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Monday, March 2, 2009

Electric Power Version 2.0

This post is a bit technical and likely of little interest to most of our customers, but we thought some of you might like to understand a bit more about smart grids and how they might work. Most local folks would be surprised to learn just how deeply involved the team at Glasgow EPB is in the work to change everything about how electricity is generated, distributed, and consumed. So, here goes...


We owe much of our prosperity over the last century to our discovery of electricity and the ways to generate, transmit, and use it to perform work. However, it turns out that nearly every method we devised to generate electricity has also generated problems with our environment and our weather. Perhaps it is time to upgrade electricity to release 2.0 and give it a new name, infotricity.

Infotricity is a product we have been experimenting with in Glasgow, Kentucky for many years. It is derived by combining the regular flow of electricity (think of it as the inorganic chemistry) with a flow of information which we know as the internet (think of it as sunlight), which results in a new product, infotricity (think of it as organic life). This is a virtual solution, not one where the actual wires are twisted together. Rather, it is a philosophy that all electric power delivery should be accompanied by a robust broadband connection which provides the intelligence for the workhorse. Once electric current is combined with, and controlled by, the river of bits, our theory is that the sum is much greater than the individual parts. If we are correct, then infotricity is to electricity as blood is to water, as a symphony is to a metronome, or as a summer breeze is to an air compressor. Infotricity is nearly organic.


Electricity is infinitely strong, but the resources we use to generate it are clearly finite and diminishing. Electricity is also infinitely mindless and clearly inorganic. If you come up with a way to generate an electromotive force, give that force a conductor, and connect that conductor to a load, and electric current will flow into that load and work will be accomplished until one of those elements is removed.

So, since electricity is unable to restrain itself from doing work until its fuel source is exhausted or the conductor is cut, we have turned the job of controlling it over to a number of equally dumb devices, mainly thermostats and timers. These guys are not in the mensa club either, yet we have entrusted them with making all the decisions about how we use billions of dollars worth of electricity each day. Further, they get to decide how much coal we burn, how much enriched uranium we need, how much water is released from hundreds of hydroelectric plants, and how much natural gas we burn to make electric power. Even though the electric bill comes to you and me, the decisions on how much energy bought were made by a $30 thermostat on your wall and a whole bunch of its $9 cousins in all of your other home appliances. And here is the real problem with that; these guys never talk to each other.

Since these thermostats and timers never talk to each other, one might then assume that they would then command the flow of electric power in a totally random and chaotic fashion which, in turn, would produce a demand for electric power in such a diverse pattern that the summation of all electric loads in a home, plotted against time, would produce a relatively flat horizontal line. But that is not the case. Instead, left on their own, these devices conspire to produce a demand for electric power which is rhythmic and tuned. In fact, an average day of electric power consumption for your home likely looks a lot like a simple sine wave. Surprisingly, there is a geometry to this chaos.

Does that mean that electricity is alive? Hardly. Does that mean it has intelligence? Absolutely not. However it does mean that our circadian rhythm has a great deal to do with our home’s use of electric power also having a circadian rhythm of its own. It means that those thermostats in your home are responding to the residents, the temperature and to the time of day by acting totally on their own. The result is a demand shape that is shaped like a sine wave, and that is very problematic. And it gets worse.

It turns out that, much like in nature where a microscopic examination of a leaf reveals tree and branch structures that are a miniature copy of the totality of the tree, the sine wave shape of energy usage at your home is similar to the shape of total daily energy usage on your street. This energy usage is nearly identical to the usage for your community, and that shape is the same as that of the total energy demand on the utility that serves your home. Hundreds of millions of dumb thermostats somehow, without talking to each other, conspire to produce a sine wave shape for the total daily energy consumption of North America. For example, the largest public utility in our country, TVA, has a daily load shape that looks exactly like the simple sine wave previously described for a single house.

Fractal geometry is at work here, and the result is that we have a very high demand for energy, which results in large amounts of coal being thrown in the fire to produce the energy needed to meet that peak, which only lasts a few hours per day. This is another huge issue, because it is far more efficient to operate generation in the sweet spot of each generator’s efficiency curve twenty four hours a day, instead of trying to force them to follow this sine wave rhythm. So, what we really need here is some chaos. We need to de-tune this circadian rhythm and flatten out the load shape.


In each of our bodies, fifty trillion cells live in harmony sharing energy, information, and purpose. They are united by a robust communications network and they are organized by a spectacular piece of software running on a powerful processor carried between our ears. In 2009 is it not possible to use a broadband network and some slightly less complicated software to convince twelve million motors and appliances within a region like the one served by TVA to live in similar harmony? If we replace the electricity, which powers those appliances today, with infotricity; if we replace water with blood, then we should be able to enjoy a symphony instead of the rhythmic ticking of the metronome.

Each time slice of the daily demand curve for TVA is made up of two hundred eighteen blocks representing the energy demand from each of TVA’s distributor utilities and the other directly served industrial customers. Those blocks are made up of the nine million smaller blocks, which represent the individual homes and businesses that connect to the distributors. Finally, each of those nine million blocks is made up of the discreet loads; the appliances, motors, heaters, and lighting loads, which live in each of our homes and businesses. It is the chance stacking of each of those blocks that adds up to create each point along the sine wave shape of our daily demand curve.

The daily infotricity demand curve could be shaped differently, with much lower peaks and more shallow valleys, resulting in dramatic reduction in the amount of generation necessary at the hottest and coldest parts of the day and the virtual elimination of the most expensive and least efficient generation sources. A broadband network and some very good software would make this possible.

While today’s electric power demand curve is established by the cadre of deaf and dumb thermostats and timers, the infotricity demand curve would be sculpted by fully conversant software and telecommunications. Each of the discreet loads could be assigned an IP address. Each IP address could, in turn, be assigned a geometric form, a polygon. Then, all the software would have to do is organize the polygons like the pieces of a puzzle, into a daily demand curve that has a lower amplitude than the wave we experience today wherein none of the loads are controlled.

Of course, this would be far from simple. The music for this symphony could not be written overnight, but today’s high speed telecommunications and processors seem to have plenty of capacity to make the calculations and deliver the messages. Surely we can also assume that the same folks who write software and applications like iGoogle and Google Earth can also pull off Electricity 2.0.

Using historic energy consumption information for each meter combined with historic weather and calendar data, an algorithm could be developed for predicting the anticipated load shape on a day-ahead basis for each meter. Once robust broadband and IP based thermostats, appliance controls, and water heaters are installed to the home or business, and an inventory of the individual loads and the associated predictable usage information and other thermodynamic data about the location are collected, the software could start ascribing a two-dimensional model of each discreet load.

As mentioned above, the two dimensional models could be described as polygons, with the height equal to the projected load in watts and the base equal to the anticipated run time. Of course, the run-time would also have a certain amount of flexibility depending on the thermodynamics of the home, the habits of the residents, and the efficiency of the appliance. For example, the polygon ascribed to a water heater would not be simply the wattage of the heating elements and the length of time necessary to fully heat the volume of water in the tank. The polygon would be described by the wattage and time necessary to warm the water from its present temperature to the target temperature at the time predicted by the resident’s next likely need for the hot water. Obviously the same would be true for the HVAC needs of the location. It is assumed that the residents would offer a certain bandwidth of acceptable temperature for the air in the location, and that this acceptable bandwidth would also need to be recognized by the operating software. This would allow flexibility in the dimensions of the polygon ascribed to the HVAC load for the location. Thus, the software assembling the puzzle pieces would also have the option of re-sizing the polygons to make them fit.

It is the complicated nature of the variables and the need for IP based temperature sensors, and other IP based controls necessary to predict the need for energy, that makes it reasonable to assume that very high capacity broadband networks will be required for an organic smart grid. Further, it is clear that an exceedingly complex piece of software to operate over that network and connect generation plant and end user devices will be required for the creation of infotricity. The transactions described here are far from simple command and control conversations, rather, infotricity delivery and the endless number of calculations necessary to make it perform organically will approach the complexity of a living organism.

Once data and algorithms are developed that result in the definition of a polygon for all of these discreet loads, the software would be tasked with assembling those polygon puzzle pieces into a daily load shape. This shape would likely still be a sine wave, but one which is dramatically dampened, as the individual fractals that support it are each detuned and scattered.

Each load would communicate its status and its need to operate via an IP address through the broadband network to the control software. At the same time, the software would be studying the weather and the predicted load shape for the address. Then, its job would be to organize the loads into a shape which is flatter than the one predicted. As this is done for individual addresses, the software would also predict the new controlled load shape for the individual home and all of the homes at the various fractal levels; the street, the town, the region, and the utility universe, attempting to arrange the new sine wave peaks to occur at different times so that the load shape for each fractal area is as flat as possible. This is how an organically modeled infotricity network might function. Obviously, this is a daunting task, but impossible? Not likely.


For the first one hundred years of our utilization of electric power, the work done by electricity had no understanding of the source or limitations of the energy. To a large extent, neither did we, the consumers of the work and the designers of the electric power networks. Electricity 1.0 was inorganic and we allowed unsophisticated devices to decide how high our peak demands were. We looked at those peaks as impossible to change. In fact, we established rates and growth policies that added to their height, and we simply burned more coal and natural gas to meet them.

Infotricity (Electricity 2.0) could forever change this unwieldy and inefficient way of accomplishing our work. The robust broadband networks are available. The IP addressable thermostats, controllers, sensors, and appliances are within our reach. The software can be written. Sophisticated interfaces that will help us all visualize our infotricity usage are being written, and we will be able to get them on our computer screens, television screens, and wall displays.

Where the electricity network has been built in huge rectangular blocks that are ill-fitted to provide power for sine wave shaped demand, the infotricity network will assemble demand to closely match the output of our cleanest and most efficient generation units. When more wind power is available, the infotricity network will maximize demand when the wind output is available. When electric vehicle production grows, the infotricity network will recognize these new loads and assign them polygons of capacity which will fit within the targeted daily load shape.

Clearly, some of this discussion is theoretical. Telecommunications and technology can no doubt reduce peak demand, but just how much is not known. We can visualize discreet loads as polygons, but can software be designed to assign those polygons to run times in anything like the way our circulatory system distributes oxygen to vital organs? If not, how close can we get?

It seems plausible that we can make dramatic improvements. Such improvements might mean that nearly all of our least efficient generation sources, combustion turbines that burn large amounts of precious natural gas, might be moth balled. If the software is just a little bit better than that, then we can start retiring some of the oldest and dirtiest coal fired plants. By the time we get to Electricity 3.0, maybe we will be smart enough to actually start fueling our total needs with nuclear power, and the remainder with totally renewable resources like hydroelectric power, wind power, geothermal power, and biomass power. Perhaps infotricity will power a totally sustainable way of life for us all.

Is anyone ready to write that software? If so, let’s call it Sunshine, because inorganic chemistry plus sunlight equals organic chemistry, and we certainly need some new life around here.