Nobody disputes windpower’s variability; that’s a given. But modern approaches to demand management, grid integration and wind forecasting are making windpower more predictable and grid friendly....
Forecasting brings wind energy under control.
time, as wind forecasts improve and become more tightly integrated into the control room, system operators will become more comfortable relying on wind power to serve load requirements. Given the nature of the wind resource, and the critical importance of maintaining reliability and security, wind might never be used as firm capacity. But already forecasting is raising the value of wind generation, both in system operations and wholesale energy markets.
Energy traders, for example, use wind forecasting data in highly sophisticated and integrated ways to improve their ability to predict market prices. And utilities and wind facility owners use forecasting data—both site-specific and centralized models—to inform their operational and marketing decisions. “They’re making choices about whether to rely on wind megawatts on an hour-ahead or day-ahead basis, or to buy backup power,” says Michael Grundmeyer, a vice president with 3Tier. “They’re making long-term decisions about how much peaking capacity to buy or trade, and for making purchase decisions on natural gas and tolling options. They’re looking at how much wind will displace the fuel on the margin, because if the wind falls off, it has an effect on the price of fuel.”
In some organized markets, traders are using wind forecast data to help them decide whether to buy or sell financial transmission rights (FTR). “Forecasts help traders figure out where wind megawatts will land and at what time,” Grundmeyer says. “That helps them manage the transmission they can access.”
And ISOs, too, are looking to financial trading data about wind energy to help them better plan their system-balancing needs. “Intra-day capacity commitments in the market feed into our current and next-day operating assessments,” says McMullen of the Midwest ISO. “If the amount of wind that’s been financially cleared is significantly off from our forecast, we’ll use that information to make commitment decisions. We monitor that as the day goes on.”
Closer integration between various types of forecast data might someday lead toward a closed-loop approach to EMS that would require less hands-on decision making by control room operators. Such automation could provide quicker responses to fast-changing conditions on the system.
“The way power systems are operated today, they have quite a lot of human oversight,” says Lauby of NERC. “But the smart grid implies dispatching distributed resources in an automated way. Over time, with artificial intelligence and learning systems, it’s possible that dispatch signals on the bulk-power system will get somewhat more automated—under the oversight of skilled operators.”
Sullivan of KEMA agrees: “Europe already is heading in that direction,” he says. “In existing decision support systems, you could attach specific resources and demand to an algorithm. We have enough sophistication right now to close that loop.”
With increasing accuracy in wind forecasting, and increasingly intelligent grid and control-room systems, the concept seems genuinely possible. And as wind farms and other variable resources play a larger role, smart balancing of wind and load will become practical for both economic and reliability purposes.
“We’ve got a lot of wind on the system, and the lights stay on,” says Storck of 3Tier. “It hasn’t