Jana Heckenbergerova

Assessment of seasonal static thermal ratings of overhead transmission conductors

Deterministic static thermal ratings of overhead transmission lines are usually conservative, causing underutilization of their potential capacity. Efforts to overcome this limitation led to the development of alternative rating strategies, based on probabilistic and dynamic methods. One such strategy is the seasonal static thermal rating. It uses a probabilistic rating approach with explicit treatment of seasonal effects on conductor temperature. In this paper, we present several variants of seasonal ratings, and analyze their performance with respect to other rating approaches. Seasonal ratings use a set of predetermined probabilistic ratings that are engaged according to the season of year or time of day. By alternating among several ratings, transmission lines can be operated closer to their actual ampacity. In addition, seasonal ratings can reduce the risk of thermal overload, compared to the uniform probabilistic rating which remains constant at all times. Despite the risk reduction, and counter to the common belief, they still pose a significant risk of conductor thermal overload. Characteristics of several seasonal rating strategies are illustrated using a case study involving a power transmission line in Newfoundland, Canada. Simulation results show that seasonal ratings can provide a modest increase in transmission line throughput, compared to the basic probabilistic rating. However, they also confirm the high levels of residual risk.

Spatial Analysis of Thermal Aging of Overhead Transmission Conductors

This paper introduces a new methodology for spatial analysis of conductor thermal aging that can be performed at three different levels: point, line, and area. The methodology uses known characteristics of transmission conductors, along with load and weather data, to determine time series of conductor temperatures and corresponding thermal aging. Weather conditions can be obtained with high resolution, providing environmental conditions virtually at every point of a transmission system. This novel approach provides a complete spatiotemporal view of the thermal state of the system, bringing a whole new dimension to the research of thermal aging. All described types of aging analysis are important for effective transmission asset management, for scheduling of line maintenance or inspections, and for planning future transmission systems.

Electric power system cost/loss optimization using Dynamic Thermal Rating and linear programming

Electric power systems consist of generation, transmission, and distribution components. As the demand for electricity grows seemingly endless, it is expected that a number of constraints, such as environmental, regulatory and economic, prevent the construction of new power plants and transmission lines. Finding improved ways to utilize the capacity supplied by existing power generation facilities and power transmission infrastructure is the problem that engineers, equipment manufacturers, and regulatory agencies are now facing.

Evaluating thermal aging characteristics of electric power transmission lines

Assessment of aging characteristics of conductors and other components of power transmission networks plays an important role in asset management systems. Due to adverse effects of conductor aging caused by annealing, the conductors lose their tensile strength. Although the loss of strength is gradual, it accumulates over time and increases the probability of outages and blackouts. Therefore, the most important factor affecting the strength of transmission conductors is the operating temperature of the line. For this reason, it is important to keep track of conductor temperatures over time, in order to identify segments of power transmission network that may require more close attention, and possibly repairs. This paper describes and illustrates a new methodology for estimating conductor thermal aging using load information and weather conditions derived from historical weather reanalysis, and interpolated to locations of power transmission lines. Conductor temperature is first determined using IEEE 738 standard, and then used to estimate loss of tensile strength in a conductor. The process is illustrated for a single location of a sample transmission line, using assumed load current and historical weather information spanning a period of five years. The simulation results show that the proposed approach provides information vital for transmission asset management and transmission network operating procedures.

Dynamic thermal rating of power transmission lines related to wind energy integration

The installations of weather-dependent renewable energy sources, such as wind turbines and solar plants, increased significantly in the last two decades. They are often built in remote areas without appropriate power grid connections. The construction of a new power transmission line or improving the old one requires significant financial and time costs. The grid operators prefer to limit the power production in order to keep the load of the power line under its rating. Instead of broadly-used static rating, the existing lines can be rated in real time using a dynamic thermal rating (DTR) system. DTR of power transmission lines can usually provide a significant increase of transmission capacity compared to the static rating. The main inputs to DTR systems are measured or forecast meteorological data. The relation of DTR to the renewable resources is obvious when we consider input parameters to the calculation scheme - wind speed, ambient temperature and shortwave radiation. Exactly same variables are determining production of wind and solar energy. A case study of virtual wind farm and corresponding power transmission line shows limits of renewable energy production at given site. The results demonstrate that the optimal size of wind farm is approximately triple when using DTR comparing to the static rating.

Characterization of a wind flutter generator

A recently developed wind harvesting device based on the aeroelastic flutter effect was bench tested using a wind tunnel. This simple device, called windbelt, consists of a tensioned Mylar ribbon (airfoil) coupled to an electromagnetic transducer, and a power conditioning unit. This paper presents a characterization of the wind flutter generator. Parameters taken into account are: power, RMS voltage, current, frequency, load resistance, wind speed, ribbon tension, and angle of attack.

Pressure-based prediction of harvestable energy for powering environmental monitoring systems

Environmental monitoring systems are useful for the study of various natural phenomena. They are often deployed in remote locations, making their reliability and energy independence important. This leads to the use of energy harvesting technologies that allow the sensor platforms to operate either independently or for extended periods of time. However, it is also important to maintain quality of the collected data, namely its temporal resolution for a given purpose. To balance the trade-off between these two aspects, an energy management scheme is required. The performance of such schemes strongly depends on the accuracy of the energy forecast, often used as one of their inputs. In this contribution, several methods of varying complexity are used to predict the total amount of daily solar energy available for harvest in the near future. All proposed methods are based solely on atmospheric surface pressure, with the aim of keeping the prediction algorithm as simple as possible.

Identification of critical aging segments and hotspots of power transmission lines

Localization of hotspots and critical aging segments of transmission lines is important for operation and asset management of power transmission systems. Conductors can lose their tensile strength due to the adverse effects of conductor aging caused by annealing. Although the loss of conductor strength is gradual, it accumulates over time and increases the probability of outages and blackouts. Therefore, it is important to keep track of conductor temperatures over time and in space, in order to identify segments of power transmission network that may require more close attention, repairs, or reinforcements. This paper describes and illustrates a new methodology for localization of hotspots and identification of critical aging segments of power transmission lines. The methodology uses load information and weather conditions derived from historical weather reanalysis to derive a time series of spatially resolved map of conductor temperatures. The temperature map is then used to estimate loss of conductor tensile strength for each span of the transmission line. The process is illustrated for a sample transmission line, using assumed load current and historical weather information spanning a period of five years. The simulation results show that the proposed approach provides information vital for transmission network operating procedures and transmission asset management.

Statistical analysis of environmental measurements for design of energy-efficient monitoring systems

Environmental monitoring systems often operate in remote locations and thus must be designed for energy-efficiency and reliability. As the main tasks of such systems are sensing, logging and delivering environmental measurements, the frequency with which are these operations executed significantly affects the overall energy consumption of the monitoring devices. This work presents the results of statistical analysis of environmental measurements (air temperature, air humidity, soil moisture and photosynthetically active radiation), and evaluates how the frequency of their collection affects the accuracy of collected samples. In particular, two independent approaches are discussed. The first approach is based on the concept of stationarity for evaluating time series models, while the second seeks to determine the probability density function through the combination of descriptive statistics with ANOVA parametric analysis. The results of these analyses show that different environmental variables should be sampled with different frequencies. Implementation of this principle will decrease energy requirements of the environmental monitoring devices, and allow their energy-efficient design and long-term uninterrupted operation under demanding field conditions.

Optimization of Wind Direction Distribution Parameters Using Particle Swarm Optimization

Data describing various natural and industrial phenomena can be modeled by directional statistical distributions. In the field of energy, wind direction and wind speed are the most important variables for wind energy generation, integration, and management. This work proposes and evaluates a new method for accurate estimation of wind direction distribution parameters utilizing the well-known Particle Swarm Optimization algorithm. It is used to optimize the parameters of a site-specific wind direction distribution model realized as a finite mixture of circular normal von Mises statistical distributions. The evaluation of the proposed algorithm is carried out using a data set describing annual wind direction on two distinct locations. Experimental results show that the proposed method is able to find good model parameters corresponding to input data.