Data Acquisition and Change Control

Data is the foundation of any grid modernization program.

Therefore, it is vital to consider the following three pivotal data components on your journey towards grid modernization:

  • Data Conversion,
  • Data Remediation, and
  • Data Change Control

As part of Data Migration and Conversion process, having an understanding of all systems and software data requirements is critical to enable successful and sustainable integration on Smart Grid implementations. Data requirements for vendor products tend to get intensive and challenging to interpret. Our approach is to simplify product data requirements in order to ensure understanding among utility stakeholder groups.

Operation of Smart Grid technologies depends heavily on complete, accurate and current data. The data backbone of Smart Grid systems takes its shape based on business requirements brought forth by the operational and management systems. The challenge in building the data infrastructure that meets DMS and OMS accuracy and latency requirements is that utilities tend to have this required data captured in disparate and dispersed source systems which often operate in silos. This includes digital structured and unstructured data and paper copies of regional maps or manufacturer specifications. The data requirements for building a multitude of Smart Grid application components become further compounded with introduction of SCADA signals in DMS and OMS to support real time data acquisition. And data surrounding SCADA signals is frequently unstructured yet mission critical for DMS applications so defining a roadmap to integrate SCADA signals into your data change processes.


Foundational Data Analysis

InfraGrid collaborates with you to identify all data sources and data elements that are available within your enterprise (including paper documentation) to determine where real data gaps exist in order to support your Smart Grid systems. This data requirement to source mapping is then used to establish the data gap universe that exists within your enterprise and defines the data infrastructure bridge we need to create to support your required DMS, GIS, or OMS network model.

This data gap analysis forms your roadmap for establishing your data foundation. Collecting millions of new data points is no doubt a transformation in itself and costs can quickly add up. For each of the data gaps we outline we conduct a feasibility and cost/benefit analysis of gathering each data element to help you make a go-no go decision, the resources required to gather data and the timelines to collect, compile and populate the data elements. Our consultants are adept at identifying various approaches to close data gaps by identifying any data conversion, integration, or migration tasks that will expedite data collection. We also help you with performing manual data remediation where automation is not an option to meet your Smart Grid data requirements by helping identify unstructured data sources such as test sheets or study data and also leveraging standard engineering defaults. This data road map also defines any network data retrofitting and approach that would be required acquire SCADA signal data to enable DMS real time information from field devices.

For our clients, we have designed and built foundational data source systems such as GIS, utility specific power system asset databases and expanded existing data models and schemas of incumbent source systems within the enterprise. Our aim is to build complete source data platform to serve your Smart Grid applications and represent a current and accurate operational network model that’s sustainable and affordable within utility business practices.

Data Change Control

Utility data is constantly changing as you expand services to new customers, perform capital work, and continue maintaining the grid. The Design to As-Built process takes time to make its way form paper or electronic mobile records into operational systems. The volatile characteristic of data within utility poses an inherent challenge to keep the data current with a level of accuracy that is good enough for Smart Grid applications and operations. While we work towards building the right data foundation and convert the network model to be utilized by your Smart Grid applications, InfraGrid also establishes best practices within your utility to establish a workable and cost effective business processes to establish Data Change control systems and protocols. These systems are established by reviewing your existing standard work procedures and integrating critical data elements that need to be updated as field changes are made. Our consultants have deployed technologies, processes, and work instructions to standardize Dx Data change to augment existing data maintenance workflows to help keep data sources, and hence your smart grid applications, current from network model standpoint.

4ii GIS – IC

InfraGrid works towards building your data and helping you bridge the data gap with an aim of making your data accurate, latent, yet sustainable while also establishing Data Change control processes and workflows to keep your network data current as your designs are in-serviced in the field or as your crews make break-fix changes to repair an outage.