Patent Application
20090070168
1. Technical Field
This disclosure relates generally to monitoring energy related data. More specifically, the disclosure relates to a social network approach to power related data analysis.
2. Background Information
Monitoring of electrical energy by consumers and providers of electric power is a fundamental function within any electric power distribution system. Electrical energy may be monitored for such purposes as usage, equipment performance and power quality, or other purposes or combinations thereof.
Power quality can be affected by a number of factors outside of voltage and current fluctuations. Some of these factors include temperature fluctuations and other weather related conditions. Power quality related events may consist of events such as sags, swells, and spikes. Such events not only cause potential harm to equipment but can also result in large losses of revenue due to outages.
Devices that perform monitoring of electrical energy may include electromechanical devices, such as, for example, a residential billing meter, or intelligent electronic devices (“IED”). IED's typically include some form of memory and microprocessors executing software to execute desired power management functions. IED's include Programmable Logic Controllers (“PLC's”), Remote Terminal Units (“RTU's”), electric power meters such as revenue meters, protective relays, fault recorders and other devices which are coupled with power distribution networks to manage and control the distribution and consumption of electrical power. An IED may perform other functions such as, for example, power distribution system protection, management of power generation, management of energy distribution and management of energy consumption.
A typical consumer or supplier of electrical energy may have many IED's installed and operating throughout their operations. For example, an engineer in charge of the electricity for a corporation with several plants will likely be in charge of a number of IED's. The IED's may operate individually, or may operate as part of a monitoring system. Each of the IED's may require unique software configurations, or multiple devices may include the same software configurations. An Enterprise Energy Management (EEM) system may be used to configure and monitor the IED's, such as through a graphical user interface.
However, managing the electrical power distribution and configurations of devices can be extremely burdensome for the consumer. Furthermore, consumers in similar industries with similar configurations and similar needs may spend an extraordinary amount of time configuring their energy related systems and determining the root cause of an outage or a problem.
This disclosure combines the information collected by an Enterprise Energy Management (EEM) system with the global expertise of the internet community of users, subject matter experts and product and service providers. The Enterprise Energy Management System with Social Network Approach to Data Analysis architecture may be better understood with reference to the following drawings and description. Other systems, methods, features and advantages will be, or will become, apparent to one with skill in the art upon examination of the following figures and detailed description. It is intended that all such additional systems, methods, features and advantages be included within this description, be within the scope of the invention, and be protected by the following claims.
Currently, online systems exist where a consumer can upload a data set and view subsets of the data. Online community services also exist where similar users can post messages regarding their concerns and even discuss possible resolutions. However, one problem with current online systems is they do not categorize data, data sets, and users using attributes.
Modern energy monitoring systems are capable of capturing and managing large volumes of data. However, many users do not have the expertise to analyze this data to gain insight into the operation of their energy network(s). Furthermore, even those who may have the expertise to analyze the data may not have the time or the resources to do so effectively. The disclosed embodiments relate to an approach to data analysis that provides tools to a community of users having expertise in a variety of areas. Using these tools, this community of users can leverage the collective intellectual capacity of the community and help each other turn volumes of monitoring system data into actionable information. Some exemplary applications of the disclosed embodiments include: identifying trends; identifying undetected, unanticipated, or unmeasurable, significance from isolated or seemingly innocuous occurrences/events; exposing perceived-isolated occurrences/events to demonstrate or reveal unseen/undetected relationships; and distinguishing meaningful data from meaningless data, e.g. noise, in large volumes of data. Thus, using a “social network” approach to data analysis by providing tools to a community of users with expertise in a variety of areas enhances the quality of the analysis while reducing the amount of time it can take to understand and resolve an issue. Furthermore, the social network approach can reduce the amount of time to find the root cause of a power related issue or problem.
A social network provides a means for a community of users with a common interest to communicate. Such user communities may be defined within an organization or entity or may be defined by the shared interests of individuals, organizations or combinations thereof, and thereby extend across organizational or other boundaries. Many social networks are web based but they do not have to be. For example, other communications protocols or media, whether or not TCP/IP based, may be utilized. A social network can provide tools to enhance communication between users and increase productivity within a user's industry. Such tools may include blogging, chat, or discussion groups. With regard to the disclosed embodiments, the social network is provided or made available to a community of users such as building managers who are responsible for managing power related consumption, power related problems/outages, or a number of other tasks that may be associated with power distribution, consumption and monitoring.
Generally, an Energy Management system may be communicatively linked with an internet based social networking system to aid in energy and power quality analysis, as well as acting as a communication medium between a provider of relevant products and services and an end user customer having a need therefore, as well as between two or more such providers and end users. For example, a facility engineer at an industrial site may experience a power quality related event such as a voltage transient. The site's EEM system collects all of the information relevant to the event and then offers the engineer the option of uploading or otherwise sending the event details to an internet based repository that other similar EEM users, as well as other subject matter experts, product and service providers, have access to. Prior or subsequent to uploading data, the engineer can search for and compare existing event details in the database with similar characteristics and/or request assistance in analyzing the voltage transient details from the other users and experts in the community, as will be described.
More specifically, the energy management system may include one or more sources of measurement data, which may include intelligent electronic devices, other measurement systems such as process automation systems, and web services, such as weather services. A central computer or cluster of computers may also be included which executes software that receives measurement data from one or more sources, archives the data and presents the data to one or more users for viewing and analysis. Further, an online service that captures and manages the relationships between a community of users, measurement data acquired by those users and data analysis operations performed by users on the measurement data may also be included.
Reference will now be made to the accompanying drawings, which form a part hereof, and which show, by way of illustration, specific exemplary embodiments. The modules in the figures are not necessarily to scale, emphasis instead being placed upon illustrating the principles of the invention. Moreover, in the figures, like referenced numerals designate corresponding parts throughout the different views. The principles described herein may, however be embodied in many different forms, and this specification should not be construed to limit the claims. Rather, these embodiments are provided so that the disclosure will be thorough and complete to those skilled in the art.
Enterprise energy management monitoring service 120, social data analysis service 116, local enterprise energy management server 114, and user devices 101 and 154 may represent various types of computing devices. These devices may generally include any device that is capable of performing computations and sending and/or receiving data over a network. The wide area network 118 and/or local area networks 128, 138 may include the Internet, a public or private intranet, an extranet, or any other network configuration to enable transfer of data and commands including wired and or wireless networks, or combinations thereof. An exemplary network configuration uses the transport Control Protocol/Internet Protocol (“TCP/IP”) network protocol suite, however, other Internet Protocol based networks are also contemplated. Communications may also include IP tunneling protocols such as those that allow virtual private networks coupling multiple intranets or extranets together via the Internet. The network may support application protocols, such as, for example, telnet, POP3, Mime, HTTP, HTTPS, PPP, TCP/IP, SMTP, proprietary protocols, or any other network protocols known in the art. For example, user devices 101 and 154 may be configured to execute a browser application that employs HTTP to request information, such as a web page, from a web server. The illustrated computing devices communicate using the wide area and local area networks 118, 128, and 138. Wide and local area networks 118, 128, and 138 may include any suitable communication network including wire line and wireless networks using any suitable network protocol and may include sub-networks such as other local area networks or wide area networks.
The measurement and analysis of power quality not only involves voltage and current measurements but other types of data may be relevant as well, such as temperature and weather conditions which may also be considered power management related data. Other relevant data types may include financial market data, current news events or other data which may be associated with or have relevance to the delivery and/or consumption of energy. The data sources 106, 108, 110, 112, 118, 122, and 126 may represent some of the possible sources of data that can be included in the data analysis. For example, the IED's 122 and 124 may collect energy related data associated with a gas utility. The IED's 132 and 134 may collect energy related data associated with an electric utility, and the IED's 142 and 144 may collect energy related data associated with a process control system such as a production line. The data source 106 may represent additional data sources that offer data relevant to the analysis of energy use. One example of such relevant data might be the hourly ambient temperature readings offered by a weather service company. Other examples include financial market data, local news data, national news data, and world news data. Other data sources not listed above may also be included in addition to those already stated.
The EEM monitoring service 120 may include a social data analysis service 116. The social data analysis service 116 may be in the form of a database but can be any computer related software module that is capable of storing and presenting views and analysis of the data collected by the EEM monitoring service 120 as described herein. The social data analysis service 116 may be combined logically and/or physically with the EEM monitoring service 120, or may be provided separately. In one embodiment, it may be more desirable to maintain the social data analysis 116 separated, logically and/or physically, from the EEM monitoring service 120 for improved reliability and to minimize security risks and data loss. In one embodiment, the EEM monitoring service 120 may be located on the enterprise energy management social network service provider's local area network. The social data analysis service 116 may be provided via a sub-network or local area network (not shown) that is separate from the sub-network or local area network (not shown) to which the EEM monitoring service 120 is coupled. The social data analysis service 116 may be hosted by an independent vendor/company that is capable of polling the EEM monitoring service 120 to obtain the requisite aggregate energy related or other data.
Site 1 and Site 2 represent two of the many possible configurations that may be used in a given site. System users 102 and 104 may represent possible members of the social network described herein. For example, system user 102 may be a building manager for building A while user 104 may be a building manager for building B. System users 102 and 104 may be unaffiliated with each other. In an alternative embodiment, the users of the architecture 100 may be limited to users of a particular organization or entity. The configurations of sites 1 and 2 are only exemplary and should not be used to limit this disclosure.
The EEM monitoring service 120 may collect energy related data from several IED's within several unrelated and/or unaffiliated sites. The EEM monitoring service 120 may also collect data from other sources that may have an impact on power or power quality. For example, the EEM monitoring service 120 may collect power related data from an online weather service. The EEM monitoring service 120 may store the power related data received by each IED and categorize the data according to various attributes.
Site 1 illustrates a common logical architecture for an enterprise energy management monitoring system at a typical installation, which may be physically located across one or more geographic regions. Several intelligent electronic devices (IEDs) 122, 132, 142 may be attached at various points of one or more energy distribution networks such as electric, gas, steam, etc. (not shown). At site 1, the IED's 122, 132, and 142 may each monitor energy related devices at different points within a local area network 128. For example, the IED 122 may represent a monitoring device for the gas utility, the IED 132 may represent a monitoring device for the electric utility and the IED 142 may represent a monitoring device for a production line, such as a device which monitors the energy consumption of the machines which make up the production line. A local enterprise energy management server 114 may collect data from one data sources 106, 108, 110, and 112 via the IED's 122, 132, and 142. The IED's 122,132, 142 may push the data to the enterprise energy management server 114 or the enterprise energy management server 114 may periodically poll the data sources for updates, or a combination of both.
In one embodiment, the enterprise energy management server (EEM server) 114 polls the IED's 122, 132, and 142 at various intervals and collects energy related data gathered by each IED. The EEM server 114 processes the data and presents the data to one or more users at the site such as system user 102. A system user 102 may view the data provided by EEM server 114 using laptop computer 101 or other device (not shown).
As described above, an enterprise energy management server 114 may collect power related data from one or more IED's. An EEM monitoring service 120 may collect power related from one or more EEM servers 114. Alternatively, an EEM server 114 may collect data from the IED's directly in addition to or in lieu of collecting data from an EEM server 114. An EEM monitoring service 120 may consist of one or more computing devices. The social data analysis service 116 may provide users with tools for shared views and analysis of the data. The social data analysis service 116 may also consist of one or more computing devices. The social data analysis service 116 may be hosted by the same entity as the EEM monitoring service 120 or it may be provided by two or more distinct entities. The social data analysis service 116 and the EEM monitoring service 120 may also reside in an area of a network such as a demilitarized zone (DMZ) to increase security by minimizing the possibility of intruders from the enterprise energy management server 114 or other sensitive/secure data on a network.
Site 2 includes data sources 118, 122, and 124; IED's 124, 134, 144; laptop computer 154, and system user 104. At site 2, the IED's 124, 134, and 144, and a computer 154 may be connected through the local area network 138. Site 2 may include an alternate configuration of IED's. The IED's 124, 134, and 144 may collect similar energy related data as IED's 122,132, and 142 in site 1 or they may be collecting energy related data from other sources. The laptop computer 154 may include a web based application for monitoring the IED's 124, 134, and 144 of Site 2. More specifically, instead of having an EEM server 114 as is provided at site 1, at site 2, the user subscribes to an EEM service that acquires data from the site, archives it and offers the data back to the user as a service. Thus, at site 2, the IED's 124, 134, and 144 send their associated energy related data directly through a central online EEM service 120 provided by an electric utility entity or an online service provider which archives, process and presents this data to one or more site 2 users. Thus, a system user 104 can view energy related data associated with site 2 through an online software tool. This approach may have an advantage of simplifying EEM monitoring system deployment because an additional/dedicated server may not be required.
A web service 106 represents one or more additional external data sources which may offer data relevant to the analysis of energy use at a local site, such as data which may have an impact on power distribution, power consumption and/or power quality. A web service 106 may be offered locally or remotely from a particular local site. For example, a web service 106 may include a weather data provider, such as a weather service company, which provides the hourly ambient temperature readings, or other real-time or forecasted weather related data. This data may be correlated with energy consumption data for energy management purposes.
The EEM monitoring service 120 may also include an attribute mapper module 420. The attribute mapper module 420 may correlate various attributes to the data sets collected by the user data module 410. A tag is generally a piece of data representative of the value of a particular attribute. For clarity herein, attributes, and their possible values, and tags, and their possible values, will be referred to interchangeably. Exemplary attributes include company affiliation, industry, geographic location, areas of expertise, or other data attributes of interest. The EEM monitoring service 120 may further include a security layer module 430 to ensure the collected data is stripped of any sensitive data that is specific to a site or a user. For example, the security layer module 430 may remove data representative of the associated company name or the exact physical or logical location of the site from the data set. The security layer module 430 may also remove additional data depending on configurations/settings made by users who are part of the social data analysis network and have chosen to upload their data to the repository 440. The security layer module 430 may help provide comfort to users of a social network who may be concerned their data or other confidential information may be exposed to the entire community or other users coupled with the wide area network 118 (shown in
The social data analysis service 116 may include a manipulation module 455, a data module 455, profile module 435, repository module 425 and a user access module 415. The data layer 445 retrieves, or is provided with, the data from the data repository module 440. Once the data is obtained, the social data analysis service provides a medium for viewing, analysis, and additional configurations of data through the manipulation module 455 and the profile module 435. Once data is manipulated, the data may be stored in a repository 425. The repository 425 may contain several databases. For example, one database may store the manipulated energy related data and another database may store the categorized data prior to manipulation. The profile module 435 will be discussed in greater detail in
A number of methods are used to highlight the relationships between data sources, measurements and users, including the use of profiles containing metadata.
Data shared on an online service is searchable by attributes contained within its profile, and can be incorporated into data analysis operations. For example, a building manager wishes to view energy consumption versus external temperature. However, the building manager may not have temperature related data for the site for which the building manager is responsible. A search on the online service may turn up an NOAA (National Oceanic and Atmospheric Administration) data source with interval temperature measurements for the building manager's location. The building manager will now be able to incorporate this data into the analysis. In another example, users can highlight a data set or analysis result (their own or one shared via the online service) and add comments. Such user comments can be organized as a discussion thread and can be searchable by other users. Users may also be able to control who has access to their data and what data they are willing to share with others through the online service. The user selection can make use of user profile metadata. For example, an industrial energy engineer may choose to share process energy consumption with everyone in his company and key account representatives at his local electric utility. Users can also share a data set and ask others to provide possible solutions to a question related to the data set or a more general question regarding configuration. Once a working solution is found, users can provide positive feedback to those who provided the solution within a rating system that builds the reputation of those who helped within an area of expertise. A rating system can also help other users with a similar problem can decide whether or not to implement the proposed change/follow the received advice.
Using the informal tagging classification approach, a user may identify the same location simply by the labels “IL”, “Chicago” and “Michigan Avenue”. These labels have no defined relationship with each other; a tagging classification approach typically does not enforce a hierarchy for labels. This informal approach does, however, allow users to quickly create their own tags. A user may, for example, add a label “Northwest corner” as an additional location descriptor for a monitoring location. To minimize multiple tags that describe the same concept (such as “Michigan Avenue” and “Michigan Ave.”) methods such as tag clouds and auto-completion of tags may be used. The attributes and tagging approaches are not mutually exclusive. A monitoring system may employ both for adding metadata to data sources, measurements and users. For more details on attributes, see copending U.S. application Ser. No. 11/845,630 entitled “Alarm Management Using Source Attributes.”
While various embodiments of the invention have been described, it will be apparent to those of ordinary skill in the art that many more embodiments and implementations are possible within the scope of the invention. Accordingly, the invention is not to be restricted except in light of the attached claims and their equivalents.
