The Long-Run Efficiency of Real-Time Electricity Pricing

By S. Borenstein. 2005

581 citations recorded by the source corpus.

Subfields: Electrical and Electronic Engineering, Renewable Energy, Sustainability and the Environment

View Paper: https://www.semanticscholar.org/paper/2b46564a9246023e5238925156e560a6edbae043

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In Electrical and Electronic Engineering

In Renewable Energy, Sustainability and the Environment

Citations in the corpus

An overview of Demand Response: Key-elements and international experience (2017, background): “On the other hand, responding to time varying pricing de ﬁ nitely contributes to the increase in the welfare of larger commercial and industrial consumers [112].”
Real-Time Demand Response Model (2010, background): “One of these new forms of agreements is the real-time pricing of electricity (RTP) [22], [23] according to which retail electric prices change frequently to reflect variations in the cost of the energy”
Demand response in electrical energy supply: An optimal real time pricing approach (2011, background): “A long-run study of RTP efficiency is conducted in [28] being demonstrated that efficiency gains from RTP are significant even where the elasticity of demand is very low.”
Real Time Pricing and Electricity Markets (2009, methodology): “The general intuition derives from Borenstein (2005) and extends his model to imperfectly competitive second stage subgames.”
Knowledge is (Less) Power: Experimental Evidence from Residential Energy Use (2014, unknown): “…of the economy.7 One of the electricity industry’s most difficult challenges relates to the mismatch between wholesale and retail prices within and across days, despite recent advances in metering technologies (Borenstein 2002, Borenstein 2005, Borenstein and Holland 2005, Joskow and Wolfram 2012).”
An economic welfare analysis of demand response in the PJM electricity market (2008, background): “Demand response also has the potential to increase the long-run efficiency of the energy market (Borenstein, 2005).”
Time-of-Use Pricing in Electricity Markets Under Different Market Structures (2012, background): “, considering capacity investments and long-term welfare transfers) of 3%–11% of the energy bill with RTP adoption, and Borenstein [3] has simulated about a quarter of these gains for seasonal TOU pricing.”
Microgrid to enable optimal distributed energy retail and end-user demand response (2018, background): “The benefits can be expected to accrue in the long run, as customers tend to adjust their consumption behaviors and make investments in energy efficient products [50].”
Evaluating the Impacts of Real-Time Pricing on the Usage of Wind Generation (2009, background): “Reference [5] suggests that the demand response resulting from RTP could have lessened the severity of the 20002001 California electricity crisis, while [6] and [7] simul ate the efficiency gains from RTP.”
Challenges for wholesale electricity markets with intermittent renewable generation at scale: the US experience (2019, background): “At least in theory, conveying real time wholesale price signals to retail customers would be efficient in the long run (Borenstein, 2005).”
Residential implementation of critical-peak pricing of electricity (2007, background): “In theory, CPP rates that are designed to more closely reflect short-term wholesale electricity costs meet this criterion better than do time-invariant or TOU rates, but not as well as do RTP rates.”
A Real-Time Demand-Response Algorithm for Smart Grids: A Stackelberg Game Approach (2016, background): “According to a long-term investigation [7], RTP is expected to bring higher efficiency”