Smart Grid Investment Trends: Follow the money, Part 1

The two biggest investment drivers right now are the need to improve utility operational effectiveness and connecting renewable energy resources to the grid

The progression of smart grid implementation in North America has been interesting to watch as the focus shifts to different stakeholders and technologies. When I look at the smart grid implementations, new investment trends are emerging. The trickier question is which trend is driving the most implementation and what benefits utilities are able to capture.

The two biggest investment drivers right now are the need to improve utility operational effectiveness – the subject of this blog — and connecting renewable energy resources to the grid. Operational effectiveness encompasses advanced metering infrastructure (AMI), distribution grid management, utility analytics (aka “Big Data”), and distributed energy resources (DERs). In each case, underlying drivers such as aging infrastructure and operational cost pressures are increasingly compelling utilities to invest in new solutions to meet new, more demanding expectations of customers, shareholders, and regulators.

I attended a conference three years ago and one of the speakers said that advanced metering infrastructure (AMI) had “hijacked” smart grid. At the time, the ARRA funding for the DOE Smart Grid Investment Grants was largely focused on AMI projects. In my opinion, this happened for three reasons. Politically, customer engagement is important and many consumers associate the meter on the side of their house with the grid and hopefully link a smart meter to a smarter grid. The second reason is that for many utilities, the business case for AMI is generally positive or at least break even. The business cases looked even better with the ARRA grants covering up to 50% of the project costs. Finally, AMI technology can be deployed within the three-year time frame required by the grants – find out more.

But if we follow the money, many utilities are finding a business case for distribution grid management investments built around improving operational reliability (Fault Detection Isolation and Restoration, or FDIR) and efficiency improvements (Volt/VAr control and optimization, or VVO). The capability to improve operations without having to convince customers to change their energy-use behavior – something that has proven to be a challenge during some AMI implementations – appears to be attractive to utilities.

Additionally, the utility investments in AMI and distribution grid management are pushing another smart grid investment trend: “Big Data”. Meter data management systems are capturing interval data from residential customer meters that can now be provided to consumers, and this data can be analyzed to help define customer usage patterns and preferences for demand response programs. Business intelligence solutions can also provide situational awareness and improved performance for grid operations based on analysis and display of operational information captured by systems such as distribution management systems.

Another “Big Data” play is asset health.Asset health management addresses the industry’s aging infrastructure and aging workforce by managing the process of capturing asset data and using this data to achieve asset reliability performance goals more efficiently. Algorithms and performance models are applied to the data to determine condition and health of assets, to provide situation awareness and identify needed condition-based maintenance, and to execute the asset maintenance that drives grid performance.

Improving operational effectiveness also means using the best of new demand response technologies for peak shaving, load shedding, and load shifting applications to gain more control over energy supply and demand. Today, two-way communications and programmable communicating thermostats or web portals for capturing consumer usage patterns and preferences have enabled more sophisticated demand response programs for residential customers. Commercial and industrial customers are now using demand response for peak shaving to avoid excessive demand charges, load shedding in response to emergency utility requests, production scheduling and load shifting based on electricity market prices, and ancillary services such as spinning reserve capacity and frequency regulation. Aggregators have emerged to offer ancillary services to the energy markets established by regional independent system operators. In each case, demand response represents new business model opportunities to more effectively and efficiently deliver power to end customers.

So far, many investments in DER applications such as distributed generation (i.e. solar PV installations), distributed energy storage, and electric vehicle charging infrastructure, are mostly pilot projects to demonstrate the technologies, quantify the benefits, and gain operational experience. Investment interest is growing in this segment.

In my next blog, I will talk more about interconnecting renewables and also how utilities are managing and monetizing distributed energy resources.

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About the author

Gary Rackliffe

Hello, I lead Smart Grid Development for ABB North America. I have more than 25 years of industry experience in both transmission and distribution (T&D) and have worked with ABB for 19 years across a variety of positions. I hold a bachelor’s and master’s degree in electric power engineering from Rensselaer Polytechnic Institute and an MBA degree from Carnegie Mellon University.
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