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In the context of project management, the attention given to project portfolio management has increased in recent years. The use of mathematical programming for portfolio management is also on the rise, because it integrates the project interactions with the multiple objectives of portfolio management into a single model. Among the possible objectives, recent studies have paid special attention to the emerging objective of future preparedness, which has not yet been incorporated into the existing mathematical models. This paper presents a mixed-integer nonlinear optimization model for portfolio selection that considers four main performance measures for project management, namely, value maximization, strategic alignment, balance, and future preparedness. Given the importance of the last measure, the purpose of this paper is to provide a more complete model that provides the marginal contribution and the best combination of projects according to the needs of the company. The model is tested using real data from two companies, one in Brazil and one in Canada, and the results obtained are coherent with their respective practices. [ABSTRACT FROM AUTHOR]

This paper presents a data-driven method for estimating annual continuous dynamic rating of power transformers to serve the long-term planning purpose. Historically, research works on dynamic rating have been focused on real-time/near-future system operations. There has been a lack of research for long-term planning oriented applications. Currently, most utility companies still rely on static rating numbers when planning power transformers for the next few years. In response, this paper proposes a novel and comprehensive method to analyze the past 5-year temperature, loading and load composition data of existing power transformers in a planning region. Based on such data and the forecasted area load composition, a future power transformer's load shape profile can be constructed by using Gaussian Mixture Model. Then according to IEEE std. C57.91-2011, a power transformer thermal aging model can be established to incorporate future loading and temperature profiles. As a result, annual continuous dynamic rating profiles under different temperature scenarios can be determined. The profiles can reflect the long-term thermal overloading risk in a much more realistic and granular way, which can significantly improve the accuracy of power transformer planning. A real utility application example in Canada has been presented to validate and demonstrate the practicality and usefulness of this method. [ABSTRACT FROM AUTHOR]

Monitoring the sea ice cover is important for both climate studies and ice operations, such as shipping. It is challenging to validate even basic essential variables, such as the sea ice extent, due to a lack of appropriate validation data. Instead of focusing on validation, this paper looks at the use of categorical triple collocation (CTC) for the task of quantitatively comparing three colocated data sets. CTC has been developed and used in earlier studies to rank binary data sets. In this paper, we extend earlier studies and bring in recent results from the binary classification community to estimate the class imbalance (the relative proportion of each class, ice or water). We then use this class imbalance to obtain quantitative estimates of the proportion correct of ice (sensitivity) and the proportion correct of water (specificity). The methodology is first tested using toy data, after which three data sets from the Gulf of Saint Lawrence, on the east coast of Canada, are used. These data sets are from an ice–ocean model, a passive microwave sea ice concentration retrieval, and a sea ice concentration retrieval from synthetic aperture radar (SAR). By looking at both the sensitivity and the specificity, it is found that the passive microwave data have difficulty in recognizing ice during freeze-up, but they perform well at obtaining the correct water observations. This distinction cannot be made by ranking the data sets. The CTC method is compared with, and found to be complementary to, a validation using ice/water states from the interactive multisensor snow and ice mapping system. [ABSTRACT FROM AUTHOR]

The Canadian Department of National Defence (DND) is developing an experimental over-the-horizon radar (OTHR) with the potential for surveillance of Canada. Because of dynamically changing ionospheric conditions in the Earth’s high-latitude and polar regions, the operating OTHR transmission frequency and elevation angle need to be adjusted regularly to maintain constant illumination of downrange targets. In this paper, the feasible operating frequency and elevation angle radar parameters are determined for short- and long-range OTHR operation using 3-D ionosphere ray-tracing simulations. Together, the collection of all feasible radar configurations forms a characteristic profile which shifts and deforms as factors such as the time of day, season, and solar activity are varied. The range of operating frequencies and elevation angles obtained from this paper will aid developing the transmitter and receiver antenna layouts for experimental OTHR configurations in the poorly understood high-latitude and polar regions. These methods will also help to form the basis of the frequency monitoring systems (FMS) that will control the configuration of these polar OTHR systems in real time. [ABSTRACT FROM AUTHOR]

The paper describes the recent development of a system for calibration of electrical instruments with harmonics measurement capability, such as revenue meters and power analyzers, under nonsinusoidal test conditions at National Research Council (NRC) Canada. The improvements implemented with respect to an earlier NRC calibration system are aimed at increasing the calibration accuracy in a wider frequency range. [ABSTRACT FROM AUTHOR]

In compensated distributed networks (CDN), minimizing the asymmetry in the shunt parameters of the power lines is a key factor for avoiding excessive neutral voltages which is necessary not only for safety but also for improving the sensitivity of detecting ground faults, particularly when bush-fire mitigation is a major concern. This paper offers a comprehensive analysis and modeling of the asymmetry of the power lines in CDN. Unlike the existing analyses which assume the asymmetry can be lumped in one phase, the proposed analysis is based on more practical assumption by considering the asymmetry in all of the phases of the power lines. The proposed analysis is used to develop an equivalent circuit for asymmetrical CDN which then used to develop a new method for calculating the per-phase asymmetries in the shunt parameters. The proposed method has been validated based on simulations of real networks. [ABSTRACT FROM AUTHOR]

In power systems, an asset class is a group of power equipment that has the same function and shares similar electrical and/or mechanical characteristics. Predicting failures for different asset classes is critical for electric utilities toward developing cost-effective asset management strategies. Previously, physical age based Weibull distribution has been widely used for failure prediction. However, this mathematical model cannot incorporate asset condition data. As a result, the prediction cannot be very specific and accurate for individual assets. To solve this important problem, this paper proposes a novel and comprehensive data-driven approach based on asset condition data: K-means clustering as an unsupervised learning method is used to analyze the inner structure of historical asset condition data and produce the asset conditional ages; logistic regression as a supervised learning method takes in both asset physical ages and conditional ages to classify and predict asset operation statuses. Furthermore, an index called average aging rate is defined to quantify, track, and estimate the relationship between asset physical age and conditional age. This approach was applied to a medium-voltage cable class in an urban distribution system in West Canada. Case studies and comparison with standard Weibull distribution are provided. The proposed approach demonstrates higher accuracy measured by F1-Score than Weibull distribution method for asset class failure prediction. [ABSTRACT FROM AUTHOR]

In 1999, BC Hydro installed optical fibers in the fluid channel of 525 kV self-contained fluid-filled submarine cables originally installed in the 1980s that connect substations in the Vancouver area of British Columbia, Canada, for the purposes of monitoring temperatures. In combination with this work, a real-time monitoring was used to collect load data and measured temperatures in an effort to optimize the ratings of the cables. The dynamic thermal circuit rating system developed by the Electric Power Research Institute was applied to the 525 kV cables as part of a project to modify the system for support of the unique characteristics of the cable system installation. Specifically, the submarine cables utilize a parallel pipe water cooling system for the shore zones. This paper describes the software modifications that were implemented to enhance the dynamic rating system to model the unique characteristics of the 525 kV cable system and discusses how recorded data collected over several seasons were used to verify and refine the cable rating model. The resulting evaluation showed good agreement of the dynamic rating system calculations with measured results and helped the utility better understand the ratings on these circuits and permitted the utility to perform simulations to evaluate various loading conditions. [ABSTRACT FROM AUTHOR]

With the rapid proliferation of cloud computing, the energy cost of datacenters and the impact of reactive power on the grid have become major concerns. This paper presents two energy management control schemes for distributed uninterruptible power supply (UPS) architectures utilizing lithium-ion ultracapacitors (LIC) for improved system efficiency and reactive power mitigation. One scheme is proposed for low-power servers with an internal dc bus, while another is proposed for medium-to-high-power server racks with an in-rack dc bus. The LIC and the dc bus interface with a bidirectional dc–dc converter, which allows the power supply unit to run in the optimal operating region for the improved system efficiency and power factor. The server-level UPS architecture is experimentally tested using a 200-kHz, bidirectional, multiphase dc–dc converter with hysteretic current-mode control, while achieving 33% reactive power mitigation. Based on the SciNet datacenter in Toronto, ON, Canada, a rack-level distributed UPS architecture is built in MATLAB, and system-level simulations indicate a 37% reduction in the reactive power. [ABSTRACT FROM AUTHOR]

Traditional connection of a generating station to the transmission grid typically requires either a new transmission line to an existing substation or building a new substation to segment an existing transmission line. Both of these options are capital intensive which often hurts economic viability especially small- or medium-size nonconventional generating stations. The direct connection to an existing transmission line, without the switching station, is the most economical solution to interconnect the generating station but it desensitizes the line protection and poses a risk to the ability of the protection to detect faults, particularly ground faults involving fault resistances. Multifunction relays, combined with communication-assisted schemes, now offer innovative solutions to overcome protection desensitization concerns. This paper describes these solutions which are successfully implemented by a large Canadian electric utility over the last two decades to tap connect numerous generators to the transmission grid. [ABSTRACT FROM PUBLISHER]