Intelligent Electricity

The popular impression of the U.S. electricity grid, often promoted by politicians and industry, is that it is maxed out, constantly on the verge of overload. In fact, the system is grossly oversized, built to handle extreme power demands that occur for only a few hours on the hottest days of the year. In New York City, peak demand is about 35,000 megawatts of electricity. Most of the time, the city’s demand is about 9,000 megawatts less­–equivalent to the output of about nine nuclear power plants. To cope with minute-by-minute changes in electricity supply and demand, grid operators must maintain large reserves of generation and transmission capacity.

Reducing the need for these reserves will mean that fewer power plants have to be built to keep up with increases in demand for electricity, saving $100 billion in construction costs and curbing future greenhouse-gas emissions. Emissions can also be reduced by replacing fossil-fuel plants with zero-emission technologies, such as solar and wind farms.

In the United States, achieving these goals will require tackling an antiquated transmission system. Half of the grid is more than 40 years old. Most of the grid is operated manually and without any real-time knowledge of what’s going on in the field. If one of the aging transformers fails, the local utility may not even know until a customer calls to complain. Such slow responses have already led to cascading power failures, such as one that blacked out 45 million people in the northeastern United States in 2003.

The solution is to construct a network of sensors and controls that will give a detailed picture of the state of the grid in real time and allow rapid reactions to variations in electricity supply and demand–a so-called smart grid. These innovations will reduce the amount of excess capacity that grid operators require and make it easier to integrate renewable sources of energy. [

Sensors on transmission lines will determine how much power the lines can carry, something that varies with temperature. (For now, operators rely on conservative estimates that squander grid capacity.) Monitors installed on transformers will warn operators of problems before they occur, avoiding costly breakdowns and outages. Automated controls on transmission and distribution systems will maintain the grid’s stability, even after intermittent sources such as wind and solar have begun making large contributions. In the part of the grid dedicated to long-distance transmission, most mechanical controls have already been replaced by digital ones that can be operated remotely–a significant step toward a smart grid. All the same, more can be done to speed up response times and further improve sensing.

A handful of demonstration projects are under way to modernize local distribution networks and extend the reach of the smart grid into homes and businesses, helping to smooth demand. Utilities already work with many industrial customers to curtail energy use during times of peak demand. With smart residential power meters, utilities can alert customers as electricity prices rise and fall with demand. Going a step further, automated appliances could respond to price signals from the meter by turning themselves off or switching to low-power mode. If, for example, 250,000 smart clothes dryers were installed in a city, during periods of peak demand, they would offset the output of an entire coal-burning power plant.

Eventually, these technologies could manage the load that plug-in hybrid and electric vehicles place on the grid when they charge. And the smart grid could make it easier for people who install solar panels and micro wind turbines to get paid for the power produced. “Over the long term,” says David Mooney, director of the Electricity, Resources, and Building Systems Integration Center at the National Renewable Energy Laboratory in Golden, CO, “it’s cheaper to put in microprocessors than transformers and power lines.”