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Utility Pricing in the Prosumer Era: An Empirical Analysis of Residential Electricity Pricing in California Felipe Castro and Duncan Callaway Energy & Resources Group University of California at Berkeley January, 2016
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Changes in the electricity sector
Controllers Controllable devices Distributed generation Home storage
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Rate reform in California
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Contributing to the policy debate
Flat rate (FR) Time-of-Use Pricing (TOU) TOU + Critical Peak Pricing (TOU & CPP) TOU + Demand Charges (TOU & DC) Real Time Pricing (RTP)
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Good rate design makes a difference
Mild efficiency gains from time-varying pricing. Some households benefit up to ten time more than others. Time-varying pricing improves the economics of renewable technologies.
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Our starting point: Peak-Load Pricing
Price, cost Quantity
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The basic model
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The basic model
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Flat rate (FR) t Constraints
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Time-of-Use (TOU) t Winter day Summer day Constraints
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Real Time Pricing (RTP)
Day 1 Day 2 Day 3 No constraints
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Bottom up model household behavior
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Bottom up model household behavior
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Bottom up model household behavior
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An updated version of the basic model
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An updated version of the basic model
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Modeling California’s electricity sector
Network model of the Western Interconnection with 240 nodes Supplement the network with a model of the California residential sector Split population into four groups Homeowners / renters Have central air conditioning / do not have Supplement the data set with meteorological information
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Aggregated efficiency gains
Changes with respect to flat rate scenario 15
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Implications for different households
% of the population Increase in household’s net surplus as a percentage of the flat rate bill % increase with respect to flat rate bill
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Effects on carbon emissions
Changes with respect to flat rate scenario
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Final thoughts on rate design
Combining a top down with a bottom up approach provides new insights. Targeting different rates to different customers will likely be a better strategy than defaulting all households into Time-of-Use. Rate design can help with climate change mitigation efforts.
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Appendix
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Effect of renewables Figure 2. Expected annual changes in the pattern of spring net load (© 2012, California ISO). Source: Kristov, Lorenzo, and Stephen Keehn. “Chapter 11 - From the Brink of Abyss to a Green, Clean, and Smart Future: The Evolution of California’s Electricity Market.” In Evolution of Global Electricity Markets, edited by Fereidoon P. Sioshansi, 297–329. Boston: Academic Press,
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Network model 240 – bus network model Exogenous time series
Avg. production MWh
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Geographic locations of generating technologies
biomass coal exogenous demand gas adv. CC gas adv. CT gas conv. CC geothermal hydro nuclear solar wind
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Economic parameters of generating technologies
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Household counts per block group and node
Units per block group Units per node
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AC ownership and temperatures
Temperature and Solar production Households with AC Households with no AC Solar irradiance [kWh] Count Count Avg. temperature [°C]
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Introducing heterogeneity and adoption
Household in North California Household in South California Retail customers Array of technologies PV panel + storage Smart thermostat Smart thermostat + PV panel PV panel Tariffs Time of Use in PGE Time of Use in SCE
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Generalizing rate structures
Peak-load pricing demand-contingent fee Generalized demand-contingent fee hourly consumption hourly consumption + other metrics hourly charges hourly charges + additional charges
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