NDLI: Research on optimal self-scheduling horizon for the wind power and large-scale CAES combined system

Content Provider	IET Digital Library
Author	Li, Yaowang Miao, Shihong Yin, Binxin Liu, Junyao Yang, Weichen Zhang, Songyan
Abstract	The self-scheduling horizon is an important schedule parameter in the self-scheduling problem. A more reasonable self-scheduling horizon can lead to higher benefits of the wind farm (WF) and large-scale compressed air energy storage (CAES) combined system. However, very few studies have been reported about the optimisation of self-scheduling horizon for a WF paired with a CAES plant. In this study, a rolling day-ahead self-scheduling framework for a WF and CAES combined system is first proposed. After that, the self-scheduling horizon optimisation model is developed in the formulation of a bilayer stochastic chance-constrained optimisation problem. The proposed model is converted into its equivalent deterministic linear formulation and then is solved. Based on the developed model, the impacts of self-scheduling horizon on the profit of the combined system are analysed. Numerical simulation results indicate that the profit of the combined system increases after using the optimal self-scheduling horizon, and the profit increment is more obvious with the increase of the CAES's energy storage capacity.
Starting Page	5197
Ending Page	5206
Page Count	10
ISSN	17518687
Volume Number	13
e-ISSN	17518695
Issue Number	Issue 22, Nov (2019)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-gtd/13/22
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-gtd.2018.7081
Journal	IET Generation, Transmission & Distribution
Publisher Date	2019-10-15
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Bilayer Stochastic Chance-constrained Optimisation Problem CAES Energy Storage Capacity CAES Plant Compressed Air Energy Storage Deterministic Linear Formulation Energy Storage Large-scale CAES Combined System Linear Programming Optimal Self-scheduling Horizon Optimisation Technique Power Generation Scheduling Power Market Power System Economics Power System Managemen Power System Operation Rolling Day-ahead Self-scheduling Framework Schedule Parameter Self-scheduling Horizon Optimisation Model Self-scheduling Problem Stochastic Programming WF Wind Farm Wind Power Wind Power Plant
Content Type	Text
Resource Type	Article
Subject	Control and Systems Engineering Energy Engineering and Power Technology Electrical and Electronic Engineering

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