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Title: Exploitation of uncertain weather forecast data in power network management
Authors: Tomisawa, Y.
Ohki, K.
Sugihara, H.
Kashima, K.
Ohta, Y.
Author's alias: 大木, 健太郎
Keywords: Stochastic model predictive control
Applications
Electric power systems
Electrical network
Parallel circuit transmission lines
Issue Date: 2016
Publisher: Elsevier BV
Journal title: IFAC-PapersOnLine
Volume: 49
Issue: 22
Start page: 85
End page: 90
Abstract: In power network management, the heat capacity of transmission lines originally arises from the line temperature constraint. The line temperatures are affected not only by the Joule heat but also by the thermal environment. This motivates us to exploit weather forecast data to improve the power management performance. The goal of this paper is to propose a stochastic model predictive control scheme for this purpose. In particular, we compensate for the probabilistic uncertainty by means of chance constraint optimization. The effectiveness of the proposed control scheme is examined through numerical simulation of power grids under the area dependent uncertainty and transmission line failure.
Rights: © 2016, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd.
The authors may share the final published article on public non-commercial sites in the terms of the Creative Commons CC-BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/).
URI: http://hdl.handle.net/2433/250512
DOI(Published Version): 10.1016/j.ifacol.2016.10.377
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