDC application 183, a topology inspector application 184, a hybrid state estimation application 182, and a data storage application 185. Memory device 181 can be one or more types, such as solid-state, electromagnetic, optical, or combinations thereof, to name just a few. Furthermore, memory device 181 can be volatile, non-volatile, transient, or a combination thereof, and some or all of memory devices 181 can be portable, such as disks, magnetic tapes, memory sticks, or cassette tapes, to name just a few.

[0027] The cloud PDC application 183 includes instructions executable by the processing device 187, which are effective for receiving phasors from the super PDC application 174. In some embodiments, the cloud PDC application 183 may also perform monitoring functions, such as, to name just one example, the visualization of power network events.

[0028] Topology inspector application 184 includes instructions executable by processing device 187, which are effective for determining the power network topology using PMU phasors received by cloud PDC application 183. If topology inspector application 184 detects any change in the on / off state of controllable switches in the power network, application 184 updates the power network topology and then transmits the updated power network topology to hybrid state estimation application 182. In some embodiments, topology inspector application 184 is configured to determine the power network topology by generating a new power network topology using PMU phasors. Since PMU phasors correspond to the latest measurements of the power network, the generated power network topology will reflect any updates to the on / off states of switches in the power network. In some embodiments, application 184 is configured to determine the power network topology by comparing PMU phasors with the network topology transmitted by SCADA master application 175 to determine whether any on / off states of controllable switches in the power network have changed since the most recent SCADA state estimation. For example, the zero-current phasor indicating that a circuit breaker in a distribution line has been opened indicates a change in the power network topology, where the network topology received from the SCADA master application 175 includes the circuit breaker's closed state.

[0029] In other embodiments, the topology inspector application 184 is configured to generate a network topology using the current set of PMU phasors and compare the generated network topology with a network topology generated using a previous set of phasors or a network topology transmitted by the SCADA master application 175. In response to determining the network topology based on the current set of PMU phasors, which includes updating the power network topology, the updated network topology is transmitted to the hybrid state estimation application 182. By updating the network topology using new phasors for each set of alignment, the cloud computing architecture 180 is configured to output a hybrid state estimate reflecting changes in the network topology in near real-time.

[0030] The hybrid state estimation application 182 includes instructions executable by the processing device 187, which are effective for generating a hybrid state estimate using the SCADA state estimate generated by the state estimation application 173 and a recently received set of PMU phasors received by the cloud PDC application 183, as described in more detail below.

[0031] Before performing mixed-state estimation, application 182 aligns the timestamps of the received SCADA state estimate and the most recent set of PMU phasors for use in mixed-state estimation by identifying the most recent SCADA state estimate and the most recent set of PMU phasors. Once aligned, application 182 converts any values ​​of the SCADA state estimate and synchronized phasor data, which are in polar coordinate format, to rectangular coordinate format. Once mixed-state estimation is complete, the estimated state is converted back from rectangular coordinate format to polar coordinate format.

[0032] The hybrid state estimation application 182 transmits the hybrid state estimate to the local control system 170 for use in the network control system. In some embodiments, the local control system 170 receives a new hybrid state estimate from the cloud computing architecture 180 every second or less. In some embodiments, the local control system 170 receives a new hybrid state estimate every half second or less.

[0033] The data storage application 185 includes instructions executable by the processing device 187, which are effective for archiving aligned phasor sets received from the local control system 170, archiving mixed state estimates generated by the state estimation application 182, archiving SCADA information received from the local control system 170, and archiving SCADA state estimates received from the local control system 170. As just one example, the data storage application 185 can maintain archived values ​​for one year.

[0034] The local control system 170 and the cloud computing architecture 180 communicate via an LCS / cloud communication network 190. Various communication protocols can be used to exchange data within the LCS / cloud communication network 190. For example, as a single example, a phasor data transfer protocol (also known as the IEEE C37.118 protocol) can be used to transfer synchronized phasor data from a super PDC application 174 to a cloud PDC application 183. As a single example, a file transfer protocol (FTP) can be used to transfer SCADA state estimates, mixed state estimates, SCADA information, and archived data between the local control system 170 and the cloud computing architecture 180.

[0035] refer to Figure 2 The illustration depicts an exemplary process 200 for state estimation of a power network, which is performed by an exemplary state estimation system (such as...). Figure 1 The state estimation system 100 is implemented. It should be understood that several changes and modifications to process 200 are envisioned, including, for example, omitting one or more aspects of process 200, adding further conditional clauses and operations, and / or reorganizing or separating operations and conditional clauses into separate processes.

[0036] Process 200 begins at operation 201, where a local control system, including a SCADA master station, receives SCADA information from multiple power network devices. The SCADA information may include measurements and power network topology. Measurements may include voltage, current, or power measurements. For example, measurements may include bus voltage, active power injection, reactive power injection, and line flow. The power network topology includes various on / off states of controllable switches in the power network. Power network devices may include remote terminal units (RTUs), intelligent electronic devices (IEDs), relays, sensors, or other devices configured to monitor the power network. The measurements and device statuses in the SCADA information may include timestamps, but the measurements are not synchronized with a common time source.

[0037] Process 200 proceeds to operation 203, where the state estimator of the local control system uses this set of SCADA information to generate a SCADA state estimate. To name just a few examples, the state estimator can use one of several algorithms to generate the SCADA state estimate, such as weighted least squares, weighted least absolute value, or extended Kalman filter.

[0038] Process 200 proceeds to operation 205, where the local control system transmits SCADA status estimates, and the cloud computing architecture receives the SCADA status estimates.

[0039] Process 200 proceeds to operation 207, where the cloud computing architecture receives a set of PMU phasors generated by multiple PMUs of the power network. In some embodiments, the set of PMU phasors is received at a cloud PDC of the cloud computing architecture from multiple PDCs of the power network. In some embodiments, the set of PMU phasors is received from a super PDC of the local control system, which has aggregated and aligned the set of PMU phasors from the multiple PDCs of the power network. Each PMU phasor corresponds to a voltage phasor or a current phasor. The set of PMU phasors is synchronized, and therefore each includes the same timestamp.

[0040] Process 200 proceeds to operation 209, where the cloud computing architecture aligns the timestamps of the SCADA estimate and the set of PMU phasors by identifying the most recently received SCADA estimate and the most recently received set of PMU phasors.

[0041] Process 200 proceeds to operation 211, where the cloud computing architecture uses the set of PMU phasors received at operation 207 to determine the current power network topology. In some embodiments, the cloud computing architecture uses the received set of PMU phasors to generate an updated network topology. In some embodiments, the received set of PMU phasors is compared with a previously generated network topology to detect changes in the power network. The cloud computing architecture then updates the power network topology in response to the detected changes.

[0042] Process 200 proceeds to operation 213, where the cloud computing architecture uses the determined power network topology from operation 211, the set of PMU phasors, and SCADA state estimates to generate a hybrid state estimate. In some embodiments, the cloud computing architecture generates the hybrid state estimate by performing weighted least squares state estimation using the following equation, where x is the state estimate vector, A is the function matrix, W is the hybrid weight matrix, and z hybrid It is a matrix of measured values:

[0043] x = [A T W -1 A] -1 [W -1 A]z hybrid (1)

[0044] The function matrix A includes the following values, where 1 represents the identity matrix, 1' represents the identity matrix with zeros on the diagonal, no voltage phasors are measured in 1', and C 1-4 It is a matrix that includes the line conductance and susceptance of those power lines from which current phasor measurements are received.

[0045]

[0046] z hybrid Includes the following values, where V r (1) and V i (1 (V) represents the real and imaginary components of the voltage estimation result from the SCADA estimation in rectangular coordinate format. r (2) and V i (2) These are the real and imaginary components of the voltage phasor measurements from this set of PMU phasors in rectangular coordinate format, and I r (2) and I i (2) These are the real and imaginary components of the current phasor measurements from this set of PMU phasors, presented in rectangular coordinate format.

[0047]

[0048] W includes the following: W1 is the weight matrix for SCADA state estimation, and W2 is the weight matrix for the set of PMU phasors. Each weight matrix can be determined based on the accuracy level of the sensor transmitting measurements to each PMU.

[0049]

[0050] Process 200 proceeds to operation 215, where the cloud computing architecture transmits the mixed state estimate, while the local control system receives the mixed state estimate.

[0051] Process 200 proceeds to operation 217, where the local control system uses mixed-state estimation to operate the power network. In some embodiments, the local control system may provide the mixed-state estimation to advanced EMS applications. To name just a few examples, mixed-state estimation can be used for economic dispatch, protection, and stability analysis. Because the mixed-state estimation is updated multiple times during the economic dispatch cycle, high-inertia generation systems can be given more time to prepare to provide power in the next dispatch cycle, and low-inertia generation systems (such as solar and wind-based power sources) can be controlled to respond to changes in the power network during the dispatch cycle. System operators can also use mixed-state estimation to reveal events that cannot be revealed by low-frequency SCADA state estimation, to name just a few, such as power fluctuations or inter-regional oscillations.

[0052] Process 200 proceeds to conditional statement 219, in which the local control system determines whether it is time to generate a new SCADA state estimate. For example, a new SCADA state estimate may be generated at SCADA intervals of 5-15 minutes. If it is time to generate a new SCADA state estimate, process 200 returns to operation 203, thus forming operation loop 223.

[0053] If the local control system determines that no new SCADA state estimate needs to be generated, process 200 returns to operation 207, thus forming operation loop 221. Whenever a new SCADA state estimate needs to be generated, process 200 executes loop 223. Within the SCADA interval, process 200 executes loop 221, which is effectively used to update the state estimate and network topology in near real-time.

[0054] Further written descriptions of several exemplary embodiments should now be provided. One embodiment is a method for state estimation in a power network, the method comprising: receiving a set of Supervisory Control and Data Acquisition (SCADA) information including a power network topology; generating a SCADA state estimate using the set of SCADA information; receiving a set of PMU phasors using a cloud computing architecture; aligning the timestamps of the SCADA estimate with the timestamps of the set of PMU phasors using the cloud computing architecture; determining the power network topology using the set of PMU phasors using the cloud computing architecture; generating a hybrid state estimate using the determined power network topology, the set of PMU phasors, and the SCADA state estimate using the cloud computing architecture; and transmitting the hybrid state estimate to a local control system.

[0055] In some embodiments of the foregoing method, the method includes generating a hybrid state estimate, comprising performing a weighted least squares state estimate using the following equations and matrices, where x is a state estimate vector, A is a function matrix, W is a hybrid weight matrix, and z hybrid This is a measurement matrix, where 1 represents the identity matrix, 1' represents an identity matrix with zeros on the diagonal, and no voltage phasors are measured in 1'. Furthermore, C... 1-4 It is a matrix that includes the line conductance and susceptance of those power lines from which current phasor measurements are received.

[0056] x = [A T W -1 A] -1 [W -1 A]z hybrid

[0057]

[0058] In some forms, the measurement matrix includes the following, where V r (1) and V i (1) These are the real and imaginary components of the voltage estimation result from SCADA estimation in rectangular coordinate format, V r (2) and V i (2) These are the real and imaginary components of the voltage phasor measurements from this set of PMU phasors in rectangular coordinate format, and I r (2) and I i (2) These are the real and imaginary components of the current phasor measurements from this set of PMU phasors, presented in rectangular coordinate format.

[0059]

[0060] In some forms, the set of SCADA information includes voltage measurements of the power network, and the power network topology includes the on / off states of circuit breakers in the power network. In some forms, generating the SCADA estimate is performed by the local control system. In some forms, the method includes iteratively performing the following steps: receiving a new set of PMU phasors; aligning the SCADA estimate timestamps with the timestamps of the new set of PMU phasors; using the new set of PMU phasors to determine the power network topology; using the SCADA state estimate and the new set of PMU phasors to generate an updated mixed state estimate; and transmitting the updated mixed state estimate until the local control system transmits a second SCADA state estimate to a cloud computing architecture. In some forms, the step of transmitting the updated mixed state estimate is performed at least once per second. In some forms, the step of transmitting the updated mixed state estimate is performed at least twice per second. In some forms, determining the power network topology includes detecting changes in the power network topology using the set of PMU phasors and updating the power network topology to include the detected changes. In some forms, determining the power network topology includes updating the on / off state of circuit breakers in response to comparing the set of PMU phasors with the power network topology.

[0061] Another exemplary embodiment is a state estimation system for a power network, the state estimation system comprising: a local control system configured to receive a set of Supervisory Control and Data Acquisition (SCADA) information including a power network topology, and to transmit a SCADA state estimate generated using the set of SCADA information; and a cloud computing architecture configured to: receive a set of PMU phasors; align the timestamps of the SCADA estimate with the timestamps of the set of PMU phasors; determine the power network topology using the set of PMU phasors; generate a hybrid state estimate using the determined power network topology, the set of PMU phasors, and the SCADA state estimate; and transmit the hybrid state estimate to the local control system.

[0062] In some forms of the aforementioned state estimation system, generating a hybrid state estimate involves performing a weighted least squares state estimate using the following equations and matrices, where x is the state estimation vector, A is the function matrix, W is the hybrid weight matrix, and z hybrid This is a measurement matrix, where 1 represents the identity matrix, 1' represents an identity matrix with zeros on the diagonal, and no voltage phasors are measured in 1'. Furthermore, C... 1-4 It is a matrix that includes the line conductance and susceptance of those power lines from which current phasor measurements are received.

[0063] x = [A T W -1 A] -1 [W -1 A]zhybrid

[0064]

[0065] In some forms, the measurement matrix includes the following, where V r (1) and V i (1) These are the real and imaginary components of the voltage estimation result from SCADA estimation in rectangular coordinate format, V r (2) and V i (2) These are the real and imaginary components of the voltage phasor measurements from this set of PMU phasors in rectangular coordinate format, and I r (2) and I i (2) These are the real and imaginary components of the current phasor measurements from this set of PMU phasors, presented in rectangular coordinate format.

[0066]

[0067] In some forms, the set of SCADA information includes voltage measurements of the power network, and the power network topology includes the on / off states of the power network circuit breakers. In some forms, generating the SCADA estimate is performed by the local control system. In some forms, the cloud computing architecture is configured to iteratively generate a new mixed state estimate each time the cloud computing architecture receives a new set of PMU phasors, using the new set of PMU phasors and the SCADA state estimate, until the local control system transmits a second SCADA state estimate to the cloud computing architecture. In some forms, the cloud computing architecture generates a new mixed state estimate at least once per second. In some forms, the cloud computing architecture generates a new mixed state estimate at least twice per second. In some forms, determining the power network topology includes using the set of PMU phasors to detect changes in the power network topology and updating the power network topology to include the detected changes. In some forms, determining the power network topology includes updating the on / off states of the power network circuit breakers in response to comparing the set of PMU phasors with the power network topology.

[0068] Although this disclosure has been illustrated and described in detail in the accompanying drawings and foregoing description, such illustrations and descriptions are to be considered illustrative in nature and not restrictive. It should be understood that only certain exemplary embodiments have been shown and described, and all variations and modifications within the spirit of this disclosure are intended to be protected. It should be understood that while the use of words such as “preferred,” “preferred,” “ideal,” or “more preferred” in the foregoing description indicates that the features so described may be more desirable, it may not be necessary, and embodiments lacking these words may be contemplated as being within the scope of this disclosure, defined by the appended claims. When reading the claims, it is intended that when words such as “a,” “an,” “at least one,” or “at least one part” are used, there is no intention to limit the claims to only one item unless expressly stated otherwise in the claims. The term “of…” can mean an association or connection with another item, and an attribution or connection to another item as indicated by the context in which it is used. Unless expressly indicated otherwise, the terms “linked to,” “linked with,” etc., include indirect connections and links, and further include but do not require direct links or links. When the language “at least a part” and / or “a part” is used, an item may include a part and / or the whole item unless specifically stated otherwise.

Claims

1. A method for state estimation in power networks, comprising: The local control system receives a set of Supervisory Control and Data Acquisition (SCADA) information, including the power network topology. The local control system uses the set of SCADA information to generate a SCADA state estimate. A set of phasors is received using a cloud computing architecture (180), each phasor providing voltage amplitude and voltage phase angle or current amplitude and current phase angle; The timestamps of the SCADA state estimation are aligned with the timestamps of the set of phasors using the cloud computing architecture (180); The power network topology is determined using the set of phasors in the cloud computing architecture (180); The cloud computing architecture (180) is used to generate a hybrid state estimate using the determined power network topology, the aligned set of phasors, and the SCADA state estimate; as well as The mixed state estimate is transmitted to a local control system (170), which uses the mixed state estimate to operate the power network.

2. The method according to claim 1, wherein, Generating the hybrid state estimate involves performing a weighted least squares state estimate.

3. The method according to claim 1, wherein, Generating the mixed state estimate involves performing a weighted least squares state estimate using the following equations and matrices: x=[A T W -1 A] -1 [W -1 A]z hybrid Where x is the state estimation vector, A is the function matrix, W is the mixture weight matrix, and z hybrid It is a measurement matrix, where 1 represents the identity matrix, 1' represents the identity matrix with zeros on the diagonal, no voltage phasors are measured in 1', and C1 to C4 are matrices that include the line conductance and susceptance of those power lines from which current phasor measurements are received.

4. The method according to claim 3, wherein, The measurement matrix z is defined using the following equation. hybrid : Where V r (1) and V i (1) These are the real and imaginary components of the voltage estimation result from the SCADA state estimation in rectangular coordinate format, V r (2) and V i (2) These are the real and imaginary components of the voltage phasor measurements from the set of phasors in rectangular coordinate format, and I r (2) and I i (2) These are the real and imaginary components of the current phasor measurements from the set of phasors in rectangular coordinate format.

5. The method according to any one of claims 1 to 4, wherein, The set of SCADA information includes voltage measurements of the power network, and the power network topology includes the on / off status of the circuit breakers in the power network.

6. The method according to any one of claims 1 to 4, wherein, The generation of SCADA status estimates is performed by the local control system (170).

7. The method according to any one of claims 1 to 4, comprising iteratively performing the following steps: receiving a new set of phasors, aligning the timestamps of the SCADA state estimate with the timestamps of the new set of phasors, using the new set of phasors to determine the power network topology, using the SCADA state estimate and the new set of phasors to generate an updated hybrid state estimate, and transmitting the updated hybrid state estimate until the local control system (170) transmits a second SCADA state estimate to the cloud computing architecture (180).

8. The method according to any one of claims 1 to 4, wherein, The step of transmitting updated hybrid state estimates is performed at least once per second.

9. The method according to any one of claims 1 to 4, wherein, The step of transmitting updated hybrid state estimates is performed at least twice per second.

10. The method according to any one of claims 1 to 4, wherein, Determining the power network topology includes: The set of phasors is used to detect changes in the topology of the power network and to update the power network topology to include the detected changes.

11. The method according to any one of claims 1 to 4, wherein, Determining the power network topology includes updating the on / off state of the circuit breakers in the power network topology in response to comparing the set of phasors with the power network topology.

12. The method according to any one of claims 1 to 4, wherein, Receiving the set of phasors includes: Receive a set of phasors from the phasor measurement unit (PMU) (130).

13. The method according to any one of claims 1 to 4, wherein, Receiving the set of phasors includes receiving a set of phasors from an intelligent electronic device (IED) or a protective relay.

14. A state estimation system for a power network, the state estimation system comprising: A local control system (170) is configured to receive a set of Supervisory Control and Data Acquisition (SCADA) information including a power network topology, and is configured to transmit SCADA state estimates generated using the set of SCADA information. as well as A cloud computing architecture (180) is configured to: receive a set of phasors, each phasor providing a voltage amplitude and voltage phase angle or a current amplitude and current phase angle; align the timestamp of the SCADA state estimate with the timestamp of the set of phasors; use the set of phasors to determine the power network topology; use the determined power network topology, the aligned set of phasors, and the SCADA state estimate to generate a hybrid state estimate; and transmit the hybrid state estimate to the local control system (170), wherein the local control system uses the hybrid state estimate to operate the power network.

15. The state estimation system according to claim 14, wherein, The cloud computing architecture (180) is configured to generate the hybrid state estimate by performing weighted least squares state estimation.

16. The state estimation system according to claim 14, wherein, The cloud computing architecture (180) is configured to generate the hybrid state estimate by performing weighted least squares state estimation using the following equations and matrices: x=[A T W -1 A] -1 [W -1 A]z hybrid Where x is the state estimation vector, A is the function matrix, W is the mixture weight matrix, and z hybrid It is a measurement matrix, where 1 represents the identity matrix, 1' represents the identity matrix with zeros on the diagonal, no voltage phasors are measured in 1', and C1 to C4 are matrices that include the line conductance and susceptance of those power lines from which current phasor measurements are received.

17. The state estimation system according to claim 16, wherein, The measurement matrix z is defined using the following equation. hybrid : Where V r (1) and V i (1) These are the real and imaginary components of the voltage estimation result from the SCADA state estimation in rectangular coordinate format, V r (2) and V i (2) These are the real and imaginary components of the voltage phasor measurements from the set of phasors in rectangular coordinate format, and I r (2) and I i (2) These are the real and imaginary components of the current phasor measurements from the set of phasors in rectangular coordinate format.

18. The state estimation system according to any one of claims 14 to 17, wherein, The set of SCADA information includes voltage measurements of the power network, and the power network topology includes the on / off status of the circuit breakers in the power network.

19. The state estimation system according to any one of claims 14 to 17, wherein, The local control system (170) is configured to generate the SCADA state estimate.

20. The state estimation system according to any one of claims 14 to 17, wherein, The cloud computing architecture (180) is configured to iteratively generate a new hybrid state estimate each time the cloud computing architecture (180) receives a new set of phasors and the SCADA state estimate, until the local control system (170) transmits the second SCADA state estimate to the cloud computing architecture (180).

21. The state estimation system according to any one of claims 14 to 17, wherein, The cloud computing architecture (180) generates a new hybrid state estimate at least once per second.

22. The state estimation system according to any one of claims 14 to 17, wherein, The cloud computing architecture (180) generates a new hybrid state estimate at least twice per second.

23. The state estimation system according to any one of claims 14 to 17, wherein, The cloud computing architecture (180) is configured to determine the power network topology in the following manner: The set of phasors is used to detect changes in the topology of the power network and to update the power network topology to include the detected changes.

24. The state estimation system according to any one of claims 14 to 17, wherein, The cloud computing architecture (180) is configured to determine the power network topology by updating the on / off state of the circuit breakers of the power network topology in response to comparing the set of phasors with the power network topology.

Images