Applying Wind Simulations for Planning and Operation of Real-Time Thermal Ratings

Greenwood, David; Ingram, Grant; Taylor, Phil

doi:10.1109/tsg.2015.2488103

Cited by 14 publications

(5 citation statements)

References 25 publications

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“…Equation ( 16) provides the voltage constraints of the network buses. Equation (17) presents the power flow constraints on the transmission lines, in which the line rating is enhanced with the DTR system.…”

Section: Problem Formulationmentioning

confidence: 99%

“…From a system-wide perspective, the DTR system was demonstrated as an efficient tool in integrating the large amount of wind power [16]. The DTR system was also shown to be able to estimate the line rating potential and the additional wind energy that can be accommodated on a DTR-enhanced line [17]. Finally, the DTR system is also able to coordinate with demand response technology for increasing the utilization of wind generation [18].…”

Section: Introductionmentioning

confidence: 99%

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Improving the Penetration of Wind Power with Dynamic Thermal Rating System, Static VAR Compensator and Multi-Objective Genetic Algorithm

2018

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The integration of renewable energy sources, especially wind energy, has been on the rise throughout power systems worldwide. Due to this relatively new introduction, the integration of wind energy is often not optimized. Moreover, owing to the technical constraints and transmission congestions of the power network, most of the wind energy has to be curtailed. Due to various factors that influence the connectivity of wind energy, this paper proposes a well-organized posterior multi-objective (MO) optimization algorithm for maximizing the connections of wind energy. In this regard, the dynamic thermal rating (DTR) system and the static VAR compensator (SVC) have been identified as effective tools for improving the loadability of the network. The propose MO algorithm in this paper aims to minimize: (1) wind energy curtailment, (2) operation cost of the network considering all investments and operations, also known as the total social cost, and (3) SVC operation cost. The proposed MO problem was solved using the non-dominated sorting genetic algorithm (NSGA) II and it was tested on the modified IEEE reliability test system (IEEE-RTS). The results demonstrate the applicability of the proposed algorithm in aiding power system enhancement planning for integrating wind energy.

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Section: Problem Formulationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Improving the Penetration of Wind Power with Dynamic Thermal Rating System, Static VAR Compensator and Multi-Objective Genetic Algorithm

2018

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“…The RTTR of overhead lines is governed by four meteorological variables, listed in order of significance: wind speed, wind direction, ambient temperature, and solar irradiance. Wind speed and direction are both heavily influenced by the local land coverage and orography [14]. Consequently, the route of an overhead line is significant in determining the likely uplift which can be achieved through RTTR, where the thermal bottlenecks are likely to occur, and where instrumentation to allow inference of the line ratings should be located.…”

Section: Overhead Line Routesmentioning

confidence: 99%

Combining energy storage and real-time thermal ratings to solve distribution network problems: benefits and challenges

Greenwood

Wade

Davison

et al. 2017

CIRED - Open Access Proceedings Journal

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Energy Storage Systems (ESS) are a combination of an energy storage medium, such as a battery or super capacitor, and a power electronic interface to allow power to be exchanged with an electrical network. Real-Time Thermal Ratings (RTTR) allows network operators to take advantage of the inherent variation in network capacity as environmental conditions fluctuate, leading to an increased rating the majority of the time. Both are emerging technologies which can provide substantial benefits to distribution network operators. They can reduce power constraints, aid in the integration of renewables, and increase network reliability and resilience. ESS are expensive to install, but they are dispatchable assets, and can provide reactive power support and voltage control to their local network. RTTR are comparatively inexpensive, but the additional capacity that is released is not dispatchable. These differences suggest that a combination of ESS and RTTR could provide robust, affordable solutions to distribution network problems that neither technology could solve in isolation. In this paper, we quantify the benefits of combining ESS and RTTR to solve distribution network problems. We demonstrate that the combination of technologies is a more effective solution to many network problems than either a conventional asset based solution, or using RTTR or ESS alone, and we identify technical and regulatory obstacles which must be overcome to harness the full potential of these, and other, emerging technologies.

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“…In [19], a new modelling method for DTR is presented which is superior in terms of both probability distribution and fitting accuracy. In [20], the wind simulations commonly employed by the wind energy industry is applied to inform rating estimation during network planning and operation. In [21], the software of Comsol Mutiphysics is used to investigate the impact of the more accurate mixed convective cooling model on overhead line conductors.…”

Section: Introductionmentioning

confidence: 99%

Real-Time Transient Thermal Rating and the Calculation of Risk Level of Transmission Lines

Liu

Yang

et al. 2018

Energies

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Abstract:With the increasing consumption of electric energy, how to improve the capacity of transmission lines within safe margins is an urgent problem to be solved. This paper presents a transient thermal rating method under real-time meteorological conditions. The result of thermal ratings under different conditions shows that this rating approach can significantly increase the capacity of the line. As some of the most critical variables are remaining time and initial temperature, their influence upon the rating is studied. The method of statistical analysis is used to determine the ampacity at different risk levels. The result indicates that with smaller remaining time, the ampacities are larger, and with larger ampacities, the risk of thermal overload is greater. The choice of risk level would heavily affect the values of ampacity.

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Applying Wind Simulations for Planning and Operation of Real-Time Thermal Ratings

Cited by 14 publications

References 25 publications

Improving the Penetration of Wind Power with Dynamic Thermal Rating System, Static VAR Compensator and Multi-Objective Genetic Algorithm

Improving the Penetration of Wind Power with Dynamic Thermal Rating System, Static VAR Compensator and Multi-Objective Genetic Algorithm

Combining energy storage and real-time thermal ratings to solve distribution network problems: benefits and challenges

Real-Time Transient Thermal Rating and the Calculation of Risk Level of Transmission Lines

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