The day is sweltering, air conditioners are cranked up, and the power grid is straining to meet demand. Today is a “needle peak” day — on the annual power demand chart, it shows up as a spike. Out of the year’s 8,760 hours, needle peaks will occupy 200 hours or less. An extreme day like this is why the grid maintains roughly twice as much power generating and transmission capacity as it uses on an average day. Even though power plants and lines are idle most of the year, this costly overbuilding is needed to cover all contingencies. The grid is built to be there “just in case.”
But what if another power resource were available that could dramatically reduce that peak demand, one that involved generating and transmitting no power at all? No, this isn’t some weird “zero energy” thing. The paradoxical sounding resource I’m talking about is already in use. It’s the demand, also known as the load, itself. The basic idea is that the grid can meet overall needs not only by supplying power, but by adjusting power use. The word for this is demand response, and it’s a fundamental aspect of the smart grid.
On the old “dumb” grid, information flow from power users to suppliers consists almost entirely of 12 meter readings a year; from suppliers to users, it is 12 power bills. One of the most profound changes introduced by the smart grid — indeed, what makes it smart — is a communications backbone that allows massive two-way information flows. An information network is overlaid on top of the power network. Demand response (DR) employs these information/communications capabilities to engage power users directly in managing the grid. In essence, information becomes a new power resource.
DR is one of the first pieces of the smart grid to emerge. Since the 1980s, utilities have worked with customers to place automatic controls on water heaters, air conditioners, and other electricity-hungry devices to lower demand during peaks. Florida Power is a good example, with nearly half a million customers in its program. Utilities work with farmers to control irrigation pumps during peaks. Many grid operators also engage large industrial and commercial customers to reduce load on those super-hot or super-cold days. Sometimes demand response is directly controlled by the utility, but often someone in the building literally goes around and turns off switches.
Typically, the utility provides credits on bills as an incentive to cut loads. From the utility’s standpoint, it’s a complex calculus, balancing DR costs with the avoided costs of serving peaks with standard generation and transmission.
What’s changing today is that the deep decline in costs for computing technologies and communications bandwidth is changing the calculus. DR is becoming easier and more economical. At the same time, the emergence of Independent Systems Operators (ISOs) to run regional power transmission systems is creating vibrant and large new markets for DR. They provide a level playing field where DR can compete with traditional power resources. Companies such as EnerNOC, Comverge, and Energy Connect are aggregating DR loads from multiple customers and marketing them to ISOs, particularly PJM Interconnect, a notably innovative ISO serving the mid-Atlantic states. These companies are offering demand resources equal to large power plants — 796 megawatts in the case of EnerNOC, 948 for Comverge.
DR comes in several flavors, and not all are as sweet for utilities. The basic division is between “firm,” meaning that customer-end equipment is under a form of direct load control (DLC) that makes it completely predictable, and “non-firm,” meaning the load is under customer control. Utilities rely on non-firm DR to reduce costs during peaks and carry them through emergencies. But utility engineers will not cancel a beefed up transmission line in favor of DR unless the load is firm, or “fully dispatchable.” They want to be able to basically turn it on and off themselves. And you can’t blame them; if the lights go out, they’re the dogs.
DR should not be confused with its close relative, energy efficiency (EE). EE seeks to reduce overall power use. DR aims to reduce use at specific hours. Sometimes that means an absolute cut in electricity consumption. For instance, when an air conditioner is cycled down during the day it will not necessarily return to full operation in the evening. But when, say, a hot water heater is turned down, it typically will shift the load to later.
That sets up a potential unintended consequence. DR could actually increase overall pollution. For example, if generation is shifted from daytime hydroelectric or cleaner gas generation to evening coal, then overall emissions could rise. So in designing DR markets, this pitfall needs to be avoided. The New England Demand Response Initiative, a multi-stakeholder group, made sure to take a look at the impacts there and found a small overall emissions reduction benefit on the New England grid from DR.
DR provides some clear environmental benefits. It can serve as a substitute for spinning reserve — power plants that run ready to supply power on short notice, typically around 10-15 percent of overall power generation. The less spinning reserve, the fewer emissions. And DR could sharply reduce the need for peaker power plants and infrastructure, with all their embedded energy and land-use impacts. Pacific Northwest National Laboratory (PNNL) calculates that moving to smart-grid technology will eliminate the need for between $46 and $117 billion in conventional utility infrastructure. That does not count investments in new smart grid technology. But one PNNL calculation gives an indication of comparative costs: smart appliances that can adjust their demand to grid conditions could, for $600 million, provide reserve capacity equal to power plants costing $6 billion, proving that “bytes are cheaper than iron.”
DR has some additional potential for promoting a greener grid, and that potential illuminates key aspects of the smart grid. Advanced DR is built on smart systems that not only control power use by individual devices, but also provide detailed information on power use down to the device. They will let utilities assemble power use data with unprecedented detail. This knowledge can be leveraged for economic value in a number of ways. One is to validate the actual effects of EE programs.
Rob Pratt with PNNL’s GridWise Program gives an example. Say a utility pays for efficiency improvements at a number of houses, and seeks to use the resulting emissions reductions to gain carbon market credits. As more regions move to carbon cap-and-trade systems, such credits will become more valuable and important. With today’s primitive information flow, these reductions could only be approximated, not verified, so gaining credits could be difficult and the utility would have less incentive to make the investments. But validated information can be taken to the carbon marketplace, so the EE is more likely to be done. This is just one of a number of ways in which DR and EE are synergistic. Future postings will delve more deeply into these interactions.
DR might also provide cost-effective, emissions-cutting means to balance intermittent renewable energy sources such as wind. Wind generation varies with availability and intensity of the resource. So wind farms are partnered with reserve power plants that fill the gap when wind speed diminishes. Often these are natural gas turbines, though in the Pacific Northwest hydroelectric dams are employed.
But what if a smart grid could automatically balance wind with adjustments in power demand? Thinking on this is still at early stages, but it is theoretically possible. Since wind varies minute to minute, the system would have to be quite sophisticated and have a broad diversity of demand resources to tap. Fraunhofer Institute modeled such a system for Germany and found “the costs of additional reserve power could be reduced … demand response may be a valuable option for integrating wind power into electricity systems.” Of course, this would also reduce greenhouse emissions by balancing fossil resources.
The application of smart technologies to the grid makes a largely one-way flow of power and information into a far richer and complex two-way stream. The greater the penetration these technologies achieve, the more power demand will become a power resource as well.
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