The green movement has created new marketplace opportunities with the emergence of intelligent green software. Industries, traditional and emerging, will soon be affected by the adoption or disregard of such technology as they move into some version of energy peak load or variable electrical pricing (where the current price is determined by the power load on the grid).



In the not-so-distant future, companies will need to prepare for the application of intelligent green software that will automatically manage specific aspects of production, distribution and consumption of electricity. This technology will enable energy customers (whether they are industrial, commercial or residential) to make smart decisions about their energy usage to cut electric bills and electricity consumption to just what they need. The good news is that this technology will not only help foster the production of efficient, smart appliances, but it will also encourage consumers to become more energy conscious and therefore more energy efficient.

The basic premise is simple. There will be devices that will automatically turn certain appliances on and off under conditions specified by the consumer. If you combine this with variable pricing in electricity and allow consumers to make decisions about which appliances to run based on the cost of running them, then you have a potential for consumer cost savings as well as power consumption reduction.

Such relatively simple devices are a significant part of smart grid technology proposals, though some proposals go even further. Some propose that the devices be used for energy suppliers as well as energy consumers. In the smart grid context, such devices can be powerful leveraging tools for consumers, enabling them to sell back power to the utilities if they have generating capacity themselves (such as from rooftop solar panels) or if they use plug-in hybrid cars.

These devices may even give consumers the capability of arranging with the utilities to buy power at a low price when the load on the grid is low, and sell it back to the utility at a higher price when the load on the grid has risen. Interestingly this benefits the utilities, since widespread adoption of such measures can save them building new plants to meet peak capacity needs.

Surprisingly, much of this technology has already been developed. It simply needs to be deployed. Test programs have shown consistent success, such as the GridWise Olympic Peninsula project, a study done by the Pacific Northwest National Laboratory. In this study, households were given digital thermostats and computer-controlled water heaters and dryers. The participants would then set the power usage of the devices based on the price of electricity at any given moment. For example, they would set the target temperature for their house, an acceptable range of variation, and their price tolerance (to the changing price of electricity). Every few minutes the devices would adjust their power usage based on the current price of electricity.

The test found that these households saved more than 10% on their yearlong electricity costs. But what energy policy planners found to be most revealing was not so much that the residents were able to reduce their consumption and save money but more surprisingly how the devices encouraged participants to alter their attitude and behavior to decrease their consumption because they now had the tool to actively monitor their consumption. This reinforces the notion that feedback is the best motivator to get people to change their habits. Weighing oneself on a scale is a perfect example of how a device can motivate people to lose weight.

From the electric utility's point of view, new startups like Grid Net are working to develop the software that will make full smart grid systems a reality. The software systems being developed for use by the power utilities take advantage of modern computing and networking technologies to increase the information available to utilities about the state of the power grid.

The ultimate goal is to build power grids that can manage their own load spikes automatically, with spare generators being brought online via software triggers (say when the alternating current frequency dips below a certain level, which is a sign of high load on the grid), or power being transferred from other parts of the grid to meet demand in nearby areas, all without human intervention).

At present, few of these software technologies are deployed or even easily purchasable. While in some cases, the technology is well understood and well developed (e.g., software to power down appliances when the electrical grid is under heavy load), it is not widely available yet for those who want to use it now.

What smart green software is pointing to is the urgency to begin planning NOW for this inevitability to help protect industries and consumers from rising energy costs.