- Email: [email protected]
What Can the Smart Grid Do for You? And What Can You Do for the Smart Grid?
David P. Chassin is staff scientist with the Energy Science & Technology Directorate at Pacific Northwest National Laboratory in Richland, Washington, where he has worked since 1992. He was Vice President of Development for Image Systems Technology from 1987 to 1992, where he pioneered a hybrid raster/vector computer-aided design technology called CAD Overlay. He led the development of building energy simulation and diagnostic systems, including Softdesk Energy and DOE’s Whole Building Diagnostician. His recent research focuses on emerging theories of complexity as they relate to highperformance large-scale simulation and modeling of the Smart Grid. He contributes to the Western Electricity Coordinating Council’s (WECC) Load Modeling Task Force and the North American Electricity Reliability Council (NERC) Load Forecasting Work Group, is a member of the WECC’s Market Integration Committee, and chair of the OASIS Blue Steering Committee. He received his B.S. of Building Science from Rensselaer Polytechnic Institute in Troy, New York.
What Can the Smart Grid Do for You? And What Can You Do for the Smart Grid? The intersection of technology and economics is where all the Smart Grid benefits arise. If we do one without the other, then utilities and consumers hardly see any enduring benefit at all and the investment made in the underlying infrastructure justified on the basis of those benefits is wasted. David P. Chassin
W
hen Lynne Kiesling of Northwestern University explains the benefits of Smart Grid technology to legislators and regulators, she always makes the point that the intersection of technology and economics is where all the Smart Grid benefits arise. If we do one without the other, then utilities and consumers hardly see any enduring benefit at all and the investment made in the underlying infrastructure justified on the basis of those benefits is wasted. The need for Smart Grid technologies to
provide sustainable and enduring benefits to the consumer is at least as important as demonstrating the business case for utilities. This point is the essence of what has come to be called the transactive behavior of the Smart Grid concept. The idea is simple to explain and it’s sometimes colloquially called prices to devices. But it is actually harder to implement reliably than one might think: in the face of a constraint or a crisis if the electric system knew how willing and able to forgo consumption your home and its appliances were,
June 2010, Vol. 23, Issue 5 1040-6190/$–see front matter # 2010 Elsevier Inc. All rights reserved., doi:/10.1016/j.tej.2010.05.001
57
then it might be able to quickly find the most cost-effective way to balance supply and demand during extreme events without having to take extreme measures, like rolling blackouts or load. he Olympic Peninsula study [1] that was completed in 2007 supports Kiesling’s assertion. This project was an important milestone in the road to the Smart Grid of the future. It focused on the question of what benefits arise and for whom when demand is an equal partner with supply in the operation of the electric system. There were two parts to the answer: (1) the technology installed in homes had a positive impact on the willingness and ability of consumers to participate, and (2) pricing signals were necessary not only to motivate consumers to respond when prices were high, but also to give consumers opportunities to make up for the response when prices were low. The bottom line: unless there is a quid pro quo, demand response is simply not sustainable in the long run.
T
58
Figure 1: Feeder Capacity is Allocated Using a Distribution Market Where Demand is Offered an Opportunity to Obtain a Fair Share of the Benefits of the Smart Grid
that (1) the customers were not actually physically connected to this feeder, and (2) the feeder constraint changed during the course study (Figure 1). The utility obtained bulk power from Bonneville Power Administration (BPA) at the MidColumbia prices. The energy price for bulk purchase through the virtual feeder was set by BPA at $81/MWh for the year-ahead purchase for the purposes of this project (although no actual purchases were made).
I. Managing Distribution Capacity
II. Consumer Control
In the Olympic Peninsula study, an open market for distribution capacity was created where the bulk power providers, homes, businesses, and industrial loads would compete for their share of the available capacity on this utility’s virtual feeder. The feeder was virtual in the sense
Residential utility customers were offered their choice of three rates for electricity. They could opt to remain on the fixed energy price that is typical for the vast majority of homes in the U.S. They could opt for a time-of-use rate, which offered cheap electricity during off-peak hours, and
expensive electricity during peak hours, with an additional critical peak price during emergencies. And finally, they could opt for a real-time price, which was recalculated every five minutes based on the balance of supply and demand at the distribution system level (Figure 2). he project demonstrated that customers could be easily recruited to participate in any of these plans. In fact, after the risks and rewards of each plan were explained to them, over 60 percent of the customers preferred the high risk/reward real-time price plan, above the medium risk/reward time-of-use plan, and the low risk/reward fixed-price plan. Because the objective of the project was to obtain roughly equal participation in the plans, it is clear in retrospect that the real-time plan was oversold. The same $150 average incentive was offered for all three plans, but
T
1040-6190/$–see front matter # 2010 Elsevier Inc. All rights reserved., doi:/10.1016/j.tej.2010.05.001
The Electricity Journal
benefit. For example, critical peak pricing does an excellent job of giving consumers incentives to cut consumption on-peak, but fails to present a reciprocal benefit, i.e., increasing consumption during times of very low consumption. In contrast, real-time pricing offers periods of very low prices before and after a very sharp peak, allowing consumers time to cost-effectively set up and recover from peak periods.
Figure 2: Consumers Were Offered a Choice of Electricity Rate Plans, and the Balance Between Them was Used to Manage the Allocation of the Feeder’s Capacity
III. Enabling Technology
funds in an incentive account from which their energy charges were deducted, while they continued to pay their regular fixed-price bills as before. Their energy charges according to the chosen pricing plan were also deducted from this incentive account. At the end of each quarter, the balance remaining in the accounts was given to the customers as a cash payment. The more favorably they responded to the price incentives, the more money they got to keep. ut having a clear cause– effect relationship is not enough: although many demand response plans offer the promise of savings, consumers often fail to realize them because of timidity in the pricing structure arising from risk aversion on the part of those who set the prices. The responses were effective because the dynamic pricing signals were present, significant, and sustained, especially when they weren’t necessarily to the utility’s
Enabling technology is an absolutely critical feature of the Smart Grid that the Olympic Peninsula study demonstrated. Consumers must be given the ability to instantly respond to fluctuations in price without having to continuously monitor prices, call home in response to text messages, or even think about the question of what to do when prices rises and fall every few minutes. The fire-and-forget technology used in the demonstration plays a critical role in the success of effective electricity pricing plans. This is where the economics and the technology meet. Everybody in the Olympic Peninsula study was given the same technology, regardless of which price plan they chose. The only difference was how it would act in response to what the consumers said. Furthermore, the very tight coupling of the residential energy management system to the utility’s energy
the expected variation was different — the higher the risk, the higher the expected variation in reward. The $150 reward represented roughly 10 percent of the average customer’s annual utility bill, but the conventional wisdom is that with higher risks come higher rewards. This suggests that there is some ‘‘early adopter’’ effect here, and this is something that program planners should consider: early results should not be used to forecast long-term results without giving due consideration to effects such as these. Customers were retained because the promised benefits were generally realized, particularly for those who exposed themselves to greater risks by choosing more volatile pricing plans. But they were also protected from potential adverse consequences of choosing a plan for which they were not well suited. At the beginning of each quarter, customers were given
B
June 2010, Vol. 23, Issue 5 1040-6190/$–see front matter # 2010 Elsevier Inc. All rights reserved., doi:/10.1016/j.tej.2010.05.001
59
time-of-use customers and avoid having them subsidize customers who don’t contribute to savings, some combination of net revenue neutrality and revenue neutrality would have to be devised.
IV. Utility Benefits Figure 3: The Available of Enabling Technology is Essential to the Effectiveness of PriceBased Control
management system is symmetric: the utility doesn’t control the home per se, rather it enables the home to respond by supplying actionable information, i.e., the present price of electricity, and by collecting useful information, i.e., willingness to forgo consumption in the very near term (Figure 3). he home energy management system controlled the thermostat, but in the case of time-of-use pricing, the thermostat was set back during peak pricing period. Customers who signed up for real-time pricing had thermostats that would submit requests for consumption over the next five minutes, with higher prices relative to the day’s average price as the temperature got more out of the comfort zone and lower prices when the comfort zone was met. When the feeder capacity market was cleared, the real-time price was sent to all devices and those that submitted requests with prices above the real-time price turned on, while those that submitted requests below the real-time price turned off.
T
60
T
he utility’s operation focuses primarily on determining the real-time price for which constrained supply matches responsive demand. This eliminates the need for the utility to be concerned about which thermostats to turn up or down, and which appliances to turn on or off. The use of the real-timeprice double auction is probably the most straightforward method for achieving such a system and making it highly scalable. The determination of the seasonal time-of-use rate must also be done with a similar approach. In the case of the Olympic Peninsula demonstration, the time-of-use rates were net revenue neutral, rather the simply revenue neutral: the cost of delivering the energy decreased due to the roughly 9 percent demand elasticity for time-of-use customers. This cost savings was passed entirely through to the consumer, hence the net revenue neutrality. In contrast, one could argue that simple revenue neutrality passes none of the savings on to the consumer, and that to share the benefits equitable with only the
Net revenue neutrality does not imply that the utility does not stand to gain anything from adopting such strategies. There are a number of important benefits that arise from Smart Grid approaches to demand response that are shared across all customers regardless of participation. Among those identified during the course of the Olympic Peninsula demonstration are the following. A. Reduced peak The study demonstrated that for very short periods of time, very significant reductions in peak load on the bulk system were possible. The largest reduction observed on peak was nearly 60 percent. For longer periods (three days or more) sustained reductions between 15 percent and 20 percent of peak were typically observed (Figure 4). B. Increased asset utilization The reduction in peak consumption was not necessarily associated with a corresponding reduction in energy use, particularly with real-time prices,
1040-6190/$–see front matter # 2010 Elsevier Inc. All rights reserved., doi:/10.1016/j.tej.2010.05.001
The Electricity Journal
Figure 4: Peak Load Reduction of 15 Percent to 20 Percent Could Be Obtained for Sustained Periods of Time
where pre-heating/cooling and recovery are often observed — the energy consumption off-peak increased by roughly the same amount as the energy consumption was reduced onpeak. Whereas time-of-use prices usually result in energy reductions and peak reductions, real-time prices only result in peak reduction. As a result, the overall asset utilization increases more when real-time prices are introduced. C. Increased customer satisfaction The participant exit survey showed very significant customer satisfaction with the systems that were installed in their homes. This is attributed to the high degree of control and autonomy that the thermostat and water heater demand response control offered customers, and most
likely contributed highly to their willingness to remain active in the program over the duration of the project. ne very important and unexpected result of the study was the demonstration of the rate portfolio planning capability. If a utility is able to offer more than one rate plan to its customers, it must answer the question of how many customers should ideally subscribe to each plan. The question can be answered using an analog to modern portfolio theory [2,3]. The approach works as follows: 1. A business objective is chosen, such as minimum energy cost or maximum peak reduction. Any metric that can be evaluated for any mix of customers on each rate plan is permissible. 2. Sales and cost data are collected to compute the metrics for each plan. Both the mean and variance of that metric should
O
be calculated for extended periods of time, such as a season or year. 3. A portfolio analysis is performed to determine the mix of customers on each plan such that the metric is question is optimal (Figure 5). 4. The plan promotion is adjusted by varying incentives, education, and marketing to attract and retain customers for the undersubscribed plans and discourage and divert customers from oversubscribed plans. The process can be updated as often as monthly to maintain the incentives necessary to sustain the optimal plan subscription. The advantage of this technique is that it is demonstrably fair and transparent, so long as the business objective is known and approved. Regulators would simply have to approve the use of the objective, from which all the planning, marketing, operational, and billing decisions would devolve in a transparent and fair manner.
V. Consumer Benefits Beyond the potential for cost savings to consumers, we have already alluded to the fact that customer satisfaction is an important benefit that utilities see. This satisfaction rises from five important considerations. A. Significant savings Customers were offered roughly 10 percent savings. Less
June 2010, Vol. 23, Issue 5 1040-6190/$–see front matter # 2010 Elsevier Inc. All rights reserved., doi:/10.1016/j.tej.2010.05.001
61
customers said that their DR-enabled water heater performance was acceptable. C. Full automation
Figure 5: Modern Portfolio Theory Can Be Used to Optimize any Utility Objective With Respect to the Number of Customers Subscribing to a Particular Electricity Rate Plan
than 10 percent savings and it becomes difficult to convince people to ‘‘play along.’’ Consider a customer with a $1,200 annual energy bill: 10 percent savings amounts to only $10/month. How much are consumers willing to do each month for less than $10? In fact, there is evidence from surveys to suggest that customers expect savings on the order of 50 percent, especially if they aren’t told exactly what savings to expect [4]. In the case of this project, the customers were told to expect $150 in savings if they responded to savings opportunities. The only difference they would see is that the riskier the pricing the higher the potential savings. Of course, with riskier pricing there was also greater potential that if they responded incorrectly to a 62
savings opportunity, then they would see no savings at all. B. Simple to use Given the limited savings, the system must be very easy to use. The notion of a ‘‘fire and forget’’ control system is vital to the largescale success of demand response programs. Our lives are already complicated enough that we can’t afford to burden consumers with demand response programs that require regular active participation to realize benefits. The customer response to the exit surveys showed a very favorable feeling toward the systems deployed in their appliances, with 94 percent of respondents saying they were satisfied with their DRenabled dryer, 80 percent satisfied with their DR-enabled thermostat, and 96 percent of
We were surprised to learn in the exit survey that 55 percent of customers couldn’t remember which pricing plan they were on. But when asked which plan they would prefer if they could participate again, 38 percent asked for the real-time price plan and 35 percent asked for time-of-use. The ease of use of a fire-and-forget approach makes it unnecessary for consumers to constantly keep in mind the details of their energy consumption. Full automation means that we must have prices getting to devices, and the ability of devices to interpret what those prices mean in the context of the consumers’ desires, without asking the consumer every time. D. Maintaining control Automation doesn’t need to come at the expense of control. In fact, we can easily see from the exit survey data that welldesigned automation can enable a sustained sense of control. Consumers are largely hesitant to cede control to the utilities, so if they remain convinced through continuous positive reinforcement that they retain autonomy, the consumers stand to benefit in the long term. Nonetheless, 94 percent of customers said they would participate in a similar program if
1040-6190/$–see front matter # 2010 Elsevier Inc. All rights reserved., doi:/10.1016/j.tej.2010.05.001
The Electricity Journal
it were offered again, in spite of the fact that 64 percent experienced one or more technical problems at some point or another. E. No-lose proposition Finally, consumers must feel that the downside aspects of subscribing to a real-time price plan or a time-of-use plan are mitigated. Consumers are not fully trusting of utilities, so at least for the short term, utilities need to promote plans that protect consumers from the potential cost impacts of misusing or misunderstanding the system. In part, utilities can do a lot to mitigate the problem by discouraging consumers from subscribing to a plan that is not well suited to their lifestyle. But mechanisms such as the double declining balance accounts may remain necessary for a time, until confidence in the system is established. In the exit survey, customer didn’t expect to pay much more for the capabilities they received. The average response to the question of how much more they would expect to pay for a ‘‘grid friendly’’ water heater was just $24, suggesting that customers expect their devices to already do what is important, not just for them, but also for the grid. They don’t expect to have to consciously change their behavior, but expect the devices to ‘‘do the right thing’’ and with no downside risk or cost to them.
VI. Conclusions The benefits observed in the Olympic Peninsula demonstration accrued to both the utilities and their consumers. We see that utilities can expect Smart Grid demand response programs to reduce their risks, increase system throughput and asset utilization, and increase customer satisfaction. Consumers also see significant benefits, particularly with respect to reduced energy costs and increased autonomy when participating in demand response programs. ut the ability of utilities and consumers to receive those benefits is contingent on an equitable distribution of all the benefits available. If either the utility or the consumers receive a disproportionate allocation of the benefits, then the overall benefits will decrease over time as the disfavored party or parties become disenchanted with the program. Furthermore, attempts to over- or underutilize the resources can lead to program fatigue and an excessively high rate of participant attrition. ome very important questions will be answered by the Smart Grid demonstrations planned to begin this year and next. The primary open question is whether we can successfully scale the methods employed on a relatively small scale in the Olympic Peninsula demonstration to much larger systems. The objective is to test these systems with more than
B
S
100,000 customers, as opposed to the 100 or so who participated in the Olympic Peninsula demonstration. Another open question we hope to learn more about in the coming year is how we best model large-scale price-based demand response programs for the purposes of utility planning, forecasting, regulation, and market operations. There is still a great deal of ongoing research in how energy management controls can and should be incorporated into consumer electronics and home appliances. This is probably the most exciting and interesting aspect of the Smart Grid, at least from the perspective of business, vendors, and manufacturers. It is not at all clear which business model for home energy management systems, if any, will prevail. It will certainly be many years before we can say with any degree of certainty which is the best approach to supporting and encouraging demand response in our daily lives.& References [1] D.J. Hammerstrom et al., Pacific Northwest GridWise Testbed Demonstration Projects Part I. Olympic Peninsula Project, PNNL-17167, Richland, WA, at http://gridwise.pnl.gov/docs/op_ project_final_report_pnnl17167.pdf [2] See http://en.wikipedia.org/ wiki/Modern_portfolio_theory [3] R. Guttromson and D. Chassin, Optimizing Retail Contracts for Electricity Markets, GridWise Architecture Council Forum, 2007, at http://www. gridwiseac.org/pdfs/forum_papers/ 101_paper_final.pdf [4] S. Shelton, NRECA/NISC GridPosium, St. Louis, April 20, 2010, at http://www.gridposium.com/
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What Can the Smart Grid Do for You? And What Can You Do for the Smart Grid? The intersection of technology and economics is where all the Smart Grid benefits arise. If we do one without the other, then utilities and consumers hardly see any enduring benefit at all and the investment made in the underlying infrastructure justified on the basis of those benefits is wasted. David P. Chassin
W
hen Lynne Kiesling of Northwestern University explains the benefits of Smart Grid technology to legislators and regulators, she always makes the point that the intersection of technology and economics is where all the Smart Grid benefits arise. If we do one without the other, then utilities and consumers hardly see any enduring benefit at all and the investment made in the underlying infrastructure justified on the basis of those benefits is wasted. The need for Smart Grid technologies to
provide sustainable and enduring benefits to the consumer is at least as important as demonstrating the business case for utilities. This point is the essence of what has come to be called the transactive behavior of the Smart Grid concept. The idea is simple to explain and it’s sometimes colloquially called prices to devices. But it is actually harder to implement reliably than one might think: in the face of a constraint or a crisis if the electric system knew how willing and able to forgo consumption your home and its appliances were,
June 2010, Vol. 23, Issue 5 1040-6190/$–see front matter # 2010 Elsevier Inc. All rights reserved., doi:/10.1016/j.tej.2010.05.001
57
then it might be able to quickly find the most cost-effective way to balance supply and demand during extreme events without having to take extreme measures, like rolling blackouts or load. he Olympic Peninsula study [1] that was completed in 2007 supports Kiesling’s assertion. This project was an important milestone in the road to the Smart Grid of the future. It focused on the question of what benefits arise and for whom when demand is an equal partner with supply in the operation of the electric system. There were two parts to the answer: (1) the technology installed in homes had a positive impact on the willingness and ability of consumers to participate, and (2) pricing signals were necessary not only to motivate consumers to respond when prices were high, but also to give consumers opportunities to make up for the response when prices were low. The bottom line: unless there is a quid pro quo, demand response is simply not sustainable in the long run.
T
58
Figure 1: Feeder Capacity is Allocated Using a Distribution Market Where Demand is Offered an Opportunity to Obtain a Fair Share of the Benefits of the Smart Grid
that (1) the customers were not actually physically connected to this feeder, and (2) the feeder constraint changed during the course study (Figure 1). The utility obtained bulk power from Bonneville Power Administration (BPA) at the MidColumbia prices. The energy price for bulk purchase through the virtual feeder was set by BPA at $81/MWh for the year-ahead purchase for the purposes of this project (although no actual purchases were made).
I. Managing Distribution Capacity
II. Consumer Control
In the Olympic Peninsula study, an open market for distribution capacity was created where the bulk power providers, homes, businesses, and industrial loads would compete for their share of the available capacity on this utility’s virtual feeder. The feeder was virtual in the sense
Residential utility customers were offered their choice of three rates for electricity. They could opt to remain on the fixed energy price that is typical for the vast majority of homes in the U.S. They could opt for a time-of-use rate, which offered cheap electricity during off-peak hours, and
expensive electricity during peak hours, with an additional critical peak price during emergencies. And finally, they could opt for a real-time price, which was recalculated every five minutes based on the balance of supply and demand at the distribution system level (Figure 2). he project demonstrated that customers could be easily recruited to participate in any of these plans. In fact, after the risks and rewards of each plan were explained to them, over 60 percent of the customers preferred the high risk/reward real-time price plan, above the medium risk/reward time-of-use plan, and the low risk/reward fixed-price plan. Because the objective of the project was to obtain roughly equal participation in the plans, it is clear in retrospect that the real-time plan was oversold. The same $150 average incentive was offered for all three plans, but
T
1040-6190/$–see front matter # 2010 Elsevier Inc. All rights reserved., doi:/10.1016/j.tej.2010.05.001
The Electricity Journal
benefit. For example, critical peak pricing does an excellent job of giving consumers incentives to cut consumption on-peak, but fails to present a reciprocal benefit, i.e., increasing consumption during times of very low consumption. In contrast, real-time pricing offers periods of very low prices before and after a very sharp peak, allowing consumers time to cost-effectively set up and recover from peak periods.
Figure 2: Consumers Were Offered a Choice of Electricity Rate Plans, and the Balance Between Them was Used to Manage the Allocation of the Feeder’s Capacity
III. Enabling Technology
funds in an incentive account from which their energy charges were deducted, while they continued to pay their regular fixed-price bills as before. Their energy charges according to the chosen pricing plan were also deducted from this incentive account. At the end of each quarter, the balance remaining in the accounts was given to the customers as a cash payment. The more favorably they responded to the price incentives, the more money they got to keep. ut having a clear cause– effect relationship is not enough: although many demand response plans offer the promise of savings, consumers often fail to realize them because of timidity in the pricing structure arising from risk aversion on the part of those who set the prices. The responses were effective because the dynamic pricing signals were present, significant, and sustained, especially when they weren’t necessarily to the utility’s
Enabling technology is an absolutely critical feature of the Smart Grid that the Olympic Peninsula study demonstrated. Consumers must be given the ability to instantly respond to fluctuations in price without having to continuously monitor prices, call home in response to text messages, or even think about the question of what to do when prices rises and fall every few minutes. The fire-and-forget technology used in the demonstration plays a critical role in the success of effective electricity pricing plans. This is where the economics and the technology meet. Everybody in the Olympic Peninsula study was given the same technology, regardless of which price plan they chose. The only difference was how it would act in response to what the consumers said. Furthermore, the very tight coupling of the residential energy management system to the utility’s energy
the expected variation was different — the higher the risk, the higher the expected variation in reward. The $150 reward represented roughly 10 percent of the average customer’s annual utility bill, but the conventional wisdom is that with higher risks come higher rewards. This suggests that there is some ‘‘early adopter’’ effect here, and this is something that program planners should consider: early results should not be used to forecast long-term results without giving due consideration to effects such as these. Customers were retained because the promised benefits were generally realized, particularly for those who exposed themselves to greater risks by choosing more volatile pricing plans. But they were also protected from potential adverse consequences of choosing a plan for which they were not well suited. At the beginning of each quarter, customers were given
B
June 2010, Vol. 23, Issue 5 1040-6190/$–see front matter # 2010 Elsevier Inc. All rights reserved., doi:/10.1016/j.tej.2010.05.001
59
time-of-use customers and avoid having them subsidize customers who don’t contribute to savings, some combination of net revenue neutrality and revenue neutrality would have to be devised.
IV. Utility Benefits Figure 3: The Available of Enabling Technology is Essential to the Effectiveness of PriceBased Control
management system is symmetric: the utility doesn’t control the home per se, rather it enables the home to respond by supplying actionable information, i.e., the present price of electricity, and by collecting useful information, i.e., willingness to forgo consumption in the very near term (Figure 3). he home energy management system controlled the thermostat, but in the case of time-of-use pricing, the thermostat was set back during peak pricing period. Customers who signed up for real-time pricing had thermostats that would submit requests for consumption over the next five minutes, with higher prices relative to the day’s average price as the temperature got more out of the comfort zone and lower prices when the comfort zone was met. When the feeder capacity market was cleared, the real-time price was sent to all devices and those that submitted requests with prices above the real-time price turned on, while those that submitted requests below the real-time price turned off.
T
60
T
he utility’s operation focuses primarily on determining the real-time price for which constrained supply matches responsive demand. This eliminates the need for the utility to be concerned about which thermostats to turn up or down, and which appliances to turn on or off. The use of the real-timeprice double auction is probably the most straightforward method for achieving such a system and making it highly scalable. The determination of the seasonal time-of-use rate must also be done with a similar approach. In the case of the Olympic Peninsula demonstration, the time-of-use rates were net revenue neutral, rather the simply revenue neutral: the cost of delivering the energy decreased due to the roughly 9 percent demand elasticity for time-of-use customers. This cost savings was passed entirely through to the consumer, hence the net revenue neutrality. In contrast, one could argue that simple revenue neutrality passes none of the savings on to the consumer, and that to share the benefits equitable with only the
Net revenue neutrality does not imply that the utility does not stand to gain anything from adopting such strategies. There are a number of important benefits that arise from Smart Grid approaches to demand response that are shared across all customers regardless of participation. Among those identified during the course of the Olympic Peninsula demonstration are the following. A. Reduced peak The study demonstrated that for very short periods of time, very significant reductions in peak load on the bulk system were possible. The largest reduction observed on peak was nearly 60 percent. For longer periods (three days or more) sustained reductions between 15 percent and 20 percent of peak were typically observed (Figure 4). B. Increased asset utilization The reduction in peak consumption was not necessarily associated with a corresponding reduction in energy use, particularly with real-time prices,
1040-6190/$–see front matter # 2010 Elsevier Inc. All rights reserved., doi:/10.1016/j.tej.2010.05.001
The Electricity Journal
Figure 4: Peak Load Reduction of 15 Percent to 20 Percent Could Be Obtained for Sustained Periods of Time
where pre-heating/cooling and recovery are often observed — the energy consumption off-peak increased by roughly the same amount as the energy consumption was reduced onpeak. Whereas time-of-use prices usually result in energy reductions and peak reductions, real-time prices only result in peak reduction. As a result, the overall asset utilization increases more when real-time prices are introduced. C. Increased customer satisfaction The participant exit survey showed very significant customer satisfaction with the systems that were installed in their homes. This is attributed to the high degree of control and autonomy that the thermostat and water heater demand response control offered customers, and most
likely contributed highly to their willingness to remain active in the program over the duration of the project. ne very important and unexpected result of the study was the demonstration of the rate portfolio planning capability. If a utility is able to offer more than one rate plan to its customers, it must answer the question of how many customers should ideally subscribe to each plan. The question can be answered using an analog to modern portfolio theory [2,3]. The approach works as follows: 1. A business objective is chosen, such as minimum energy cost or maximum peak reduction. Any metric that can be evaluated for any mix of customers on each rate plan is permissible. 2. Sales and cost data are collected to compute the metrics for each plan. Both the mean and variance of that metric should
O
be calculated for extended periods of time, such as a season or year. 3. A portfolio analysis is performed to determine the mix of customers on each plan such that the metric is question is optimal (Figure 5). 4. The plan promotion is adjusted by varying incentives, education, and marketing to attract and retain customers for the undersubscribed plans and discourage and divert customers from oversubscribed plans. The process can be updated as often as monthly to maintain the incentives necessary to sustain the optimal plan subscription. The advantage of this technique is that it is demonstrably fair and transparent, so long as the business objective is known and approved. Regulators would simply have to approve the use of the objective, from which all the planning, marketing, operational, and billing decisions would devolve in a transparent and fair manner.
V. Consumer Benefits Beyond the potential for cost savings to consumers, we have already alluded to the fact that customer satisfaction is an important benefit that utilities see. This satisfaction rises from five important considerations. A. Significant savings Customers were offered roughly 10 percent savings. Less
June 2010, Vol. 23, Issue 5 1040-6190/$–see front matter # 2010 Elsevier Inc. All rights reserved., doi:/10.1016/j.tej.2010.05.001
61
customers said that their DR-enabled water heater performance was acceptable. C. Full automation
Figure 5: Modern Portfolio Theory Can Be Used to Optimize any Utility Objective With Respect to the Number of Customers Subscribing to a Particular Electricity Rate Plan
than 10 percent savings and it becomes difficult to convince people to ‘‘play along.’’ Consider a customer with a $1,200 annual energy bill: 10 percent savings amounts to only $10/month. How much are consumers willing to do each month for less than $10? In fact, there is evidence from surveys to suggest that customers expect savings on the order of 50 percent, especially if they aren’t told exactly what savings to expect [4]. In the case of this project, the customers were told to expect $150 in savings if they responded to savings opportunities. The only difference they would see is that the riskier the pricing the higher the potential savings. Of course, with riskier pricing there was also greater potential that if they responded incorrectly to a 62
savings opportunity, then they would see no savings at all. B. Simple to use Given the limited savings, the system must be very easy to use. The notion of a ‘‘fire and forget’’ control system is vital to the largescale success of demand response programs. Our lives are already complicated enough that we can’t afford to burden consumers with demand response programs that require regular active participation to realize benefits. The customer response to the exit surveys showed a very favorable feeling toward the systems deployed in their appliances, with 94 percent of respondents saying they were satisfied with their DRenabled dryer, 80 percent satisfied with their DR-enabled thermostat, and 96 percent of
We were surprised to learn in the exit survey that 55 percent of customers couldn’t remember which pricing plan they were on. But when asked which plan they would prefer if they could participate again, 38 percent asked for the real-time price plan and 35 percent asked for time-of-use. The ease of use of a fire-and-forget approach makes it unnecessary for consumers to constantly keep in mind the details of their energy consumption. Full automation means that we must have prices getting to devices, and the ability of devices to interpret what those prices mean in the context of the consumers’ desires, without asking the consumer every time. D. Maintaining control Automation doesn’t need to come at the expense of control. In fact, we can easily see from the exit survey data that welldesigned automation can enable a sustained sense of control. Consumers are largely hesitant to cede control to the utilities, so if they remain convinced through continuous positive reinforcement that they retain autonomy, the consumers stand to benefit in the long term. Nonetheless, 94 percent of customers said they would participate in a similar program if
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it were offered again, in spite of the fact that 64 percent experienced one or more technical problems at some point or another. E. No-lose proposition Finally, consumers must feel that the downside aspects of subscribing to a real-time price plan or a time-of-use plan are mitigated. Consumers are not fully trusting of utilities, so at least for the short term, utilities need to promote plans that protect consumers from the potential cost impacts of misusing or misunderstanding the system. In part, utilities can do a lot to mitigate the problem by discouraging consumers from subscribing to a plan that is not well suited to their lifestyle. But mechanisms such as the double declining balance accounts may remain necessary for a time, until confidence in the system is established. In the exit survey, customer didn’t expect to pay much more for the capabilities they received. The average response to the question of how much more they would expect to pay for a ‘‘grid friendly’’ water heater was just $24, suggesting that customers expect their devices to already do what is important, not just for them, but also for the grid. They don’t expect to have to consciously change their behavior, but expect the devices to ‘‘do the right thing’’ and with no downside risk or cost to them.
VI. Conclusions The benefits observed in the Olympic Peninsula demonstration accrued to both the utilities and their consumers. We see that utilities can expect Smart Grid demand response programs to reduce their risks, increase system throughput and asset utilization, and increase customer satisfaction. Consumers also see significant benefits, particularly with respect to reduced energy costs and increased autonomy when participating in demand response programs. ut the ability of utilities and consumers to receive those benefits is contingent on an equitable distribution of all the benefits available. If either the utility or the consumers receive a disproportionate allocation of the benefits, then the overall benefits will decrease over time as the disfavored party or parties become disenchanted with the program. Furthermore, attempts to over- or underutilize the resources can lead to program fatigue and an excessively high rate of participant attrition. ome very important questions will be answered by the Smart Grid demonstrations planned to begin this year and next. The primary open question is whether we can successfully scale the methods employed on a relatively small scale in the Olympic Peninsula demonstration to much larger systems. The objective is to test these systems with more than
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100,000 customers, as opposed to the 100 or so who participated in the Olympic Peninsula demonstration. Another open question we hope to learn more about in the coming year is how we best model large-scale price-based demand response programs for the purposes of utility planning, forecasting, regulation, and market operations. There is still a great deal of ongoing research in how energy management controls can and should be incorporated into consumer electronics and home appliances. This is probably the most exciting and interesting aspect of the Smart Grid, at least from the perspective of business, vendors, and manufacturers. It is not at all clear which business model for home energy management systems, if any, will prevail. It will certainly be many years before we can say with any degree of certainty which is the best approach to supporting and encouraging demand response in our daily lives.& References [1] D.J. Hammerstrom et al., Pacific Northwest GridWise Testbed Demonstration Projects Part I. Olympic Peninsula Project, PNNL-17167, Richland, WA, at http://gridwise.pnl.gov/docs/op_ project_final_report_pnnl17167.pdf [2] See http://en.wikipedia.org/ wiki/Modern_portfolio_theory [3] R. Guttromson and D. Chassin, Optimizing Retail Contracts for Electricity Markets, GridWise Architecture Council Forum, 2007, at http://www. gridwiseac.org/pdfs/forum_papers/ 101_paper_final.pdf [4] S. Shelton, NRECA/NISC GridPosium, St. Louis, April 20, 2010, at http://www.gridposium.com/
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