The Federal Role in Electric System R&D During a Time of Industry Transition: An Application of Scenario Analysis
The U.S. electric power system is in transition from one that has been centrally planned and controlled to one that will rely increasingly on competitive market forces to determine its operation and expansion. Unique features of electric power, including the need to match supply and demand in real time, the interconnectedness of the networks through which power flows, and the rapid propagation of disturbances throughout the grid pose unique challenges for ensuring the reliability of the system. These challenges are likely to become even more difficult in the future. As the reliability events of 1996 and the market events of 1998 and 1999 demonstrate, the reliability of the grid and the integrity of the markets it supports are integral to the nation's economic well-being. This white paper is one of six commissioned by the Department of Energy (DOE) Transmission Reliability Program to establish a foundation for a multi-year program of federally funded research, development, and demonstration (RD&D) projects to maintain and enhance the reliability of the U.S. electric power system as the electricity industry undergoes restructuring. In this white paper, we develop scenarios that represent four possible states of the industry during the next three to 10 years. We outline the RD&D they require and describe appropriate federal roles in making these investments. Specific aspects of the scenarios, their RD&D needs, and federal priorities are explored in greater depth in the other five white papers. The four scenarios we developed should not be confused with predictions or even end states that we believe are necessarily desirable. We assume that all forecasts are wrong, but that the value of the scenarios is in the thinking they inspire regarding what the future could be, and what is needed to get there. Using the scenarios as a starting point, a robust set of federal priorities that is consistent with a variety of possible futures can be identified.