Nasiri, Nima, Zeynali, Saeed, Najafi Ravadanegh, Sajad and Marzband, Mousa (2022) A tactical scheduling framework for wind farm‐integrated multi‐energy systems to take part in natural gas and wholesale electricity markets as a price setter. IET Generation, Transmission & Distribution, 16 (9). pp. 1849-1864. ISSN 1751-8687
|
Text (Final published version)
IET Generation Trans Dist - 2022 - Nasiri - A tactical scheduling framework for wind farm‐integrated multi‐energy systems.pdf - Published Version Available under License Creative Commons Attribution 4.0. Download (2MB) | Preview |
|
|
Text (Advance online version)
IET Generation Trans Dist - 2022 - Nasiri - A tactical scheduling framework for wind farm‐integrated multi‐energy systems.pdf - Published Version Available under License Creative Commons Attribution 4.0. Download (2MB) | Preview |
|
|
Text
Main_file.pdf - Accepted Version Download (3MB) | Preview |
Abstract
The wind integrated multi-energy systems (MES) have gained significant momentum in recent years on account of their self-sufficiency and attractive clean attributes. This study puts forward a bi-level multi-follower optimization framework to study the tactical response of a wind integrated MES in the wholesale electricity market (WEM) and the natural gas market (NGM) as a price setter. At the upper level, the MES endeavors to minimize the overall operational costs by giving the best offer/bid in WEM/NGM, and by utilizing thermal energy storage (TES), compressed air energy storage (CAES), and natural gas storage (NGS). When the MES submits offers/bids in WEM and NGM, the NGM and WEM operators, as individual followers, clear their respective markets to maximize public welfare and announce the ultimate market-clearing price (MCP). Additionally, risk-averse and risk-seeker information gap decision theory (IGDT) have been deployed to provide various decision-making options for MES operators considering wind underproduction and overproduction scenarios. Standard 6-node natural gas network (NGN) and 6-bus transmission system (TS) have been deployed to model WEM and NGM, respectively. The results testify to the capabilities of the MES in influencing the decisions of WEM and NGM.
Item Type: | Article |
---|---|
Subjects: | H800 Chemical, Process and Energy Engineering |
Department: | Faculties > Engineering and Environment > Mathematics, Physics and Electrical Engineering |
Depositing User: | John Coen |
Date Deposited: | 18 Feb 2022 15:14 |
Last Modified: | 26 May 2022 14:45 |
URI: | http://nrl.northumbria.ac.uk/id/eprint/48496 |
Downloads
Downloads per month over past year