Abstract:
A method for providing an identification of individual smart meters among a plurality of smart meters communicably coupled in a networked grid area based on a unique identification number stored in the memory of the smart meter is provided. The method includes calculating a first value corresponding to the unique identification number, receiving a query message including a second value corresponding to the unique identification number of one of the plurality of smart meters and determining if the first value matches the second value. The method further includes sending a response message including the unique identification number if the first value matches the second value. The method may further include assigning logical identification numbers to each of the smart meters.

Description:
BACKGROUND 
     1. Technical Field 
     The present disclosure is related to smart meters arranged in a smart grid. In particular, the present disclosure is related to methods for polling and identifying the individual smart meters in a smart grid by a utility provider or host device. 
     2. Discussion of Related Art 
     Traditional power grids transmit power from a limited number of central power generators to many users. However, traditional power grids are more or less the same as they have been since the beginning of the 20th century, and have not kept up with advances in technology. Consequently, there has been a push to switch many traditional power grids to a more modern smart grid. A smart grid has the capabilities of delivering electricity to consumers using digital technology with two-way communications to, among other things, control appliances at consumers&#39; homes to save energy, reduce cost and increase reliability. Smart grids may be made possible by applying sensing, measurement and control devices with two-way communications to electricity production, transmission, distribution and consumption parts of the power grid that communicate information about grid condition to system users, operators and automated devices, making it possible for users and the devices connected to the grid to dynamically respond to changes in grid condition. 
     A smart grid would include an intelligent monitoring system with two-way communication capabilities that keeps track of all electricity flowing in the system. As part of the intelligent monitoring system, smart meters may be installed at locations across the grid. A smart meter is the term given to utility (i.e., electrical, water, or natural gas) consumption meters that have additional functionality. For example smart meters can record consumption in intervals of an hour or less, and the consumption information can be communicated to the utility or the consumer via a communications network. Smart meters may also include real-time or near real-time sensors, and be configured to provide utility outage notifications to the utility as well as the consumer. 
     An important technology in making a smart grid work is automatic meter reading (AMR). AMR is the technology of automatically collecting consumption, diagnostic, and status data from utility meters, including smart meters. The collected data can then be transferred to a central database for billing, troubleshooting, and analyzing. AMR provides multiple benefits over current technologies. For example, AMR eliminates the need of a utility representative to physically travel to a consumer&#39;s location and perform a manual reading of the meter. AMR also provides for the ability to bill based on real-time or near real-time consumption instead of traditional methods of billing based on previous or predicted consumption, and allows both utility providers and consumers to better control the use and production of utility services. 
     However, AMR requires that a central, or host computer, often at the utility provider but sometimes in the grid, occasionally poll the meters to determine how many meters are connected to the grid as well as the identification number of each meter. A utility provider representative can go into the field, physically inspect each meter, and then manually input the identification number of each meter into the central computer. This approach takes a considerable amount of time and increases the probability of mistakes arising through human error. For smart meters or other types of devices which are communicatively coupled to the central computer, the central computer can poll each of the devices connected to the central computer to determine the identification number of each device and the total number of devices. However, the identification number is often long and polling all of the devices for each number can take quite some time. Binary searching has been proposed as an alternative, which reduces the searching space and speeds up the searching time. However, a binary search requires a mask having the same bit length as the identification numbers to be on the channel. These bit lengths may are long enough to be easily corrupted by noise. Moreover, in an ideal case, the complexity of binary searching is N*log 2 L, where N is the number of devices connected to a host or master device, and L is the bit length of the identification number. Furthermore, because in a binary search the mask only masks half of the devices, the other half of the devices will respond to a host or master device, increasing the probability of conflicts. Accordingly, there is a need to provide for a better system for determining the number of devices connected to a grid, the identification number of each device on the grid, and for searching for a particular device on the grid. 
     SUMMARY 
     Consistent with some embodiments, there is provided a method for providing an identification of individual smart meters among a plurality of smart meters communicably coupled in a networked grid area based on a unique identification number stored in the memory of the smart meter. The method includes calculating a first value corresponding to the unique identification number, receiving a query message including a second value corresponding to the unique identification number of one of the plurality of smart meters and determining if the first value matches the second value. The method further includes sending a response message including the unique identification number if the first value matches the second value. 
     Consistent with some embodiments, there is also provided a method for identifying individual smart meters among a plurality of smart meters in a networked grid area by a host device, the host device including a processor, a memory, and a communications interface, the memory including instructions for execution by the processor for performing the method, the method including the steps of sending a query message to the smart meters in the networked grid area, wherein the query message including a first value corresponding to a unique identification number of an individual smart meter of the plurality of smart meters. The method also includes the steps of receiving a response message from the individual smart meter having the unique identification number, assigning a logical identification number to the individual smart meter, storing the logical identification number and the unique identification number in a memory of the smart meter, and sending the logical identification number to the individual smart meter. 
     Further consistent with some embodiments, there is also provided a smart grid having at least one host device and a plurality of smart meters, the host device and the plurality of smart meters being communicably coupled in the smart grid. The identity of the smart meters in the smart grid may be determined by performing a method including calculating a first value corresponding to an identification value unique to each smart meter, sending a query message to the plurality of smart meters in the smart grid, wherein the query message including a second value corresponding to the identification value unique to each smart meter. The method also includes receiving the query message, determining if the second value matches the first value, and sending a response message if the second value matches the first value. 
     These and other embodiments will be described in further detail below with respect to the following figures. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG. 1  is a diagram illustrating an arrangement of smart meters in a grid area, consistent with some embodiments. 
         FIG. 2  is a diagram illustrating a smart meter according to some embodiments. 
         FIG. 3  is a flowchart illustrating an algorithm for locating and identifying other smart meters in a grid area. 
     
    
    
     In the drawings, elements having the same designation have the same or similar functions. 
     DETAILED DESCRIPTION 
     In the following description specific details are set forth describing certain embodiments. It will be apparent, however, to one skilled in the art that the disclosed embodiments may be practiced without some or all of these specific details. The specific embodiments presented are meant to be illustrative, but not limiting. One skilled in the art may realize other material that, although not specifically described herein, is within the scope and spirit of this disclosure. 
       FIG. 1  is a diagram illustrating an arrangement of smart meters in a grid area, consistent with some embodiments. As shown in  FIG. 1 , a grid area  100  includes a plurality of smart meters  102  and at least one host  104 . Smart meters  102  may be meters that are capable of metering a utility, such as power, energy, and/or water, consumed by a consumer, and, when part of a smart grid having power line communication (PLC), communicating the metered values to the utility vendor or utility provider. Consistent with some embodiments, a repeater  106  may be configured to act as a host  104  while still retaining the functionality of smart meter  102  and be capable of metering a utility, such as power, energy, and/or water, consumed by a consumer, but also including additional instructions stored in a memory for initiating an algorithm that polls and identifies smart meters  102  in grid area  100 , as will be explained in  FIG. 3 . In some embodiments, host  104  may not be a smart meter but instead be a processing device, such as a computer, that is coupled to the grid area  100  through the internet, a network, or through PLC, and includes at least instructions for initiating an algorithm that locates smart meters  102  in grid area  100 . For example, host  104  may be located at a utility vendor site. 
     Returning to  FIG. 1 , smart meters  102  are coupled together throughout grid area  100  through connection  108 . According to some embodiments, connection  108  may be a power line connection, such that smart meters  102  are coupled together via power lines in a transformer area. In such embodiments, connection  108  may be capable of supporting power line communication, including broadband over power lines (BPL), such that the smart meters  102  in grid area  100  form a network and may communicate with one another and to a utility vendor (not shown) through connection  108 . In other embodiments, smart meters  102  may include wireless communication capabilities such that the smart meters are coupled together and to a utility vendor using wireless technologies. Such wireless technologies may include, but are not limited to, radio frequency (RF), Wi-Fi™, Bluetooth™, ZigBee™, or Wavenis wireless technologies. By providing communication capabilities between smart meters  102 , smart meters  102  in grid area  100  may form a “smart grid.” Although  FIG. 1  only illustrates grid area  100  as including 4 smart meters  102 , a single host  104 , and a single repeater  106 , a grid area  100  may have many more or many fewer smart meters, hosts, and/or repeaters. In some embodiments, grid area  100  may have about three hundred smart meters. 
       FIG. 2  is a diagram illustrating a smart meter according to some embodiments. As shown in  FIG. 2 , smart meter  102  is coupled to other smart meters (not shown) via connection  108 . Consistent with some embodiments, smart meter  102  may also be coupled to utility vendor or provider  200  via connection  108  or via a wireless connection  202 . Consistent with further embodiments, smart meter  102  may be coupled to a host  104  or repeater  106  (not shown) via connection  108  or wireless connection  202 , or, in yet other embodiments, a smart meter  102  may act as a repeater  106  and may be used as a host  104 . Through wireless connection  202  or connection  106 , smart meter  102  may provide metering information to utility vendor or provider  200 , such as energy, power, and/or water usage. Metering information may be determined by meter sense circuitry  204  included as electronics  206  in smart meter  102 . 
     Consistent with some embodiments, smart meter  102  may include a processor, such as CPU  208 , coupled to a memory  210 , both of which may be coupled to a communications interface  212 . Communications interface  212  may be used to facilitate communications with other smart meters  102 , utility vendors/providers  200 , and host  104 , over connection  106  or wireless connection  202 . Smart meter  102  may further include a display  214  which may provide metering information, such as a current usage of power, energy, or water. Consistent with some embodiments, display  214  may be a quartz display, a dial, a liquid crystal display (LCD), a organic light emitting diode (OLED) display, or a light emitting diode (LED) display. 
     Memory  210  may store information about the smart meter, such as the unique ID of the smart meter. Memory  210  may further store instructions for execution by the processor to perform specific functions. For example, in some embodiments, CPU  208  may be configured to execute instructions stored in memory  210  to execute algorithms for analyzing metering information and transmitting metering information to utility vendor/provider  200  through communications interface  212 . Consistent with some embodiments, CPU  208  may be configured to execute instructions stored in memory  210  to perform an algorithm for locating and identifying other smart meters  102  in a grid area  100 . In particular, if smart meter  102  is a repeater  106  and used as a host  104 , memory  210  may store instructions for generating pick-up messages for locating and identifying all smart meters  102  in grid area  100 , and assigning logical IDs to identified smart meters  102 . Or, memory  210  may include instructions for responding to a pick-up message generated by host  104 , receiving an acceptance message from host  104 , and storing a logical ID generated by host  104 . 
       FIG. 3  is a flowchart illustrating an algorithm for locating and identifying smart meters in a grid area. The algorithm illustrated in  FIG. 3  will be discussed in conjunction with  FIGS. 1 and 2 , for the purposes of illustration. Consistent with some embodiments, steps of the algorithm may be executed by processors  208  of smart meters  102  and/or host  104 , wherein, in some embodiments, host  104  may be a repeater  106  or another processing device. Moreover, the algorithm illustrated in  FIG. 3  may be used for locating and identifying smart meters in a grid area which may be coupled together and to a host through power line connection (PLC) or wirelessly, such that the smart meters in the grid area form a network. Furthermore, the algorithm illustrated in  FIG. 3  may be used following a new installation or an upgrade of legacy meters to smart meters. In such situations, the unique IDs of each of the smart meters in the grid area are not known to the utility vendor or operator or, the number of smart meters in the grid area is not known. Thus, smart meter  102  will not have an assigned logical ID stored in memory  210 . When there is no assigned logical ID, CPUs  208  of smart meters  102  execute instructions stored in memory  210  to calculate a hash value based on its stored unique ID (Step  300 ). The hash value may be calculated using any known hash function, such as MD5, SHA-1, or CRC. The generated hash value may then be stored in memory  210 . 
     Similarly, a host device  104  will be programmed to execute a pick-up function for locating specific slave devices in a grid area  100 . Host  104  will proceed to send a pick-up message (Step  302 ) to all smart meters  102  in grid area  100  which may be networked via PLC or wirelessly, as discussed above. Consistent with some embodiments, pick-up message may be sent over a dedicated broadcast channel in the PLC or wireless network of grid area  100  designed for receiving important messages such as pick-up messages. The pick-up message includes a hash value designating a specific smart meter  102  in grid area  100 . Consistent with some embodiments, the pick-up message may further include a header and cyclic redundancy check (CRC) bits, or checksum bits. One example of a pick-up message is illustrated below: 
                                
According to some embodiments, pick-up messages generated and sent out by host device  104  includes iteratively generated hash values to scan for all available smart meters  102 .
 
     The sent pick-up message is detected and received at all smart meters  102  in grid area  100  (Step  304 ). CPUs  208  of smart meters  102  then execute instructions in memory  210  to first determine whether the received pick-up message is valid (Step  306 ). Message validity may be determined by analyzing the CRC information included in the pick-up message or otherwise comparing the CRC information in the pick-up message to CRC values generated at smart meters  102 . If the pick-up message is not determined to be valid, it is ignored (Step  308 ). If the pick-up message is determined to be valid, processors  208  in smart meters  102  execute instructions stored in memory  210  to determine if the hash value received in the pick-up message matches the hash value stored in memory  210  generated based on the unique ID of smart meter  102  (Step  310 ). If the received hash value does not match the stored hash value, smart meter  102  ignores the pick-up message (Step  312 ). If the received hash value matches the stored hash value, smart meter  102  will prepare to send a response message to host  104  by checking for conflicts on the network (Step  314 ). Conflicts may arise on the dedicated channel of the PLC or wireless network when host  104  is transmitting a message or another smart meter  102  is sending a response. If conflicts are detected, CPU  208  of smart meter  102  initiates a delay (Step  316 ). After the delay has expired, smart meter  102  will again check for conflicts (Step  314 ) and continue initiating a delay (Step  316 ) until there are no conflicts detected on the grid network. Similarly, in case conflicts interfere with the sending of a pick-up message from host  104 , host  104  will continue to send the same pick-up message until a response has been received. 
     Once there are no conflicts detected on the grid network, smart meter  102  sends a response message to host  104  (Step  318 ). Consistent with some embodiments, response message includes the unique ID value of smart meter  102  along with a CRC value or checksum bits to show validity. One example of a response message is shown below: 
                                
The response message is then transmitted to host  104  over the grid network.
 
     After receiving the response message from smart meter  102 , a processor of host  104  executes instructions for assigning a logical ID to the responsive smart meter  102  (Step  320 ). The assigned logical ID and the received unique ID are then stored as a pair in a routing table stored in a memory of host  104  (Step  322 ). Host  104  then sends a message to the responsive smart meter  102  using the received unique ID that the responsive smart meter  102  has been accepted as part of the grid network along with the responsive smart meter&#39;s  102  assigned logical ID (Step  324 ). Steps  302 - 324  are repeated for all smart meters  102  in grid area  100 . That is, host  104  continues to scan the network by generating pick-up messages having iterative hash values until the entire hash value space has been scanned and/or until all smart meters  102  in grid area  100  have responded and been added to the routing table of host  104 . Once the routing table of host  104  has been populated, searching for a particular smart meter  102  may be done by matching the assigned logical ID of smart meter  102  with the unique ID of smart meter  102 . 
     By providing instructions for carrying out an automated scan of smart meters in a grid area, the unique IDs of all of the smart meters in a grid area may be determined without having to send a technician into the field to manually determine the unique IDs of each of the smart meters in the grid area. Moreover, by mapping the unique IDs to a hash value, the host can scan from, for example 0-127 for a 7-bit hash value, which significantly reduces the amount of time and bandwidth needed to determine the unique IDs of all of the smart meters in the grid area. Consequently, embodiments as described herein may provide a better system for determining the number of devices connected to a grid, the identification number of each device on the grid, and for searching for a particular device on the grid. The examples provided above are exemplary only and are not intended to be limiting. One skilled in the art may readily devise other systems consistent with the disclosed embodiments which are intended to be within the scope of this disclosure. As such, the application is limited only by the following claims.