Dynamic Thermal Rating System Relieves Transmission Constraint

Abstract

1 1Abstract--Dynamic thermal line rating can optimize transmission operation by capturing previously unutilized line capacity while simultaneously improving system reliability. This paper will introduce a new system for dynamically determining the thermal rating of an overhead line. The paper will focus on a case study by describing how the system was used to relieve a transmission line constraint for a wind farm in the mid-western United States. A description of the particular constraint will be presented, followed by a discussion of the installation of the dynamic rating system and the integration of the dynamic rating data into operations. Results from the first summer of operation of the system will also be presented. I. NOMENCLATUREThermal rating -the maximum current or MVA that can be transferred over a transmission line without exceeding the specified maximum operating temperature of that line.Static rating -the thermal rating of a line as determined by assumed weather conditions. A line may have multiple static ratings (e.g. summer, winter).Dynamic rating -the thermal rating of a line that is determined in real-time using actual weather conditions. Transmission line constraint -a situation where a line transfer is limited by either normal system flow or postcontingent flow (flow that would result if a failure occurred somewhere in the system) exceeding the rating of the line.

Review of dynamic line rating systems for wind power integration

“…[100] compares the traditional static rating and DLR, infers that a high capacity of overhead lines is not used during a large percentage of the time. Other similar studies in this line are the one performed in Spain by the University of Cantabria in [62], or still the research work carried out by Marshall Municipal Utilities, Shaw Energy Delivery Services and Xcel Energy in Minnesota (USA) [53]. The latter underlines that the actual line rating is above the static rating 96% of the time.…”

“…Ampacity is calculated from the solar temperature T s and the calculated equivalent wind velocity [50,51]. Some application cases are shown in [45,52,53].…”

Hybrid Hierarchical Communication Network Optimal Placement for Transmission Line Online Monitoring in Smart Grid

“…Combining with the comprehensive Vague value matrix, all schemes of Pareto optimal solution set are scored as shown in Table I. (2,5,8,11,14,17,20,23,26,29,32,35,38,41,44,47,49) 2 (3,8,13,18,23,28,33,38,43,48) 3 (4,11,18,25,32,38,43,48) 4 (5,14,23,32,40,47) 5 (6,17,28,37,46) 6 (7,20,33,45) Six schemes of Pareto optimal solution set for communication network planning are listed in Table I. They don't dominate each other.…”

A Cognitive Radio-Based Energy-Efficient System for Power Transmission Line Monitoring in Smart Grids

“…Wireless sensors are put in various components of transmission lines to collect different physical and electrical parameters of the transmission lines (like sagging, vibration, electric current density, icing effects, vegetation, overheating, etc.) [1,2]. However, delivering the huge amount of collected information to the PCC, located miles away, in a long hop-by-hop linear topology is the most critical task in developing a smart transmission grid (STG) due to short ranges, low data rates, less successful data delivery, unbalanced energy consumption, and higher data collisions in wireless sensors.…”