NDLI: Recursive dynamic regression-based two-stage compensation algorithm for dynamic economic dispatch considering high-dimensional correlation of multi-wind farms

Content Provider	IET Digital Library
Author	Xie, Min Ke, Shaojia Xiong, Jing Cheng, Peijun Liu, Mingbo
Abstract	Large-scale wind farms connected to the power grid have brought great challenges to power-system dispatch. In this study, an improved two-stage compensation stochastic optimisation algorithm based on recursive dynamic regression is proposed to solve the day-ahead dynamic economic-dispatching problem considering the high-dimensional correlation of multiple wind farms. First, a copula function is used to describe the correlation of high-dimensional wind farms. Second, a two-stage compensation stochastic-optimisation algorithm is proposed to convert the dynamic economic-dispatching model to a two-stage model with mutual iteration by decoupling the conventional and stochastic variables. In this decoupled model, the calculation of the expected compensation cost is critical and usually limited by the dimension of the correlated wind farms, which leads to inefficient convergence and long computation times. To solve those problems, a recursive dynamic multivariable linear regression method based on global least squares is proposed to improve the two-stage stochastic optimisation algorithm. This improved two-stage compensation algorithm overcomes the dimensional disaster of traditional stochastic optimisation methods and can solve the dynamic economic dispatching problem considering the high-dimensional correlation of multiple wind farms. Finally, the practicability and efficiency of the proposed algorithm are verified by the examples of an IEEE118 system and an actual provincial system.
Starting Page	475
Ending Page	481
Page Count	7
ISSN	17521416
Volume Number	13
e-ISSN	17521424
Issue Number	Issue 3, Feb (2019)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-rpg/13/3
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-rpg.2018.5494
Journal	IET Renewable Power Generation
Publisher Date	2018-11-27
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Conventional Variables Correlated Wind Farms Day-ahead Dynamic Economic-dispatching Problem Decoupled Dynamic Economic-dispatching Model Dimensional Disaster Dynamic Economic Dispatch Dynamic Economic Dispatching Problem Dynamic Updating Expected Compensation Cost High-dimensional Correlation High-dimensional Wind Farms Large-scale Wind Farms Multiple Wind Farms Multiwind Farms Optimisation Optimisation Technique Power Generation Dispatch Power Generation Economics Power Grid Power System Economics Power System Managemen Power System Operation Power-system Dispatch Recursive Dynamic Multivariable Linear Regression Method Recursive Dynamic Regression-based Two-stage Compensation Algorithm Regression Analysis Statistics Stochastic Linearised SCUC Stochastic Programming Stochastic Variables Traditional Stochastic Optimisation Method Two-stage Compensation Stochastic Optimisation Algorithm Two-stage Compensation Stochastic-optimisation Algorithm Two-stage Model Two-stage Stochastic Optimisation Algorithm Wind Power Plant Wind-power Generation
Content Type	Text
Resource Type	Article
Subject	Renewable Energy, Sustainability and the Environment

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