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intensive peak load generating sources to less CO2-intensive intermediate or base-load power plants. This presents an interesting future where demand response and distributed generation resources can be managed on strictly economic-based criteria, strictly CO2-based criteria, or a mixture of both. • To realize the estimated reductions the smart grid can deliver, two offsetting increases in consumption need to be accounted for. The first assumes that a server is needed in every distribution substation to monitor end-use loads, provide two-way communications with customers and, where user permitted, provide automated demand response. The number of distribution substations is unknown, so an assumption of 100,000 substations is made based upon an estimated 300 to 400 thousand feeders and 3 to 5 feeders per substation. Each server is expected to draw 1kw for every hour of the day throughout the year, thus increasing expected energy consumption by nearly 1 B kWh/year. The second assumes that demand response/GFA devices are installed in the entire stock of 466 M appliances (heat pumps, air conditioners, dryers, refrigerators, and freezers) (EIA-AEO 2008), individually draw a load of 1 to 5 w every hour of the day throughout the year, to additionally increase expected energy consumption by 4 to 20 B kWh. The combined effect of the two offsets may increase the 2030 electric utility sector energy and CO2 emissions by 0.1% to 0.4%. While the increase is small and may not be considered important, it does point to the need for technology developers to minimize the increased loads of smart grid technologies. 5.4PDF Image | The Smart Grid: An Estimation of the Energy and CO2 Benefits
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