|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|93898||2018||12 صفحه PDF||سفارش دهید||9997 کلمه|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Applied Energy, Volume 213, 1 March 2018, Pages 658-669
This paper addresses the problem faced by an aggregator of small prosumers, when participating in the energy market. The aggregator exploits the flexibility of prosumersâ 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-usersâ 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 1000Â 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).