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Finally, the shape of the HVAC model provides important clues about the home’s thermal performance upon which to base further analysis. The balance temperature—the outside temperature at which the home needs neither heating or cooling because of heat gains from appliances and the sun−is noted as approximately 60oF. Thermal physics suggest the balance temperature is the ratio of these heat gains to the envelope heat coefficient (the heat loss per degree F indoor-outside temperature difference). The slope of the heating and cooling parts of the curve indicate the ratio of the heat loss coefficient and the heating or cooling system efficiency, respectively. The information that can be derived from a smart grid’s infrastructure can provide deeper and much more valuable insights into the performance of individual buildings and populations of customers than simple analysis of monthly bills. With the advent of AMI, near-real-time communication systems, and the advanced data management and demand response control strategies, a smart grid may be capable of: • providing simple diagnostics of energy systems to provide early detection of problems • supporting high-fidelity M&V of savings from energy efficiency programs • ensuring the persistence of savings from energy efficiency over time • data mining to identify customers with significant energy efficiency opportunities • providing detailed feedback to customers on how to reduce their energy costs and carbon footprint • analyzing the effects of behavior on energy consumption for populations of customers • attributing carbon credits to utilities or customers, as appropriate. The first two bullets are mechanisms analyzed in the next two sub-sections of this report. It is important to understand what, if any, the marginal costs for deploying a smart grid capable of delivering these benefits are. The cost of AMI and associated communication systems are justified by other services preformed, and near-universal deployment of AMI in a smart grid is generally a given. The time resolution provided can bring about some of these potential benefits. The additional insight provided by the disaggregation of the total load into end uses in homes and small commercial buildings is dependent upon the deployment of smart thermostats, at a minimum. These thermostats need to be capable of providing on/off status for heating and cooling back to a home or building’s local area network, or the AMI meter itself. Such capabilities are available today and by 2030 we assume such thermostats will be nearly universal, since enough consumers will be participating in demand response programs to drive marginal hardware costs down to negligible levels. This assumes that direct load-control approaches, which do not require a thermostat but simply interrupt power to a device, are not the predominant form of demand response. This assumption is based on industry trends to more consumer-friendly approaches using thermostats, and the diminishing differential in cost between the two approaches. Electric water heaters are likely to be similarly equipped (with load-control devices capable of reporting on/off status) in parts of the country, because they are important targets for demand response today, and involve little perceptible sacrifice in amenity. Smart appliances are the focus of an intense development effort on the part of manufacturers today. If utility programs provide incentives such as 3.16PDF Image | The Smart Grid: An Estimation of the Energy and CO2 Benefits
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