Paper Info
Title
Optimal Bidding Strategy of an Aggregator Based on Customers’ Responsiveness Behaviors Modeling
Abstract
Residential customers account for an indispensable part in the demand response (DR) program for their capability to provide flexibility when the system required. However, their available DR capacity has not been fully comprehended by the aggregator, who needs the information to bid accurately on behalf of the residential customers in the market transaction. To this end, this paper devised an optimal bidding strategy for the aggregator considering the bottom-up responsiveness of residential customers. Firstly, we attempt to establish the customers' responsiveness function in relation to different incentives, during which a home energy management system (HEMS) is introduced to implement load adjustment for electrical appliances. Secondly, the function is applied to the aggregator's decision-making process to formulate the optimal bidding strategy in the day-ahead (DA) market and the optimal scheduling scheme for the energy storage system (ESS) with the aim to maximize its own revenue. Finally, the validity of the proposed method is verified using the dataset from the Pecan Street experiment in Austin. The obtained outcome demonstrates the practical rationality of the proposed method.
Year
DOI
Venue
2020
10.1109/IAS44978.2020.9334893
2020 IEEE Industry Applications Society Annual Meeting
Keywords
DocType
ISSN
Aggregator,Bidding Strategy,Demand Response,Responsiveness modeling,Day-ahead market
Conference
0197-2618
ISBN
Citations 
PageRank 
978-1-7281-7193-7
0
0.34
References 
Authors
0
7
Name
Order
Citations
PageRank
Xiaoxing Lu100.34
Kangping Li201.01
Fei Wang354.91
Zhao Zhen401.01
Jingang Lai511.50
Miadreza Shafie-khah602.37
João P. S. Catalão701.69