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Pricing for Retail Electricity

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1 Pricing for Retail Electricity
INFORMS Revenue Management & Pricing Section Conference John Quillinan – IBM Global Business Services 25 June 2011 Pricing for Retail Electricity

2 The dilemma How do I meet peak energy demand with
an aging infrastructure increasing population with larger homes and a greater number of appliances, amidst rising fossil fuel costs, pressure to look at renewable fuel sources environment concerns The energy industry faces the dilemma of meeting peak energy demand with an aging infrastructure and increasing population with larger homes and a greater number of appliances, amidst rising fossil fuel costs, pressure to look at renewable fuel sources, and environment concerns.

3 One solution is demand management programs such as pricing
As the rate of energy usage increases at 2.3% per year, demand management is one means of dealing with the increasing demands for energy Using more efficient rate designs or pricing and through interruptible services, demand can be shifted from peak times, thus reducing the need for more power plants The next frontier for the revenue management and pricing practice will be helping the retail energy providers develop pricing programs, which vary prices at critical peak demand periods and discount prices the rest of the time. As the rate of energy usage increases at an average of 2.3% per year, demand management is one means of dealing with the increasing demands for energy. Using more efficient rate designs or pricing and through interruptible services, demand can be shifted from peak times, thus reducing the need for more power plants. The next frontier for the revenue management and pricing practice will be helping the retail energy providers develop pricing programs, which vary prices at critical peak demand periods and discount prices the rest of the time.

4 World population is projected to rise to more than 9 billion
The energy world is facing an unprecedented time of uncertainty with rising fuel prices, increasing demand for energy, an aging infrastructure, social and political pressure to look at renewable fuel sources, and environmental concerns. The volatility of wholesale energy pricing also adds to this uncertainty. Utility companies are facing a future with the need to invest in assets for additional power generation. Utility companies also have to deal with an aging infrastructure increasingly unable to cope with the demands of increased population, larger homes, and greater number of appliances. In the meantime, the world population is projected to rise to more than 9 billion (see Figure 1) from approximately 6.9 billion today (According to the International Programs Center, U.S. Census Bureau, the total population of the World, projected to 06/18/2011 at 04:37 UTC (EST+5) is 6,925,541,168.)

5 Consumer use of plug-in vehicles charged will increase demand
Plug-in hybrids & electric vehicles are expected reach 39% of new sales by 2035, making a big contribution to emissions abatement. At the same time, consumer use of plug-in vehicles charged through the smart grid will increase demand for electricity.

6 Conserving the environment has become a major social and political issue
Power generation creates forty one percent of worldwide CO2 emissions and is the largest manmade source of CO2 emissions. Some of the environmental concerns facing energy and utility organizations are acid rain visual pollution and site concerns nuclear waste disposal decommissioning of nuclear plants thermal pollution Greenhouse effect exposure to electromagnetic fields Energy companies are also under pressure by social and political interest to invest in renewable fuel sources. Because renewable fuel sources are generally more capital intensive than fossil fuels, the investment needed to provide the extra renewable fuel sources capacity is very large. The investment estimate in renewables to produce electricity is $5.7 trillion (in year-2009 dollars) over the period (IEA, 2010). Investment needs are greatest in China, which has now emerged as a leader in wind power and photovoltaic production, as well as a major supplier of the equipment. Conserving the environment has become a major social and political issue. Power generation creates forty one percent of global CO2 emissions, the primary cause of human-induced climate change. (IEA, 2010). Because its generation remains largely based on fossil fuels, electricity is the largest and the fastest-growing source of energy-related CO2 emissions (IEA, 2011). Some of the environmental concerns facing energy and utility organizations are acid rain, visual pollution and site concerns, nuclear waste disposal, decommissioning of nuclear plants, thermal pollution, Greenhouse effect, and exposure to electromagnetic fields. In the meantime, the environmental community is concerned with the finite availability and rising cost of fossil fuels, climate change as the result of consuming fossil fuels, and management of a utility company's carbon footprint.

7 World electricity demand will increase by about 87% between 2007 and 2035, or 2.3% per year on average It is anticipated that world primary energy demand will increase by about 87% between 2007 and 2035, or 2.3% per year on average.

8 One thousand seven hundred billion kilowatt hours each year are wasted due to distribution losses
Meanwhile, one thousand seven hundred billion kilowatt hours each year was wasted due to distributions losses.

9 Demand management is a means of dealing with meeting increasing demands for energy
This can be accomplished via shifting demand through a more efficient rate design, or price-triggered Demand Response program, and through interruptible services or reliability-triggered Demand Response programs. In the case of electric utility service, while there is normally only one provider of utility delivery services available, customers do have both short-and long-term choices to make regarding the actual consumption of electricity. In the short-term, the choices for a residential customer may boil down to a decision to turn the lights off when they leave the house. In the long-term, for example, the customer might reduce future electricity usage by buying a more efficient appliance when there is a need to replace an old appliance. Identified several decades ago, demand management is a means of dealing with meeting increasing demands for energy. This can be accomplished via shifting demand through a more efficient rate design, or price-triggered Demand Response program, and through interruptible services or reliability-triggered Demand Response programs. The assumption is that customers will make usage decisions with high regard to the prices they face in demand management pricing. In the case of electric utility service, while there is normally only one provider of utility delivery services available, customers do have both short-and long-term choices to make regarding the actual consumption of electricity. In the short-term, the choices for a residential customer may boil down to a decision to turn the lights off when they leave the house. In the long-term, for example, the customer might reduce future electricity usage by buying a more efficient appliance when there is a need to replace an old appliance.

10 Energy usage could be shifted to non-peak periods
With time-differentiated rates, some activities (perhaps hot water heating) could shift to a lower cost period. A utility customer could decide to move to a smaller or better-insulated facility. Even greater opportunities for such responses are likely to exist in some portions of the commercial and industrial sectors (where companies have flexibility to alter their usage patterns). For example, a paper mill might grind pulpwood at low off-peak rates into a storage silo, and thereby still be able to operate the rest of the facility continuously, as required by technological considerations. With time-differentiated rates, some activities (perhaps hot water heating) could shift to a lower cost period. Similarly, a utility customer could decide to move to a smaller or better-insulated facility. Even greater opportunities for such responses are likely to exist in some portions of the commercial and industrial sectors (where companies have flexibility to alter their usage patterns). For example, a paper mill might grind pulpwood at low off-peak rates into a storage silo, and thereby still be able to operate the rest of the facility continuously, as required by technological considerations.

11 Utility rate design has a role to play in guiding customer consumption decisions on an efficient path Dynamic pricing provides customers a price signal that more accurately reflects actual energy costs during the most critical hours of the year. Price signals provided by dynamic pricing can lead to reduced electricity use during peak periods when electricity is expensive and increased use during off peak times when it is cheaper—thereby lowering costs for all. Utility rate design has a role to play in guiding customer consumption decisions on an efficient path. Dynamic electricity pricing in a system where prices vary for about 100 hours annually during critical peak demand periods and discount prices the rest of the time can save customers money and push them to shift some demand to off-peak hours. Dynamic pricing provides customers a price signal that more accurately reflects actual energy costs during the most critical hours of the year. Price signals provided by dynamic pricing can lead to reduced electricity use during peak periods when electricity is expensive and increased use during off peak times when it is cheaper—thereby lowering costs for all.

12 From a rate design perspective, a static (or flat) rate is economically inefficient
When wholesale costs rise above the fixed retail price, the lack of price-responsive demand causes higher resource costs to be incurred than would otherwise be needed When wholesale costs fall below the fixed price, consumers forgo consumption that they otherwise might use productively at lower prices to expand economic activity From a rate design perspective, a static (or flat) rate is economically inefficient because it shields customers from wholesale market price volatility. Wholesale market prices can have considerable volatility from day to day and hour to hour, and there is always uncertainty about future values. Static retail rates give consumers inaccurate information about the actual resource cost of generating and delivering power. When wholesale costs rise above the fixed retail price, the lack of price-responsive demand causes higher resource costs to be incurred than would otherwise be needed. When wholesale costs fall below the fixed price, consumers forgo consumption that they otherwise might use productively at lower prices to expand economic activity. More importantly, static rates increase the total cost of meeting demand by requiring utilities to generate or purchase power even when electricity is at its highest cost. These costs are ultimately passed on to consumers.

13 Rate design changes must be made carefully
Utilities can evaluate their rates against five criteria to configure their offerings. Simplicity & Ease of Understanding Customer value proposition Retail-wholesale market connection Incentive to reduce peak demand Incentive for permanent load shifting Let’s review a few of the most popular rates (see if you recognize which one your home is on). Rate design changes must be made carefully, with a strong emphasis on informing customers. Utilities can evaluate their rates against five criteria to configure their offerings Simplicity & Ease of Understanding Will customers be able to quickly understand the rate? Is it actionable? Customer value proposition Does the rate provide customers with a significant bill savings opportunity? Retail-wholesale market connection Does the rate satisfy legislative and regulatory requirements regarding connection to the wholesale market? Incentive to reduce peak demand Is the rate expected to produce significant reductions in peak demand? Incentive for permanent load shifting Will the rate encourage customers to permanently shift load from higher cost hours to lower cost hours? Let’s review a few of the most popular rates (see if you recognize which one your home is on).

14 Rate design changes must be made carefully
Utilities can evaluate their rates against five criteria to configure their offerings. Criteria Description Simplicity & Ease of Understanding Will customers be able to quickly understand the rate? Is it actionable? Customer value proposition Does the rate provide customers with a significant bill savings opportunity? Retail-wholesale market connection Does the rate satisfy legislative and regulatory requirements regarding connection to the wholesale market? Incentive to reduce peak demand Is the rate expected to produce significant reductions in peak demand? Incentive for permanent load shifting Will the rate encourage customers to permanently shift load from higher cost hours to lower cost hours? Let’s review a few of the most popular rates (see if you recognize which one your home is on).

15 Flat rate versus inclining block rate
About two-thirds of Americans today receive electric service on either flat or declining block rates. The same rate applies regardless of the time of usage, and total energy consumption The flat rate is an average cost of energy, and does not send a price signal to the consumer Example The vast majority of US households are currently on a very simple flat rate tariff in which the marginal price per kilowatt-hour consumed does not vary other than year-to-year or perhaps season-to-season. The same rate applies regardless of the time of usage, and total energy consumption within a billing cycle. This rate is an average cost of energy, and does not send a price signal to the consumer to reduce their energy consumption. This rate design features an inverted block rate structure, meaning that the customer’s rate progressively increases (in steps) as their consumption within a month increases. The Inclining Block Rate features an inverted block rate structure, meaning that the customer’s rate progressively increases (in steps) as their consumption within a month increases.

16 Time-of-Use (TOU) rates, which constitute the most common form of product differentiation in the electric power industry The TOU rate divides the day into two or more periods, with a different rate for each period. For example, a peak period might a period from 10 am to 6 pm on weekdays, with the remaining hours being considered off-peak. The rate is higher during the peak period and lower during the off-peak, mirroring the variation in the cost of supplying electricity during those periods. With the TOU, there is certainty as to what the rates will be and when they will occur. The TOU rate is not ‘‘dispatchable,’’ and is not technically considered a ‘‘dynamic’’ rate. Time-of-Use (TOU) rates, which constitute the most common form of product differentiation in the electric power industry, are set higher for electric power consumed during peak demand to reflect the higher marginal costs of peak load generation, which thus induces customers to shift their consumption to off-peak time. The TOU rate divides the day into two or more periods, with a different rate for each period. For example, a peak period might a period from 10 am to 6 pm on weekdays, with the remaining hours being considered off-peak. The rate would be higher during the peak period and lower during the off-peak, mirroring the variation in the cost of supplying electricity during those periods. With the TOU, there would be certainty as to what the rates would be and when they would occur. In other words, the TOU rate is not ‘‘dispatchable,’’ and would not technically be considered a ‘‘dynamic’’ rate according to many definitions.

17 Super Peak TOU Rates are similar in concept to basic TOU rates.
A super peak rate applies during a specific period of the day when demand and wholesale prices are the highest This rate design still includes on peak and off-peak periods as well as super peak period. Super Peak TOU Rates are similar in concept to basic TOU rates. A super peak rate applies during a specific period of the day when demand and wholesale prices are the highest. This rate design still includes on peak and off-peak periods as well as super peak period.

18 Critical Peak Price is a similar concept to TOU with the exception that peak pricing is only applied on a few “event” days .The utility commonly advertise event days a day in advance, based on a forecast of particularly high demand. The ratio of on peak to off-peak price is higher for CPP event days than in a TOU program. The same rate structure is applied on every event day. A CPP can be applied on top of a regular TOU rate as shown in the figure to the left. Critical Peak Price is a similar concept to TOU with the exception that peak pricing is only applied on a few “event” days, typically when wholesale prices are the highest. The utility commonly advertise event days a day in advance, based on a forecast of particularly high demand. The ratio of on peak to off-peak price is higher for CPP event days than in a TOU program. The same rate structure is applied on every event day. Sometimes, CPP is applied on top of a regular TOU rate as shown in the figure

19 Rather than charging a higher rate during critical events, the Peak Time Rebate (PTR) gives customers the opportunity to buy through at the existing rate. The PTR provides a level of bill protection that is not embedded in these other rates. Because it provides a rebate during critical events but does not increase the rate during other hours, in the short run a customer’s bill can only decrease under the PTR. However, Payment of the rebates will result in an increase in the utility’s revenue requirement and, as a result, an increase in the electricity rate in the future. Rather than charging a higher rate during critical events, the PTR gives customers the opportunity to buy through at the existing rate. However, customers have an incentive for reducing critical-peak usage in the form of a rebate that for each kilowatt-hour of load reduction that is provided during the critical period.

20 Participants in Real Time Pricing (RTP) programs pay for energy at a rate with the link to the hourly market price for electricity. Participants are made aware of the hourly prices on either a day-ahead or an hour-ahead basis. Participants in RTP programs pay for energy at a rate with the link to the hourly market price for electricity. Participants are made aware of the hourly prices on either a day-ahead or an hour-ahead basis. Typically, only the largest customers (generally above one megawatt of load) face hour-ahead prices.

21 Participants in RTP programs pay for energy at a rate with the link to the hourly market price for electricity. Although RTP offers consumers the greatest potential for economic rewards,, it is often perceived as complicated or risky relative to average cost pricing Although the regulators that approve electric utilities’ pricing structures typically share economist’s intuition about the benefits of RTP, they are often concerned that consumers perceive RTP as complicated or risky relative to average cost pricing

22 AMI is prerequisite for dynamic pricing programs
Outside of pilot programs, fewer than 50,000 residential customers receive service using dynamic pricing tariffs, and they are located in a few states, such as California, Florida and Illinois. A major reason why dynamic pricing has not been offered to residential customers is the absence of advanced metering infrastructure (AMI), which is a technological prerequisite. To facilitate pricing structures, electric utilities must install household electricity meters that record usage at least hourly, instead of the traditional mechanical meter that displays cumulative total usage only. These hourly meters are often called “advanced meters”, “interval meters”, or “smart meters”. Today, outside of pilot programs, fewer than 50,000 residential customers receive service using dynamic pricing tariffs, and they are located in a few states, such as California, Florida and Illinois. A major reason why dynamic pricing has not been offered to residential customers is the absence of advanced metering infrastructure (AMI), which is a technological prerequisite. (Faruqui, Hledik and Sergici, 2010). To facilitate pricing structures, electric utilities must install household electricity meters that record usage at least hourly, instead of the traditional mechanical meter that displays cumulative total usage only. These hourly meters are often called “advanced meters”, “interval meters”, or “smart meters”.

23 If it has not already happened, a smart meter may be coming to your home
Many utilities have conducted pilot projects, installing the meters in a subset of houses and applying time-varying rates, to gauge potential savings associated with demand reductions against installation costs. . Other economic benefits to the utility of installing advanced meters are the elimination of manual meter reading, and rapid automatic notification of power outages The American Reinvestment and Recovery Act combined with private investment will put us on pace to deploy more than 40 million smart meters in American homes and businesses over the next few years that will help consumers cut their utility bills To explore the return on investment of installing advanced meters, many utilities have conducted pilot projects, installing the meters in a subset of houses and applying time-varying rates, to gauge potential savings associated with demand reductions (Faruqui and Wood, 2008) against installation costs. Other economic benefits to the utility of installing advanced meters are the elimination of manual meter reading, and rapid automatic notification of power outages. A recent US federal energy bill encourages the installation of advanced meters to support time-varying pricing (US Congress, 2005 Section 1252). By October 1, 2012, in accordance with guidelines established by the Secretary under paragraph (2), all Federal buildings shall, for the purposes of efficient use of energy and reduction in the cost of electricity used in such buildings, be metered. Each agency shall use, to the maximum extent practicable, advanced meters or advanced metering devices that provide data at least daily and that measure at least hourly consumption of electricity in the Federal buildings of the agency. The American Reinvestment and Recovery Act combined with private investment will put us on pace to deploy more than 40 million smart meters in American homes and businesses over the next few years that will help consumers cut their utility bills. (US DOE, 2009).

24 According to DOE EIA, 50% of U. S
According to DOE EIA, 50% of U.S. households are expected to have a smart meter in 2020. The Institute for Energy Efficiency estimates that approximately 65 million smart meters will be deployed by 2020, representing 50% of U.S. households. According to DOE EIA, 50% of U.S. households are expected to have a smart meter in 2020. The Institute for Energy Efficiency estimates that approximately 65 million smart meters will be deployed by 2020, representing 50% of U.S. households.

25 Does price really elicit a demand response?
So far, we have discussed different rate designs for electricity usage, but the looming question is “Does price really elicit a demand response?” So far, we have discussed different rate designs for electricity usage, but the looming question is “Does price really elicit a demand response?” Is demand for electricity price-elastic?

26 There have been dozens of experiments
There have been dozens of experiments carried out over the past 30 years According to Ahmed Faruqui, 30 pricing pilots carried out.

27 Is demand for electricity price-elastic?
According to dozens of experiments that have been carried out over the past 30 years, it is, and customers do exhibit a demand response when subjected to dynamic pricing. The key findings are: Not every customer will respond Some will respond marginally Some will respond a lot In the aggregate, they do respond quite a bit and their responses persist over time We also know the demand response to pricing programs will vary. Is demand for electricity price-elastic? According to dozens of experiments that have been carried out over the past 30 years (see Table 1), customers will exhibit a demand response when subjected to dynamic pricing. The key findings are: Not every customer will respond Some will respond marginally Some will respond a lot In the aggregate, they do respond quite a bit and their responses persist over time We also know the demand response to pricing programs will vary

28 We also know the demand response to pricing programs will vary
Most of the factors contributing to the variability are: Use of air conditioning Presence or absence of enabling technology Climate differences Weather conditions Household size Appliance Stock Price of substitute fuels Most of the factors contributing to the variability are: Use of air conditioning Presence or absence of enabling technology Climate differences Weather conditions Household size Appliance Stock Price of substitute fuels

29 Customers with CAC have a greater ability to reduce consumption .
In California’s statewide pricing pilot, customers with central air-conditioning (CAC) dropped loads by 16%, twice as much as customers without CAC. Households or residential customers are major contributors to peak demand. Faruqui and Sergici (2009) state that in the US residential customers account for a third of over-all electrical energy consumption and for a larger share of peak demand. In California’s statewide pricing pilot, residential customers responded differently (Faruqui, 2007). Thirty percent of the customers accounted for 80% of the impact. On average, residential customer dropped peak loads on critical days by 13 percent. Customers with central air-conditioning (CAC) dropped loads by 16%, twice as much as customers without CAC. The presence of enabling technologies boost impacts substantially. Newsham and Bowker found that technology to automate response to price signals increases on-peak savings compared to using price signals alone. The presence of enabling technologies can boost customer response substantially.

30 Enabling technologies play a role in customer response.
Utilities can offer enabling technology to automate household response to price signals. A smart thermostat can be programmed to automatically increase cooling set-point temperature during peak hours in response to a CPP event signal from a pager or similar system. Enabling technologies play a role in customer response. Utilities can offer enabling technology to automate household response to price signals. For example, a thermostat that can be programmed to automatically increase cooling set-point temperature during peak hours in response to a CPP event signal from a pager or similar system. By lowering the set-point temperature on your thermostat on heating days, or increasing the set-point temperature on your thermostat on cooling days, the end user can reduce their electricity usage during a peak period. In California’s statewide pricing pilot, customers with smart thermostats dropped loads by almost twice as much as the average residential customer. Moreover, those on gateway systems dropped loads by almost twice as much as customers with smart thermostats, i.e. by about 50%. In California’s statewide pricing pilot, customers with smart thermostats dropped loads by almost twice as much as the average residential customer. Those on gateway systems dropped loads by almost twice as much as customers with smart thermostats, i.e. by about 50%.

31 Here are some examples of enabling technology.
Energy Management In Home Display Energy Orb Direct Load Control Programmable Thermostat

32 Enabling technologies play a role in customer response.
Across pricing pilots, the percent reduction in peak loads are significantly higher for programs with enabling technology than those program without technology. Across pricing pilots, the percent reduction in peak loads are significantly higher for programs with enabling technology than those program without technology.

33 Weather conditions have an impact on peak reductions from dynamic pricing.
In an analysis of billing data for 70,000 households in the San Diego region during a five-year period, the nearby weather station’s daily temperature data was matched to the start and end dates for each bill. Billing-period heating and cooling degree-days, which are highly predictive measures of home heating and cooling energy demand, were used for weather variables. When measured carefully to account for billing-cycle timing, local weather and geographic effects, the relationship between weather and residential electricity consumption was found to be statistically significant. Weather conditions and climate difference can be concluded as confounding factors. Reiss and White (2008) examined data from actual (metered) energy usage for a large representative sample of households in the San Diego region during a five-year period. In their analysis of billing data for 70,000 households in the San Diego region, Reiss and White construct a household’s weather variables using the matched weather station’s daily temperature data and the exact start and end dates for each bill. The weather variables are billing-period heating and cooling degree-days, which are highly predictive measures of home heating and cooling energy demand. When measured carefully to account for billing-cycle timing, local weather, and geographic effects, the relationship between weather and residential electricity consumption was found to be statistically significant. Hence, weather conditions and climate difference can be concluded as confounding factors.

34 Demand response can vary by region.

35 Generally, hotter regions tend to experience greater peak reductions.
Dynamic prices were found to have a substantical impact in a hot climate Generally, hotter regions tend to experience greater peak reductions. Dynamic prices were found to have a substantical impact in a hot climate They had a modest but statistically significant impact even in a mild climate. They had a modest but statistically significant impact even in a mild climate.

36 Household with high levels of consumption are more responsive to price increases.
Household consumption levels, a possible measure of household size, respond differently. In an analysis of billing data for 70,000 households in the San Diego region over a five year period, households using 1000 KWh or more per month, which is typical for a large single family dwelling with air conditioning, on average reduced their consumption by approximately 25%. In contrast, households that use 200 KWh or less per month, typical of small households (one or two members) residing in apartment, exhibited a zero mean consumption response to the dramatic rise in prices. Average household consumption fell 13% over a short span of approximately 60 days, in response to an unannounced price increase, and attributed most of the response due to the subset of consumers with high consumption levels. Household with high levels of consumption are more responsive to price increases. Reiss and White evaluated income elasticity of demand and household consumption level as possible confounding factors. While income elasticity of demand has little or no effect on consumption, they found that household consumption levels, a possible measure of household size, responded differently. In their analysis of billing data for 70,000 households in the San Diego region over a five year period, households using 1000 KWh or more per month, which is typical for a large single family dwelling with air conditioning, on average reduced their consumption by approximately 25%. In contrast, households that use 200 KWh or less per month, typical of small households (one or two members) residing in airport, exhibited a zero mean consumption response to the dramatic rise in prices. In the end, Reiss and White found average household consumption fell 13% over a short span of approximately 60 days, in response to an unannounced price increase, and attributed most of the response due to the subset of consumers with high consumption levels.

37 PRISM is a model for evaluating pricing programs.
Faruqui and Wood (2009) lay out a methodology for quantifying the benefits to customers and utilities of dynamic pricing programs. A modeling system called The PRISM (Pricing Impact Simulation Model) Suite is the approach employed to assess load response. Faruqui and Wood (2009) lay out a methodology for quantifying the benefits to customers and utilities of dynamic pricing programs. A modeling system called The PRISM (Pricing Impact Simulation Model) Suite is the approach employed to assess load response.

38 PRISM was developed during the California Statewide Pricing Pilot.
PRISM was developed during the California Statewide Pricing Pilot, and became the basis for evaluating the potential of pricing program in the Federal Energy Regulatory Commission (FERC) Assessment.

39 PRISM became basis for evaluating the potential of pricing programs in the Federal Energy Regulatory Commission (FERC) Assessment. PRISM was developed during the California Statewide Pricing Pilot. The FERC Assessment (2009) predicts that peak demand will increase 15% by 2018 without demand response programs. It also found that the full-scale deployment of demand response programs, such as dynamic pricing, could reduce U.S. peak demand 14 and 20 percent of peak demand, or 138,000 to 188,000 MW by 2019. This would eliminate the need for roughly 2,000 peaking power plants. The FERC Assessment (2009) predicts that peak demand will increase 15% by 2018 without demand response programs. It also found that the full-scale deployment of demand response programs, such as dynamic pricing, could reduce U.S. peak demand 14 and 20 percent of peak demand, or 138,000 to 188,000 MW by This would eliminate the need for roughly 2,000 peaking power plants.

40 The challenge for revenue managers and analysts: Which rate designs to recommend, and for each which prices to recommend by customer segment. Address the 5 criteria (mentioned earlier) Simplicity & Ease of Understanding Customer value proposition Retail-wholesale market connection Incentive to reduce peak demand Incentive for permanent load shifting. Understanding exogenous variables is important to understanding the typical demand response profile, and which customer classes are most likely to respond.. This would eliminate the need for roughly 2,000 peaking power plants. The challenge for revenue managers and analysts: which rate designs to recommend, and for each which prices to recommend by customer segment. Address the 5 criteria (mentioned earlier) Simplicity & Ease of Understanding Customer value proposition Retail-wholesale market connection Incentive to reduce peak demand Incentive for permanent load shifting. Understanding exogenous variables is important to understanding the typical demand response profile, and which customer classes are most likely to respond.. This would eliminate the need for roughly 2,000 peaking power plants.

41 Utility needs to make its pricing programs revenue-neutral
At the same time, customers who make an effort to minimize electricity consumption during peak periods should see a reduction in their monthly electric bills. If an average customer were to make no behavior changes, they should in theory see no change in their monthly electric bill. . It would not be a good situation if the only customers who opt-in to dynamic pricing programs are the ones who would get lower bills simply by switching over to dynamic pricing rates and not making any reductions in their peak loads. How do I make my pricing programs revenue-neutral It would not be a good situation if the only customers who opt-in to dynamic pricing programs are the ones who would get lower bills simply by switching over to dynamic pricing rates and not making any reductions in their peak loads. The figure shows the timing of bill changes induced by a revenue neutral (at average baseline usage) TOU design. The higher price during the on-peak period (PP), combined with the lower price during the off-peak period (POP), relative to the flat price, imply peak-period bill increases and off-peak bill reductions. For the average customer usage pattern, these bill changes offset each other completely, leaving no net annual bill change (i.e., revenue neutrality) before accounting for any load response. However, in practice, the typical range of usage patterns in the residential class implies that some customers (e.g., those with a greater than average share of peak period usage) will experience overall bill increases, while others (e.g., those with a less than average share of peak-period usage) will see bill reductions even before undertaking any load response.

42 In conclusion, this is the next frontier for revenue management and pricing professionals.
More efficient energy rate programs are possible with the growing installation of advanced electric meters that measure power consumption hourly - or even more frequently - so that the price can vary according to demand. Dynamic pricing, in the form of time-of-use rates, critical peak pricing, or real-time pricing, reflects the change in wholesale costs for producing and transmitting electricity during peak hours, when more power plants are in use and the electrical grid is congested. By offering discounts for off-peak power - and charging a premium for peak power - utilities can reduce the need to build more infrastructure to handle short-duration spikes in consumption, ultimately reducing the overall cost of power. More efficient energy rate programs are possible with the growing installation of advanced electric meters that measure power consumption hourly - or even more frequently - so that the price can vary according to demand. Time-based, real-time and dynamic pricing reflect the change in wholesale costs for producing and transmitting electricity during peak hours, when more power plants are in use and the electrical grid is congested. By offering discounts for off-peak power - and charging a premium for peak power - utilities can reduce the need to build more infrastructure to handle short-duration spikes in consumption, ultimately reducing the overall cost of power. It’s Time for ‘Carpe Diem’ in the Energy Industry, and the next frontier for revenue management and pricing professionals.


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