The Smart Grid Research Consortium (SGRC)


The US electric system is in the initial stages of a “smart grid” transformation that many have compared to development of the telephone system, the interstate highway system and the Internet. The smart grid provides advanced communication, automation and control of the entire electric system from generating plants to the operation of electric equipment inside homes, commercial buildings and industrial plants. Smart grid programs improve utility system efficiency and reliability, reduce utility operating costs, enhance customer participation in energy management, and reduce the need for new generating plants, carbon dioxide emissions and energy consumption.

However, utility investments required to implement comprehensive smart grid initiatives are substantial and many smart grid hardware and software technologies are just now evolving with limited experience to evaluate options. Many utilities are concerned that some smart grid investments may not pay for themselves over time or that mistakes in making near term smart grid decisions may increase costs and limit benefits.

Determining the business case for smart grid investments is especially difficult for electric cooperatives, municipalities, and other publicly owned utilities because of their typically smaller size, limited staff and the greater importance of fixed costs relative to the number of their customers. However, coops and publicly owned electric utilities reflect an important part of the electric infrastructure providing 24 percent of total US electric sales and 31 percent of residential electric sales.

In spite of their important role in the US electric system, cooperative and municipal utilities have received much less research, media and vendor attention with respect to smart grid issues than investor-owned utilities.


The SGRC was initiated at Texas A&M University early in 2010 to develop and apply a comprehensive cost/benefit smart grid analysis framework for application at electric cooperatives, municipal and other public utilities. The Consortium was developed and led by Dr. Jerry Jackson, an energy economist with 30 years' experience in new technology market analysis, electric utility modeling and forecasting and financial analysis and a Texas A&M professor.

The SGRC transitioned to an independent research and consulting firm in January 2011 with Dr. Jackson as the Leader and Research Director. Objectives of the SGRC remain the same: to assist electric cooperatives and public utilities quantitatively evaluate smart grid investments including developing investment strategies, evaluating vendor proposals and assessing ongoing investment programs.

SGRC developed the industry's first and only quantitative, utility-detailed, smart grid financial investment analysis framework for municipal and cooperative utilities. This framework, the Smart Grid Investment Model (SGIM)TM has been applied for 16 cooperative and municipal utilities.

The SGRC Difference  

Several characteristics make an SGRC smart grid investment analysis unique:

  • Development and application of utility-specific customer class end-use (e.g., residential AC) monthly hourly load profiles to determine system load impacts of individual smart grid technologies and programs
  • Implementation of the comprehensive Smart Grid Investment Model (SGIM) quantitative financial analysis model
  • Optional implementation of the SGIM at utility sites
  • Free SGRC continuous maintenance of each utilities SGIM model after project completion
  • Ability to revisit utility SGIM analysis at any time in the future without "reinventing the wheel" saving time and money.

SGRC Research  

Part of the SGRC mission is to address and incorporate new smart grid issues in the Smart Grid Investment Model and applications analysis. This commitment ensures that each member utility will always have access to relevant technical and program issues in the future. Impacts of substation and feeder-level DA and Volt/VAR initiatives and detailed customer engagement program analysis are two current ongoing research and analysis development areas.