DocumentCode :
1144718
Title :
Purchase-Bidding Strategies of an Energy Coalition With Demand-Response Capabilities
Author :
Menniti, Daniele ; Costanzo, Ferdinando ; Scordino, Nadia ; Sorrentino, Nicola
Author_Institution :
Dept. of Electron., Comput., & Syst. Sci., Univ. of Calabria, Arcavacata of Rende, Italy
Volume :
24
Issue :
3
fYear :
2009
Firstpage :
1241
Lastpage :
1255
Abstract :
The implementation of demand-response programs (DRP) has gained interest as a means to alleviate energy consumption during peak-hours. Two explanations account for the success of such programs which involve both utilities and electricity consumers, with the latter often organized into coalitions: the system operator meets its goal of reducing the load peak; simultaneously, electricity consumers achieve economic benefits when reducing consumption during peak hours. In this paper, a Monte Carlo-based algorithm has been proposed for the formulation of multiple purchase offers in the day-ahead energy market (DAEM) by coalitions in which consumers vary in their sensitivity to DRP, manifesting different responsiveness to hourly tariffs based on the hourly market clearing prices. Being able to monitor how coalition members use air-conditioning in the presence of variable hourly energy tariffs, the coordinator can then define a purchase-bidding strategy, depending on how price-sensitive the coalition is. Simulation results show that the presence of a price-sensitive demand leads not only to a subsequent reduction in energy prices during peak-hours but also leads to a decrease in their inter-hour volatility.
Keywords :
Monte Carlo methods; air conditioning; energy consumption; load forecasting; power markets; power system economics; Monte Carlo algorithm; air conditioning; day ahead energy market; demand response programs; electricity consumers; energy coalition; energy consumption; energy tariffs; multiple purchase offers; price sensitive demand; purchase bidding strategy; Air conditioning; Delay; Energy consumption; Load management; Monitoring; Monte Carlo methods; Power demand; Power generation economics; Power system simulation; Temperature; Demand-response; inter-hour volatility; power demand; power system economics; price volatility;
fLanguage :
English
Journal_Title :
Power Systems, IEEE Transactions on
Publisher :
ieee
ISSN :
0885-8950
Type :
jour
DOI :
10.1109/TPWRS.2009.2023750
Filename :
5170201
Link To Document :
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