There’s no question that today’s economic, regulatory and business uncertainties are challenging energy and utility executives to redefine the very foundation of their competitive value. In a market environment where even the basic rules and regulations are vague — and continually evolving — attaining and sustaining a tangible competitive advantage, while also meeting tough demands for improved reliability and customer response, can be daunting.
The many years utilities have spent redefining their business processes and the automation tools that support them have resulted in much more streamlined operations, while also significantly improving personnel productivity. Automated systems for the management of outages, customer information, work orders, mobile work forces and other critical operations have long become the norm, and investments in distribution automation have resulted in systems that operate more efficiently, with fewer outages, as well as assets that are better utilized and maintained.
The New Wave in Utility Automation
Today, we’re at the starting point of a new evolution in utility automation – one that’s driven not so much by new technologies, as in previous years, but by the ability to more fully leverage the information that’s already been created and is stored in the data archives maintained by every utility. The new generation is not focused on what’s taking place on the distribution network, but rather on better leveraging data – one of our most abundant yet most under-utilized resources - to reveal why specific events happen. It is focused, in general, on transforming data into knowledge that can then be analyzed to bring about positive business results. And in an era where costs can only be cut so far, finding new ways to achieve bottom line results is critical.
For many years, utilities have been archiving the operational (real-time) and non-operational (historic) information captured by the systems they’ve installed to automate numerous processes – SCADA, substation automation (SA), outage management (OMS), customer information (CIS), work management (WMS), mobile workforce management (MWM), enterprise resource planning (ERP) and geographic information systems (GIS) used to manage the distribution network.
Today’s thought leadership shift is to focus on how this archived operational and non-operational data can be combined with emerging analytic functionality to meet a host of business needs, for example, to more readily identify parts of the network that are at the greatest risk of potential failure. If integrated properly, heads-up information stored by these systems can also aid utilities in proactive replacement or reinforcement of weak links, thus reducing the probability of unplanned events. And this is just the tip of the iceberg when it comes to ways in which data can be transformed into knowledge that fosters business success.
The Data Mart
A recent study conducted by IBM showed that today, the typical company utilizes only 2% to 4% of the data collected in operational systems. Data marts are one way to more fully leverage and use data to produce measurable improvements in business performance.
A data mart, as defined in this article, is a repository of the measurement and event data recorded by automated systems. This data might be stored in an enterprise-wide database, data warehouse or specialized database. In practice, the terms data mart and data warehouse are sometimes used interchangeably; however, a data mart tends to start from the analysis of user needs, while a data warehouse starts from an analysis of what data already exists and how it can be collected in such a way that it can be used later. The emphasis of a data mart is on meeting the specific demands of a particular group of users in terms of analysis, content, presentation and ease-of-use.
Most automated utility systems are installed by the vendor with built-in data marts developed specifically to archive data for that problem domain. For some utilities, this means a decade of logged historical performance data is available for integration and analysis.
More recently, additional benefits and returnson- investment have been realized through the integration of – and sharing of data among - these systems. Integration has not only minimized redundancy in data creation and maintenance but has also created operational threads that share data and provide all personnel in the organization with access to information critical to the reliability, safety and fitness of the distribution network.
Integration in Practice
Each data mart contains the information relevant to the system that recorded it, for example:
Today, many utilities routinely mine individual data marts created by these individual systems for purposes like analyzing historical work order logs to identify transformers needing refurbishment or replacement and reviewing ERP archives to determine revenue generated from individual infrastructure components. Much greater value will be derived, however, from the ability to integrate these rich information resources. The next step is to analyze these data marts as cohesive units, a logical consideration since these automated systems work together within the context of utility operations. However, the stumbling block to analyzing these data sets in an integrated fashion has been the lack of a practical methodology or a product designed to handle disparate data sources.
Benefiting from Data Mart Integration
Through the integration and analysis of archived operational data and non-operational data, utilities can provide their personnel, specifically the engineering staff, with valuable system performance and reliability information that can result in more productive use of assets. This information will enable the utility to better understand where to focus future investments in the replacement, maintenance and upgrading of facilities.
Data mart integration will also provide maintenance operations personnel with more accurate details of how each sub-system and component performed under actual operating conditions, especially during peak loads. Based on this information, they can better prioritize which assets need attention and where scheduled work can be deferred on equipment that is performing above specifications.
In another example of the benefits of data mart integration, planning engineers can leverage performance and reliability information on switching and conductor materials to analyze the impact of scaling material quality up or down. With real data available to them, planners will have a more accurate and cost-effective view of what quality materials should be used in a specific installation, saving money by not over-building the equipment.
Integration in Practice
KEMA is currently assisting the Los Angeles Department of Water and Power (LADWP) with the integration of key information and control systems for over 20 user groups, including substation operators, control center operations, transmission and distribution engineering and planning. This energy control system upgrade project requires an assessment of the information requirements across LADWP for the SCADA and substation automation systems, as well as strategic planning for implementation of a new information management infrastructure.
The information will flow from power system monitoring equipment through IEDs over a new fiber-optic wide-area network (WAN) and into a real-time data mart. This centralized storage will provide secure access to analog and status readings (operational data), as well as fault event logs and oscillography (non-operational data). The readings will be synchronized using GPS clocks to provide “sequence of events” capabilities necessary to determine the exact causes of complex outages.
Several technologies will be evaluated to determine the final architecture. OSIsoft™ PI has become a leader in the management of real-time plant information, and will likely play a vital role in data acquisition from various sources, as well as provide efficient storage of the flood of analog and digital readings. Additional OLAP (on-line analytical processing) tools may be used to tie enterprise information together into a comprehensive data warehouse. One of the goals of the first phase is to ensure that a solid foundation is built, upon which additional capabilities can later be added.
Executives, management, analysts and operations personnel will all have access to the data using linked spreadsheets, an intranet web portal and customized screens organized to display the data in the format best suited to support specific job tasks. Users will have the ability to get up-to-the minute readings, find peaks over various time periods, display alarm and status indicators, and view historical trends over any desired timeframe.
Jack Waizenegger, the LADWP electrical engineer managing the project, explains that one of the goals of the energy control system upgrade project is to enable easy access to valuable power system information by building an electronic bridge from the control system to the enterprise network. Previously the energy control system, the legacy SCADA and RTU system, and each system protection relay was its own island. The same was true for every meter, voltage regulator and so on. Waizenegger says, “Replacing current manual efforts to collect and process data with an integrated information network between systems and user groups will increase efficiency, reduce costs and provide excellent decision support tools.”
The LADWP looks forward to harnessing the benefits of the upgrade project. “We’ve penciled out tangible savings by improving the efficiencies of both our machine and human processes,” says Waizenegger. “We can also see possible decreases in the duration of unplanned outages. And our customers will be direct beneficiaries of these time and money savings.”
The LADWP example is just one of many ways that utilities can benefit by integrating data marts into a “one-stop shop” repository for the retrieval of information that’s critical to both strategic and tactical operating decisions. The integrated data mart concept will soon be regarded as essential tools in the business environment of the modern utility.
GIS as an Integration Tool
Another approach for integrating data marts is through a tool that many utilities already have in place – the GIS. If the GIS and the automated components of other systems already exist, utilities can integrate data from the OMS, WMS, MWM, CIS, ERP, SA Systems and SCADA with GIS, which in turn, will feed integrated data to an engineering analysis tool.
Why the GIS? A GIS is, in effect, a “live” map of the distribution network and its individual components. It links infrastructure assets to a land base with a real-world coordinate system. The architecture of the GIS is ideally suited for integration of data marts because it was designed to accept input from different data sources and relate them to each other for thematic analysis.
Leveraging the GIS, users can pinpoint where events occurred, or are projected to occur, within the network model and then view and analyze the facilities relative to this time and place of the event. By using the GIS to overlay associated data points, engineers can more readily see how multiple smaller events escalate to a major event like an outage. Incidents that once seemed unrelated can thus be viewed from a new perspective, revealing trends that might not otherwise have been detected.
Once data from the various data marts have been integrated and georeferenced, the GIS can feed a composite view of this data to an off-the-shelf engineering analysis and modeling tool designed to measure system performance and predict infrastructure reliability.
Conclusion
There are several approaches for implementing an integrated approach to data marts, but theses approaches all have one thing in common. When implemented correctly, integrated data marts - and the ability to analyze these data marts as cohesive units in an integrated fashion - have the power to put information about the distribution system – and customers – onto the desktops of every department in the enterprise for analysis. And when accurate, timely information is available to personnel at all levels, everyone starts making better decisions - and that benefits the entire organization, along with the customers it serves.
About the Authors
Dean Zastava is Director of iAdvantage services for KEMA Inc. He has more than 30 years of experience in the utility industry, both as a utility employee and private consultant. He has held leadership positions in projects for gas and electric utilities, pipeline companies, and municipal utilities in the North America and Asia. He has recognized expertise in planning and directing the implementation of utility information technology solutions where customer service and work process optimization are important features of the delivered solution. Zastava provides unique added value to clients’ system integration and business process change initiatives. Zastava can be reached at dzastava@kemaconsulting.com
John McDonald is a Senior Principal Consultant and Manager of Automation, Reliability and Asset Management with KEMA Inc. With three decades experience in the electric utility industry, McDonald has developed power application software for both Energy Management System (EMS) and Distribution Management Systems (DMS) applications, developed distribution automation and load management systems, managed EMS and DMS projects, and assisted Intelligent Electronic Devise (IED) suppliers in the automation of their IEDs. McDonald, the IEEE PES President Elect, currently assists electric utilities in substation automation, distribution SCADA, communications protocols and DMSs. McDonald can be reached at jmcdonald@kemaconsulting.com
The many years utilities have spent redefining their business processes and the automation tools that support them have resulted in much more streamlined operations, while also significantly improving personnel productivity. Automated systems for the management of outages, customer information, work orders, mobile work forces and other critical operations have long become the norm, and investments in distribution automation have resulted in systems that operate more efficiently, with fewer outages, as well as assets that are better utilized and maintained.
The New Wave in Utility Automation
Today, we’re at the starting point of a new evolution in utility automation – one that’s driven not so much by new technologies, as in previous years, but by the ability to more fully leverage the information that’s already been created and is stored in the data archives maintained by every utility. The new generation is not focused on what’s taking place on the distribution network, but rather on better leveraging data – one of our most abundant yet most under-utilized resources - to reveal why specific events happen. It is focused, in general, on transforming data into knowledge that can then be analyzed to bring about positive business results. And in an era where costs can only be cut so far, finding new ways to achieve bottom line results is critical.
For many years, utilities have been archiving the operational (real-time) and non-operational (historic) information captured by the systems they’ve installed to automate numerous processes – SCADA, substation automation (SA), outage management (OMS), customer information (CIS), work management (WMS), mobile workforce management (MWM), enterprise resource planning (ERP) and geographic information systems (GIS) used to manage the distribution network.
Today’s thought leadership shift is to focus on how this archived operational and non-operational data can be combined with emerging analytic functionality to meet a host of business needs, for example, to more readily identify parts of the network that are at the greatest risk of potential failure. If integrated properly, heads-up information stored by these systems can also aid utilities in proactive replacement or reinforcement of weak links, thus reducing the probability of unplanned events. And this is just the tip of the iceberg when it comes to ways in which data can be transformed into knowledge that fosters business success.
The Data Mart
A recent study conducted by IBM showed that today, the typical company utilizes only 2% to 4% of the data collected in operational systems. Data marts are one way to more fully leverage and use data to produce measurable improvements in business performance.
A data mart, as defined in this article, is a repository of the measurement and event data recorded by automated systems. This data might be stored in an enterprise-wide database, data warehouse or specialized database. In practice, the terms data mart and data warehouse are sometimes used interchangeably; however, a data mart tends to start from the analysis of user needs, while a data warehouse starts from an analysis of what data already exists and how it can be collected in such a way that it can be used later. The emphasis of a data mart is on meeting the specific demands of a particular group of users in terms of analysis, content, presentation and ease-of-use.
Most automated utility systems are installed by the vendor with built-in data marts developed specifically to archive data for that problem domain. For some utilities, this means a decade of logged historical performance data is available for integration and analysis.
More recently, additional benefits and returnson- investment have been realized through the integration of – and sharing of data among - these systems. Integration has not only minimized redundancy in data creation and maintenance but has also created operational threads that share data and provide all personnel in the organization with access to information critical to the reliability, safety and fitness of the distribution network.
Integration in Practice
Each data mart contains the information relevant to the system that recorded it, for example:
- SCADA contains operational data and nonoperational data from all the field devices connected to the SCADA system.
- The substation automation system contains operational data for SCADA and the data warehouse, as well as valuable nonoperational information from all substation devices for the data warehouse, and subsequently for mobile workforce management, maintenance management, and other utility systems.
- The outage system data mart stores historical information on the time, duration and cause of outages, as well as the customers impacted by each outage, actual operating network configurations and switching logs.
- The mobile workforce management data mart archives records of inspection observations and preventative maintenance performed in the field, along with logs on personnel productivity.
- Work management system data marts maintain a history of work orders pertaining to facility maintenance and installation, as well as information on construction crew productivity.
- The customer information system maintains billing and load data and tracks trouble calls made by customers, along with the recorded levels of customer service response.
- Enterprise resource planning systems record the financial investment in each component and its current book value.
Today, many utilities routinely mine individual data marts created by these individual systems for purposes like analyzing historical work order logs to identify transformers needing refurbishment or replacement and reviewing ERP archives to determine revenue generated from individual infrastructure components. Much greater value will be derived, however, from the ability to integrate these rich information resources. The next step is to analyze these data marts as cohesive units, a logical consideration since these automated systems work together within the context of utility operations. However, the stumbling block to analyzing these data sets in an integrated fashion has been the lack of a practical methodology or a product designed to handle disparate data sources.
Benefiting from Data Mart Integration
Through the integration and analysis of archived operational data and non-operational data, utilities can provide their personnel, specifically the engineering staff, with valuable system performance and reliability information that can result in more productive use of assets. This information will enable the utility to better understand where to focus future investments in the replacement, maintenance and upgrading of facilities.
Data mart integration will also provide maintenance operations personnel with more accurate details of how each sub-system and component performed under actual operating conditions, especially during peak loads. Based on this information, they can better prioritize which assets need attention and where scheduled work can be deferred on equipment that is performing above specifications.
In another example of the benefits of data mart integration, planning engineers can leverage performance and reliability information on switching and conductor materials to analyze the impact of scaling material quality up or down. With real data available to them, planners will have a more accurate and cost-effective view of what quality materials should be used in a specific installation, saving money by not over-building the equipment.
Integration in Practice
KEMA is currently assisting the Los Angeles Department of Water and Power (LADWP) with the integration of key information and control systems for over 20 user groups, including substation operators, control center operations, transmission and distribution engineering and planning. This energy control system upgrade project requires an assessment of the information requirements across LADWP for the SCADA and substation automation systems, as well as strategic planning for implementation of a new information management infrastructure.
The information will flow from power system monitoring equipment through IEDs over a new fiber-optic wide-area network (WAN) and into a real-time data mart. This centralized storage will provide secure access to analog and status readings (operational data), as well as fault event logs and oscillography (non-operational data). The readings will be synchronized using GPS clocks to provide “sequence of events” capabilities necessary to determine the exact causes of complex outages.
Several technologies will be evaluated to determine the final architecture. OSIsoft™ PI has become a leader in the management of real-time plant information, and will likely play a vital role in data acquisition from various sources, as well as provide efficient storage of the flood of analog and digital readings. Additional OLAP (on-line analytical processing) tools may be used to tie enterprise information together into a comprehensive data warehouse. One of the goals of the first phase is to ensure that a solid foundation is built, upon which additional capabilities can later be added.
Executives, management, analysts and operations personnel will all have access to the data using linked spreadsheets, an intranet web portal and customized screens organized to display the data in the format best suited to support specific job tasks. Users will have the ability to get up-to-the minute readings, find peaks over various time periods, display alarm and status indicators, and view historical trends over any desired timeframe.
Jack Waizenegger, the LADWP electrical engineer managing the project, explains that one of the goals of the energy control system upgrade project is to enable easy access to valuable power system information by building an electronic bridge from the control system to the enterprise network. Previously the energy control system, the legacy SCADA and RTU system, and each system protection relay was its own island. The same was true for every meter, voltage regulator and so on. Waizenegger says, “Replacing current manual efforts to collect and process data with an integrated information network between systems and user groups will increase efficiency, reduce costs and provide excellent decision support tools.”
The LADWP looks forward to harnessing the benefits of the upgrade project. “We’ve penciled out tangible savings by improving the efficiencies of both our machine and human processes,” says Waizenegger. “We can also see possible decreases in the duration of unplanned outages. And our customers will be direct beneficiaries of these time and money savings.”
The LADWP example is just one of many ways that utilities can benefit by integrating data marts into a “one-stop shop” repository for the retrieval of information that’s critical to both strategic and tactical operating decisions. The integrated data mart concept will soon be regarded as essential tools in the business environment of the modern utility.
GIS as an Integration Tool
Another approach for integrating data marts is through a tool that many utilities already have in place – the GIS. If the GIS and the automated components of other systems already exist, utilities can integrate data from the OMS, WMS, MWM, CIS, ERP, SA Systems and SCADA with GIS, which in turn, will feed integrated data to an engineering analysis tool.
Why the GIS? A GIS is, in effect, a “live” map of the distribution network and its individual components. It links infrastructure assets to a land base with a real-world coordinate system. The architecture of the GIS is ideally suited for integration of data marts because it was designed to accept input from different data sources and relate them to each other for thematic analysis.
Leveraging the GIS, users can pinpoint where events occurred, or are projected to occur, within the network model and then view and analyze the facilities relative to this time and place of the event. By using the GIS to overlay associated data points, engineers can more readily see how multiple smaller events escalate to a major event like an outage. Incidents that once seemed unrelated can thus be viewed from a new perspective, revealing trends that might not otherwise have been detected.
Once data from the various data marts have been integrated and georeferenced, the GIS can feed a composite view of this data to an off-the-shelf engineering analysis and modeling tool designed to measure system performance and predict infrastructure reliability.
Conclusion
There are several approaches for implementing an integrated approach to data marts, but theses approaches all have one thing in common. When implemented correctly, integrated data marts - and the ability to analyze these data marts as cohesive units in an integrated fashion - have the power to put information about the distribution system – and customers – onto the desktops of every department in the enterprise for analysis. And when accurate, timely information is available to personnel at all levels, everyone starts making better decisions - and that benefits the entire organization, along with the customers it serves.
About the Authors
Dean Zastava is Director of iAdvantage services for KEMA Inc. He has more than 30 years of experience in the utility industry, both as a utility employee and private consultant. He has held leadership positions in projects for gas and electric utilities, pipeline companies, and municipal utilities in the North America and Asia. He has recognized expertise in planning and directing the implementation of utility information technology solutions where customer service and work process optimization are important features of the delivered solution. Zastava provides unique added value to clients’ system integration and business process change initiatives. Zastava can be reached at dzastava@kemaconsulting.com
John McDonald is a Senior Principal Consultant and Manager of Automation, Reliability and Asset Management with KEMA Inc. With three decades experience in the electric utility industry, McDonald has developed power application software for both Energy Management System (EMS) and Distribution Management Systems (DMS) applications, developed distribution automation and load management systems, managed EMS and DMS projects, and assisted Intelligent Electronic Devise (IED) suppliers in the automation of their IEDs. McDonald, the IEEE PES President Elect, currently assists electric utilities in substation automation, distribution SCADA, communications protocols and DMSs. McDonald can be reached at jmcdonald@kemaconsulting.com
