To transform our current infrastructure into this kind of self-healing smart grid, several technologies must be deployed and integrated. The first step is to build a processor into each switch, circuit breaker, transformer and bus bar—the huge conductors carrying electricity away from generators. Each transmission line should then be fitted with a processor that can communicate with the other processors, all of which would track the activity of their particular piece of the puzzle by monitoring sensors built into their systems.

Once each piece of equipment is being monitored, the millions of electromechanical switches currently in use should be replaced with solid-state, power-electronic circuits, which themselves must be beefed up to handle the highest transmission voltages: 345 kilovolts and beyond. This upgrade from analog to digital devices will allow the entire network to be digitally controlled, the only way real-time self-monit-oring and self-healing can be carried out.

A complete transition also requires digitization of the small, low-voltage distribution lines that feed each home and business. A key element is to replace the decades-old power meter, which relies on turning gears, with a digital meter that can not only track the current going into a building but also track current sent back out. This will allow utilities to much better assess how much power and reactive power is flowing from independent producers back into the grid. It will also allow a utility to sense very local disturbances, which can provide an earlier warning of problems that may be mounting, thereby improving look-ahead simulation. And it will allow utilities to offer customers hour-by-hour rates, including incentives to run appliances and machines during off-peak times that might vary day to day, reducing demand spikes that can destabilize a grid. Unlike a meter, this digital energy portal would allow network intelligence to flow back and forth, with consumers responding to variations in pricing. The portal is a tool for moving beyond the commodity model of electricity delivery into a new era of energy services as diverse as those in today’s dynamic telecommunications market.

The EPRI project to design a prototype smart grid, called the Complex Interactive Networks/Systems Initiative, was conducted from 1998 to 2002 and involved six university research consortia, two power companies and the U.S. Department of Defense. It kicked off several subsequent, ongoing efforts at the U.S. Department of Energy, the National Science Foundation, the DOD and EPRI itself to develop a central nervous system for the power grid. Collectively, the work shows that the grid can be operated close to the limit of stability, as long as operators constantly have detailed knowledge of what is happening everywhere. An operator would monitor how the system is changing, as well as how the weather is affecting it, and have a solid sense of how to best maintain a second-by-second balance between load (demand) and generation.

As an example, one aspect of the EPRI’s Intelligrid program is to give operators greater ability to foresee large-scale instabilities. Current SCADA systems have a 30-second delay or more in assessing the isolated bits of system behavior that they can detect—analogous to flying a plane by looking into a foggy rearview mirror instead of the clear airspace ahead. At EPRI, the Fast Simulation and Modeling project is developing faster-than-real-time, look-ahead simulations to anticipate problems—analogous to a master chess player evaluating his or her options several moves ahead. This kind of grid self-modeling, or self-consciousness, would avoid disturbances by performing what-if analyses. It would also help a grid self-repair—adapt to new conditions after an outage, or an attack, the way a fighter plane reconfigures its systems to stay aloft even after being damaged.

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