Reducing electricity consumption peaks with parametrised dynamic pricing strategies given maximal unit prices

Nicolas Höning; J.A. La Poutré

Reducing electricity consumption peaks with parametrised dynamic pricing strategies given maximal unit prices

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific

Abstract

Demand response is a crucial mechanism for flattening of peak loads. For its implementation, we not only require consumers who react to price changes, but also intelligent
strategies to select prices. We propose a parametrised metastrategy for dynamic pricing and identify suitable strategies for given scenarios through offline optimisation using a population model. We also model an important and novel constraint: a price cap (a maximal unit price) for consumer protection. We show in computational simulations that the maximal unit price influences the peak reduction potential of dynamic pricing. We compare our dynamic pricing approach with a constant pricing approach and show that our approach, used by a profitoptimising seller, is both peak-reducing and equally profitable.

Original language	English
Title of host publication	Proceedings of International Workshop on Intelligent Agent Technology, Power Systems and Energy Markets 2013
Editors	Z Vale, J Sousa, F Lopes, H Coelho
Place of Publication	Piscataway, NJ
Publisher	IEEE
Pages	1-5
Number of pages	5
Publication status	Published - 2013
Externally published	Yes
Event	IATEM 2013, Prague, Czech - Piscataway, NJ, USA Duration: 27 Aug 2013 → 27 Aug 2013

Publication series

Name
Publisher	IEEE

Conference

Conference	IATEM 2013, Prague, Czech
Period	27/08/13 → 27/08/13

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Cite this

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title = "Reducing electricity consumption peaks with parametrised dynamic pricing strategies given maximal unit prices",

abstract = "Demand response is a crucial mechanism for flattening of peak loads. For its implementation, we not only require consumers who react to price changes, but also intelligentstrategies to select prices. We propose a parametrised metastrategy for dynamic pricing and identify suitable strategies for given scenarios through offline optimisation using a population model. We also model an important and novel constraint: a price cap (a maximal unit price) for consumer protection. We show in computational simulations that the maximal unit price influences the peak reduction potential of dynamic pricing. We compare our dynamic pricing approach with a constant pricing approach and show that our approach, used by a profitoptimising seller, is both peak-reducing and equally profitable.",

author = "Nicolas H{\"o}ning and {La Poutr{\'e}}, J.A.",

year = "2013",

language = "English",

publisher = "IEEE",

pages = "1--5",

editor = "Z Vale and J Sousa and F Lopes and H Coelho",

booktitle = "Proceedings of International Workshop on Intelligent Agent Technology, Power Systems and Energy Markets 2013",

address = "United States",

note = "IATEM 2013, Prague, Czech ; Conference date: 27-08-2013 Through 27-08-2013",

}

Reducing electricity consumption peaks with parametrised dynamic pricing strategies given maximal unit prices. / Höning, Nicolas; La Poutré, J.A.
Proceedings of International Workshop on Intelligent Agent Technology, Power Systems and Energy Markets 2013. ed. / Z Vale; J Sousa; F Lopes; H Coelho. Piscataway, NJ: IEEE, 2013. p. 1-5.

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific

TY - GEN

T1 - Reducing electricity consumption peaks with parametrised dynamic pricing strategies given maximal unit prices

AU - Höning, Nicolas

AU - La Poutré, J.A.

PY - 2013

Y1 - 2013

N2 - Demand response is a crucial mechanism for flattening of peak loads. For its implementation, we not only require consumers who react to price changes, but also intelligentstrategies to select prices. We propose a parametrised metastrategy for dynamic pricing and identify suitable strategies for given scenarios through offline optimisation using a population model. We also model an important and novel constraint: a price cap (a maximal unit price) for consumer protection. We show in computational simulations that the maximal unit price influences the peak reduction potential of dynamic pricing. We compare our dynamic pricing approach with a constant pricing approach and show that our approach, used by a profitoptimising seller, is both peak-reducing and equally profitable.

AB - Demand response is a crucial mechanism for flattening of peak loads. For its implementation, we not only require consumers who react to price changes, but also intelligentstrategies to select prices. We propose a parametrised metastrategy for dynamic pricing and identify suitable strategies for given scenarios through offline optimisation using a population model. We also model an important and novel constraint: a price cap (a maximal unit price) for consumer protection. We show in computational simulations that the maximal unit price influences the peak reduction potential of dynamic pricing. We compare our dynamic pricing approach with a constant pricing approach and show that our approach, used by a profitoptimising seller, is both peak-reducing and equally profitable.

UR - http://oai.cwi.nl/oai/asset/21506/21506B.pdf

M3 - Conference contribution

SP - 1

EP - 5

BT - Proceedings of International Workshop on Intelligent Agent Technology, Power Systems and Energy Markets 2013

A2 - Vale, Z

A2 - Sousa, J

A2 - Lopes, F

A2 - Coelho, H

PB - IEEE

CY - Piscataway, NJ

T2 - IATEM 2013, Prague, Czech

Y2 - 27 August 2013 through 27 August 2013

ER -

Reducing electricity consumption peaks with parametrised dynamic pricing strategies given maximal unit prices

Abstract

Publication series

Conference

UN SDGs

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