One of the main challenges of energy storage units in renewable power plants is determining an efficient and optimal energy trading strategy as the majority of the electricity should be traded in the day-ahead market when no highly-accurate forecast data about wind energy availability is in access. High-Temperature Heat and Power Storage (HTHPS) system is a new energy storage technology that has received special interest from the leading energy companies in Northern Europe. In this paper, a novel model is presented to determine the optimal participation of the HTHPS system coupled with a wind farm in the energy market including the heat and electricity market. It is supposed that the owner of the mentioned system makes a decision based on forecasted data for wind generation and energy prices. The proposed problem is introduced in the optimization problem framework as a non-convex optimization problem. The simulation is carried out on a real case study related to a wind farm in Denmark coupled with an air-based HTHPS system and the results reveal the significant efficiency and appropriate performance of the proposed model to detect the best bidding strategy.
|Titel||2020 International Conference on Smart Energy Systems and Technologies (SEST)|
|Status||Udgivet - sep. 2020|
|Begivenhed||3rd International Conference on Smart Energy Systems and Technologies, SEST 2020 - Virtual, Istanbul, Tyrkiet|
Varighed: 7 sep. 2020 → 9 sep. 2020
|Konference||3rd International Conference on Smart Energy Systems and Technologies, SEST 2020|
|Periode||07/09/2020 → 09/09/2020|
|Sponsor||Yildiz Teknik Universitesi|