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The Path of Least Resistance
By James Cormier-Chisholm |
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The author outlines a way to reduce worldwide greenhouse gas emissions and save billions of dollars in the process ( published in the UK Petroleum Review in June of 2005).
Countries are wasting millions of tonnes of coal, natural gas, and oil every year. This is due to electrical lines being placed in areas where power lines are being exposed to conditions that promote loss of electricity.
Fortunately, an easy way is proposed here to increase power line efficiency. The solution will not only lower fossil fuel consumption and greenhouse gas emissions, it will save hundreds of billions of dollars and increase per capita income levels. And the fix can be applied now. |
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The issue of power line losses came to my attention in June 2004, when I was doing research as to why California was suffering from a series of blackouts. In looking at power line distribution data from the US, a surprising set of relationships were found which formed the basis of a new viewpoint on more efficient power distribution. These relationships were picked up by a nonlinear spline regression analysis. Spline data mining is not new; the technique as a drafting technique began hundreds of years ago with boat building. As the computer age developed, mathematicians transferred this old but useful shipbuilding technique into mathematical formulas and algorithms for use in computer systems. By the 1990s, statisticians developed spline regression analysis to model complex nonlinear data statistical data. |
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When applied to power loss data, the technique uncovered a previously unknown statistical relationship between power loss and altitude above mean sea level. In addition, it picked up a second relationship between air moisture content and power line losses. Simply put, power lines have less power line loss in regions where there is less moisture, or regions that are at higher altitudes, (See Figures 1 and 2). |
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Figure 1. Power Line Losses Vs Altitude Above Mean Sea Level |
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Why does this correlation exist? Power line losses occur through a process called heat of resistance; electrons move through the wires, heat of resistance converts some of the electrical energy into wasteful heat. Resistance in the wires increases as air temperature increases; the hotter the air, the more electrical energy is converted into heat. As you go lower in altitude, air temperature generally increases, as does power line losses. Most of this loss occurs at altitudes below 400 feet (122 meters) above mean sea level. By simply shifting power lines above this mark, power line losses can be reduced significantly. |
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Figure 2 % Surface Water to Dry Land Relates to Power Loss |
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Power line losses also occur through leakage; electricity leaks through line insulation into the air as a field of force around power lines. The amount of leakage rises as humidity rises. As can be seen in Figure 2, air moisture is positively correlated with wasted energy. By moving power lines away from bodies of water, power line losses can be reduced significantly. Did engineers miss these relationships for over 100 years? |
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Well, yes and no - ever since the first electrical grids were constructed, engineers understood heat of resistance loss was a major waste in electrical energy transport. But heat of resistance was primarily understood as being linearly related to distance travelled. So engineers optimized for distance between cities, towns and electrical generation stations. Engineers made straight lines on a map, and shaped the electrical grid that way. |
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However, those original power line loss studies assumed an ideal temperature of resistance, ignoring the fact that over large geographic distances, temperature and moisture content of air vary greatly. Engineers essentially took a lab value for heat of resistance and air moisture content, and projected these "ideal" values over the entire electrical grid system. These "rule of thumb" lab values then passed into textbooks and became ingrained engineering practice. In reality higher regional ambient air temperatures and moisture air levels means power lines traveling through higher temperature and moisture regions suffer higher heat of resistance and electrical power line loss than predicted in textbooks.
The Power of the Pocketbook |
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The power loss work led to an observation; in regions where power losses were highest, factories suffer higher costs for electricity on average. This means less money to pay workers. In contrast, people working for factories in regions where power losses are less tend to have better pay. |
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A further spline regression analysis was carried out to try predicting per capita income levels using the same input variables as used for power line losses, i.e. altitude of US States and the ratio of water to dry land by US State. The results correlated very closely, as seen by a comparison of predicted per capita income levels by US State to actual levels of per capita income (Figure 3). In other words, climate predicts power line losses and power line losses predicts part of your pay check. This is the first example of a demonstrated relationship between per capita income and climate. |
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Figure 3. Regression Spline Analysis using altitude and ratio of water to land predicts average per capita income levels by US State accurately
What if power lines were put up higher?
The analysis predicts a group average increase of US $2,400 if all high-tension power lines are raised above 400 (122 meters) feet in altitude. The highest capital gain would be in New York State, increasing by US $3,227 in average per capita income (highest income gain of all US States). The least income gain, at US $1374, is Louisiana. If we take all the income increases by US State across all States, and multiply these income figures by the working population by US State, an overall national income increase for the US of $352 billion per annum is possible.[1]
In addition, if you shift power grids to reduce losses by altitude and moisture, the same amount of electricity can be created using far fewer fossil fuels. The US department of Energy predicts that the country will create 5,985 million metric tonnes of carbon dioxide emissions while producing electricity in 2005. Shifting the power lines would reduce greenhouse gas carbon dioxide emissions by approximately 13.8%, or by 831.1 million metric tonnes, more than enough to meet Kyoto Protocol guidelines.
Monetary savings would also be significant. If power lines were raised on average above 400 feet, the statistical formula predicts that reduced electrical wastage would produce a savings of US $98 Billion per annum.
So, what can be done?
The easy answer is to simply shift as many electricity lines as possible so that they are away from large bodies of water and above 400 feet in altitude. However, in the developed world a lot of money has been invested into the existing power grid and it would be expensive to duplicate them. Even though the advantages are obvious, it would also take several years to approve rights of way for new transmission lines. There is also the issue of political will.
Fortunately, the data points to 'low hanging fruit', where significant gains can be made quickly. The selfsame spline regressive data mining formula could also be used to map where these low hanging fruit are and also provide optimal new pathways could be laid for future power transmission lines. As for the entire transmission grid, lines require periodic maintenance, and much value can be obtained by simply raising their height. Longer term solutions, such as shifting lines away from the coast into hill country, promoting sectors of the economy (like Silicon Valley) that use a lot of electricity into higher altitude areas and shifting population centres to higher altitudes can follow over generations. The Third World, which has a less-developed grid, can benefit from programs that properly site new lines so that they benefit from efficiencies right from the beginning. Through applied knowledge, humanity can increase the efficiency of its electricity system, meet and exceed Kyoto obligations and save billions of dollars. All that is required is the will to act.
Biography
Jim Cormier-Chisholm is owner of Data Forest Mining, Inc., a data mining consultant firm. A native of Cape Breton Island, Canada, Cormier-Chisholm holds a degree in Geology and an MBA with specialization in financial statistical data mining from Saint Mary's University. He has spent the past 13 years working for Environment Canada as a consultant and as a geoscientist for the mining industry. He can be reached at: [email protected]
[1] US Census Bureau, Working Population Figures by US State, Found at: http://factfinder.census.gov/home/saff/main.html?_lang=en&_ts= |
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