Svoboda | Graniru | BBC Russia | Golosameriki | Facebook

short-paper

Monotonic marginal pricing: demand response with price certainty

Authors:

William G. Temple,

Richard T.B. MaAuthors Info & Claims

ACM SIGMETRICS Performance Evaluation Review, Volume 41, Issue 3

Pages 65 - 70

https://doi.org/10.1145/2567529.2567551

Published: 10 January 2014 Publication History

Abstract

In this paper we develop a general dynamic pricing scheme based on consumer-indexed marginal cost, and demonstrate its properties in a simulated electricity market derived from New York ISO data. We show that monotonic marginal (MM) pricing provides price certainty, ensuring that every consumer's instantaneous price is non-increasing for a constant consumption level. Additionally, we show that MM pricing ensures budget balance for energy suppliers, allowing them to recover any operating costs and a profit margin. Using a Summer 2012 peak load day as a case study, we simulate a population of over 25000 electricity users and evaluate the performance of an example MM pricing plan versus historical real-time prices under various demand elasticities. The results demonstrate that MM pricing can provide system-level demand response and cost savings comparable with real-time pricing, while protecting consumers from price volatility.

References

[1]

M. H. Albadi and E. El-Saadany. Demand Response in Electricity Markets: An Overview. In IEEE Power Engineering Society General Meeting, 2007.

[2]

H. Allcott. Rethinking real-time electricity pricing. Resource and Energy Economics, 2011.

[3]

R. Baldick, U. Helman, B. Hobbs, and R. O'Neill. Design of Efficient Generation Markets. Proceedings of the IEEE, 2005.

[4]

G. Barbose, C. Goldman, and B. Neenan. A Survey of Utility Experience with Real Time Pricing. Technical report, Lawrence Berkeley National Laboratory, 2004.

[5]

S. Borenstein. Customer Risk from Real-Time Retail Electricity Pricing: Bill Volatility and Hedgability. The Energy Journal, 2007.

[6]

S. Borenstein and S. Holland. On the Efficiency of Competitive Electricity Markets with Time-Invariant Retail Prices. RAND Journal of Economics, 2005.

[7]

S. Braithwait, D. Hansen, and M. O'Sheasy. Retail Electricity Pricing and Rate Design in Evolving Markets. Technical report, Edison Electric Institute, 2007.

[8]

DOE. Benefits of demand response in electricity markets and recommendations for achieving them. Technical report, United States Department of Energy, 2006.

[9]

Energy Information Administration. Electric Power Monthly, Table 5.6.A. http://www.eia.gov/electricity/monthly/.

[10]

S. E. Fleten and E. Pettersen. Constructing Bidding Curves for a Price-Taking Retailer in the Norwegian Electricity Market. IEEE Transactions on Power Systems, 2005.

[11]

D. Flynn. Thermal Power Plant Simulation and Control. Institution of Engineering and Technology, 2003.

[12]

D. Hammerstrom, T. Oliver, R. Melton, and R. Ambrosio. Standardization of a Hierarchical Transactive Control System. Grid Interop, 2009.

[13]

E. Hausman, R. Hornby, and A. Smith. Bilateral Contracting in Deregulated Electricity Markets. Technical report, Synapse Energy Economics Inc., 2008.

[14]

A. E. Kahn, P. C. Cramton, R. H. Porter, and R. D. Tabors. Pricing in the California Power Exchange Electricity Market: Should California Switch from Uniform Pricing to Pay-as-Bid Pricing? Technical report, California Power Exchange, 2001.

[15]

L. Kleinrock. Queueing Systems. John Wiley & Sons, 1975.

Digital Library

[16]

N. Kumar, P. Besuner, S. Lefton, D. Agan, and D. Hilleman. Power Plant Cycling Costs. Technical report, National Renewable Energy Laboratory, 2012.

[17]

J.-Y. Le Boudec and D.-C. Tomozei. Demand Response Using Service Curves. In IEEE Innovative Smart Grid Technologies Europe, 2011.

[18]

Monitoring Analytics, LLC. State of the Market Report for PJM: January through September. Technical report, PJM Interconnection, 2012.

[19]

NYISO. Demand response activations. http://www.nyiso.com/public/webdocs/markets_ operations/market_data/demand_response/Demand_ Response/Demand_Response_Activations/Historic_EDRP_ and_SCR_Activation_Information.pdf.

[20]

NYISO. Market & operational data. http://www.nyiso.com/public/markets_operations/market_data/pricing_data/index.jsp.

[21]

NYSEG. Typical residential electricity bill amount. https://www.nyseg.com/YourAccount/readingyourbill/electricitycost.html.

[22]

M. Roozbehani, M. Dahleh, and S. Mitter. Volatility of Power Grids Under Real-Time Pricing. IEEE Transactions on Power Systems, 2012.

[23]

D. Ton, M. A. Biviji, E. Nagypal, and J. Wang. Tool for Determining Price Elasticity of Electricity Demand and Designing Dynamic Price Program. In IEEE Innovative Smart Grid Technologies, 2013.

Cited By

Yoo YJeon SNewaz SLee IChoi J(2021)Energy Trading among Power Grid and Renewable Energy Sources: A Dynamic Pricing and Demand Scheme for Profit MaximizationSensors10.3390/s2117581921:17(5819)Online publication date: 30-Aug-2021
https://doi.org/10.3390/s21175819
Javed HBeg MMujtaba HMajeed HAsim M(2018)Fairness in Real-Time Energy Pricing for Smart Grid Using Unsupervised LearningThe Computer Journal10.1093/comjnl/bxy071Online publication date: 13-Jul-2018
https://doi.org/10.1093/comjnl/bxy071
Munoz-Alvarez DTong L(2016)On the efficiency of connection charges under renewable integration in distribution systems2016 Information Theory and Applications Workshop (ITA)10.1109/ITA.2016.7888162(1-6)Online publication date: Jan-2016
https://doi.org/10.1109/ITA.2016.7888162
Show More Cited By

Index Terms

Monotonic marginal pricing: demand response with price certainty

Recommendations

Pricing commodities

How should a seller price her goods in a market where each buyer prefers a single good among his desired goods, and will buy the cheapest such good, as long as it is within his budget? We provide efficient algorithms that compute near-optimal prices for ...
Pricing with markups in industries with increasing marginal costs

We study a game that models a market in which heterogeneous producers of perfect substitutes make pricing decisions in a first stage, followed by consumers that select a producer that sells at lowest price. As opposed to Cournot or Bertrand competition, ...
Pricing Rule in a Clock Auction

We analyze a discrete clock auction with lowest-accepted-bid (LAB) pricing and provisional winners, as adopted by India for its 3G spectrum auction. In a perfect Bayesian equilibrium, the provisional winner shades her bid, whereas provisional losers do ...

Comments

Information & Contributors

Information

Published In

ACM SIGMETRICS Performance Evaluation Review Volume 41, Issue 3

December 2013

111 pages

ISSN:0163-5999

DOI:10.1145/2567529

Editor:
Giuliano Casale
Imperial College London, London

Issue’s Table of Contents

Copyright © 2014 Authors.

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 10 January 2014

Published in SIGMETRICS Volume 41, Issue 3

Check for updates

Qualifiers

Short-paper

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

5
Total Citations
View Citations
99
Total Downloads

Downloads (Last 12 months)3
Downloads (Last 6 weeks)1

Reflects downloads up to 27 Aug 2024

Other Metrics

View Author Metrics

Citations

Cited By

Yoo YJeon SNewaz SLee IChoi J(2021)Energy Trading among Power Grid and Renewable Energy Sources: A Dynamic Pricing and Demand Scheme for Profit MaximizationSensors10.3390/s2117581921:17(5819)Online publication date: 30-Aug-2021
https://doi.org/10.3390/s21175819
Javed HBeg MMujtaba HMajeed HAsim M(2018)Fairness in Real-Time Energy Pricing for Smart Grid Using Unsupervised LearningThe Computer Journal10.1093/comjnl/bxy071Online publication date: 13-Jul-2018
https://doi.org/10.1093/comjnl/bxy071
Munoz-Alvarez DTong L(2016)On the efficiency of connection charges under renewable integration in distribution systems2016 Information Theory and Applications Workshop (ITA)10.1109/ITA.2016.7888162(1-6)Online publication date: Jan-2016
https://doi.org/10.1109/ITA.2016.7888162
Azuma SNakamoto TIzumi SKitao TMaruta I(2015)Randomized automated demand response for real-time pricing2015 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT)10.1109/ISGT.2015.7131807(1-5)Online publication date: Feb-2015
https://doi.org/10.1109/ISGT.2015.7131807
Tang WJain RRajagopal R(2014)Stochastic dynamic pricing: Utilizing demand response in an adaptive manner53rd IEEE Conference on Decision and Control10.1109/CDC.2014.7040400(6446-6451)Online publication date: Dec-2014
https://doi.org/10.1109/CDC.2014.7040400

View Options

Get Access

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Media

Figures

Other

Tables

View Issue’s Table of Contents