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Optimal supply and demand bidding strategy for an aggregator of small prosumers (vol 213, pg 658, 2018)

Title
Optimal supply and demand bidding strategy for an aggregator of small prosumers (vol 213, pg 658, 2018)
Type
Article in International Scientific Journal
Year
2018
Authors
José Iria
(Author)
Other
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Filipe Soares
(Author)
Other
The person does not belong to the institution. The person does not belong to the institution. The person does not belong to the institution. View Authenticus page Without ORCID
Journal
Title: Applied EnergyImported from Authenticus Search for Journal Publications
Vol. 213
Pages: 658-669
ISSN: 0306-2619
Publisher: Elsevier
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Publicação em ISI Web of Knowledge ISI Web of Knowledge - 0 Citations
Publicação em Scopus Scopus - 0 Citations
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Other information
Authenticus ID: P-00N-X0Z
Resumo (PT):
Abstract (EN): This paper addresses the problem faced by an aggregator of small prosumers, when participating in the energy market. The aggregator exploits the flexibility of prosumers' appliances, in order to reduce its market net costs. Two optimization procedures are proposed. A two-stage stochastic optimization model to support the aggregator in the definition of demand and supply bids. The aim is to minimize the net cost of the aggregator buying and selling energy at day-ahead and real-time market stages. Scenario-based stochastic programing is used to deal with the uncertainty of electricity demand, end-users' behavior, outdoor temperature and renewable generation. The second optimization is a model predictive control method to set the operation of flexible loads in real-time. A case study of 1000 small prosumers from the Iberian market is used to compare four day-ahead bidding strategies and two real-time control strategies, as well as the performance of combined day-ahead and real-time strategies. The numerical results show that the proposed strategies allow the aggregator to reduce the net cost by 14% compared to a benchmark typically used by retailers (inflexible strategy).
Language: English
Type (Professor's evaluation): Scientific
No. of pages: 12
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