As commodity prices increase, efforts to improve efficiency are quickly becoming the best avenue for businesses looking to lower the costs of their operations. Utilities, including electricity, natural gas, and water, present ample opportunities for cost savings through improvements in their utilization. Reduction of consumption, timing of use, and manner of deployment can all result in significant cost savings. For instance, peak electric use charges can be a substantial portion of an industrial customer's electrical utility bill. Simply redistributing the times when power-intensive equipment is used can result in significant savings. As another example, recycling the heat from used hot water flowing down a drain can reduce the cost of heating the incoming source water.
Massive utility savings are out there and their associated cost reductions can be had by simply recognizing cost saving opportunities and implementing a strategic plan for the corresponding utility use.
In the real world, identifying and evaluating potential utility cost saving opportunities is difficult and extremely complex. Implementation of utility cost saving measures can also be a challenge, and may take considerable investments in time and money to realize. As a result, absent concrete evidence of where savings will be obtained and the magnitude of those savings, businesses are reluctant to invest the up-front capital required to make the changes. Therefore, a solution is needed whereby granular utility data may be easily gathered, managed, and analyzed to help identify these opportunities and subsequently to confirm the energy savings of projects undertaken.
Furthermore, a solution is needed whereby granular utility data is analyzed to identify equipment or machinery which is operating out of its normal range, or out of its normal range under the current circumstances, in order to conserve energy or reduce maintenance costs. Equipment of machinery that is using more of a resource (air, water, electricity, etc.) may be doing so because of improper or inadequate maintenance or because of wear or other damage.
The same types of granular utility data can serve cost savings needs in many ways. However, this can only be accomplished if the data are properly collected, stored, analyzed, and distributed. The present invention solves the problem of collecting, storing, analyzing, and distributing necessary information for deducing and ultimately improving overall utility costs as it pertains to any of a number of selected and/or identified areas within an entity, such as an organization, corporation, campus, municipality, or a portion thereof. In doing so, the present invention bring a level of flexibility which allows for just about any type of sensor to be utilized with the system absent the need for pre-programming or dedicated drivers.
A system for receiving utility data from a plurality of devices is disclosed. In one embodiment, the data received is segregated into defined channels with each channel having a user-specified unit type. Furthermore, several calculated channels are created from those channels based upon mathematical formulas.
In a further embodiment, dynamic reports and dashboard views are created based upon the calculated channels. Those dynamic reports and dashboard views are hosted at static unique web addresses to facilitate their subsequent distribution and display.
Further objects, features and advantages of the present invention shall become apparent from the detailed drawings and descriptions provided herein. Each embodiment described herein is not intended to address every object described herein, and each embodiment does not include each feature described. Some or all of these features may be present in the corresponding independent or dependent claims, but should not be construed to be a limitation unless expressly recited in a particular claim.
For the purposes of promoting an understanding of the principles of the invention, reference will now be made to the embodiments illustrated in the drawings and specific language will be used to describe the same. It will nevertheless be understood that no limitation of the scope of the invention is thereby intended. Any alterations and further modifications in the described embodiments, and any further applications of the principles of the invention as described herein are contemplated as would normally occur to one skilled in the art to which the invention relates.
Disclosed is an automated utility data aggregation, warehousing, management, and reporting platform. Also disclosed is a universal multi-location utility monitoring service suitable for collecting granular data from any utility meter (e.g. energy, water, or gas meters) or the like and evaluating the efficiency of various aspects of the system based upon the data collected, its user specified definition, and up to date information acquired from various external sources. The service operates at a central server which collects information from a number of potentially diverse sources for inclusion in a database. In one form, the central server collects static data—such as initial setup and factual information with respect to an entity, dynamic data—such as utility data, and acquired data—such as current weather and publicly available utility costs. Turning to
It shall be appreciated that only one example monitoring system 10, only one data collector 20, and only one server 30 are shown to preserve clarity, but that any number of each may be included and/or interconnected to provide the desired functionality for one or more entities. For example, one or more utility meters 12 may be used with a relay node 18 in order to gather and transmit utility data to a data collector 20. The use of relay nodes 18 depends on several factors such as wireless transmission ranges, utility locations, and sub-metering desires. Environmental meters 14 and other monitors 16 may utilize the same relay node, different relay nodes, or no relay nodes to accomplish their data transmission to the data collector 20. Additionally, an organization may include one or more data collectors 20 at each facility being monitored, with each data collector 20 servicing one or more monitoring systems 10, depending on the size and scope of the monitoring being performed. For example, a data collector 20 and corresponding monitoring system(s) 10 may be included within each building located on a monitored site. Accordingly, servers 30 will be located at a distinct geographic location from monitoring systems 10 and data collectors 20, such as greater than 1 mile, 5 miles, or 20 miles. Furthermore, servers 30 may communicate with multiple combinations of monitoring systems 10 and data collectors 20, including where those combinations themselves are located are different geographic locations, such as those which are greater than 1 mile, 5 miles, or 20 miles apart.
It shall also be appreciated that only a few types of conceivable outputs 50 are shown, but that any number of outputs, including those of various types known to those of skill in the art, are contemplated. Likewise, the processed data 31 is not the only avenue of generating outputs, but is the primary one envisioned for the current embodiment of the system. Outputs 50 could also be generated from the data assembler 32 or the data repository 34 by various means. Indeed, working examples of dashboard views 54 generated by querying the data repository 34 have been demonstrated in practice. The four primary types of outputs 50 currently envisioned are alerts 52, dashboard views 54, reports 56, and ERP system inputs 58. Example illustrations of these output types are provided herein.
Turning to the specifics of the system in
A data collector 20 includes a processor 22, a communication interface 24 configured to communicate, either through a wired or wireless connection, with one or more servers 30, temporary data store 26, and one or more input ports 28 for connection to monitoring systems 10. Processor 22 of data collector 20 is programmed to handle the incoming stream of input data 11 connected to the inputs 28, storing the raw data in a temporary data store 26, and periodically communicating the collected data 21 via a communication interface 24. The granular raw data 11 is stored within temporary data store 26, which may be any form of electronic storage, such as one or more types of solid-state electronic memory, magnetic memory, or optical memory, just to name a few. In another form, the data collector 20 may be configured to connect to a file transfer protocol (FTP) site on servers 30, such as with respect to data repository 34. Each data collector 20 may be provided with a specific location, folder of the like where it is to store the collected data 21. In a further form, there may be separate folders for each monitoring system 10, each data collector 20, each facility, each entity, or the like. Preferably, the FTP site is secured, such a by access credentials, which may be provided to the monitoring user or stored within data collector 20 during configuration.
In one form, the data collector 20 may be a Modbus-enabled device capable of wired and wireless communication, such as the AcquiSuite, offered by Obvius located at 3300 NW 211th Terrace, Hillsboro, Oreg. 97124. It should be noted that in some forms, relay nodes 18 are not required and even the monitoring system 10 and data collector 20 may be combined into a single device, in which case raw data 11 is handled internally to the device; in fact, the AcquiSuite is capable of operating in this configuration. Data collectors 20 transmit the collected data 21 to one or more servers 30 for storage, processing, and reporting.
Servers 30 operate via the combination of a data assembler 32, a data repository 34, and a report engine 36. It shall be appreciated that these components may be comprised of software modules and/or business logic which is resident on servers 30. One or more of the servers which make up servers 30 is operatively connected to a communications media (e.g., the Internet, local area network, wide area network, or digital network) so as to receive the collected data 21 from one or more data collectors 20. Once received, the collected data 21 is processed by the data assembler 32 and stored within a data repository 34 in a format designed to facilitate later reporting. For example, formatted utility data is associated with an entity, such as the operator of the location at which the data was collected. The formatted data may also be further associated with a specific division, location, branch, or the like of an organization, depending upon where it is received from. For example, the files may be provided with an indication of the associations or those associations may be determined from the device the files are received from or which folder the files were uploaded to. Beyond this simple type of association, more complex types of associations are made, such as correlating data by time stamp, internet protocol addresses, hardware IDs, or serial numbers across monitoring systems 10 at different locations. Additionally, the data repository 34 is operationally connected to a report engine 36 which is operable to present data analysis and reporting applications to a set of subscribing remote users. In one form, the remote users are the set of authorized users designated by each entity whose facilities include one or more monitoring systems 10 and data collectors 20, and which are currently subscribed to the service. Furthermore, the data analysis and reporting application presented to each remote user is operable only upon the portion of the data maintained within the data repository 34 which is attributed to their associated entity.
In addition to receiving and processing the collected data 21, servers 30 are capable of collecting and correlating other types of pertinent data from other data sources 33 for inclusion in their respective data repositories 34 via data assemblers 32. These additional types of data may include data such as weather information, minute-by-minute temperature, wind speed, relative humidity, cloudiness, and precipitation readings received via an RSS feed from a national or local weather station for a specific location. In one form, the weather station may be operated by the National Weather Service. Additionally, current energy rates may be collected from a number of applicable energy providers, such as by screen scraping of energy provider web pages or other data acquisition methods. In addition, data may be input directly by users to accommodate data not readily available by other means.
The servers 30, in conjunction with the various other components of the system, provide one or more user interfaces, which allow a user to log in from a remote location and monitor the current status of various monitored systems 10. For example, total energy consumption or the energy consumption of a particular sub-system or component according to the data received from its collective/associated utility meters 12. Additionally, historical data, such as the past 24 hours, past week, current month, current year, or some other specified period of energy usage statistics may be provided. The user interface may take various forms, from an installed application on a computer, to a web site, to a mobile device application. The user interface aspect of the system is not shown in
In the illustrated embodiment represented in
Turning to
When a new facility is established, according to one for of the present invention, a data folder is established within data repository 34 of
Once a facility is established, the system 9 may begin to receive data from the devices of monitoring system(s) 10. However, at this point, the data received by system 9 may not have any particular meaning. For example, the data may be in tabular form without any specific meaning assigned to each column, row, or the like. Furthermore, the data may be received in one of many forms, including a comma separate value format.
Turning to
List box 72 shows a listing of all of the current channels which are defined and accessible to the current user. Furthermore, should the user choose, the channels included within list box 72 may be pared down by selecting a particular facility, building or device within drop down boxes 73, 74 and/or 75. Additionally, the screen 70, in a further form, may provide a search box to enable a user to further or more quickly pare down the resulting channels displayed.
Focusing on the right hand portion of screen 70, the creating of a new channel will now be described. Initially, a new channel is provided with a name which is entered into name field 76. Additionally, the units associated with the new channel are entered into field 77. In another form, the units may selected from a pre-defined list via a drop down box, which preferably includes a wide variety of common units, such as degrees, kilowatts, kilowatts/hour, % humidity, gallons, gallons per minute, just to name a few representative examples. It shall be appreciated that a pre-defined list may be supplemented by the user if desired to include any unit label desired. In addition to a unit type, each channel may also be identified with a particular utility category by a category drop down box 78. Exemplary categories for use include electric, water, gas, environment, etc. These categories may be used to quickly add large numbers of channels to reports based upon their type. Also required for each channel is an indication of whether the channel is cumulative, meaning that each data point received is in addition to those previously received. This indication is made by selecting or not leaving empty check box 79. One example of a cumulative channel would be one which is received from a flow meter which merely pulses upon the occurrence of an event, such as the flow of a specified volume of liquid or the like.
System 9 also provides for the creating of “calculated channels” which are similar to channels except that they may be a combination of one or more channels. Furthermore, each calculated channel is defined by a mathematical equation having at least one mathematical operator, such as “+”, “−”, “*” or “/”. This enables a user to arrive at a calculated channel for subsequent use in reporting, monitoring, or alarm generation without requiring a specific monitoring device or device driver. For example, in the event of a pulse-based flow meter, a calculated channel may be created where the definition is “30*# of pulses” (in gallons). Furthermore, in the case facility with six air conditions, their load may be calculated by monitoring the load on the pane they are connected to as well as monitoring the devices connected to that panel which aren't air conditioners, and creating a calculated channel which subtracts the other devices from the load detected at the panel. This may result in efficiencies, such as a reduction in the number of utility meters or the like required to achieve the desired monitoring.
As shown in
Turning to
Turning to
Once the dashboard is established, server 30 may be programmed so as to periodically automatically update the dashboard view. Furthermore, server 30 may publish the dashboard view at a static web-page address, which is defined by static web address 106 of screen 100. This static web-page address may be accessible outside of the security traditional user access restrictions of system 10. This allows for dashboard views to be e-mailed to third-parties, accessed by users without logging into the web based application, and/or to be displayed automatically on a monitor or the like, such as within the actual monitored facility.
As described above, in one form the dashboard view 112 of illustrative page 110 is posted to a web-page located at a static web address by servers 30. The static web address is them made available to the user for subsequent distribution, such as by e-mail or the like to other users. Furthermore, the static web address operates outside of the user access restrictions implemented by the web-based application. Accordingly, the dashboard view 112 may be shared quickly and easily with other within an organization, such as by e-mail or the like, whether they are authorized users or not. Additionally, smart displays may be configured to display a certain dashboard view 112, report, or combination of the above on a smart monitor, television or the like. In a further form, the monitor may cycle through one or more of the above mentioned displays by visiting a series of pre-programmed static web addresses.
In a further form, the server 30 performs analysis on the collected data stored in the data repository 34 by constructing mathematical computer models (e.g., using techniques of operations research). For instance, the server may calculate the total energy cost for an entity over a specific period of time based on forecast conditions or the expected performance of a device based on specified conditions, such as weather conditions. This information enables a system owner to easily determine the cost of conducting certain necessary activities at a specific time versus another time, or the cost of one system as opposed to another. Additionally, these calculations enable the triggering of modeled performance alerts, as described above.
In still another form, the server 30 may enable a remote user to define tenants or other divisions for sub-metering purposes. In doing so, the total set of various monitoring systems 10 associated with the entity are able to be assigned to distinct subsets which represent the desired tenants or sub-parts. Once defined, all of the functionality described about, including reporting and notifications, may be customized and executed on these subsets. Additionally, multiple-tenant reports and functions can be executed, simply by selecting the desired tenants.
In an additional form, the server 30 may provide access to collected data 21 or processed data 31 for use as input to one or more ERP (Enterprise Resource Planning) systems 58. Due to the large variety of ERP systems in the market and the need to customize each one to a specific business, the interface with ERP systems is necessarily flexible. In one of the simplest manifestations, CSV (comma separated values) files with pre-defined content can be output to a pre-defined location (e.g., a file server on the Internet) by a server 30 for later consumption by an ERP system 58. Another simple implementation would be to allow on-demand queries by an ERP system 58 directly to a data repository 34 on a server 30.
The collection of the data described above would normally be a time-consuming process, the automated natured of it reduces labor costs associated with operating, evaluating, and maintain such a system. Furthermore, the data collected is much more accurate, granular, and up to date as the system does not rely upon utility bills or other comparable reports which are often generated weeks after the time when the data are generated.
While the invention has been illustrated and described in detail in the drawings and foregoing description, the same is to be considered as illustrative and not restrictive in character, it being understood that only the preferred embodiment has been shown and described and that all equivalents, changes, and modifications that come within the spirit of the inventions as described herein and/or by the following claims are desired to be protected.
This application claims the benefit of U.S. Provisional Application Ser. No. 61/568,307, filed Dec. 8, 2011 which is hereby incorporated by reference in its entirety.
Number | Date | Country | |
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61568307 | Dec 2011 | US |