WO2014152408A2 - Electric power system control with planning of energy demand and energy efficiency using ami-based data analysis - Google Patents

Electric power system control with planning of energy demand and energy efficiency using ami-based data analysis Download PDF

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Publication number
WO2014152408A2
WO2014152408A2 PCT/US2014/027310 US2014027310W WO2014152408A2 WO 2014152408 A2 WO2014152408 A2 WO 2014152408A2 US 2014027310 W US2014027310 W US 2014027310W WO 2014152408 A2 WO2014152408 A2 WO 2014152408A2
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WO
WIPO (PCT)
Prior art keywords
voltage
energy
conservation
electric power
meter
Prior art date
Application number
PCT/US2014/027310
Other languages
English (en)
French (fr)
Other versions
WO2014152408A3 (en
Inventor
Melissa A. PESKIN
Phillip W. Powell
Original Assignee
Dominion Resources, Inc.
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
Application filed by Dominion Resources, Inc. filed Critical Dominion Resources, Inc.
Priority to KR1020157029528A priority Critical patent/KR20150132469A/ko
Priority to AU2014239865A priority patent/AU2014239865A1/en
Priority to MX2015011547A priority patent/MX2015011547A/es
Priority to CN201480015451.0A priority patent/CN105122169A/zh
Priority to EP14769578.7A priority patent/EP2972643A4/en
Priority to JP2016502402A priority patent/JP2016517685A/ja
Priority to BR112015022540A priority patent/BR112015022540A2/pt
Priority to CA2905075A priority patent/CA2905075A1/en
Publication of WO2014152408A2 publication Critical patent/WO2014152408A2/en
Priority to IL240647A priority patent/IL240647A0/he
Publication of WO2014152408A3 publication Critical patent/WO2014152408A3/en

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Classifications

    • HELECTRICITY
    • H02GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02JCIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00Circuit arrangements for ac mains or ac distribution networks
    • HELECTRICITY
    • H02GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02JCIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J13/00Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
    • H02J13/00006Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network characterised by information or instructions transport means between the monitoring, controlling or managing units and monitored, controlled or operated power network element or electrical equipment
    • H02J13/00016Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network characterised by information or instructions transport means between the monitoring, controlling or managing units and monitored, controlled or operated power network element or electrical equipment using a wired telecommunication network or a data transmission bus
    • H02J13/00017Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network characterised by information or instructions transport means between the monitoring, controlling or managing units and monitored, controlled or operated power network element or electrical equipment using a wired telecommunication network or a data transmission bus using optical fiber
    • HELECTRICITY
    • H02GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02JCIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J13/00Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
    • H02J13/00006Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network characterised by information or instructions transport means between the monitoring, controlling or managing units and monitored, controlled or operated power network element or electrical equipment
    • H02J13/00028Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network characterised by information or instructions transport means between the monitoring, controlling or managing units and monitored, controlled or operated power network element or electrical equipment involving the use of Internet protocols
    • HELECTRICITY
    • H02GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02JCIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J13/00Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
    • H02J13/00032Systems characterised by the controlled or operated power network elements or equipment, the power network elements or equipment not otherwise provided for
    • H02J13/00034Systems characterised by the controlled or operated power network elements or equipment, the power network elements or equipment not otherwise provided for the elements or equipment being or involving an electric power substation
    • HELECTRICITY
    • H02GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02JCIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00Circuit arrangements for ac mains or ac distribution networks
    • H02J3/12Circuit arrangements for ac mains or ac distribution networks for adjusting voltage in ac networks by changing a characteristic of the network load
    • HELECTRICITY
    • H02GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02JCIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2203/00Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
    • H02J2203/20Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
    • YGENERAL 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
    • Y02TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02EREDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E40/00Technologies for an efficient electrical power generation, transmission or distribution
    • Y02E40/70Smart grids as climate change mitigation technology in the energy generation sector
    • YGENERAL 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
    • Y02TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02EREDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E60/00Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation
    • YGENERAL 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
    • Y04INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
    • Y04SSYSTEMS 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
    • Y04S10/00Systems supporting electrical power generation, transmission or distribution
    • Y04S10/50Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications
    • YGENERAL 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
    • Y04INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
    • Y04SSYSTEMS 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
    • Y04S40/00Systems 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
    • Y04S40/12Systems 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
    • Y04S40/124Systems 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
    • YGENERAL 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
    • Y04INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
    • Y04SSYSTEMS 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
    • Y04S40/00Systems 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
    • Y04S40/20Information technology specific aspects, e.g. CAD, simulation, modelling, system security

Definitions

  • the present disclosure relates to a method, an apparatus, a system and a computer program for controlling an electric power system, including planning the distribution circuits with respect to optimizing voltage, conserving energy, and reducing demand. More particularly, the disclosure relates to an implementation of planning electrical demand and energy efficiency, using advanced metering infrastructure ("AMI")-based data analysis.
  • AMI advanced metering infrastructure
  • This method enables the direct determination of the capability of a circuit to reduce energy usage and electrical demand based on an implementation of proposed configuration changes of an electric power system.
  • the method may be used to accurately quantify a projection of the value of the energy efficiency and electrical demand reduction savings resulting from implementation of proposed modifications in an electric power system and compare a cost/benefit of each proposed modification.
  • this method is capable of using the AMI-based measurements to identify specific problems with the electric power system, allowing the operation of the electric power system to be appropriately modified based on the identification of these problems.
  • Electricity is commonly generated at a power station by electromechanical generators, which are typically driven by heat engines fueled by chemical combustion or nuclear fission, or driven by kinetic energy flowing from water or wind.
  • the electricity is generally supplied to end users through transmission grids as an alternating current signal.
  • the transmission grids may include a network of power stations, transmission circuits, substations, and the like.
  • the generated electricity is typically stepped-up in voltage using, for example, generating step-up transformers, before supplying the electricity to a transmission system. Stepping up the voltage improves transmission efficiency by reducing the electrical current flowing in the transmission system conductors, while keeping the power transmitted nearly equal to the power input.
  • the stepped-up voltage electricity is then transmitted through the transmission system to a distribution system, which distributes the electricity to end users.
  • the distribution system may include a network that carries electricity from the transmission system and delivering it to end users.
  • the network may include medium- voltage (for example, less than 69k V) power lines, electrical substations, transformers, low-voltage (for example, less than lkV) distribution wiring, electric meters, and the like.
  • ADVANCED METERING INFRASTRUCTURE AND SUBSTATION CENTRALIZED VOLTAGE CONTROL describe a voltage control and energy conservation system for an electric power transmission and distribution grid configured to supply electric power to a plurality of user locations.
  • Various embodiments described herein provide a novel method, apparatus, system and computer program for controlling an electric power system, including implementation of voltage planning for electrical energy delivery systems (EEDS) using secondary voltages measured by advanced metering infrastructure (AMI) ('AMI-based measurements”).
  • the AMI-based measurements and voltage planning may be used to optimize the energy efficiency and demand reduction capability of the EEDS, including that specifically obtained from implementing conservation voltage reduction (CVR) in the EEDS.
  • CVR conservation voltage reduction
  • the AMI-based measurements and voltage planning may also be used to improve the reliability of the voltage performance for the energy usage system (EUS) and energy usage devices (EUD) attached to the electrical energy distribution connection system (EEDCS).
  • the energy planning process projects the voltage range capability of a given electrical energy delivery system (EEDS) (made up of an energy supply system (ESS) that connects electrically via the electrical energy distribution connection system (EEDCS) to one or more energy usage systems (EUS)) at the customer secondary level (the EUS) by measuring the level of change in energy usage from voltage management for the EEDS.
  • the EPP can also determine potential impacts of proposed modifications to the equipment and/or equipment configuration of the EEDS and/or to an energy usage device (EUD) at some electrical point(s) on an electrical energy delivery system (EEDS) made up of many energy usage devices randomly using energy at any given time during the measurement.
  • EUD energy usage device
  • the purpose of the energy validation process is to measure the level of change in energy usage for the EEDS for a change in voltage level.
  • the specifics of an example EVP are covered in co-pending U.S. patent application nos. 61/789085 and 14/193,980, entitled ELECTRIC POWER SYSTEM CONTROL WITH MEASUREMENT OF ENERGY DEMAND AND ENERGY EFFICIENCY USING T - DISTRIBUTIONS.("the co-pending /P006 application”), the entirety of which are incorporated herein, although other EVPs may also be used.
  • One purpose of the EPP system of the disclosed embodiments is to estimate the capability of the EEDS to accommodate voltage change and predict the level of change available.
  • the potential savings in energy provided by the proposed modification to the system can be calculated by multiplying the CVR factor (% change in energy/% change in voltage) (as may be calculated by the EVP, an example of which is described in the co-pending /P006 application, although other methods of calculating a CVR factor may also be used) by the available change in voltage (as determined by the EPP) to determine the available energy and demand savings over the time interval being studied.
  • the electrical energy supply to the electrical energy delivery system (EEDS) is measured in watts, kilowatts (kw), or Megawatts (Mw) (a) at the supply point of the ESS and (b) at the energy user system (EUS) or meter point. This measurement records the average usage of energy (AUE) at each of the supply and meter points over set time periods such as one hour.
  • the test for energy use improvement is divided into two basic time periods: The first is the time period when the improvement is not included, i.e., in "OFF" state. The second time period is when the improvement is included, i.e., in "ON” state. Two variables must be determined to estimate the savings capability for a
  • the CVR factor an example calculation of which is described in the co-pending /P006 application, although other methods of calculating a CVR factor may also be used.
  • the calculation of the change in voltage capability is the novel approach to conservation voltage reduction planning using a novel characterization of the EEDS voltage relationships that does not require a detailed loadflow model to implement.
  • the input levels to the EEDCS from the ESS are recorded at set intervals, such as one hour periods for the time being studied.
  • the input levels to the EUS from the EEDCS, at the same intervals for the time being studied, are measured using the AMI system and recorded.
  • the EEDS specific relationship between the ESS measurements and the EUS usage measurements is characterized using a linear regression technique over the study period. This calculation specifically relates the effects of changes in load at the ESS to change in voltage uniquely to each customer EUS using a common methodology.
  • the model can be used to apply simple linear optimization to determine the best method of improving the EEDS to meet the desired energy modification.
  • this method can optimize the cost/benefit of modifications allowing the user to select the best choice of
  • the energy planning process can be used to take the AMI data from multiple AMI EUS points and build a linear model of the voltage using the linearization technique.
  • These multiple point models can be used to predict voltage behavior for a larger radial system (e.g., a group of contiguous transmission elements that emanate from a single point of connection) by relating the larger system linear characteristics to the system modification of capacitor installation, regulator installation, and impedance modifications to allow the building of a simple linear model of the voltage
  • the energy planning process can be used to take the AMI data from multiple AMI EUS points and multiple ESS points and build a linear model of the voltage using the linearization technique.
  • EPP energy planning process
  • These multiple ESS and EUS point models can be used to predict voltage behavior for a larger radial system by relating the larger system linear characteristics to the system modification of capacitor installation, regulator installation, and impedance modifications to allow the building of a simple linear model of the voltage characteristics with multiple modifications made.
  • the new model representing the modifications the optimization can optimize the cost/benefit of various
  • the energy planning process can be used to take the AMI data from multiple AMI EUS points and multiple ESS points and build a linear model of the voltage using the linearization technique.
  • the linear model that exists for normal operation can be determined based on the characteristics of the linearization.
  • the other EUS points on the EEDS can be filtered to determine the ones, if any, that are displaying abnormal behavior characteristics and the abnormal EUS points can be compared against a list of expected characteristics denoting specific abnormal behavior that represents the potential of low reliability performance.
  • the characteristics of a poorly connected meter base has been characterized to have certain linear characteristics in the model.
  • the observed linear characteristics that represent this abnormal condition can be used to identify any of the EUS meters that exhibit this behavior, using the voltage data from AMI. This allows resolution of the abnormality before customer equipment failure occurs and significantly improves the reliability of the EEDS.
  • the energy planning process can be used to take the AMI data from multiple AMI EUS points and multiple ESS points and build a linear model of the voltage using the linearization technique. Using this model and the measured AMI data the EPP can be used to project the initial group of meters that can be used in the voltage management system to control the minimum level of voltage across the EEDS for implementation of CVR.
  • the energy planning process can be used to take the AMI data from multiple AMI EUS points and multiple ESS points and build a linear model of the voltage using the linearization technique.
  • the voltage data can be used to provide location information about the meter connection points on the circuit using voltage correlation analysis. This method matches the voltages by magnitude and by phase using a technique that uses the voltage data for each meter to provide the statistical analysis. Common phase voltage movement is correlated and common voltage movement by circuit is identified using linear regression techniques. This information when combined with the latitude and longitude information on the meter can provide specific connectivity checks for primary based applications such as outage management and DMS real-time models.
  • FIG. 1 shows an example of an EEDS made up of an electricity generation and distribution system connected to customer loads, according to principles of the disclosure
  • FIG. 2 shows an example of a voltage control and conservation (VCC) system being measured at the ESS meter point, the EUS made up of Advanced Metering Infrastructure (AMI) measuring voltage and energy, and the control system VCC and an EPP according to the principles of the disclosure;
  • VCC voltage control and conservation
  • AMI Advanced Metering Infrastructure
  • FIG. 3 shows an example of an EEDS made up of an EES, an EEDCS and multiple EUS, and outlines the methods of determining losses in the EEDCS and the EUS associated with voltage conservation control (VCC), according to principles of the disclosure;
  • VCC voltage conservation control
  • FIG. 4 shows an example of an Energy Planning Process (EPP) system with metering points (AMI) used in analysis, including the systems that affect voltage control as well as the devices or equipment that can be modified to change the EEDS performance according to principles of the disclosure;
  • EPP Energy Planning Process
  • AMI metering points
  • FIG. 5 shows a distribution system example of how the ESS data is correlated with the EUS data using linear regression to build the simple linear model of the voltage behavior of a EEDCS and customer loads, according to principles of the disclosure
  • FIG. 6 shows a distribution system example of how the primary system is modeled to determine the change in linear system characteristics that are developed for specific modifications to the connection equipment and voltage control equipment, according to principles of the disclosure
  • FIG. 7 shows an example of voltage data for an EEDCS for one set of
  • FIG. 8 shows an example of the results of the linear regression analysis of the example data from FIG. 7, according to the principles of the disclosure.
  • FIG. 9 shows an example of the results of the linear regression analysis histograms of the example data from FIG. 7, according to the principles of the disclosure.
  • FIG. 10 shows an example of the results of the linear regression analysis histograms of the example data from FIG. 7, according to the principles of the disclosure
  • FIG. 11 shows an example of an Energy Planning Process (EPP) map of the planning process for controlling voltage, according to the principles of the disclosure
  • FIG. 12 shows an example of a histogram of the EUS AMI voltage data used to identify the voltage outliers for developing modification plans for the EEDS, according to principles of the disclosure
  • FIG. 13 shows a distribution circuit example of an application that maps the EUS AMI data to a circuit one line diagram for use by the planners to develop circuit modifications with their existing circuit planning software, according to principles of the disclosure;
  • FIG. 14 shows a distribution circuit example of a mapping of the AMI voltage points to specific zones and blocks to match up with specific control devices on the EEDS, according to principles of the disclosure.
  • FIG. 15 shows an example of a summary chart for the example circuit shown in FIG. 14 that has been processed through the EPP to produce the selection of the initial meters for each block, according to principles of the disclosure.
  • a "computer”, as used in this disclosure, means any machine, device, circuit, component, or module, or any system of machines, devices, circuits, components, modules, or the like, which are capable of manipulating data according to one or more instructions, such as, for example, without limitation, a processor, a microprocessor, a central processing unit, a general purpose computer, a super computer, a personal computer, a laptop computer, a palmtop computer, a notebook computer, a desktop computer, a workstation computer, a server, or the like, or an array of processors, microprocessors, central processing units, general purpose computers, super computers, personal computers, laptop computers, palmtop computers, notebook computers, desktop computers, workstation computers, servers, or the like.
  • a "server”, as used in this disclosure, means any combination of software and/or hardware, including at least one application and/or at least one computer to perform services for connected clients as part of a client-server architecture.
  • the at least one server application may include, but is not limited to, for example, an application program that can accept connections to service requests from clients by sending back responses to the clients.
  • the server may be configured to run the at least one application, often under heavy workloads, unattended, for extended periods of time with minimal human direction.
  • the server may include a plurality of computers configured, with the at least one application being divided among the computers depending upon the workload. For example, under light loading, the at least one application can run on a single computer. However, under heavy loading, multiple computers may be required to run the at least one application.
  • the server, or any if its computers, may also be used as a workstation.
  • a “database”, as used in this disclosure, means any combination of software and/or hardware, including at least one application and/or at least one computer.
  • the database may include a structured collection of records or data organized according to a database model, such as, for example, but not limited to at least one of a relational model, a hierarchical model, a network model or the like.
  • the database may include a database management system application (DBMS) as is known in the art.
  • At least one application may include, but is not limited to, for example, an application program that can accept connections to service requests from clients by sending back responses to the clients.
  • the database may be configured to run the at least one application, often under heavy workloads, unattended, for extended periods of time with minimal human direction.
  • a “communication link”, as used in this disclosure, means a wired and/or wireless medium that conveys data or information between at least two points.
  • the wired or wireless medium may include, for example, a metallic conductor link, a radio frequency (RF) communication link, an Infrared (IR) communication link, an optical communication link, or the like, without limitation.
  • the RF communication link may include, for example, WiFi, WiMAX, IEEE 802.11, DECT, 0G, 1G, 2G, 3G or 4G cellular standards, Bluetooth, and the like.
  • Devices that are in communication with each other need not be in continuous communication with each other, unless expressly specified otherwise.
  • devices that are in communication with each other may communicate directly or indirectly through one or more intermediaries.
  • a "computer-readable medium”, as used in this disclosure, means any medium that participates in providing data (for example, instructions) which may be read by a computer. Such a medium may take many forms, including non-volatile media, volatile media, and transmission media. Non- volatile media may include, for example, optical or magnetic disks and other persistent memory. Volatile media may include dynamic random access memory (DRAM). Transmission media may include coaxial cables, copper wire and fiber optics, including the wires that comprise a system bus coupled to the processor. Transmission media may include or convey acoustic waves, light waves and electromagnetic emissions, such as those generated during radio frequency (RF) and infrared (IR) data communications.
  • RF radio frequency
  • IR infrared
  • Computer-readable media include, for example, a floppy disk, a flexible disk, hard disk, magnetic tape, any other magnetic medium, a CD-ROM, DVD, any other optical medium, punch cards, paper tape, any other physical medium with patterns of holes, a RAM, a PROM, an EPROM, a FLASH-EEPROM, any other memory chip or cartridge, a carrier wave as described hereinafter, or any other medium from which a computer can read.
  • sequences of instruction may be delivered from a RAM to a processor, (ii) may be carried over a wireless transmission medium, and/or (iii) may be formatted according to numerous formats, standards or protocols, including, for example, WiFi, WiMAX, IEEE 802.1 1, DECT, 0G, 1G, 2G, 3G or 4G cellular standards, Bluetooth, or the like.
  • an energy planning process (EPP) system 1700 (shown in FIG. 2) is provided.
  • the EPP system 1700 performs the planning functions of the disclosed embodiments, and is described in more detail below.
  • a voltage control and conservation (VCC) system 200 may also be provided, which includes three subsystems, including an energy delivery (ED) system 300, an energy control (EC) system 400 and an energy regulation (ER) system 500.
  • the VCC system 200 is configured to monitor energy usage at the ED system 300 and determine one or more energy delivery parameters at the EC system (or voltage controller) 400.
  • the EC system 400 may then provide the one or more energy delivery parameters C ED to the ER system 500 to adjust the energy delivered to a plurality of users for maximum energy conservation.
  • the EVP system 600 is used to monitor the change in EEDS energy from the VCC system 200.
  • the EVP system 600 monitors through communications link 610 all metered energy flow and determines the change in energy resulting from a change in voltage control at the ER system 500.
  • the EVP system 600 also reads weather data information through a communication link 620 from an appropriate weather station 640 to execute the EVP process 630.
  • An example EVP system 600 is more fully described in the co-pending /P006 application, although other EVPs can also be used.
  • the EPP system 1700 reads the historical databases 470 via
  • the EPP system 1700 can process this historical data along with measured AMI data to identify problems, if any, on the EEDS system 700.
  • the EPP system 1700 is also able to identify any outlier points in the analysis caused by proposed system modifications and to identify the initial meters to be used for monitoring by VCC system 200 until the adaptive process (discussed in the 2013/0030591 publication) is initiated by the control system.
  • the VCC system 200 is also configured to monitor via communication link 610 energy change data from EVP system 600 and determine one or more energy delivery parameters at the EC system (or voltage controller) 400.
  • the EC system 400 may then provide the one or more energy delivery parameters C ED to the ER system 500 to adjust the energy delivered to a plurality of users for maximum energy conservation.
  • the EC system 400 may use the energy change data to control the EEDS 700 in other ways. For example, components of the EEDS 700 may be modified, adjusted, added or deleted, including the addition of capacitor banks, modification of voltage regulators, changes to end-user equipment to modify customer efficiency, and other control actions.
  • the VCC system 200 may be integrated into, for example, an existing load curtailment plan of an electrical power supply system.
  • the electrical power supply system may include an emergency voltage reduction plan, which may be activated when one or more predetermined events are triggered.
  • the predetermined events may include, for example, an emergency, an overheating of electrical conductors, when the electrical power output from the transformer exceeds, for example, 80% of its power rating, or the like.
  • the VCC system 200 is configured to yield to the load curtailment plan when the one or more predetermined events are triggered, allowing the load curtailment plan to be executed to reduce the voltage of the electrical power supplied to the plurality of users.
  • FIG. 1 is similar to FIG.
  • the electricity generation and distribution system 100 includes an electrical power generating station 1 10, a generating step-up transformer 120, a substation 130, a plurality of step-down transformers 140, 165, 167, and users 150, 160.
  • the electrical power generating station 1 10 generates electrical power that is supplied to the step-up transformer 120.
  • the step-up transformer steps-up the voltage of the electrical power and supplies the stepped-up electrical power to an electrical transmission media 125.
  • the ESS 800 includes the station 1 10, the step-up transformer 120, the substation 130, the step- down transformers 140, 165, 167, the ER 500 as described herein, and the electrical transmission media, including media 125, for transmitting the power from the station 1 10 to users 150, 160.
  • the EUS 900 includes the ED 300 system as described herein, and a number of energy usage devices (EUD) 920 that may be consumers of power, or loads, including customer equipment and the like.
  • the EEDCS system 1000 includes transmission media, including media 135, connections and any other equipment located between the ESS 800 and the EUS 900.
  • the electrical transmission media may include wire conductors, which may be carried above ground by, for example, utility poles 127, 137 and/or underground by, for example, shielded conductors (not shown).
  • the electrical power is supplied from the step-up transformer 120 to the substation 130 as electrical power E / réelle(t), where the electrical power E / perhaps in MegaWatts (MW) may vary as a function of time t.
  • the substation 130 converts the received electrical power E / perhaps(t) to E S uppiy(t) and supplies the converted electrical power ⁇ 5 ⁇ ⁇ ( ⁇ ) to the plurality of users 150, 160.
  • the substation 130 may adjustably transform the voltage component V / réelle(t) of the received electrical power E / perhaps(t) by, for example, stepping- down the voltage before supplying the electrical power Es upp i y (t) to the users 150, 160.
  • the electrical power E Supp iy(t) supplied from the substation 130 may be received by the step-down transformers 140, 165, 167 and supplied to the users 150, 160 through a transmission medium 142, 162, such as, for example, but not limited to, underground electrical conductors (and/or above ground electrical conductors).
  • Each of the users 150, 160 may include an Advanced Meter Infrastructure (AMI) 330.
  • the AMI 330 may be coupled to a Regional Operations Center (ROC) 180.
  • the ROC 180 may be coupled to the AMI 330, by means of a plurality of communication links 175, 184, 188, a network 170 and/or a wireless communication system 190.
  • the wireless communication system 190 may include, but is not limited to, for example, an RF transceiver, a satellite transceiver, and/or the like.
  • the network 170 may include, for example, at least one of the Internet, a local area network (LAN), a wide area network (WAN), a metropolitan area network (MAN), a personal area network (PAN), a campus area network, a corporate area network, the electrical transmission media 125, 135 and transformers 140, 165, 167, a global area network (GAN), a broadband area network (BAN), or the like, any of which may be configured to communicate data via a wireless and/or a wired communication medium.
  • the network 170 may be configured to include a network topology such as, for example, a ring, a mesh, a line, a tree, a star, a bus, a full connection, or the like.
  • the AMI 330 may include any one or more of the following: A smart meter; a network interface (for example, a WAN interface, or the like); firmware; software; hardware; and the like.
  • the AMI may be configured to determine any one or more of the following: kilo-Watt-hours (kWh) delivered; kWh received; kWh delivered plus kWh received; kWh delivered minus kWh received; interval data; demand data; voltage; current; phase; and the like. If the AMI is a three phase meter, then the low phase voltage may be used in the average calculation, or the values for each phase may be used independently. If the meter is a single phase meter, then the single voltage component will be averaged.
  • the AMI 330 may further include one or more collectors 350 (shown in FIG. 2) configured to collect AMI data from one or more AMIs 330 tasked with, for example, measuring and reporting electric power delivery and consumption at one or more of the users 150, 160.
  • the one or more collectors may be located external to the users 150, 160, such as, for example, in a housing holding the step-down transformers 140, 165, 167.
  • Each of the collectors may be configured to communicate with the ROC 180.
  • the VCC system 200 plugs into the DMS and AMI systems to execute the voltage control function.
  • the EVP system 600 collects weather data and uses the AMI data from the ESS system 800 to calculate the energy savings level achieved by the VCC system 200.
  • the EPP system 1700 provides a process to continually improve the performance of the EEDS by periodically reviewing the historical AMI voltage data and providing identification of problem EUS voltage performance and the modifications needed to increase the efficiency and reliability of the EEDS system 700, using the VCC system 200.
  • FIG. 2 shows an example of the VCC system 200 with the EVP system 600 monitoring the change in energy resulting from the VCC controlling the EEDS in the more efficient lower 5% band of voltage, according to principles of the disclosure.
  • the VCC system 200 includes the ED system 300, the EC system 400 and the ER system 500, each of which is shown as a broken-line ellipse.
  • the VCC system 200 is configured to monitor energy usage at the ED system 300.
  • the ED system 300 monitors energy usage at one or more users 150, 160 (shown in FIG. 1) and sends energy usage information to the EC system 400.
  • the EC system 400 processes the energy usage information and generates one or more energy delivery parameters C ED , which it sends to the ER system 500 via communication link 430.
  • the ER system 500 receives the one or more energy delivery parameters C ED and adjusts the electrical power supplied to the users 150, 160 based on the received energy delivery parameters C ED -
  • the EVP system 600 receives the weather data and the energy usage data and calculates the energy usage improvement from the VCC 200.
  • the VCC system 200 minimizes power system losses, reduces user energy consumption and provides precise user voltage control.
  • the VCC system 200 may include a closed loop process control application that uses user voltage data provided by the ED system 300 to control, for example, a voltage set point Vsp on a distribution circuit (not shown) within the ER system 500.
  • the VCC system 200 may control the voltages Vsu PP i y ® of the electrical power Es upp i y ® supplied to the users 150, 160, by adjusting the voltage set point Vsp of the distribution circuit in the ER system 500, which may include, for example, one or more load tap changing (LTC) transformers, one or more voltage regulators, or other voltage controlling equipment to maintain a tighter band of operation of the voltages V Delivered of the electric power ⁇ Delivered® delivered to the users 150, 160, to lower power losses and facilitate efficient use of electrical power delivered® at the user locations 150 or 160.
  • LTC load tap changing
  • the VCC system 200 controls or adjusts the voltage s pply® of the electrical power Es upp i y ® supplied from the EC system 500 based on AMI data, which includes measured voltage V Meter® data from the users 150, 160 in the ED system 300, and based on validation data from the EVP system 600 and information received from the EPP system 1700.
  • the VCC system 200 may adjust the voltage set point VSP at the substation or line regulator level in the ER system 500 by, for example, adjusting the LTC transformer (not shown), circuit regulators (not shown), or the like, to maintain the user voltages Meter® in a target voltage band eand-n, which may include a safe nominal operating range.
  • the VCC system 200 is configured to maintain the electrical power ⁇ Delivered® delivered to the users 150, 160 within one or more voltage bands eand-n-
  • the energy may be delivered in two or more voltage bands eand-n substantially simultaneously, where the two or more voltage bands may be substantially the same or different.
  • the value Veand-n may be determined by the following expression [1] :
  • ⁇ Band-n V SP + AV
  • ⁇ - ⁇ is a range of voltages
  • n is a positive integer greater than zero corresponding to the number of voltage bands ⁇ that may be handled at substantially the same time
  • Vsp is the voltage set point value
  • AV is a voltage deviation range.
  • the VCC system 200 may maintain the electrical power delivered to the users 150, 160 within a band Veand-i equal to, for example, 1 1 IV to 129V for rural applications, where Vsp is set to 120V and AV is set to a deviation of seven-and-one-half percent (+/- 7.5%).
  • the VCC system 200 may maintain the electrical power E De i ivere d(t) delivered to the users 150, 160 within a band Veand-2 equal to, for example, 1 14V to 126V for urban applications, where VSP is set to 120V and AV is set to a deviation of five (+/- 5%>).
  • the VCC system 200 may maintain the electrical power E De i ivered (t) delivered to the users 150, 160 at any voltage band Veand-n usable by the users 150, 160, by determining appropriate values for VSP and AV.
  • the values VSP and AV may be determined by the EC system 400 based on the energy usage information for users 150, 160, received from the ED system 300.
  • the EC system 400 may send the VSP and AV values to the ER system 500 as energy delivery parameters CED, which may also include the value Veand-n-
  • the ER system 500 may then control and maintain the voltage V DeiivereJ ) of the electrical power E De i ivered (t) delivered to the users 150, 160, within the voltage band eand-n-
  • the energy delivery parameters CED may further include, for example, load-tap-changer (LTC) control commands.
  • the EVP system 600 may further measure and validate energy savings by comparing energy usage by the users 150, 160 before a change in the voltage set point value VSP (or voltage band Veand-n) to the energy usage by the users 150, 160 after a change in the voltage set point value VSP (or voltage band eand-n), according to principles of the disclosure. These measurements and validations may be used to determine the effect in overall energy savings by, for example, lowering the voltage ⁇ " 1 Delivered ⁇ ) of the electrical power E De i ivere d(t) delivered to the users 150, 160, and to determine optimal delivery voltage bands Veand-n for the energy power E De i ivere d(t) delivered to the users 150, 160.
  • ER SYSTEM 500
  • the ER system 500 may communicate with the ED system 300 and/or EC system 400 by means of the network 170.
  • the ER system 500 is coupled to the network 170 and the EC system 400 by means of communication links 510 and 430, respectively.
  • the EC system 500 is also coupled to the ED system 300 by means of the power lines 340, which may include communication links.
  • the ER system 500 includes a substation 530 which receives the electrical power supply E / réelle(t) from, for example, the power generating station 1 10 (shown in FIG. 1) on a line 520.
  • the electrical power E / perhaps(t) includes a voltage V / réelle(t) component and a current I / réelle(t) component.
  • the substation 530 adjustably transforms the received electrical power E / nieth(t) to, for example, reduce (or step-down) the voltage component V / mecanic(t) of the electrical power E / perhaps(t) to a voltage value Vsu PP i y (i) of the electrical power supplied to the plurality of AMIs 330 on the power supply lines 340.
  • the substation 530 may include a transformer (not shown), such as, for example, a load tap change (LTC) transformer.
  • the substation 530 may further include an automatic tap changer mechanism (not shown), which is configured to automatically change the taps on the LTC transformer.
  • the tap changer mechanism may change the taps on the LTC transformer either on-load (on-load tap changer, or OLTC) or off-load, or both.
  • the tap changer mechanism may be motor driven and computer controlled.
  • the substation 530 may also include a buck/boost transformer to adjust and maximize the power factor of the electrical power
  • the substation 530 may include one or more voltage regulators, or other voltage controlling equipment, as known by those having ordinary skill in the art, that may be controlled to maintain the output the voltage component Ysuppiyft) of the electrical power E Su ppiy(t) at a predetermined voltage value or within a predetermined range of voltage values.
  • the substation 530 receives the energy delivery parameters CED from the EC system 400 on the communication link 430.
  • the energy delivery parameters CED may include, for example, load tap coefficients when an LTC transformer is used to step-down the input voltage component V / mecanic(t) of the electrical power E / mecanic(t) to the voltage component Vsu PP i y (i) of the electrical power Es upP i y (i) supplied to the ED system 300.
  • the load tap coefficients may be used by the ER system 500 to keep the voltage component Vs u i y (t) on the low- voltage side of the LTC transformer at a predetermined voltage value or within a predetermined range of voltage values.
  • the LTC transformer may include, for example, seventeen or more steps (thirty- five or more available positions), each of which may be selected based on the received load tap coefficients. Each change in step may adjust the voltage component Vs uPP i y (t) on the low voltage side of the LTC transformer by as little as, for example, about five-sixteenths (0.3%), or less.
  • the LTC transformer may include fewer than seventeen steps.
  • each change in step of the LTC transformer may adjust the voltage component Vs uPP i y (i) on the low voltage side of the LTC transformer by more than, for example, about five-sixteenths (0.3%).
  • the voltage component Vs u i y (t) may be measured and monitored on the low voltage side of the LTC transformer by, for example, sampling or continuously measuring the voltage component Vs uPP i y (i) of the stepped-down electrical power ⁇ Su PP iy(i) and storing the measured voltage component Vsu PP i y (i) values as a function of time t in a storage (not shown), such as, for example, a computer readable medium.
  • the voltage component Vs u i y (t) may be monitored on, for example, a substation distribution bus, or the like. Further, the voltage component Vs uPP i y (i) may be measured at any point where measurements could be made for the transmission or distribution systems in the ER system 500.
  • the voltage component V / mecanic(t) of the electrical power E / perhaps(t) input to the high voltage side of the LTC transformer may be measured and monitored.
  • the current component ls upP i y (i) of the stepped-down electrical power Es upP i y (i) and the current component I / suits(t) of the electrical power E / perhaps(t) may also be measured and monitored.
  • a phase difference cp / dealt(t) between the voltage V / mecanic(t) and current I / perhaps(t) components of the electrical power E /zzi(t) may be determined and monitored.
  • phase difference q>su PP i y (t) between the voltage Vsu PP i y (i) and current ls upP iy(i) components of the electrical energy supply Es upp i y (t) may be determined and monitored.
  • the ER system 500 may provide electrical energy supply status information to the EC system 400 on the communication links 430 or 510.
  • the electrical energy supply information may include the monitored voltage component Vs u i y (t)-
  • the electrical energy supply information may further include the voltage component V / réelle(t), current components I / perhaps(t), ls u i y (t), and/or phase difference values cp/country(t), q>s uPP i y (t), as a function of time t.
  • the electrical energy supply status information may also include, for example, the load rating of the LTC transformer.
  • the electrical energy supply status information may be provided to the EC system 400 at periodic intervals of time, such as, for example, every second, 5 sec, 10 sec, 30 sec, 60 sec, 120 sec, 600 sec, or any other value within the scope and spirit of the disclosure, as determined by one having ordinary skill in the art.
  • the periodic intervals of time may be set by the EC system 400 or the ER system 500.
  • the electrical energy supply status information may be provided to the EC system 400 or ER system 500 intermittently.
  • the electrical energy supply status information may be forwarded to the EC system 400 in response to a request by the EC system 400, or when a predetermined event is detected.
  • the predetermined event may include, for example, when the voltage component Vs uPP i y (i) changes by an amount greater (or less) than a defined threshold value V ' su PP i y empshoid (for example, 130V) over a predetermined interval of time, a temperature of one or more components in the ER system 500 exceeds a defined temperature threshold, or the like.
  • the ED system 300 includes a plurality of AMIs 330.
  • the ED system 300 may further include at least one collector 350, which is optional.
  • the ED system 300 may be coupled to the network 170 by means of a communication link 310.
  • the collector 350 may be coupled to the plurality of AMIs 330 by means of a
  • the AMIs 330 may be coupled to the ER system 500 by means of one or more power supply lines 340, which may also include
  • Each AMI 330 is configured to measure, store and report energy usage data by the associated users 150, 160 (shown in FIG. 1). Each AMI 330 is further configured to measure and determine energy usage at the users 150, 160, including the voltage component VMete i) and current component of the electrical power EMeier(t) used by the users 150, 160, as a function of time.
  • the AMIs 330 may measure energy usage every, for example, minute (teo sec), five minutes ⁇ t 300 sec), ten minutes ⁇ teoo sec), or more, or at time intervals variably set by the AMI 330 (for example, using a random number generator).
  • the AMIs 330 may average the measured voltage VMete i) and/or values over predetermined time intervals (for example, 5 min., 10 min., 30 min., or more).
  • the AMIs 330 may store the measured electrical power usage E M eter(i), including the measured voltage component VMeter(i) and/or current component as AMI data in a local (or remote) storage (not shown), such as, for example, a computer readable medium.
  • Each AMI 330 is also capable of operating in a "report-by-exception" mode for any voltage or energy usage E M eter(i) that falls outside of a target component band.
  • the target component band may include, a target voltage band, a target current band, or a target energy usage band.
  • the AMI 330 may sua sponte initiate communication and send AMI data to the EC system 400.
  • the "report-by-exception" mode may be used to reconfigure the AMIs 330 used to represent, for example, the lowest voltages on the circuit as required by changing system conditions.
  • the AMI data may be periodically provided to the collector 350 by means of the communication links 320. Additionally, the AMIs 330 may provide the AMI data in response to a AMI data request signal received from the collector 350 on the communication links 320.
  • the AMI data may be periodically provided directly to the EC system 400 (for example, the MAS 460) from the plurality of AMIs, by means of , for example, communication links 320, 410 and network 170.
  • the collector 350 may be bypassed, or eliminated from the ED system 300.
  • the AMIs 330 may provide the AMI data directly to the EC system 400 in response to a AMI data request signal received from the EC system 400.
  • the EC system for example, the MAS 460
  • the EC system for example, the MAS 460
  • the EC system may carry out the functionality of the collector 350 described herein.
  • the request signal may include, for example, a query (or read) signal and a AMI identification signal that identifies the particular AMI 330 from which AMI data is sought.
  • the AMI data may include the following information for each AMI 330, including, for example, kilo-Watt-hours (kWh) delivered data, kWh received data, kWh delivered plus kWh received data, kWh delivered minus kWh received data, voltage level data, current level data, phase angle between voltage and current, kVar data, time interval data, demand data, and the like.
  • the AMIs 330 may send the AMI data to the meter automation system server MAS 460.
  • the AMI data may be sent to the MAS 460 periodically according to a predetermined schedule or upon request from the MAS 460.
  • the collector 350 is configured to receive the AMI data from each of the plurality of AMIs 330 via the communication links 320.
  • the collector 350 stores the received AMI data in a local storage (not shown), such as, for example, a computer readable medium (e.g., a non-transitory computer readable medium).
  • the collector 350 compiles the received AMI data into a collector data.
  • the received AMI data may be aggregated into the collector data based on, for example, a geographic zone in which the AMIs 330 are located, a particular time band (or range) during which the AMI data was collected, a subset of AMIs 330 identified in a collector control signal, and the like.
  • the collector 350 may average the voltage component VMeter(i) values received in the AMI data from all (or a subset of all) of the AMIs 330.
  • the EC system 400 is able to select or alter a subset of all of the AMIs 330 to be monitored for predetermined time intervals, which may include for example 15 minute intervals. It is noted that the predetermined time intervals may be shorter or longer than 15 minutes.
  • the subset of all of the AMIs 330 is selectable and can be altered by the EC system 400 as needed to maintain minimum level control of the voltage Vsuppiy(t) supplied to the AMIs 330.
  • the collector 350 may also average the electrical power EMeier(t) values received in the AMI data from all (or a subset of all) of the AMIs 330.
  • the compiled collector data may be provided by the collector 350 to the EC system 400 by means of the communication link 310 and network 170.
  • the collector 350 may send the compiled collector data to the MAS 460 (or ROC 490) in the EC system 400.
  • the collector 350 is configured to receive collector control signals over the network 170 and communication link 310 from the EC system 400. Based on the received collector control signals, the collector 350 is further configured to select particular ones of the plurality of AMIs 330 and query the meters for AMI data by sending a AMI data request signal to the selected AMIs 330. The collector 350 may then collect the AMI data that it receives from the selected AMIs 330 in response to the queries.
  • the selectable AMIs 330 may include any one or more of the plurality of AMIs 330.
  • the collector control signals may include, for example, an identification of the AMIs 330 to be queried (or read), time(s) at which the identified AMIs 330 are to measure the V Meie r(t), E Me ier(t) and/or p M et er (t) ( pMete f) is the phase difference between the voltage VMeier(t) and current lMeter(i) components of the electrical power EMeter(i) measured at the identified AMI 330), energy usage information since the last reading from the identified AMI 330, and the like.
  • the collector 350 may then compile and send the compiled collector data to the MAS 460 (and/or ROC 490) in the EC system 400.
  • the EC system 400 may communicate with the ED system 300 and/or ER system 500 by means of the network 170.
  • the EC system 400 is coupled to the network 170 by means of one or more communication links 410.
  • the EC system 400 may also communicate directly with the ER system 500 by means of a
  • the EC system 400 includes the MAS 460, a database (DB) 470, a distribution management system (DMS) 480, and a regional operation center (ROC) 490.
  • the ROC 490 may include a computer (ROC computer) 495, a server (not shown) and a database (not shown).
  • the MAS 460 may be coupled to the DB 470 and DMS 480 by means of communication links 420 and 440, respectively.
  • the DMS 480 may be coupled to the ROC 490 and ER SYSTEM 500 by means of the communication link 430.
  • the database 470 may be located at the same location as (for example, proximate to, or within) the MAS 460, or at a remote location that may be accessible via, for example, the network 170.
  • the EC system 400 is configured to de-select, from the subset of monitored AMIs 330, a AMI 330 that the EC system 400 previously selected to monitor, and select the AMI 330 that is outside of the subset of monitored AMIs 330, but which is operating in the report-by-exception mode.
  • the EC system 400 may carry out this change after receiving the sua sponte AMI data from the non-selected AMI 330.
  • the EC system 400 may remove or terminate a connection to the de-selected AMI 330 and create a new connection to the newly selected AMI 330 operating in the report-by-exception mode.
  • the EC system 400 is further configured to select any one or more of the plurality of AMIs 330 from which it receives AMI data comprising, for example, the lowest measured voltage component VMeier(t), and generate an energy delivery parameter C ED based on the AMI data received from the AMI(s) 330 that provide the lowest measured voltage component Meter ⁇ - [0095]
  • the MAS 460 may include a computer (not shown) that is configured to receive the collector data from the collector 350, which includes AMI data collected from a selected subset (or all) of the AMIs 330.
  • the MAS 460 is further configured to retrieve and forward AMI data to the ROC 490 in response to queries received from the ROC 490.
  • the MAS 460 may store the collector data, including AMI data in a local storage and/or in the DB 470.
  • the DMS 480 may include a computer that is configured to receive the electrical energy supply status information from the substation 530.
  • the DMS 480 is further configured to retrieve and forward measured voltage component VMeier(t) values and electrical power E Me ter(i) values in response to queries received from the ROC 490.
  • the DMS 480 may be further configured to retrieve and forward measured current component values in response to queries received from the ROC 490.
  • the DMS 480 also may be further configured to retrieve all "report-by-exception" voltages VMeier(t) from the AMIs 330 operating in the "report-by-exception” mode and designate the voltages VMeier(t) as one of the control points to be continuously read at predetermined times (for example, every 15 minutes, or less (or more), or at varying times).
  • the "report-by-exception voltages ⁇ Mete ) may be used to control the EC 500 set points.
  • the DB 470 may include a plurality of relational databases (not shown).
  • the DB 470 includes a large number of records that include historical data for each AMI 330, each collector 350, each substation 530, and the geographic area(s) (including latitude, longitude, and altitude) where the AMIs 330, collectors 350, and substations 530 are located.
  • the DB 470 may include any one or more of the following information for each AMI 330, including: a geographic location (including latitude, longitude, and altitude); a AMI identification number; an account number; an account name; a billing address; a telephone number; a AMI type, including model and serial number; a date when the AMI was first placed into use; a time stamp of when the AMI was last read (or queried); the AMI data received at the time of the last reading; a schedule of when the AMI is to be read (or queried), including the types of information that are to be read; and the like.
  • the historical AMI data may include, for example, the electrical power EMeier(t) used by the particular AMI 330, as a function of time. Time t may be measured in, for example, discrete intervals at which the electrical power E Me ter magnitude (kWh) of the received electrical power E Me ter(i) is measured or determined at the AMI 330.
  • the historical AMI data includes a measured voltage component VMeier(t) of the electrical energy EMeier(t) received at the AMI 330.
  • the historical AMI data may further include a measured current component lMeter(t) and/or phase difference c Meier(t) of the electrical power E Me ter(t) received at the AMI 330.
  • the voltage component VMeier(t) may be measured at a sampling period of, for example, every five seconds, ten seconds, thirty seconds, one minute, five minutes, ten minutes, fifteen minutes, or the like.
  • the current component lMeier(t) and/or the received electrical power E Me ter(i) values may also be measured at substantially the same times as the voltage component V e*e (t).
  • the DB 470 may include historical data from the very beginning of when the AMI data was first collected from the AMIs 330 through to the most recent AMI data received from the AMI 330.
  • the DB 470 may include a time value associated with each measured voltage component YMeteAt), current component lMeteAt), phase component q>Meter(t) and/or electrical power B Me teAt), which may include a timestamp value generated at the AMI 330.
  • the timestamp value may include, for example, a year, a month, a day, an hour, a minute, a second, and a fraction of a second.
  • the timestamp may be a coded value which may be decoded to determine a year, a month, a day, an hour, a minute, a second, and a fraction of a second, using, for example, a look up table.
  • the ROC 490 and/or AMIs 330 may be configured to receive, for example, a WWVB atomic clock signal transmitted by the U.S. National Institute of Standards and Technology (NIST), or the like and synchronize its internal clock (not shown) to the WWVB atomic clock signal.
  • the historical data in the DB 470 may further include historical collector data associated with each collector 350.
  • the historical collector data may include any one or more of the following information, including, for example: the particular AMIs 330 associated with each collector 350; the geographic location (including latitude, longitude, and altitude) of each collector 350; a collector type, including model and serial number; a date when the collector 350 was first placed into use; a time stamp of when collector data was last received from the collector 350; the collector data that was received; a schedule of when the collector 350 is expected to send collector data, including the types of information that are to be sent; and the like.
  • the historical collector data may further include, for example, an external temperature value ⁇ collector® measured outside of each collector 350 at time t.
  • the historical collector data may further include, for example, any one or more of the following for each collector 350: an atmospheric pressure value P 'collector® measured proximate the collector 350 at time t; a humidity value Hcoiiecto® measured proximate the collector 350 at time t; a wind vector value W ' collector® measured proximate the collector 350 at time t, including direction and magnitude of the measured wind; a solar irradiant value L Co iiector® (kW/m ) measured proximate the collector 350 at time t; and the like.
  • the historical data in the DB 470 may further include historical substation data associated with each substation 530.
  • the historical substation data may include any one or more of the following information, including, for example: the
  • MVA Megavolt Ampere
  • the historical substation data may include, for example, the electrical power E S uppiy(t) supplied to each particular AMI 330, where E Su ppi y (t) is measured or determined at the output of the substation 530.
  • the historical substation data includes a measured voltage component Ysu PP iy t) of the supplied electrical power Bs U ppi y ( ), which may be measured, for example, on the distribution bus (not shown) from the transformer.
  • the historical substation data may further include a measured current component ls upP i y (i) of the supplied electrical power Bs Upp i y ( ).
  • the voltage component Vsu PP i y (i), the current component ls upP iy(i), and/or the electrical power E Supp i y (t) may be measured at a sampling period of, for example, every five seconds, ten seconds, thirty seconds, a minute, five minutes, ten minutes, or the like.
  • the historical substation data may further include a phase difference value q>s uPP i y (t) between the voltage Vsu PP i y (i) and current ls upP i y (i) signals of the electrical power ⁇ Supply , which may be used to determine the power factor of the electrical power ⁇ Suppi y (i) supplied to the AMIs 330.
  • the historical substation data may further include, for example, the electrical power E / mein(t) received on the line 520 at the input of the substation 530, where the electrical power E / perhaps(t) is measured or determined at the input of the substation 530.
  • the historical substation data may include a measured voltage component V / mein(t) of the received electrical power E / perhaps(t), which may be measured, for example, at the input of the transformer.
  • the historical substation data may further include a measured current component I / nieth(t) of the received electrical power E / bland(t).
  • the voltage component V / perhaps(t), the current component I / perhaps(t), and/or the electrical power E / perhaps(t) may be measured at a sampling period of, for example, every five seconds, ten seconds, thirty seconds, a minute, five minutes, ten minutes, or the like.
  • the historical substation data may further include a phase difference (p / mecanic(t) between the voltage component V / perhaps(t) and current component I / perhaps(t) of the electrical power E / spirit(t).
  • the power factor of the electrical power E / perhaps(t) may be determined based on the phase difference cp / discourse(t).
  • the EC system 400 may save aggregated kW data at the substation level, voltage data at the substation level, and weather data to compare to energy usage per AMI 330 to determine the energy savings from the VCC system 200, and using linear regression to remove the effects of weather, load growth, economic effects, and the like, from the calculation.
  • control may be initiated from, for example, the ROC computer 495.
  • a control screen 305 may be displayed on the ROC computer 495, as shown, for example, in FIG. 3 of the US 2013/0030591 publication.
  • the control screen 305 may correspond to data for a particular substation 530 (for example, the TRABUE SUBSTATION) in the ER system 500.
  • the ROC computer 495 can control and override (if necessary), for example, the substation 530 load tap changing transformer based on, for example, the AMI data received from the ED system 300 for the users 150, 160.
  • the ED system 300 may determine the voltages of the electrical power supplied to the user locations 150, 160, at predetermined (or variable) intervals, such as, e.g., on average each 15 minutes, while maintaining the voltages within required voltage limits.
  • the substation 530 may be controlled through the direct communication link 430 from the ROC 490 and/or DMS 480, including transmission of data through communication link 430 to and from the ER 500, EUS 300 and EVP 600.
  • an operator can initiate a voltage control program on the ROC computer 490, overriding the controls, if necessary, and monitoring a time it takes to read the user voltages VMeier(t) being used for control of, for example, the substation LTC transformer (not shown) in the ER system 500.
  • FIG. 3 of the co-pending /P006 application shows an example energy validation process 600 for determining the amount of conservation in energy per customer realized by operating the VCC system in FIGS. 1-2 of the present application.
  • the process is started 601 and the data the ON and OFF periods is loaded 602 by the process manager.
  • the next step is to collect 603 the hourly voltage and power (MW) data from the metering data points on the VCC system from the DMS 480 which may be part of a supervisory control and data acquisition (SCAD A) type of industrial control system.
  • SCAD A supervisory control and data acquisition
  • the data is processed 605, 606, 607, 608 to improve its quality using filters and analysis techniques to eliminate outliers that could incorrectly affect the results, as describe further below. If hourly pairing is to be done the hourly groups are determined 609 using the linear regression techniques. The next major step is to determine 611, 612, 613, 614, 615, 616, 617 the optimal pairing of the samples, as described further below .
  • FIG. 2 also shows an example of the EPP system 1700 applied to a distribution circuit, that also may include the VCC system 200 and the EVP system 600, as discussed previously.
  • the EPP system 1700 collects the historic energy and voltage data from the AMI system from database 470 and/or the distribution management systems (DMS) 480 and combines this with the CVR factor analysis from the EVP system 600 (discussed in detail in the co-pending /P006 application) to produce a robust planning process (EPP system 1700) for correcting problems and improving the capability of the VCC system 200 to increase the energy efficiency and demand reduction applications.
  • DMS distribution management systems
  • FIG. 3 shows the overview of the breakdown of the approach to the
  • the EPP system 1700 The ESS 800 supplies energy and voltage from fixed points tied to the transmission and generation sources on the ESS 800.
  • the EEDCS 1000 connects the ESS 800 to the EUS 900 with primary and secondary electrical connections, typical to electric distribution systems.
  • the AMI meters 330 of AMI system measure both the inputs from the ESS 800 in energy and voltage and the inputs to the EUS 900 in energy and voltage. As show in FIG.
  • the percentage of energy loss in the EEDCS 1000 that can be controlled is orders of magnitude lower that the percentage of energy loss on the EUS 900 that can be controlled. As an example, on the distribution system the EEDCS 1000 losses are less than 5% of the total and the losses on the EUS 900 are more than 95% of the total.
  • a performance criteria definition can be derived to allow full optimization of the EEDCS 1000 design based on the independent variables. Based on the linearization of the power and voltage relationships, this enables optimization on a near radial EEDCS 1000 which can be formulated as a search of the boundary conditions of the linear optimization problem.
  • FIG. 4 describes the planning variables and measurement systems that are used to build the EPP system 1700 and provide the input for the voltage optimization design.
  • the top boxes denote each of the systems within the EEDS 700, e.g., ESS 800, EEDCS 1000, EUS 900 and ED system 300.
  • the list below each of the boxes include examples of controllable planning elements that may be optimized and provided for cost/benefit analysis using the EPP system 1700.
  • the cost/benefit analysis can be included in the optimization or the list of modifications from the voltage optimization can be broken into a prioritized list of project modifications to be evaluated in sequence by cost/benefit.
  • the AMI meter points 330 denote the locations at which measurements are taken that are used to formulate the model and the data needed for the optimization calculations.
  • the chart 1750 in FIG. 5 shows how the voltage data from the ESS
  • the linearization technique (described with respect to FIGs. 7-10) used to create the chart 1750 is an important aspect of the disclosed embodiments.
  • the ability of the EPP system 1700 to use a simple linearization technique to relate the source (e.g., ESS) voltage and delivery (e.g., EUS) voltage creates an efficient method to calculate the voltage ranges available based on variations of ESS and EUS load data forecast by the EEDS system 700 owners. This method also enables the application of a novel linear optimization process that can quickly evaluate various changes to the EEDCS 1000 and document the resulting change in voltage range capability.
  • FIG. 6 shows a method used to model the system to relate the simple linear model to the potential changes identified by the EPP system 1700.
  • the linear model is changed to represent the effect of the modification on the system. For example, if a proposed system modification is to add an additional capacitor to the transmission line at location As of the system, this could be modeled by changing the appropriate variables at location A M of the model.
  • the system is evaluated by the EPP system 1700 to determine if the proposed modification results in additional voltage range. This additional voltage range can be used with the determined CVR factor capacity to calculate the energy savings and the demand savings based on the forecasted ESS loads to determine a combined energy improvement effect of the proposed system modification.
  • the EPP system 1700 performs the evaluations over 24 hour intervals of one hour up to yearly intervals of 8760 hour intervals. This gives the ability to optimize the number and priority of the modification projects and search the solutions for the optimum combination of the modifications to the EEDS 700.
  • FIGs. 7- 10 show a linearization example for one ESS 800 and EUS
  • the ESS D A T A is the AMI data from the ESS 800 and the EUS D A T A is the AMI data from the EUS.
  • This data (ESS D A T A and EUS D A T A) is used to perform the evaluation.
  • FIG. 8 shows that 88 to 89 % of the variation in voltage drop from ESS to EUS can be explained by the linear technique (e.g., the R value is 88.3%, which describe how well the regression line fits the set of data).
  • the remaining residual represents the normalized variation at the EUS that is characteristic of the "ON" and "OFF" nature of the load switching occurring at the EUS. This characterization of the EUS is critical to an efficient method of planning the distribution secondary voltage performance and tracking its reliability.
  • FIGs. 9 and 10 show the calculations for how well the model represents the 24 hour performance of the EUS. This is consistent to within one half volt and the residuals are highly normalized. This gives a great view into characterizing "normal" EUS behavior as well as measuring abnormal EUS behavior.
  • the system is an excellent model to be implemented in the EPP system 1700.
  • FIG. 11 is a flow diagram showing the energy planning process 1500
  • AMI data is measured voltage data from EUS 900
  • ESS data is measured voltage data from ESS 800
  • CVR factor is calculated by EVP 600.
  • historical AMI data and historical ESS data are input, for example, from database 470 at step 1502.
  • the linearization model as discussed above with respect to FIGs. 7-10, is built at step 1503.
  • the data read-in by the process and the forecast of energy use at the ESS are used to determine the range of voltage operation and identify the normal outliers (e.g., voltages not within limits). If any voltages are outside of normal limits, these are resolved by the traditional planning process (e.g., traditional field resolution methods) at step 1505.
  • the traditional planning process e.g., traditional field resolution methods
  • the next step 1506 is to identify any patterns of voltages denoting specific problems impacting voltage reliability, in accordance with this disclosure.
  • problems which create recognizable patterns in the linearization process comparison include a poor connection between a meter and a meter base, an overloaded secondary conductor, an overloaded secondary transformer, an incorrect transformer tap setting, an incompatible type of meter connected in a meter base, and a bad neutral connection. These can be identified, for example, as a data point lying outside of the linear regression (see e.g., point X on chart 1750 of FIG. 5).
  • the problems are identified, they are put into the project process to resolve first at step 1507. Once resolved, the corrected linearization model is used to calculate the new range of performance using the CVR factor, at step 1508. If the determined savings is satisfactory for the next operating period (step 1509), the process moves to the next step 1510. If not the linearization model is run again with tighter tolerances (e.g. returns to step 1504) and the process is repeated until the targeted energy improvement is derived.
  • the final step 1510 is to choose a new set of initial meters for monitoring and/or to configure the VCC 200 to operate with the new level of system performance forecasted by the EPP 1700. This information is then supplied to the VCC 200 and the EVP 600 to configure the controls over the next operating period.
  • FIG. 12 shows an example of the display for the outlier identification
  • FIG. 13 shows the display screen that transfers the AMI data analysis to a geographic one line chart that can be used by the planner to determine the best combination of modifications at the secondary level or EUS level without having to do a detailed secondary model.
  • the information can also be combined with various GIS representations to give the planning key information for selecting the best group of circuit modifications to optimize the performance of the voltage.
  • FIG. 14 illustrates the final step in the EPP process 1700, where the new meter information and the modifications are translated into the control information used by the EPP system 1700 by identifying which meters are associated with each block and zone of the control.
  • Each "zone” refers to all AMIs 330 downstream of a regulator and upstream of the next regulator (e.g., LTC, regulator) and each "block” refers to areas within the sphere of influence of features of the distribution system (e.g., a specific capacitor).
  • LTC next regulator
  • the LTC Zone includes all AMIs 330 downstream of the LTC and upstream of regulator 1402 (e.g., the AMIs 330 in Bl and B2)
  • the Regulator Zone includes all AMIs 330 downstream of regulator 1402 (e.g., the AMIs 300 in B3)
  • Block 2 (B2) includes all AMIs 330 within the influence (upstream or downstream) of capacitor 1403.
  • FIG. 15 shows an example of the final file for configuring the initial set of meters for monitoring in CVR, using the EPP system 1700.
  • the recommended set is given by the EPP system 1700.
  • the user may be allowed to change this recommended set if additional considerations, such as critical customers or other criteria, override the automatic selection process inside the EPP system 1700.
  • This final configuration is then transferred directly to the VCC configuration file for implementation.

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KR1020157029528A KR20150132469A (ko) 2013-03-15 2014-03-14 Ami-기반 데이터 분석을 이용하여 에너지 수요 및 에너지 효율의 계획으로 전력 시스템을 제어
AU2014239865A AU2014239865A1 (en) 2013-03-15 2014-03-14 Electric power system control with planning of energy demand and energy efficiency using AMI-based data analysis
MX2015011547A MX2015011547A (es) 2013-03-15 2014-03-14 Control del sistema de energia electrico con planeacion de la demanda de energia y energia eficiente utilizando el analisis de datos con base en la infraestructura de medicion avanzada.
CN201480015451.0A CN105122169A (zh) 2013-03-15 2014-03-14 利用基于ami的数据分析来计划能量需求和能量效率的电力系统控制
EP14769578.7A EP2972643A4 (en) 2013-03-15 2014-03-14 Electric power system control with planning of energy demand and energy efficiency using ami-based data analysis
JP2016502402A JP2016517685A (ja) 2013-03-15 2014-03-14 Amiに基づくデータ解析を用いたエネルギー需要およびエネルギー効率の計画を伴う電力系統制御
BR112015022540A BR112015022540A2 (pt) 2013-03-15 2014-03-14 controle de sistema de potência elétrica com planejamento de demanda de energia e eficiência de energia com o uso de análise de dados com base em ami
CA2905075A CA2905075A1 (en) 2013-03-15 2014-03-14 Electric power system control with planning of energy demand and energy efficiency using ami-based data analysis
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WO2016123327A1 (en) * 2015-01-29 2016-08-04 Dominion Resources, Inc. Electric power system control with measurement of energy demand and energy efficiency
EP3125397A1 (de) * 2015-07-29 2017-02-01 Siemens Aktiengesellschaft Verfahren, datenverarbeitungsanordnung und computerprogrammprodukt zur nachrüstung eines elektrischen energienetzes sowie verfahren zur optimierung eines bestehenden elektrischen energienetzes
US9847639B2 (en) 2013-03-15 2017-12-19 Dominion Energy, Inc. Electric power system control with measurement of energy demand and energy efficiency
US9887541B2 (en) 2013-03-15 2018-02-06 Dominion Energy, Inc. Electric power system control with measurement of energy demand and energy efficiency using T-distributions
US10274985B2 (en) 2013-03-15 2019-04-30 Dominion Energy, Inc. Maximizing of energy delivery system compatibility with voltage optimization
US10386872B2 (en) 2013-03-15 2019-08-20 Dominion Energy, Inc. Electric power system control with planning of energy demand and energy efficiency using AMI-based data analysis
US10476273B2 (en) 2013-03-15 2019-11-12 Dominion Energy, Inc. Management of energy demand and energy efficiency savings from voltage optimization on electric power systems using AMI-based data analysis
US10732656B2 (en) 2015-08-24 2020-08-04 Dominion Energy, Inc. Systems and methods for stabilizer control
SE1951342A1 (en) * 2019-11-25 2021-05-26 Climeon Ab Method and module controller for controlling a power producing system

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WO2020192920A1 (de) * 2019-03-28 2020-10-01 Siemens Aktiengesellschaft Verfahren zum überwachen einer elektrischen einrichtung
KR102515188B1 (ko) * 2020-04-22 2023-03-31 한국전력공사 에지 컴퓨팅에서 다중 ami 데이터 스트림 가속처리를 위한 하이브리드 딥 러닝 스케줄링 방법

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US10775815B2 (en) 2013-03-15 2020-09-15 Dominion Energy, Inc. Electric power system control with planning of energy demand and energy efficiency using AMI-based data analysis
US10784688B2 (en) 2013-03-15 2020-09-22 Dominion Energy, Inc. Management of energy demand and energy efficiency savings from voltage optimization on electric power systems using AMI-based data analysis
US10666048B2 (en) 2013-03-15 2020-05-26 Dominion Energy, Inc. Electric power system control with measurement of energy demand and energy efficiency using t-distributions
US11132012B2 (en) 2013-03-15 2021-09-28 Dominion Energy, Inc. Maximizing of energy delivery system compatibility with voltage optimization
US9887541B2 (en) 2013-03-15 2018-02-06 Dominion Energy, Inc. Electric power system control with measurement of energy demand and energy efficiency using T-distributions
US10274985B2 (en) 2013-03-15 2019-04-30 Dominion Energy, Inc. Maximizing of energy delivery system compatibility with voltage optimization
US10386872B2 (en) 2013-03-15 2019-08-20 Dominion Energy, Inc. Electric power system control with planning of energy demand and energy efficiency using AMI-based data analysis
US10476273B2 (en) 2013-03-15 2019-11-12 Dominion Energy, Inc. Management of energy demand and energy efficiency savings from voltage optimization on electric power systems using AMI-based data analysis
US10768655B2 (en) 2013-03-15 2020-09-08 Dominion Energy, Inc. Maximizing of energy delivery system compatibility with voltage optimization
US9847639B2 (en) 2013-03-15 2017-12-19 Dominion Energy, Inc. Electric power system control with measurement of energy demand and energy efficiency
WO2016123327A1 (en) * 2015-01-29 2016-08-04 Dominion Resources, Inc. Electric power system control with measurement of energy demand and energy efficiency
CN104917187A (zh) * 2015-07-14 2015-09-16 国家电网公司 一种电网系统的控制方法及装置
EP3125397A1 (de) * 2015-07-29 2017-02-01 Siemens Aktiengesellschaft Verfahren, datenverarbeitungsanordnung und computerprogrammprodukt zur nachrüstung eines elektrischen energienetzes sowie verfahren zur optimierung eines bestehenden elektrischen energienetzes
US10664630B2 (en) 2015-07-29 2020-05-26 Siemens Aktiengesellschaft Method, data processing arrangement and computer program product for retrofitting an electrical energy network and method for optimizing an existing electrical energy network
US11755049B2 (en) 2015-08-24 2023-09-12 Dominion Energy, Inc. Systems and methods for stabilizer control
US10732656B2 (en) 2015-08-24 2020-08-04 Dominion Energy, Inc. Systems and methods for stabilizer control
US11353907B2 (en) 2015-08-24 2022-06-07 Dominion Energy, Inc. Systems and methods for stabilizer control
SE1951342A1 (en) * 2019-11-25 2021-05-26 Climeon Ab Method and module controller for controlling a power producing system

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