Last summer, I had an experience that made me realize how, in the future, utility network operators will need to work based on data they get from assets they may or may not own.

When my neighborhood lost power for a half day due to a hailstorm, my “lucky” neighbor invited us to his air-conditioned home, conveniently powered by recently installed solar panels and battery storage! Despite his kind nature, this neighbor’s luck ran out the following week during a rain event when he realized his roof and solar panels had been damaged by that earlier hailstorm.The result was a roof replacement, loss of solar generation for two weeks, and a large bill.

This story provides a glimpse into the evolving problems facing utility network operators today.

Decarbonization is challenging network operators

As a society, we increasingly demand clean energy to decarbonize the planet. In response, utility network operators are investing heavily in technology to modernize the grid infrastructure and design it to accommodate consumer-generated energy, known as the prosumers of the new world.

Most network operators recognize that data assets are as important as equipment assets in order to keep informed about events that affect the energy supply. This includes assets for which, currently, they have less visibility, as more distributed energy resources (DERs) and customer-owned, behind-the-meter (BTM) assets are added - which affect grid operations.

So, if my neighbor’s solar panels go out, will that mean that I can’t charge my EV?

An integrated network data model is needed

While insight-driven decisions increasingly are required to operate digital energy grids, many network operators have “islanded” datasets located within specific business systems - such as geographic information, network management, SCADA, or enterprise asset management systems. By operating data in silos, they risk missing opportunities afforded by managing data assets at an enterprise level.

The International Electrotechnical Commission (IEC) is working to standardize data attributes that model assets that operate on the grid. The IEC 61970/61968 Common Information Model (CIM) seeks to provide a utility distribution network operator (DNO) and vendors with a standard definition of assets that can be used to achieve a simplified and up to date view of the electric grid, installed equipment, existing configuration and operated state.

Network operators need a way to extract, cleanse and load quality data into an integrated network model built on the IEC standards. By taking such an approach, they can move away from disparate “island” datasets into a single holistic view of the entire transmission and distribution network of physical assets.

Enabling value-added services and improved data quality

This approach also enables a holistic view of assets, which allows network operators to develop new business applications that use higher quality datasets to provide enhanced simulation and power - flow analysis and drive artificial intelligence and machine learning to automate decision - making and operate the grid at higher efficiency. Enterprise data asset management can also provide the backbone to improve coordination of data across all enterprise solutions and instigate a continuous improvement approach to prevent data assets from becoming stale and ineffective.

As a technology solution provider, CGI is playing a part in investing in data assets and the technology ecosystem to keep them from becoming irrelevant. We have worked with several clients to establish our CGI OpenGrid360 solution suite to provide the integrated data required to effectively manage asset maintenance, electric outage, new infrastructure construction and report on work performed in the field - and keep my EV charged.

I invite you to read more on this topic in a blog by my colleague Simon Boyer, Solving data challenges to accelerate the energy transition.

About this author

Picture of Steve Ridley

Steve Ridley

Director, Consulting Delivery

Steve is part of the leadership team within the utilities practice of CGI’s U. S. operations. He leads the consultancy practice responsible for identifying solutions that use emerging technologies to help solve current client challenges and anticipate future needs.

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