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WO2009042581A1 - Indexage de stabilité en temps réel pour la surveillance d'énergie intelligente et la gestion d'un système de réseau d'alimentation électrique - Google Patents

Indexage de stabilité en temps réel pour la surveillance d'énergie intelligente et la gestion d'un système de réseau d'alimentation électrique Download PDF

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Publication number
WO2009042581A1
WO2009042581A1 PCT/US2008/077355 US2008077355W WO2009042581A1 WO 2009042581 A1 WO2009042581 A1 WO 2009042581A1 US 2008077355 W US2008077355 W US 2008077355W WO 2009042581 A1 WO2009042581 A1 WO 2009042581A1
Authority
WO
WIPO (PCT)
Prior art keywords
electrical system
electrical
real
data
recited
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Ceased
Application number
PCT/US2008/077355
Other languages
English (en)
Inventor
Adib Nasle
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Power Analytics Corp
Original Assignee
Edsa Micro Corp
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Priority claimed from US12/121,552 external-priority patent/US9557723B2/en
Application filed by Edsa Micro Corp filed Critical Edsa Micro Corp
Priority to AU2008304566A priority Critical patent/AU2008304566A1/en
Priority to EP08833071A priority patent/EP2193467A1/fr
Priority to CA2698606A priority patent/CA2698606A1/fr
Publication of WO2009042581A1 publication Critical patent/WO2009042581A1/fr
Anticipated expiration legal-status Critical
Ceased legal-status Critical Current

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Classifications

    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B23/00—Testing or monitoring of control systems or parts thereof
    • G05B23/02—Electric testing or monitoring
    • G05B23/0205—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults
    • G05B23/0259—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterized by the response to fault detection
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B15/00—Systems controlled by a computer
    • G05B15/02—Systems controlled by a computer electric
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B17/00—Systems involving the use of models or simulators of said systems
    • G05B17/02—Systems involving the use of models or simulators of said systems electric
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B23/00—Testing or monitoring of control systems or parts thereof
    • G05B23/02—Electric testing or monitoring
    • G05B23/0205—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults
    • G05B23/0218—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterised by the fault detection method dealing with either existing or incipient faults
    • G05B23/0243—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterised by the fault detection method dealing with either existing or incipient faults model based detection method, e.g. first-principles knowledge model
    • G05B23/0254—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterised by the fault detection method dealing with either existing or incipient faults model based detection method, e.g. first-principles knowledge model based on a quantitative model, e.g. mathematical relationships between inputs and outputs; functions: observer, Kalman filter, residual calculation, Neural Networks
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
    • G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
    • G05B13/04—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators
    • H02J13/1321—
    • H02J13/1323—
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02B—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO BUILDINGS, e.g. HOUSING, HOUSE APPLIANCES OR RELATED END-USER APPLICATIONS
    • Y02B90/00—Enabling technologies or technologies with a potential or indirect contribution to GHG emissions mitigation
    • Y02B90/20—Smart grids as enabling technology in buildings sector
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E60/00—Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
    • Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
    • Y02P90/80—Management or planning
    • Y02P90/82—Energy audits or management systems therefor
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
    • Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
    • Y04S10/00—Systems supporting electrical power generation, transmission or distribution
    • Y04S10/50—Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
    • Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
    • Y04S20/00—Management or operation of end-user stationary applications or the last stages of power distribution; Controlling, monitoring or operating thereof
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
    • Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
    • Y04S40/00—Systems for electrical power generation, transmission, distribution or end-user application management characterised by the use of communication or information technologies, or communication or information technology specific aspects supporting them
    • Y04S40/12—Systems for electrical power generation, transmission, distribution or end-user application management characterised by the use of communication or information technologies, or communication or information technology specific aspects supporting them characterised by data transport means between the monitoring, controlling or managing units and monitored, controlled or operated electrical equipment
    • Y04S40/124—Systems for electrical power generation, transmission, distribution or end-user application management characterised by the use of communication or information technologies, or communication or information technology specific aspects supporting them characterised by data transport means between the monitoring, controlling or managing units and monitored, controlled or operated electrical equipment using wired telecommunication networks or data transmission busses

Definitions

  • Figure 17 is a diagram illustrating an example process for predicting in real-time various parameters associated with an alternating current (AC) arc flash incident, in accordance with one embodiment.
  • AC alternating current
  • the data connection 110 is a wireless data connection.
  • sensors e.g., configuration files, etc.
  • analytics engine 118 e.g., configuration files, analytics logic, etc.
  • calibration parameters e.g., configuration files, calibration parameters, etc.
  • virtual system modeling engine 124 e.g., configuration files, simulation parameters, etc.
  • virtual system model of the system under management e.g., virtual system model operating parameters and configuration files.
  • data from those various components of the monitored system 102 can be displayed on a client 128 display panel for viewing by a system administrator or equivalent.
  • the analytics server 116 includes a variety of components.
  • the analytics server 116 is implemented in a Web-based configuration, so that the analytics server 116 includes (or communicates with) a secure web server 530 for communication with the sensor systems 519 (e.g., data acquisition units, metering devices, sensors, etc.) and external communication entities 534 (e.g., web browser, "thin client” applications, etc.).
  • a variety of user views and functions 532 are available to the client 128 such as: alarm reports, Active X controls, equipment views, view editor tool, custom user interface page, and XML parser.
  • equation 15 can then be used to determine I a d ⁇ ntsym in step 1178.
  • FIG. 19 is a flow chart illustrating an example process for conducting a realtime power capacity assessment of an electrical power distribution and transmission system, in accordance with one embodiment.
  • the stability of an electrical power system can be classified into two broad categories: transient (angular) stability and voltage stability (i.e., power capacity).
  • Voltage stability refers to the electrical system's ability to maintain acceptable voltage profiles under different system topologies and load changes (i.e., contingency events). That is, voltage stability analyses determine bus voltage profiles and power flows in the electrical system before, during, and immediately after a major disturbance.
  • voltage instability stems from the attempt of load dynamics to restore power consumption beyond the capability of the combined transmission and generation system.
  • One factor that comes into play is that unlike active power, reactive power cannot be transported over long distances. As such, a power system rich in reactive power resources is less likely to experience voltage stability problems. Overall, the voltage stability of a power system is of paramount importance in the planning and daily operation of an electrical system.
  • Examples of a monitored system includes machinery, factories, electrical systems, processing plants, devices, chemical processes, biological systems, data centers, aircraft carriers, and the like. It should be understood that the monitored system can be any combination of components whose operations can be monitored with conventional sensors and where each component interacts with or is related to at least one other component within the combination.
  • the associative memory layer observes the interactions between the neocortical model 2202 and the real-time sensory inputs from the sensory layer 2204 to learn and understand complex relationships inherent within the monitored system. As the neocortical model 2202 matures over time, the neocortical catalyst process becomes increasingly accurate in making predictions about the operational aspects of the monitored system. This combination of the neocortical model 2202, sensory layer 2204 and associative memory model layer 2206 works together to learn, refine, suggest and predict similarly to how the human neocortex operates.
  • Figure 23 is an example process for real-time three-dimensional (3D) visualization of the health, reliability, and performance of an electrical system, in accordance with one embodiment.
  • 3D three-dimensional
  • the operating mode(s) can relate to the multiple load levels that the electrical system operates under. That is, the virtual system model of the electrical system can be simulated under various power system load configurations or capacity conditions.
  • the system is simulated as operating under a base load power configuration. That is, the electrical system can be simulated as operating continuously at its maximum rated power output. Under this configuration, power systems only shut down to perform maintenance or if something breaks. Accordingly, the ability to test under such conditions cannot be achieved in conventional systems.
  • the electrical system can be simulated as operating under a load following power configuration. That is, the electrical system is simulated as operating in a fluctuating manner by adjusting its power output as demand for electricity fluctuates throughout the day.
  • the electrical system is simulated as operating at various different power load capacity levels. For example, the electrical system may be simulated as operating at 10%, 25%, 50%, 75%, or 100% of its rated power generation capacity.
  • the 3D visualization engine 2402 is interfaced with the predictive elements of the power analytics server and communicatively connected to the data acquisition hub 112 and the client 128.
  • the data acquisition hub 112 is communicatively connected via data connections 110 to a plurality of sensors that are embedded throughout the electrical system 102.
  • the data acquisition hub 112 may be a standalone unit or integrated within the analytics server 116 and can be embodied as a piece of hardware, software, or some combination thereof.
  • the data connections 110 are "hard wired" physical data connections (e.g., serial, network, etc.).
  • the data from the various components of the electrical system and the real-time predictions (forecasts) about the health, performance, reliability and availability of the electrical system can be displayed on a client 128 display panel for viewing by a system administrator or equivalent.
  • the data may be summarized in a hard copy report 2404.
  • MOVs motor operated valves
  • a user-defined model type for each mode may be provided.
  • start may be modeled as a constant current
  • full speed may be modeled by constant power.
  • the modeling for the opening mode may be the same as modeling for the closing mode;
  • the understanding of stability trajectories may be automated, and their relevance to overall power system stability. For example, power system security may no longer be dependent upon the sole judgment of an individual user, but now may be automated.
  • the Transient Stability Modeling Engine 3002 can be configured to process the real-time data output, the predicted data output, historical data output and forecasted aspects about the operation of the electrical system 102 to generate a user interface that can convey system security index values of the electrical system 102 to a user (i.e., electrical system 102 owner/system administrator/operator).
  • the system security index values can be the real-time operational performance of the individual components of the electrical system 102.
  • the operational state can be the predicted operational performance of the electrical system 102.
  • the operational state can be a historical data trending display of the historical operational performance of the electrical system 102.

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  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Automation & Control Theory (AREA)
  • Business, Economics & Management (AREA)
  • Human Resources & Organizations (AREA)
  • Economics (AREA)
  • Strategic Management (AREA)
  • Entrepreneurship & Innovation (AREA)
  • Marketing (AREA)
  • General Business, Economics & Management (AREA)
  • Educational Administration (AREA)
  • Development Economics (AREA)
  • Operations Research (AREA)
  • Quality & Reliability (AREA)
  • Tourism & Hospitality (AREA)
  • Game Theory and Decision Science (AREA)
  • Theoretical Computer Science (AREA)
  • Artificial Intelligence (AREA)
  • Evolutionary Computation (AREA)
  • Mathematical Physics (AREA)
  • General Engineering & Computer Science (AREA)
  • Testing And Monitoring For Control Systems (AREA)
  • Remote Monitoring And Control Of Power-Distribution Networks (AREA)

Abstract

La présente invention concerne un système et un procédé de surveillance intelligente et de gestion d'un système électrique. Le système comprend un composant d'acquisition de données, un serveur analytique d'alimentation et un terminal client. Le composant d'acquisition de données acquiert une sortie de données en temps réel du système électrique. Le serveur analytique d'alimentation est composé d'un moteur d'index de sécurité de système électrique en temps réel qui calcule des valeurs d'index de sécurité de système en temps réel à partir de données d'indice de stabilité générées depuis un modèle de système virtuel du système électrique. Le terminal client affiche les valeurs d'index de sécurité de système pour évaluer la sécurité et la stabilité du système électrique.
PCT/US2008/077355 2007-09-24 2008-09-23 Indexage de stabilité en temps réel pour la surveillance d'énergie intelligente et la gestion d'un système de réseau d'alimentation électrique Ceased WO2009042581A1 (fr)

Priority Applications (3)

Application Number Priority Date Filing Date Title
AU2008304566A AU2008304566A1 (en) 2007-09-24 2008-09-23 Real-time stability indexing for intelligent energy monitoring and management of electrical power network system
EP08833071A EP2193467A1 (fr) 2007-09-24 2008-09-23 Indexage de stabilité en temps réel pour la surveillance d'énergie intelligente et la gestion d'un système de réseau d'alimentation électrique
CA2698606A CA2698606A1 (fr) 2007-09-24 2008-09-23 Indexage de stabilite en temps reel pour la surveillance d'energie intelligente et la gestion d'un systeme de reseau d'alimentation electrique

Applications Claiming Priority (4)

Application Number Priority Date Filing Date Title
US97464907P 2007-09-24 2007-09-24
US60/974,649 2007-09-24
US12/121,552 2008-05-15
US12/121,552 US9557723B2 (en) 2006-07-19 2008-05-15 Real-time predictive systems for intelligent energy monitoring and management of electrical power networks

Publications (1)

Publication Number Publication Date
WO2009042581A1 true WO2009042581A1 (fr) 2009-04-02

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PCT/US2008/077355 Ceased WO2009042581A1 (fr) 2007-09-24 2008-09-23 Indexage de stabilité en temps réel pour la surveillance d'énergie intelligente et la gestion d'un système de réseau d'alimentation électrique

Country Status (4)

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EP (1) EP2193467A1 (fr)
AU (1) AU2008304566A1 (fr)
CA (1) CA2698606A1 (fr)
WO (1) WO2009042581A1 (fr)

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EP2299346A1 (fr) * 2009-09-18 2011-03-23 General Electric Company Systèmes, procédés et appareil de surveillance et de contrôle d'une machine à éolienne
WO2011140369A1 (fr) * 2010-05-05 2011-11-10 Greensleeves, LLC Châssis d'énergie et dispositif d'échange d'énergie
EP2607690A1 (fr) * 2011-12-22 2013-06-26 Siemens Aktiengesellschaft Système de commande de parc éolien
EP2779052A1 (fr) * 2013-03-15 2014-09-17 Rockwell Automation Technologies, Inc. Systèmes et procédés de mise à jour de valeurs de confiance avec des informations sur l'énergie associées à un système d'automatisation industrielle
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CN111208384A (zh) * 2018-11-19 2020-05-29 中国电力科学研究院有限公司 一种智能电网管理系统
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CN114999095A (zh) * 2022-05-23 2022-09-02 山东建筑大学 基于时间和空间融合的建筑电气火灾监测方法及系统
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WO2010118760A1 (fr) * 2009-04-17 2010-10-21 Nec Europe Ltd. Procédé et système pour la surveillance de la consommation d'énergie dans un environnement ict
EP2299346A1 (fr) * 2009-09-18 2011-03-23 General Electric Company Systèmes, procédés et appareil de surveillance et de contrôle d'une machine à éolienne
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