Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14279/22050
Title: A Robust Coordinated Expansion Planning Model For Wind Farm-Integrated Power Systems With Flexibility Sources Using Affine Policies
Authors: Dehghan, Shahab 
Amjady, Nima 
Aristidou, Petros 
Major Field of Science: Engineering and Technology
Field Category: Electrical Engineering - Electronic Engineering - Information Engineering
Keywords: Dynamic thermal rating (DTR);Energy storage (ES);Planning;Robust optimization;Switching;Wind power
Issue Date: Sep-2020
Source: IEEE Systems Journal, 2020, vol. 14, no. 3, pp. 4110 - 4118
Volume: 14
Issue: 3
Start page: 4110
End page: 4118
Journal: IEEE Systems Journal 
Abstract: This article presents a two-stage adaptive robust coordinated generation and transmission expansion planning model for a wind farm-integrated power system. Also, dynamic thermal rating (DTR) systems, energy storage systems, and optimal line switching maneuvers are considered as various flexible sources to enhance the flexibility of the power system in response to uncertain variations of net system demand. The proposed approach characterizes the uncertainty of demands, wind power, and DTRs in each representative day by a polyhedral uncertainty set. Additionally, the k-means clustering technique is used to obtain upward/downward variations of correlated uncertain parameters in each representative day and to construct the uncertainty set. The proposed model is inherently intractable as it includes infinite constraints modeling enforced techno-economic limitations for all realizations of uncertain parameters. To resolve this limitation, the proposed intractable model is recast as a tractable mixed-integer linear programming problem using affine policies. The proposed approach is implemented on the Garver 6-bus and IEEE 73-bus test systems. Simulation results illustrate its flexibility, practicality, and tractability.
URI: https://hdl.handle.net/20.500.14279/22050
ISSN: 19379234
DOI: 10.1109/JSYST.2019.2957045
Rights: © IEEE
Type: Article
Affiliation : University of Leeds 
Semnan University 
Publication Type: Peer Reviewed
Appears in Collections:Άρθρα/Articles

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