The Challenge of Smart Grid Data
The Challenge of Smart Grid Data
Utilities undertaking efforts to improve efficiency, customer service and deliver always-on reliability face a broad range of challenges. Today, the dramatic evolution of utility distribution grids includes a focus on the integration of powerful information systems to complement generations-old power flow networks.
“Utility information, and the data networks which support it, is changing from high-latency, batch-oriented processing to low-latency, streaming and asynchronous real-time operations”
Utility information, and the data networks which support it, is changing from high-latency, batch-oriented processing to low-latency, streaming and asynchronous real-time operations. These new data requirements include measurement data, alarms, event logs, status data, and most importantly, system controls commands. In addition, the old paradigm of single purpose independent operational networks is going away and these networks are increasingly interconnected – so no operations group can control and operate without fear of interfering with others.
This transformation of data is happening not only in grid operations, but also in the customer experience and energy markets arenas. Coupled with the change in data types, data volumes are also rapidly increasing. This increasing wave of data creates additional opportunities to use grid-related data. New metrics are being developed as opportunities to develop actionable intelligence mature. This challenge expands as new constituents place new demands for distribution and customer information that the utility possesses.
As utility operations become more technology dependent, increasingly steeped in data and communications technologies, the organizational challenge becomes determining how, and by whom, the technology should be managed. Traditional utility IT organizations have focused on Enterprise class software systems (such as ERP, Finance, HR, Payroll) and vertically applied software systems (such as GIS, Asset Management, CIS). These traditional applications support the highly centralized, high latency, batch oriented characteristics described above.
In contrast, operational technologies trend towards having significant number of inputs from millions of sensors sending near real time data. They are more “field” oriented, often requiring bucket trucks and lineman to access equipment located in restricted zones. They tend to be highly decentralized and are evolving toward distributed computing environments as the Smart Sensors become more Smart Computing Endpoints that communicate directly to each other rather than through centralized applications. The complexity of the technologies and networks is rapidly exceeding the capabilities of traditional operational groups to effectively manage them using their traditional operations processes.
Finally, the applications of powerful data analytics tools, data visualization, and data mining is becoming a key requirement to effectively leveraging this new Grid Data Network. It’s through these analytics capabilities that utilities will be able to actually apply this technology to facilitate improvements in the safety, reliability, security, and cost effectiveness of the distribution of electricity, as well as the integration of new distributed energy sources, and the improved engagement of customers in the process.
So, who should own the Smart Grid Data Network?
The dilemma created by the integration of these new capabilities is to effectively manage these burgeoning new technologies without burdening operational effectiveness. The ultimate goal is to
fully leverage the technologies while maintaining the agility and responsiveness required of utility operations groups. Inherent in this dilemma is the question; should operations groups manage the technology themselves and develop IT skills in data management, software management, and configuration management? Or should IT manage the technology but integrate operations into a “partnership” of combined purpose, shared asset management responsibilities, and a mutual culture of operational agility?
Part of the answer may lie in whether there is a logical demarcation point between Enterprise Networks and Grid Controls Networks. Potential points of demarcation between IT and operations might include:
■ Grid Application Servers
■ Grid Communications Network Controllers
■ WAN - Network Backhaul collection points
■ NAN - Mesh and/or Network take-out points
■ Smart Grid endpoint communications modules
■ Smart Grid endpoint devices
■ In-Home Communications networks
■ In-Home devices
Any of these points along the Grid Data system could be “owned” by IT or Operations (or perhaps both in a well-defined asset management model). However, designating a definitive demarcation must have a logical basis for optimized and effective Grid Data and Network management. There are many considerations for suggesting the basis of this demarcation point, including:
■ Internet Protocol (IP): The extent to which IP is the basis for data transmission within the Grid Data Network’s architecture such that standard network tools (and traditional network management IT processes) can be applied. Proprietary vendor protocols and specialized network management tools are still very prevalent even though “standard” protocols may be used. Thus, well-honed IT processes, based on network management tools developed for IP networks may not be applicable to Grid Network management needs.
■ Scale: The number of network nodes encompassing a Smart Grid Data Network may be exponentially larger than a traditional Utility Enterprise Data Network. As each Smart Endpoint becomes a data network node, the sheer scale of the network and data flows to be managed become significantly larger than traditional IT Enterprise networks. Thus, the logical demarcation may be aligned to layers of the Smart Grid architecture which are purely communications nodes rather than integrated Sensor/Controller/ Communications nodes. This may also enable better alignment to the Asset Management governance model and the expected asset owner for the various Smart Grid elements.
■ Security: Smart Grid devices and data networks which enable grid controls (and therefore carry significant safety and reliability responsibilities) are appropriately governed by a set of security compliance requirements developed by the North American Electric Reliability Corporation (NERC). While IT data networks (and IT governance processes) also adhere to strict security compliance regulations, the NERC requirements are developed uniquely for Grid Controls. Thus, devices governed by NERC compliance may be uniquely managed by those who carry other NERC compliance requirements.
Where do we go from here?
The challenge of rapidly expanding Smart Grid data networks will force an evolution of technology management strategies at utilities. To successfully prepare for this next phase of network and data management, these strategies will need to include:
■ A strategy for IT and operations to come together to jointly manage Smart Grid Data Networks. This strategy must effectively combine the strengths of IT and operations by joining these two functions in partnership rather than a “takeover” by one or stove-pipe exclusion of either. A well-defined asset management and responsibilities governance model will greatly assist with this transformation.
■ A strategy for leveraging the accelerating amounts of Smart Grid data through specific, operations focused data analytics use cases. As more data comes faster, a focus on value prioritized and action-specific analytics use cases will enable the effective leverage of Smart Grid technology by grid operators and the continuous extraction of value from the Smart Grid Data Network.
■ A steady transition towards standards based Smart Grid systems to enable deeper, non-proprietary toolsets and more repeatable, reliable IT governance processes for Smart Grid data networks.