Smart Metering: Improving Consumer Energy Efficiency Jessica ...
Smart Metering: Improving Consumer Energy Efficiency Jessica Vasconcellos Virginia Liaison Office July 24, 2009 On my honor as a University student, on this assignment I have neither given nor received unauthorized aid as defined by Honor Guidelines for papers in Science, Technology and Society Courses. Signed:
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Executive Summary Energy consumption in the United States has increased 230% since 1973. In an average residence, large appliances consume over 60 percent of the electricity in the home. By reducing the energy used by these appliances and other electricity consuming devices, the demands for fuel and effects of carbon dioxide emissions will decrease. One of the solutions to decreasing energy consumption is the development of the smart grid. The smart grid uses advanced technologies to improve energy efficiency in all aspects of the electrical grid. On the end user level, the smart grid manifests itself as smart meters that electronically send information to the power companies and provide the consumer with more information to adopt energy efficient habits. In contrast, the current meters installed have mechanical counters. These meters do not promote energy conservation because the only feedback on the consumer‟s energy consumption is a monthly, quarterly or yearly bill. There are a wide variety of meters available but, on average, a 5-20 percent savings can be realized from using a smart metering system. As many of these meters use wireless communication systems, there is an opportunity to develop broadband over power line–broadband delivered via the existing power lines. With access to broadband, programs such as telehealth and distance learning can flourish throughout the Commonwealth of Virginia. As with any system, there are some issues that need to be resolved before success is achieved. In the smart metering system, the meters are using unsecure bandwidth, leaving them vulnerable to cyber attacks. There are also no industry standards for smart meters to guide power companies and smart metering developers. There is minimal funding for smart metering systems and other smart grid applications, but the widespread adoption of these meters requires more extensive funding. Currently, most of the costs fall on the power company or the consumer.
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Table of Contents Executive Summary ..................................................................................................................... i Table of Figures ......................................................................................................................... iii Acknowledgements ................................................................................................................... iv The Proposed Smart Grid ............................................................................................................ 3 Smart Meters .............................................................................................................................. 4 Effectiveness of Advanced Metering Infrastructure................................................................... 10 Evaluation of Smart Meters ................................................................................................... 10 Evaluation of Behavioral Change.......................................................................................... 11 Other Pertinent Issues ............................................................................................................... 11 Smart Metering Recommendation ............................................................................................. 12 Conclusion ............................................................................................................................... 13 Works Cited ............................................................................................................................. 14
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Table of Figures Figure 1. Electrical Grid (GetSmartGrid.org, 2009)……………………………………………………………2. Figure 2. Smart Grid Communication (GetSmartGrid.org, 2009) ....................................................................... 4 Figure 3. Wirelessly Read Meter (Dominion Power, 2009) ................................................................................ 5 Figure 4. Holmes Online Energy Management System (DIY Kyoto, 2009) ........................................................ 6 Figure 5. Tendril Insight (Tendril, 2009) ............................................................................................................ 7 Figure 6. Ambient Orb (Ambient Devices, 2009) ............................................................................................... 7 Figure 7. Google PowerMeter (Google.org, 2009) ............................................................................................. 8
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Acknowledgements
I would like to thank those who have helped me with this project. They have assisted in ways that no amount of literature research would have. Jason Christopher FERC Electrical Engineer Office of Electric Reliability
Julie Simon FERC, Deputy Director Division of Policy Development
Rahim Amerkhail FERC Energy Industry Analyst
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Introduction The United States has been struggling with the reduction of energy consumption in recent years. The current American lifestyle demands a considerable amount of electricity and this amount increases each year. The electricity consumption for United States has grown from 1, 712, 909 million kilowatts in 1973 to 3,891,705 million kilowatts in 2007, almost a 230% increase (Electricity End Usage, 2008). This rate is alarming, as the United States has limited fuel sources and as the concern for the effect of global warming from energy usage becomes more prevalent. In 2001, 31 percent of residential energy consumption comes from the use of heating, ventilation and air conditioning units. Kitchen and laundry appliances consist of another third of residential energy consumption, with refrigerators consuming the most energy (U.S. Household Electricty Report, 2005). This rate of consumption will continue to grow causing the demand on the power system to be even greater. This causes a serious problem on the already strained power system. One solution to this problem is developing a power grid that improves energy efficiency and encourages consumer conservation. Smart grid is an umbrella term that refers to a large array of technologies and improvements to the current electric power system. The term “smart grid” originated from the US Department of Energy‟s Smart Grid Initiative. The Department of Energy defines smart grid as an integrated communication infrastructure that uses advanced sensing communications and control technologies to generate and distribute electricity more effectively, economically and securely (Smart Electricity Grid, 2009). The electric utility industry defines a smart electrical grid as a system where consumers can adjust their consumption of power depending on the availability of electricity (Smart Electricity Grid, 2009). Others define the smart grid as a group of technologies that give the electric grid the characteristics of a computer network (Kaplan, 2009). Generally, the smart grid is an electrical system 1
that provides a two-way communications system between the power company and the end user. This more energy efficient version of the electrical grid requires the use of newer technologies and updates of the current system. Current Electrical System Electrical power is produced in generating plants that burn combustible fuels such as a coal, natural gas, or biomass or from non-combustible energy sources like wind, solar, geothermal, and nuclear. Dominion Power, the most prevalent electric company in the Commonwealth of Virginia, primarily uses coal to provide power to their customers but supplements that with wind, biomass fuels, hydroelectric, and nuclear generating plants (Power, 2009). From the generating plants, transmission lines carry the electricity from the power plant to demand centers. These transmission lines carry extremely high voltage power. Through a series of transformers in the distribution system, the voltage is reduced so that the power can be delivered to the end-user at a usable voltage (Kaplan, 2009).
Figure 1. Electrical Grid (GetSmartGrid.org, 2009) Demonstates the current electrical grid in the United States
In the current electric system, there is only one-way communication where electricity is generated and then passed to the consumer. The consumer‟s usage is recorded through a mechanical meter attached to the house that displays a counter of the kilowatt hours consumed. To be read, a
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technician must travel to each site and record the change in kilowatt hours. If there is an outage, the power company is not aware of it until the consumer notifies the company. Then, to diagnose a problem, a technician must travel to the site and evaluate it on an individual basis. These meters are a burden to both the consumer and the power companies. The only feedback on the consumer‟s energy consumption is a monthly, quarterly or yearly bill. There is no incentive for the consumer to conserve energy during peak hour, when the rate is the highest and the demand for energy is the greatest, because the rate of energy is averaged over billing length. These meters are also inconvenient for the power company because someone must physically travel to each meter and record the reading, creating the millions of tons of carbon dioxide that are contributing to global warming (Faruqui, Sergici, & Wood, Moving Toward Utility-Scale Deployment of Dynamic Pricing in Mass Markets, June 2009). There are also other issues within the current power system that contribute to the inadequacy of the power system such as cybersecurity, reliability, and tracking that will not be discussed here. There have been improvements to the electrical system in the United States but not on the scale of what is required to effectively serve consumers and reduce energy consumption (Kaplan, 2009). The Proposed Smart Grid There are a myriad of different plans and goals to modernize the current power system into the proposed smart grid. These technologies range from advanced meters in homes to more advanced software at the transmission centers. The goals of the smart grid are to better predict energy usage, record energy usage, provide efficient energy, and decrease energy usage. More specifically, the smart grid should monitor the grid‟s conditions, independently detect and diagnose problems and outages, and handle the inclusion of renewable energy sources (Kaplan, 2009). On a residential level, the smart grid should price and supply electricity in order to assist the consumer in making energy efficient decisions about their energy consumption (Kaplan, 2009).
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Figure 1. Smart Grid Communication (GetSmartGrid.org, 2009) Shows the proposed information sharing structure for the smart grid
The power industry has identified five recommendations that will be the most effective in creating an updated smart grid: create more energy-efficient buildings, promote the adoption of more energy efficient appliances, commercialize plug-in hybrid vehicles, support a more energy efficient rate structure for energy consumption, and accelerate the adoption of smart meters and advanced metering infrastructure (Initiative, 2009). Smart Meters Similar to the definition of smart grid, the definition of a smart meter encompasses a large array of metering systems. The main similarity between these meters is that they can communicate back to the power company and provide improved monitoring sources to the consumer. Many of these metering systems rely on broadband in the home. They also create opportunities to implement broadband into buildings that are not equip with this technology. Below are the main types of metering systems. Some meters do not require any additional change to the electrical grid in order to assist in energy conservation. The most basic of these meters is a wireless meter. These meters look similar to the current meters except they have a digital readout instead of a mechanical one.
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Figure 2. Wirelessly Read Meter (Dominion Power, 2009) These meters are similar to current meters with a digital readout instead of a mechanical system
These meters use a wireless technology to transmit information back to the power company. This assists in reporting outages more quickly and conserves energy. It is no longer necessary for a technician to go to each home and read the meter so there is a reduction in the pollution and energy consumption of the trucks (Faruqui, Sergici, & Wood, June 2009). Dominion Power recently initiated a pilot program in Charlottesville, VA installing 46,500 of these wireless meters. It is expected that this program will automatically reduce energy consumption by 4 percent and reduce carbon dioxide emissions by 12,000 tons annually (approximately 2,100 cars). As part of this program, energy usage and billing information will be available on their website (SmartGrid Charlottesville, 2009). Online management tools have become a popular concept for energy and metering companies. These applications incorporate a wide variety of information to provide information to the consumer about their energy consumption. Puget Sound Energy‟s pilot program incorporates an online energy management tool that provides an energy profile that reads every 15 minutes, hourly or daily and updates the next morning. The site also displays a variety of charts, graphs and spreadsheets that display energy usage statistics (Puget Sound Energy, 2009). There are also programs like DIY Kyoto„s Wattson
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and Holmes which is an online program that shows personal energy usage that compares the consumer‟s rate with other Wattson users worldwide (Wired Magazine, 2009).
Figure 3. Holmes Online Energy Management System (DIY Kyoto, 2009) Demonstrates the complexity of online monitoring
This leads to in home devices which show some of the same information as the online management tools, but without the need of a computer. These provide up to date information on the home‟s consumption such as instantaneous energy consumption (in dollars per hour or kW per hour), the cumulative cost of electricity (dollars), power (watts), cumulative electricity consumed (kilowatt-hours), projected monthly bill (dollars), energy translated into greenhouse gas emissions (kg and kg per hour), time, and temperature, depending on the complexity of the device (Faruqui, Sergici, & Sharif, May 2009). An example of these meters is the Tendril Insight meter which tracks kilowatts and cost per hour and communicates to other networked smart devices such as thermostat, electricity meters, outlets and their own internet tracking tool.
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Figure 4. Tendril Insight (Tendril, 2009) Shows a typical in home device and the information that is provided
The meters alert the user to price adjustments and consumption values via audio and visual alerts. Included in this system are outlet controllers which measure and control the energy consumption of standard electrical outlets to track specific appliances. This allows feedback of energy usage (Tendril, 2009). Other types of meters are more subtle when conveying information. A popular meter, the Ambient Orb changes color depending on some market or usage characteristics. (Wired Magazine, 2009).
Figure 5. Ambient Orb (Ambient Devices, 2009) This is an example of the Ambient Orb in residential use 7
There are also more advanced in home devices such as Agilewaves, targeted at higher-end homes and larger buildings. These devices track and manage energy, gas and water consumption in real time from web-enabled devices such as computers and mobile devices (Technology, 2009). This mobile technology aspect is also used in Greenbox technologies. Greenbox can notify the user via text message of peak time rate, high usage, weekly usage reports, and send out tips and recommendations based on usage (Products, 2009). Google has been working with these companies such as Tendril and Greenbox to create Google Powermeter which is an advanced online energy information tool that can be used with any system (Google PowerMeter, 2009).
Figure 6. Google PowerMeter (Google.org, 2009) This is an example of the graphs available in the PowerMeter system
These metering systems to improve user efficiency can also track individual appliances to determine usage and increase the user‟s energy efficiency. Appliance companies, such as GE, are creating Smart Appliance s that interact with these smart metering systems. These appliances include dishwashers, microwaves, heating and air conditioning units, washing machines and other devices that consume considerable amounts of energy. These appliances are fitted with communication technology 8
that can transfer their energy usage as well as monitor the pricing of power and automatically react to these increases. For example, when these appliances detect a peak hour rate they can pause or delay the dishwasher, turn off the light on the microwave, or increase the temperature in the refrigerator until the rates decrease (Research, 2009). This will drastically improve energy efficiency as these major appliances consume about 60 percent of the energy usage in the home. Although these meters are helpful in determining when energy is most expensive, without a change in the pricing system there is a limit to the effectiveness of the smart meters. To be most effective the meters need to rely on a demand pricing system which does not blend the rates of energy throughout the billing period. The demand pricing system charges higher rates during the time that most power is being used and expensive generating plants are functioning (Hsu, 1997). The generating plants used during peak hours are kept idle for the rest of the hours of the year, which equates to system inefficiencies. The cost of these reserve generating plants cause the energy rate to be much higher during peak demand hours than in other hours of the year (Faruqui, Sergici, & Wood, June 2009) . Many of the simpler meters can be purchased and installed by the consumer. The meters that display real-time price signals from the utility are usually more complex and often require professional installation by the utility. (Faruqui, Sergici, & Sharif, May 2009). The pricing of these meters can range between $100 and $175 and can reach up to $525 (Faruqui, Sergici, & Wood, June 2009). These meters do not only help the consumer but also help the power companies to provide improved customer service. All of these meters transmit data back to the companies so that they can track the amount of energy being consumed in each area. This provides the data to the companies so that they can predict high usage, potential issues with service, and other aspects that can more effectively deliver power.
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Effectiveness of Advanced Metering Infrastructure The variety and innovation of these smart meters is encouraging but there are still questions on the effectiveness and the consumer‟s long term commitment to energy conservation. The use of smart meters in the home is a relatively new practice thus long term data is not available yet what data is available indicates that smart metering can be successful. Evaluation of Smart Meters Similar to any user device, user friendly features are essential to any metering system. Meters have been found to be most useful if they show instantaneous usage, total expenditure and historic data (Darby, April 2006) with a computerized display (Fischer, 2008). With an effective unit, consumers can realize a considerable reduction in their electricity bill. There is expected to be an even greater decrease with a dynamic pricing model. In the long term, even those that do not switch their usage to smart meters or dynamic pricing systems will also have a decrease in their electric bills as the high demand plants are no longer necessary (Faruqui, Sergici, & Wood, June 2009). Quantitatively, a conscious effort to look at the monthly energy bill and subsequently adopt habits that are energy efficient without a smart meter result in savings between 0% and 10% depending on the information given. Within this approach, a look at an individual‟s past energy consumption was more effective than observing others‟ energy consumption (Darby, April 2006). In comparison, there is a 5-15 percent savings from using only a metering system (Darby, April 2006). With the use of in home devices and dynamic pricing there is even a greater savings with a decrease of 10-20 percent of electric bills (Faruqui, Sergici, & Sharif, May 2009). Of in home devices, the Ambient Orb was recorded to reduce peak energy consumption by 40 percent. It is believed that this approach is more effective than a one-time alarm or text message because it was a persistent, unobtrusive reminder (Wired Magazine, 2009).
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Evaluation of Behavioral Change As expected, the longer the duration of the trial and the more information that is available, the more persistent the changes. (Henryson, Hakansson, & Pyrko, 2000). In a 3-year trial, the changes became so routine that at the end of the 3 years, many of the households did not remember making any energy efficient changes at the beginning of the trial (Wilhite & Ling, 1995). Other pilot programs found after a mere three months of energy efficient behaviors it is unlikely that a consumer will go back to their ineffective habits (Project, 1994/95, 95/96, 96/97). Consumers respond more with enabling technologies that automatically alter the behavior of devices than technologies where a conscious effort must be made to change the behavior (Faruqui, Sergici, & Wood, June 2009). Yet these changes are based on the specifications of the pilot. Many of these pilot programs are widely different in structure and make design comparison difficult. Many of the pilots that employ newer technologies have not concluded and thus their total effectiveness is not known (Faruqui, Sergici, & Sharif, May 2009). Other Pertinent Issues As many of these meters use broadband systems or wireless internet there is an option to look into broadband over power line applications and power line carrier options which use the existing power line to deliver broadband to the home (Kumar, 2008). This characteristic is extremely helpful for rural areas that could benefit greatly from broadband access. Rural access to broadband has becomes a leading concern for Virginia‟s Secretary of Technology Office. With access to broadband, fields such as telehealth and distance learning can be accomplished throughout the Commonwealth. Yet, with great benefits also come some serious issues and concerns with these meters. As many are connected to the internet, there is a need to provide security in the metering systems. Without extensive cybersecurity, it would be possible to gain access into individual‟s homes or to entire regions
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of power lines. This could be a port of access for malicious individuals to attack Americans. Currently, these smart meters are operating at unlicensed bandwidths, which mean access to these meters is extremely easy. There is a need for bandwidth to be set aside for these metering systems. Furthermore, there are standards for the system called interoperability standards that have not been established for the smart grid. These standards are being developed by federal agencies such as Federal Energy Regulatory Commission, Department of Energy, National Institute of Standards and Technology and other organizations such as IEEE. These protocols and model standards are necessary so that system can interact with each other and that power companies and consumers may have access to more than one meter (Smart Grid Interoperability Standards Project, 2009). Smart Metering Recommendation The smart metering system and other related smart grid programs have recently received $4.5 billion in funding from the American Recovery and Reinvestment Act of 2009 (Kaplan, 2009). Also, the Emergency Economic Stabilization Act of 2008 shortens the depreciation period for smart meters and other smart grid equipment from 20 years to 10 years (H.R 1424, 2008). By adopting smart meters, there could be leaps and bounds made on energy conservation. Many experts in the field believe that smart metering is an excellent starting point to accomplishing the entire smart grid (Subcommitee on Energy and Environment of the House of Representatives, 2009). The choice of metering system as well as the infrastructure requires some consideration of the future of the grid as well as the compatibility with other systems or parts of other systems. The most effective meters, as mentioned above, require change in the pricing plan and infrastructure which requires a joint effort for state and federal governments and power companies. Due to the fact that the standards for these meters have not been established, any meter that is adopted should have upgradable firmware to adapt to the changing market. Furthermore, the standards that are being developed should be
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taken into account when a smart meter is chosen to ensure the longevity of the meter. Some markets that have adopted a certain type of meter just a few years ago, are already having to invest in newer models as their chosen models are obsolete (Kaplan, 2009) The cost of these meters, and thus changing the meters, usually falls onto the power company and the consumer which is a deterrent to both groups to adopt these technologies. Funding should be provided to assist the power companies in adopting these technologies beyond what has already been contributed. Conclusion The issue of energy conservation has become a very popular issue and problem with most Americans. By providing an easy way to improve energy efficiency, overall consumer consumption will significantly decrease. Smart metering provides easy to use interfaces that provide access to energy efficient solutions without considerable lifestyle changes or effort. These smart meters will not only help residential and commercial building but also assist the power companies in improving their companies.
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Works Cited Agilewaves. (2009). Technology. Retrieved July 15, 2009 from http://www.agilewaves.com/technology Ambient Devices. (2009). Ambient orb. Retrieved July 15, 2009 from http://www.ambientdevices.com/cat/products.html Darby, S. (April 2006). The Effectiveness of feedback on energy consumption. Environmental Change Institute: University of Oxford. DIY Kyoto (2009). Holmes Online Energy Management System. Retrieved July 12, 2009 from http://www.diykyoto.com/uk/holmes/why-use-holmes Dominion Power. (2009). Electric generating station. Retrieved July 15, 2009 from http://www.dom.com/about/stations/index.jsp Dominion Power. (2009). SmartGrid charlottesville. Retrieved July 14, 2009 from http://www.dom.com/about/conservation/smartgrid-charlottesville.jsp Dominion Power (2009). Wireless read meter. Retrieved July 15, 2009 from http://dom.com/about/conservation/smartgrid-charlottesville.jsp Edison Energy Initiative (2009). Industry initiatives. Retrieved July 12, 2009 from http://www.eei.org/ourissues/EnergyEfficiency/Pages/IndustryInitiatives.aspx Effectively transforming our electric delivery system to a smart grid: hearing before the subcommitee on energy and environment of the house of representatives. (2009). One-Hundred Eleventh Congress.
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Electricity end usage. (2008). Monthly Energy Review, 89-109. Energy Interval Service. (2009). Puget sound energy. Retrieved June 20, 2009 from http://www.pse.com/Pages/default.aspx Energy Information Administration. (2005). U.S. household electricty report. Retrieved July 21, 2009 from http://www.eia.doe.gov/emeu/reps/enduse/er01_us.html Faruqui, A., Sergici, S., & Sharif, A. (May 2009). The Impact of informational feedback on energy consumption - a survey of the experimental evidence. San Francisco: The Brattle Group, Inc. Faruqui, A., Sergici, S., & Wood, L. (June 2009). Moving toward utility-scale deployment of dynamic pricing in mass markets. IEE. Fischer, C. (2008). Feedback on household electricity consumption: a tool for saving energy? Energy Efficiency , 79-104. GetSmartGrid.org. (2009). Electrical Grid. Retrieved July 14, 2009 from http://getsmartgrid.org/whatissmartgrid.html GetSmartGrid.org. (2009). Smart grid communication. Retrieved July 14, 2009 from http://getsmartgrid.org/talk.html Google.org. (2009). Google PowerMeter. Retrieved July 10, 2009 from http://google.org/powermeter Greenbox. (2009). Products. Retrieved July 15, 2009 from http://www.getgreenbox.com/company/for-consumers/
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(2008). H.R 1424. Henryson, J., Hakansson, T., & Pyrko, J. (2000). Energy efficiency in buildings through information-Swedish perspective. Energy Policy , 169-180. Hsu, M. (1997). An introduction to the pricing of electric power transmission. Utilities Policy, 257-270. Kaplan, S. M. (2009). Electric power transmission: background and policy issues. Washington, DC: Congression Research Service. Kumar, V. (2008). Intelligent in-house smart metering. Annual Review of Communications, 175189. Levy, R., Herter, K., & Wilson, J. (2004). Unlocking the potential for efficiency and demand response through advanced metering. Berkeley, CA: Lawrence Berkeley National Laboratory. National Institute of Standards and Technology. (2009). Smart Grid Interoperability Standards Project. Retrieved July 19, 2009 from http://www.nist.gov/smartgrid/ Pacific Northwest National La.boratory. (2009). Research. Retrieved June 25, 2009 from http://www.pnl.gov/research/ Project, W. L. (1994/95, 95/96, 96/97). Annual reports. Tendril. (2009). Consumer products. Retrieved July 15, 2009 from http://tendrilinc.com/utilities/utility-products/products/ Tendril. (2009). Tendril Insight. Retrieved July 3, 2009 from http://www.tendrilinc.com/consumers/products/insight/ 16
Virginia's Office of Telework Promotion and Broadband Assistance. (2009). Smart electricity grid. (2009). Retrieved June 21, 2009 from http://www.otpba.vi.virginia.gov/apps_smart_electric.shtml Wilhite, H., & Ling, R. (1995). Measured energy savings from a more informative energy bill. Energy and buildings , 145-155. Wired Magazine. (2009). Clive Thompson thinks: desktop orb could reform energy hogs. Retrieved July 7, 2009 from http://www.wired.com/techbiz/people/magazine/15-08/st_thompson
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Executive Summary Energy consumption in the United States has increased 230% since 1973. In an average residence, large appliances consume over 60 percent of the electricity in the home. By reducing the energy used by these appliances and other electricity consuming devices, the demands for fuel and effects of carbon dioxide emissions will decrease. One of the solutions to decreasing energy consumption is the development of the smart grid. The smart grid uses advanced technologies to improve energy efficiency in all aspects of the electrical grid. On the end user level, the smart grid manifests itself as smart meters that electronically send information to the power companies and provide the consumer with more information to adopt energy efficient habits. In contrast, the current meters installed have mechanical counters. These meters do not promote energy conservation because the only feedback on the consumer‟s energy consumption is a monthly, quarterly or yearly bill. There are a wide variety of meters available but, on average, a 5-20 percent savings can be realized from using a smart metering system. As many of these meters use wireless communication systems, there is an opportunity to develop broadband over power line–broadband delivered via the existing power lines. With access to broadband, programs such as telehealth and distance learning can flourish throughout the Commonwealth of Virginia. As with any system, there are some issues that need to be resolved before success is achieved. In the smart metering system, the meters are using unsecure bandwidth, leaving them vulnerable to cyber attacks. There are also no industry standards for smart meters to guide power companies and smart metering developers. There is minimal funding for smart metering systems and other smart grid applications, but the widespread adoption of these meters requires more extensive funding. Currently, most of the costs fall on the power company or the consumer.
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Table of Contents Executive Summary ..................................................................................................................... i Table of Figures ......................................................................................................................... iii Acknowledgements ................................................................................................................... iv The Proposed Smart Grid ............................................................................................................ 3 Smart Meters .............................................................................................................................. 4 Effectiveness of Advanced Metering Infrastructure................................................................... 10 Evaluation of Smart Meters ................................................................................................... 10 Evaluation of Behavioral Change.......................................................................................... 11 Other Pertinent Issues ............................................................................................................... 11 Smart Metering Recommendation ............................................................................................. 12 Conclusion ............................................................................................................................... 13 Works Cited ............................................................................................................................. 14
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Table of Figures Figure 1. Electrical Grid (GetSmartGrid.org, 2009)……………………………………………………………2. Figure 2. Smart Grid Communication (GetSmartGrid.org, 2009) ....................................................................... 4 Figure 3. Wirelessly Read Meter (Dominion Power, 2009) ................................................................................ 5 Figure 4. Holmes Online Energy Management System (DIY Kyoto, 2009) ........................................................ 6 Figure 5. Tendril Insight (Tendril, 2009) ............................................................................................................ 7 Figure 6. Ambient Orb (Ambient Devices, 2009) ............................................................................................... 7 Figure 7. Google PowerMeter (Google.org, 2009) ............................................................................................. 8
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Acknowledgements
I would like to thank those who have helped me with this project. They have assisted in ways that no amount of literature research would have. Jason Christopher FERC Electrical Engineer Office of Electric Reliability
Julie Simon FERC, Deputy Director Division of Policy Development
Rahim Amerkhail FERC Energy Industry Analyst
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Introduction The United States has been struggling with the reduction of energy consumption in recent years. The current American lifestyle demands a considerable amount of electricity and this amount increases each year. The electricity consumption for United States has grown from 1, 712, 909 million kilowatts in 1973 to 3,891,705 million kilowatts in 2007, almost a 230% increase (Electricity End Usage, 2008). This rate is alarming, as the United States has limited fuel sources and as the concern for the effect of global warming from energy usage becomes more prevalent. In 2001, 31 percent of residential energy consumption comes from the use of heating, ventilation and air conditioning units. Kitchen and laundry appliances consist of another third of residential energy consumption, with refrigerators consuming the most energy (U.S. Household Electricty Report, 2005). This rate of consumption will continue to grow causing the demand on the power system to be even greater. This causes a serious problem on the already strained power system. One solution to this problem is developing a power grid that improves energy efficiency and encourages consumer conservation. Smart grid is an umbrella term that refers to a large array of technologies and improvements to the current electric power system. The term “smart grid” originated from the US Department of Energy‟s Smart Grid Initiative. The Department of Energy defines smart grid as an integrated communication infrastructure that uses advanced sensing communications and control technologies to generate and distribute electricity more effectively, economically and securely (Smart Electricity Grid, 2009). The electric utility industry defines a smart electrical grid as a system where consumers can adjust their consumption of power depending on the availability of electricity (Smart Electricity Grid, 2009). Others define the smart grid as a group of technologies that give the electric grid the characteristics of a computer network (Kaplan, 2009). Generally, the smart grid is an electrical system 1
that provides a two-way communications system between the power company and the end user. This more energy efficient version of the electrical grid requires the use of newer technologies and updates of the current system. Current Electrical System Electrical power is produced in generating plants that burn combustible fuels such as a coal, natural gas, or biomass or from non-combustible energy sources like wind, solar, geothermal, and nuclear. Dominion Power, the most prevalent electric company in the Commonwealth of Virginia, primarily uses coal to provide power to their customers but supplements that with wind, biomass fuels, hydroelectric, and nuclear generating plants (Power, 2009). From the generating plants, transmission lines carry the electricity from the power plant to demand centers. These transmission lines carry extremely high voltage power. Through a series of transformers in the distribution system, the voltage is reduced so that the power can be delivered to the end-user at a usable voltage (Kaplan, 2009).
Figure 1. Electrical Grid (GetSmartGrid.org, 2009) Demonstates the current electrical grid in the United States
In the current electric system, there is only one-way communication where electricity is generated and then passed to the consumer. The consumer‟s usage is recorded through a mechanical meter attached to the house that displays a counter of the kilowatt hours consumed. To be read, a
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technician must travel to each site and record the change in kilowatt hours. If there is an outage, the power company is not aware of it until the consumer notifies the company. Then, to diagnose a problem, a technician must travel to the site and evaluate it on an individual basis. These meters are a burden to both the consumer and the power companies. The only feedback on the consumer‟s energy consumption is a monthly, quarterly or yearly bill. There is no incentive for the consumer to conserve energy during peak hour, when the rate is the highest and the demand for energy is the greatest, because the rate of energy is averaged over billing length. These meters are also inconvenient for the power company because someone must physically travel to each meter and record the reading, creating the millions of tons of carbon dioxide that are contributing to global warming (Faruqui, Sergici, & Wood, Moving Toward Utility-Scale Deployment of Dynamic Pricing in Mass Markets, June 2009). There are also other issues within the current power system that contribute to the inadequacy of the power system such as cybersecurity, reliability, and tracking that will not be discussed here. There have been improvements to the electrical system in the United States but not on the scale of what is required to effectively serve consumers and reduce energy consumption (Kaplan, 2009). The Proposed Smart Grid There are a myriad of different plans and goals to modernize the current power system into the proposed smart grid. These technologies range from advanced meters in homes to more advanced software at the transmission centers. The goals of the smart grid are to better predict energy usage, record energy usage, provide efficient energy, and decrease energy usage. More specifically, the smart grid should monitor the grid‟s conditions, independently detect and diagnose problems and outages, and handle the inclusion of renewable energy sources (Kaplan, 2009). On a residential level, the smart grid should price and supply electricity in order to assist the consumer in making energy efficient decisions about their energy consumption (Kaplan, 2009).
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Figure 1. Smart Grid Communication (GetSmartGrid.org, 2009) Shows the proposed information sharing structure for the smart grid
The power industry has identified five recommendations that will be the most effective in creating an updated smart grid: create more energy-efficient buildings, promote the adoption of more energy efficient appliances, commercialize plug-in hybrid vehicles, support a more energy efficient rate structure for energy consumption, and accelerate the adoption of smart meters and advanced metering infrastructure (Initiative, 2009). Smart Meters Similar to the definition of smart grid, the definition of a smart meter encompasses a large array of metering systems. The main similarity between these meters is that they can communicate back to the power company and provide improved monitoring sources to the consumer. Many of these metering systems rely on broadband in the home. They also create opportunities to implement broadband into buildings that are not equip with this technology. Below are the main types of metering systems. Some meters do not require any additional change to the electrical grid in order to assist in energy conservation. The most basic of these meters is a wireless meter. These meters look similar to the current meters except they have a digital readout instead of a mechanical one.
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Figure 2. Wirelessly Read Meter (Dominion Power, 2009) These meters are similar to current meters with a digital readout instead of a mechanical system
These meters use a wireless technology to transmit information back to the power company. This assists in reporting outages more quickly and conserves energy. It is no longer necessary for a technician to go to each home and read the meter so there is a reduction in the pollution and energy consumption of the trucks (Faruqui, Sergici, & Wood, June 2009). Dominion Power recently initiated a pilot program in Charlottesville, VA installing 46,500 of these wireless meters. It is expected that this program will automatically reduce energy consumption by 4 percent and reduce carbon dioxide emissions by 12,000 tons annually (approximately 2,100 cars). As part of this program, energy usage and billing information will be available on their website (SmartGrid Charlottesville, 2009). Online management tools have become a popular concept for energy and metering companies. These applications incorporate a wide variety of information to provide information to the consumer about their energy consumption. Puget Sound Energy‟s pilot program incorporates an online energy management tool that provides an energy profile that reads every 15 minutes, hourly or daily and updates the next morning. The site also displays a variety of charts, graphs and spreadsheets that display energy usage statistics (Puget Sound Energy, 2009). There are also programs like DIY Kyoto„s Wattson
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and Holmes which is an online program that shows personal energy usage that compares the consumer‟s rate with other Wattson users worldwide (Wired Magazine, 2009).
Figure 3. Holmes Online Energy Management System (DIY Kyoto, 2009) Demonstrates the complexity of online monitoring
This leads to in home devices which show some of the same information as the online management tools, but without the need of a computer. These provide up to date information on the home‟s consumption such as instantaneous energy consumption (in dollars per hour or kW per hour), the cumulative cost of electricity (dollars), power (watts), cumulative electricity consumed (kilowatt-hours), projected monthly bill (dollars), energy translated into greenhouse gas emissions (kg and kg per hour), time, and temperature, depending on the complexity of the device (Faruqui, Sergici, & Sharif, May 2009). An example of these meters is the Tendril Insight meter which tracks kilowatts and cost per hour and communicates to other networked smart devices such as thermostat, electricity meters, outlets and their own internet tracking tool.
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Figure 4. Tendril Insight (Tendril, 2009) Shows a typical in home device and the information that is provided
The meters alert the user to price adjustments and consumption values via audio and visual alerts. Included in this system are outlet controllers which measure and control the energy consumption of standard electrical outlets to track specific appliances. This allows feedback of energy usage (Tendril, 2009). Other types of meters are more subtle when conveying information. A popular meter, the Ambient Orb changes color depending on some market or usage characteristics. (Wired Magazine, 2009).
Figure 5. Ambient Orb (Ambient Devices, 2009) This is an example of the Ambient Orb in residential use 7
There are also more advanced in home devices such as Agilewaves, targeted at higher-end homes and larger buildings. These devices track and manage energy, gas and water consumption in real time from web-enabled devices such as computers and mobile devices (Technology, 2009). This mobile technology aspect is also used in Greenbox technologies. Greenbox can notify the user via text message of peak time rate, high usage, weekly usage reports, and send out tips and recommendations based on usage (Products, 2009). Google has been working with these companies such as Tendril and Greenbox to create Google Powermeter which is an advanced online energy information tool that can be used with any system (Google PowerMeter, 2009).
Figure 6. Google PowerMeter (Google.org, 2009) This is an example of the graphs available in the PowerMeter system
These metering systems to improve user efficiency can also track individual appliances to determine usage and increase the user‟s energy efficiency. Appliance companies, such as GE, are creating Smart Appliance s that interact with these smart metering systems. These appliances include dishwashers, microwaves, heating and air conditioning units, washing machines and other devices that consume considerable amounts of energy. These appliances are fitted with communication technology 8
that can transfer their energy usage as well as monitor the pricing of power and automatically react to these increases. For example, when these appliances detect a peak hour rate they can pause or delay the dishwasher, turn off the light on the microwave, or increase the temperature in the refrigerator until the rates decrease (Research, 2009). This will drastically improve energy efficiency as these major appliances consume about 60 percent of the energy usage in the home. Although these meters are helpful in determining when energy is most expensive, without a change in the pricing system there is a limit to the effectiveness of the smart meters. To be most effective the meters need to rely on a demand pricing system which does not blend the rates of energy throughout the billing period. The demand pricing system charges higher rates during the time that most power is being used and expensive generating plants are functioning (Hsu, 1997). The generating plants used during peak hours are kept idle for the rest of the hours of the year, which equates to system inefficiencies. The cost of these reserve generating plants cause the energy rate to be much higher during peak demand hours than in other hours of the year (Faruqui, Sergici, & Wood, June 2009) . Many of the simpler meters can be purchased and installed by the consumer. The meters that display real-time price signals from the utility are usually more complex and often require professional installation by the utility. (Faruqui, Sergici, & Sharif, May 2009). The pricing of these meters can range between $100 and $175 and can reach up to $525 (Faruqui, Sergici, & Wood, June 2009). These meters do not only help the consumer but also help the power companies to provide improved customer service. All of these meters transmit data back to the companies so that they can track the amount of energy being consumed in each area. This provides the data to the companies so that they can predict high usage, potential issues with service, and other aspects that can more effectively deliver power.
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Effectiveness of Advanced Metering Infrastructure The variety and innovation of these smart meters is encouraging but there are still questions on the effectiveness and the consumer‟s long term commitment to energy conservation. The use of smart meters in the home is a relatively new practice thus long term data is not available yet what data is available indicates that smart metering can be successful. Evaluation of Smart Meters Similar to any user device, user friendly features are essential to any metering system. Meters have been found to be most useful if they show instantaneous usage, total expenditure and historic data (Darby, April 2006) with a computerized display (Fischer, 2008). With an effective unit, consumers can realize a considerable reduction in their electricity bill. There is expected to be an even greater decrease with a dynamic pricing model. In the long term, even those that do not switch their usage to smart meters or dynamic pricing systems will also have a decrease in their electric bills as the high demand plants are no longer necessary (Faruqui, Sergici, & Wood, June 2009). Quantitatively, a conscious effort to look at the monthly energy bill and subsequently adopt habits that are energy efficient without a smart meter result in savings between 0% and 10% depending on the information given. Within this approach, a look at an individual‟s past energy consumption was more effective than observing others‟ energy consumption (Darby, April 2006). In comparison, there is a 5-15 percent savings from using only a metering system (Darby, April 2006). With the use of in home devices and dynamic pricing there is even a greater savings with a decrease of 10-20 percent of electric bills (Faruqui, Sergici, & Sharif, May 2009). Of in home devices, the Ambient Orb was recorded to reduce peak energy consumption by 40 percent. It is believed that this approach is more effective than a one-time alarm or text message because it was a persistent, unobtrusive reminder (Wired Magazine, 2009).
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Evaluation of Behavioral Change As expected, the longer the duration of the trial and the more information that is available, the more persistent the changes. (Henryson, Hakansson, & Pyrko, 2000). In a 3-year trial, the changes became so routine that at the end of the 3 years, many of the households did not remember making any energy efficient changes at the beginning of the trial (Wilhite & Ling, 1995). Other pilot programs found after a mere three months of energy efficient behaviors it is unlikely that a consumer will go back to their ineffective habits (Project, 1994/95, 95/96, 96/97). Consumers respond more with enabling technologies that automatically alter the behavior of devices than technologies where a conscious effort must be made to change the behavior (Faruqui, Sergici, & Wood, June 2009). Yet these changes are based on the specifications of the pilot. Many of these pilot programs are widely different in structure and make design comparison difficult. Many of the pilots that employ newer technologies have not concluded and thus their total effectiveness is not known (Faruqui, Sergici, & Sharif, May 2009). Other Pertinent Issues As many of these meters use broadband systems or wireless internet there is an option to look into broadband over power line applications and power line carrier options which use the existing power line to deliver broadband to the home (Kumar, 2008). This characteristic is extremely helpful for rural areas that could benefit greatly from broadband access. Rural access to broadband has becomes a leading concern for Virginia‟s Secretary of Technology Office. With access to broadband, fields such as telehealth and distance learning can be accomplished throughout the Commonwealth. Yet, with great benefits also come some serious issues and concerns with these meters. As many are connected to the internet, there is a need to provide security in the metering systems. Without extensive cybersecurity, it would be possible to gain access into individual‟s homes or to entire regions
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of power lines. This could be a port of access for malicious individuals to attack Americans. Currently, these smart meters are operating at unlicensed bandwidths, which mean access to these meters is extremely easy. There is a need for bandwidth to be set aside for these metering systems. Furthermore, there are standards for the system called interoperability standards that have not been established for the smart grid. These standards are being developed by federal agencies such as Federal Energy Regulatory Commission, Department of Energy, National Institute of Standards and Technology and other organizations such as IEEE. These protocols and model standards are necessary so that system can interact with each other and that power companies and consumers may have access to more than one meter (Smart Grid Interoperability Standards Project, 2009). Smart Metering Recommendation The smart metering system and other related smart grid programs have recently received $4.5 billion in funding from the American Recovery and Reinvestment Act of 2009 (Kaplan, 2009). Also, the Emergency Economic Stabilization Act of 2008 shortens the depreciation period for smart meters and other smart grid equipment from 20 years to 10 years (H.R 1424, 2008). By adopting smart meters, there could be leaps and bounds made on energy conservation. Many experts in the field believe that smart metering is an excellent starting point to accomplishing the entire smart grid (Subcommitee on Energy and Environment of the House of Representatives, 2009). The choice of metering system as well as the infrastructure requires some consideration of the future of the grid as well as the compatibility with other systems or parts of other systems. The most effective meters, as mentioned above, require change in the pricing plan and infrastructure which requires a joint effort for state and federal governments and power companies. Due to the fact that the standards for these meters have not been established, any meter that is adopted should have upgradable firmware to adapt to the changing market. Furthermore, the standards that are being developed should be
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taken into account when a smart meter is chosen to ensure the longevity of the meter. Some markets that have adopted a certain type of meter just a few years ago, are already having to invest in newer models as their chosen models are obsolete (Kaplan, 2009) The cost of these meters, and thus changing the meters, usually falls onto the power company and the consumer which is a deterrent to both groups to adopt these technologies. Funding should be provided to assist the power companies in adopting these technologies beyond what has already been contributed. Conclusion The issue of energy conservation has become a very popular issue and problem with most Americans. By providing an easy way to improve energy efficiency, overall consumer consumption will significantly decrease. Smart metering provides easy to use interfaces that provide access to energy efficient solutions without considerable lifestyle changes or effort. These smart meters will not only help residential and commercial building but also assist the power companies in improving their companies.
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Works Cited Agilewaves. (2009). Technology. Retrieved July 15, 2009 from http://www.agilewaves.com/technology Ambient Devices. (2009). Ambient orb. Retrieved July 15, 2009 from http://www.ambientdevices.com/cat/products.html Darby, S. (April 2006). The Effectiveness of feedback on energy consumption. Environmental Change Institute: University of Oxford. DIY Kyoto (2009). Holmes Online Energy Management System. Retrieved July 12, 2009 from http://www.diykyoto.com/uk/holmes/why-use-holmes Dominion Power. (2009). Electric generating station. Retrieved July 15, 2009 from http://www.dom.com/about/stations/index.jsp Dominion Power. (2009). SmartGrid charlottesville. Retrieved July 14, 2009 from http://www.dom.com/about/conservation/smartgrid-charlottesville.jsp Dominion Power (2009). Wireless read meter. Retrieved July 15, 2009 from http://dom.com/about/conservation/smartgrid-charlottesville.jsp Edison Energy Initiative (2009). Industry initiatives. Retrieved July 12, 2009 from http://www.eei.org/ourissues/EnergyEfficiency/Pages/IndustryInitiatives.aspx Effectively transforming our electric delivery system to a smart grid: hearing before the subcommitee on energy and environment of the house of representatives. (2009). One-Hundred Eleventh Congress.
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Electricity end usage. (2008). Monthly Energy Review, 89-109. Energy Interval Service. (2009). Puget sound energy. Retrieved June 20, 2009 from http://www.pse.com/Pages/default.aspx Energy Information Administration. (2005). U.S. household electricty report. Retrieved July 21, 2009 from http://www.eia.doe.gov/emeu/reps/enduse/er01_us.html Faruqui, A., Sergici, S., & Sharif, A. (May 2009). The Impact of informational feedback on energy consumption - a survey of the experimental evidence. San Francisco: The Brattle Group, Inc. Faruqui, A., Sergici, S., & Wood, L. (June 2009). Moving toward utility-scale deployment of dynamic pricing in mass markets. IEE. Fischer, C. (2008). Feedback on household electricity consumption: a tool for saving energy? Energy Efficiency , 79-104. GetSmartGrid.org. (2009). Electrical Grid. Retrieved July 14, 2009 from http://getsmartgrid.org/whatissmartgrid.html GetSmartGrid.org. (2009). Smart grid communication. Retrieved July 14, 2009 from http://getsmartgrid.org/talk.html Google.org. (2009). Google PowerMeter. Retrieved July 10, 2009 from http://google.org/powermeter Greenbox. (2009). Products. Retrieved July 15, 2009 from http://www.getgreenbox.com/company/for-consumers/
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(2008). H.R 1424. Henryson, J., Hakansson, T., & Pyrko, J. (2000). Energy efficiency in buildings through information-Swedish perspective. Energy Policy , 169-180. Hsu, M. (1997). An introduction to the pricing of electric power transmission. Utilities Policy, 257-270. Kaplan, S. M. (2009). Electric power transmission: background and policy issues. Washington, DC: Congression Research Service. Kumar, V. (2008). Intelligent in-house smart metering. Annual Review of Communications, 175189. Levy, R., Herter, K., & Wilson, J. (2004). Unlocking the potential for efficiency and demand response through advanced metering. Berkeley, CA: Lawrence Berkeley National Laboratory. National Institute of Standards and Technology. (2009). Smart Grid Interoperability Standards Project. Retrieved July 19, 2009 from http://www.nist.gov/smartgrid/ Pacific Northwest National La.boratory. (2009). Research. Retrieved June 25, 2009 from http://www.pnl.gov/research/ Project, W. L. (1994/95, 95/96, 96/97). Annual reports. Tendril. (2009). Consumer products. Retrieved July 15, 2009 from http://tendrilinc.com/utilities/utility-products/products/ Tendril. (2009). Tendril Insight. Retrieved July 3, 2009 from http://www.tendrilinc.com/consumers/products/insight/ 16
Virginia's Office of Telework Promotion and Broadband Assistance. (2009). Smart electricity grid. (2009). Retrieved June 21, 2009 from http://www.otpba.vi.virginia.gov/apps_smart_electric.shtml Wilhite, H., & Ling, R. (1995). Measured energy savings from a more informative energy bill. Energy and buildings , 145-155. Wired Magazine. (2009). Clive Thompson thinks: desktop orb could reform energy hogs. Retrieved July 7, 2009 from http://www.wired.com/techbiz/people/magazine/15-08/st_thompson
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