Agent-based modeling of the demand-side flexibility

B. Kladnik; A. Gubina; G. Artac; K. Nagode; I. Kockar

doi:10.1109/PES.2011.6039772

Agent-based modeling of the demand-side flexibility

B. Kladnik, A. Gubina, G. Artac, K. Nagode, I. Kockar

Electronic And Electrical Engineering

Research output: Contribution to conference › Paper

15 Citations (Scopus)

Abstract

The paper presents an agent-based approach to model the flexibility of the demand-side. It uses Q-learning algorithm to model a behavior of a demand-side agent, so to investigate the elasticity of the demand to the change in price. Often, market simulation models assume that the demand elasticity is known, however due the lack of data this elasticity is not easy to determine. The objective of this paper is to evaluate the flexibility of the total system demand, and the shift in the consumption with the price, i.e. increase in the demand when the price is low, and a decrease in the demand when the price is high. The here presented model of a demand-side agent is incorporated into the market simulator with double-sided auctions, and is tested on the Slovenian market. However, this approach can be used to estimate flexibility in any system for which the forecasted demand data and generation offers are know.

Original language	English
Pages	1 -8
Number of pages	8
DOIs	https://doi.org/10.1109/PES.2011.6039772
Publication status	Published - 1 Jul 2011
Event	IEEE Power and Energy Society General Meeting 2011 - Ljubljana, Slovenia Duration: 24 Jul 2011 → …

Conference

Conference	IEEE Power and Energy Society General Meeting 2011
Country/Territory	Slovenia
City	Ljubljana
Period	24/07/11 → …

Keywords

Q-learning algorithm
Slovenian market
agent-based modeling
demand data forecasting
demand elasticity
demand-side flexibility
double-sided auctions
market simulation models
learning (artificial intelligence)
power engineering computing
power generation economics
power markets
pricing

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10.1109/PES.2011.6039772

Cite this

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title = "Agent-based modeling of the demand-side flexibility",

abstract = "The paper presents an agent-based approach to model the flexibility of the demand-side. It uses Q-learning algorithm to model a behavior of a demand-side agent, so to investigate the elasticity of the demand to the change in price. Often, market simulation models assume that the demand elasticity is known, however due the lack of data this elasticity is not easy to determine. The objective of this paper is to evaluate the flexibility of the total system demand, and the shift in the consumption with the price, i.e. increase in the demand when the price is low, and a decrease in the demand when the price is high. The here presented model of a demand-side agent is incorporated into the market simulator with double-sided auctions, and is tested on the Slovenian market. However, this approach can be used to estimate flexibility in any system for which the forecasted demand data and generation offers are know.",

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AU - Gubina, A.

AU - Artac, G.

AU - Nagode, K.

AU - Kockar, I.

PY - 2011/7/1

Y1 - 2011/7/1

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AB - The paper presents an agent-based approach to model the flexibility of the demand-side. It uses Q-learning algorithm to model a behavior of a demand-side agent, so to investigate the elasticity of the demand to the change in price. Often, market simulation models assume that the demand elasticity is known, however due the lack of data this elasticity is not easy to determine. The objective of this paper is to evaluate the flexibility of the total system demand, and the shift in the consumption with the price, i.e. increase in the demand when the price is low, and a decrease in the demand when the price is high. The here presented model of a demand-side agent is incorporated into the market simulator with double-sided auctions, and is tested on the Slovenian market. However, this approach can be used to estimate flexibility in any system for which the forecasted demand data and generation offers are know.

KW - Q-learning algorithm

KW - Slovenian market

KW - agent-based modeling

KW - demand data forecasting

KW - demand elasticity

KW - demand-side flexibility

KW - double-sided auctions

KW - market simulation models

KW - learning (artificial intelligence)

KW - power engineering computing

KW - power generation economics

KW - power markets

KW - pricing

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ER -

Agent-based modeling of the demand-side flexibility

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Agent-based modeling of the demand-side flexibility

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