Cao, J, Du, W and Wang, HF (2016) Weather-Based Optimal Power Flow With Wind Farms Integration. IEEE Transactions on Power Systems, 31 (4). 3073 -3081.

[img]
Preview
Text
cao-Weather-Based Optimal Power Flow with wind farm integration-revised.pdf - Accepted Version

Download (975kB) | Preview

Abstract

In conventional optimal power flow (OPF), parameters of electrical components such as resistance and thermal ratings of the overhead lines, are assumed to be constant despite the fact that they are strongly sensitive to the weather effect (e.g., temperature or wind speed) which influences the accuracy of optimal power flow results. This paper introduces a weather-based optimal power flow (WB-OPF) algorithm with wind farm integration by considering the temperature related resistance and dynamic line rating (DLR) of overhead transmission lines. A method of calculating the current-temperature relationship of bare overhead lines, given the weather conditions, is presented as a set of coupled temperature and power flow equations. A simplified general model is proposed to calculate the dynamic line rating (DLR) for maximizing the utilization of wind power. A Primal-dual Interior Point (PDIP) method is developed to solve the WB-OPF problem. The effectiveness of the proposed method is evaluated and demonstrated in the paper by two example power systems.

Item Type: Article
Additional Information: © 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Uncontrolled Keywords: Dynamic line rating (DLR), electro-thermal coupling, weather effects, weather-based optimal power flow (WB-OPF), wind generation
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions: Faculty of Natural Sciences > School of Geography, Geology and the Environment
Depositing User: Symplectic
Date Deposited: 04 Apr 2019 09:43
Last Modified: 04 Apr 2019 09:46
URI: http://eprints.keele.ac.uk/id/eprint/6123

Actions (login required)

View Item View Item