Open AccessOptimal bidding strategy for wind farms considering local demand response resources
Author(s) -
Zhao Shengnan,
Wang Beibei,
Yang Xuechun,
Yang Shengchun
Publication year - 2019
Publication title -
iet renewable power generation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.005
H-Index - 76
ISSN - 1752-1424
DOI - 10.1049/iet-rpg.2018.5579
Subject(s) - bidding , purchasing , wind power , revenue , environmental economics , purchasing power , demand response , electric power system , computer science , operations research , business , power (physics) , reliability engineering , economics , electricity , engineering , electrical engineering , finance , marketing , physics , quantum mechanics , keynesian economics
The negative impacts imposed by wind power on power systems can be decomposed into different time scales. Demand response (DR) can relieve these impacts by providing different auxiliary services. However, based on the current integration requirement, wind farms cannot earn more even if they try to provide power with less negative impacts. In this regard, three indicators are proposed for three different time scales to evaluate these efforts of wind power resources. The system operator sets the purchasing price of wind power by using these indicators. It aims to encourage wind farms to improve their output curves by purchasing the DR supporting services products. In the next step, a bi‐level optimisation model is developed to assist the wind farms in their bidding and DR purchasing strategies. The case studies show that the proposed model can reduce wind power curtailment and improve the power's features. Moreover, by using the indicators as the integration requirement, the revenue of wind farms and the economic benefit of system dispatch are improved.