Electrical load growth and the addition of renewable energy generation occur at a rate that can outpace transmission development. As a consequence, transmission lines may become constrained. To accommodate load growth or distributed generation connections, one option is to operate existing transmission facilities up to their actual physical capacity rather than a conservative estimate of line capacity. Dynamic thermal rating of transmission lines provides actual current-carrying capacity of overhead lines based on real-time operating conditions. Dynamic Thermal Line Rating (DTLR) approaches vary significantly from one study to another in implementation, objectives and outcomes. Existing literature has presented several methodologies for DTLR adoption. This paper provides a comprehensive study of the literature on DTLR. It presents a survey and evaluation of various DTLR technologies, DTLR equipment, challenges with DTLR deployment, real world applications, and future approaches to DTLR implementation. The presented work is organized to allow a reader to understand and compare various DTLR approaches.

Dynamic thermal rating of transmission lines: A review

Condition monitoring for overhead power lines is critical for power transmission networks to improve their reliability, detect potential problems in the early stage, and ensure the utilization of the transmitting full capacity. Energy harvesting can be an effective solution for autonomous self-powered wireless sensors. In this paper, a novel bow-tie-shaped coil is proposed, which is placed directly under overhead power lines to scavenge the magnetic field energy. Compared to the conventional method by mounting the energy harvester on the power lines, this approach provides more flexibility and space to power bigger sensors such as the weather station. As the harvesting coil cannot entirely enclose the power lines, the demagnetization factor that is closely related to the core geometry should be considered and optimized. Thus a new bow-tie-shape core is designed to produce a much lower demagnetization factor (hence more power) than that of the conventional solenoid. The selection of core material is studied and found that Mn–Zn ferrite is the most suitable core material because it greatly reduces the eddy current losses and also has high permeability. Experiment results show that the bow-tie coil could have a power density of 1.86 μW/cm 3 when placed in a magnetic flux density of 7 $\mu{\rm T_{rms}}$ . This value is 15 times greater than the reported results under the same condition. If a longer bow-tie coil with more turns is placed in a magnetic flux density of $11 \mu{\rm T_{rms}}$ , the produced power density is 103.5 μW/cm3, which is comparable to a solar panel working during a cloudy day. Thus, the proposed solution is a very efficient and attractive method for harvesting the magnetic field energy for a range of monitoring applications.

Magnetic Field Energy Harvesting Under Overhead Power Lines

Energy systems are quickly evolving through the development of new technologies and the emergence of new operational and market design paradigms. In particular, the global push for sustainability is driving the transition towards a pronounced redesign. In fact, renewable energy integration is occurring at a massive scale, and several other exciting developments are finding their place in modern energy systems, such as distributed energy resources, demand response, energy storage technologies, and local energy markets. In this dynamic context, the process of energy policy design and implementation has found new challenges, and in supporting this key process, expansion planning models and tools can play an essential role. For example, these models can be employed to estimate the impact of a multitude of policy instruments. Thus, there is a wide interest in these tools and a variety of such models, as evidenced by a rich literature and a fast-paced evolution of this research area. Motivated by this, this work presents a comprehensive and up-to-date review on expansion planning models and tools with emphasis on their application to energy policy analysis. In particular, this paper reviews the most significant policy instruments, with an emphasis in renewable energy integration, the optimization models that have been developed for expansion planning, and existing decision-support tools for energy policy analysis. Finally, this paper also discusses the trends in the literature and the most pressing current challenges in the development and use of expansion planning models for energy policy analysis.

A comprehensive review on expansion planning: Models and tools for energy policy analysis

When a wind power system is connected to a network point there is a limit of power generation based on the characteristics of the network and the loads connected to it. Traditionally, transmission line limits are estimated conservatively assuming unfavourable weather conditions (high ambient temperature, full sun and low wind speed). However, the transmission capacity of an overhead line increases when wind speed is high, due to the cooling caused by wind in the distribution lines. Dynamic line rating (DLR) systems allow monitoring real weather conditions and calculating the real capacity of lines. Thus, when planning wind power integration, if dynamic line limits are considered instead of the conservative and static limits, estimated capacity increases. This article reviews all technologies developed for real-time monitoring during the last 30 years, as well as some case studies around the world, and brings out the benefits and technical limitations of employing dynamic line rating on overhead lines. Further, the use of these DLR systems in wind integration is reviewed.

/pdf/review-of-dynamic-line-rating-systems-for-wind-power-5dbzvebaot.pdf

Review of dynamic line rating systems for wind power integration

A Techno-Economic Analysis of solar hydrogen production by electrolysis in the north of Chile and the case of exportation from Atacama Desert to Japan

Dynamic thermal rating (DTR) has been seen as an important tool for planning and operation of power systems, and recently, for smart-grid applications. To implement an effective DTR system, it is necessary to install monitoring stations along the studied lines, with a tradeoff between accurate estimations and equipment investments. In this paper, a novel heuristic is developed for identifying the number and locations of critical monitoring spans for the implementation of DTR. The heuristic is based on the use of historical-simulated weather data, obtained from a Mesoscale Weather Model, and the statistical analysis of the thermal capacities computed in each span along the line. The heuristic is applied to a line that is 325 km long in North Chile. Optimal monitoring sets, including the number and location of required monitoring stations, are determined for different confidence levels in all line segments. The results are compared to an equidistant monitoring strategy. The proposed heuristic shows robustness since it outperforms the equidistant monitoring strategy in all of the analyzed cases, especially for the longer line segments, which are subject to more complex weather patterns.

Identification of Critical Spans for Monitoring Systems in Dynamic Thermal Rating

Optimizing Hydrothermal Scheduling with Non-Convex Irrigation Constraints: Case on the Chilean Electricity System

There is a growing interest to increase temporal resolution in power system optimization models in order to improve representation of intermittent renewable generation and thus capture more variability and costs. This increase in temporal resolution, however, presents important modeling challenges since the optimization problem complexity grows with the higher number of variables and constraints needed to represent further (discrete) time periods. In this context, this paper proposes a modeling approach in continuous time, based on a pseudo-spectral representation of Chebyshev polynomials that can be applied to a variety of power system optimization problems. In particular, this paper illustrates a specific application of the proposed modeling approach to determine continuous time operation of a small-scale power system, highlighting its main advantages such as the continuous temporal resolution, straightforward implementation of differential and integral constraints needed to properly model flexibility, and reduction of computational burden. Comparison between continuous and discrete time power system operation solutions is also presented.

Chebyshev based continuous time power system operation approach

A simple index for ventriculoarterial coupling.

The increasing use of variable generation technologies (VGTs) in power systems, such as wind and photovoltaic generation, has introduced new challenges in the definition of capacity remuneration mechanisms for promoting system reliability. In this context, in this article we propose a novel framework for determining the capacity value of VGTs to contribute to the generation system adequacy, as well as a corresponding method for allocating capacity payments in hydrothermal power systems. We show that the capacity value of VGTs increases with the presence of water reservoirs, since VGTs help relieving hydropower plants from using scarce water resources during off-peak hours thus making more resources available to supply the demand during peak hours.

/pdf/capacity-payment-allocation-in-hydrothermal-power-systems-qxoo7n1vyp.pdf

Marcelo Matus

Papers

Identification of Critical Spans for Monitoring Systems in Dynamic Thermal Rating

Optimizing Hydrothermal Scheduling with Non-Convex Irrigation Constraints: Case on the Chilean Electricity System

Chebyshev based continuous time power system operation approach

A simple index for ventriculoarterial coupling.

Capacity payment allocation in hydrothermal power systems with high shares of renewable energies