Compact fluorescent lamps (CFLs) are gaining widespread acceptance due to energy conservation concerns. The CFL is a significant harmonic source since its current total harmonic distortion can exceed 100%. Although each CFL consumes only a small amount of power, mass-deployed CFLs could become a significant harmonic source. This paper presents a frequency-domain harmonic model for the CFL. This model is suitable for assessing the collective impact of a large number of CFLs since it includes the impact of supply-voltage harmonics on the harmonic currents produced by the CFLs. The model is subsequently simplified and two variations are proposed. The model and its variations are verified by comparing their results with the measurements taken from various CFLs. Furthermore, the attenuation characteristics of CFLs are investigated. The results reveal the conditions in which the simplified models can be applied with acceptable errors.

Under the deregulated environment, electric utility companies have been encouraged to ensure maximum system reliability through the employment of cost-effective long-term asset management strategies. Previously, the age based Weibull distribution has been used vastly for modeling and forecasting aging failures. However, this model is only based on asset age and does not consider additional information such as asset infant mortality period and equipment energization delay. Some works on modifying Weibull distribution functions to model bathtub-shaped failure rate function can be practically difficult due to model complexity and inexplicit parameters. To improve the existing methods, this paper proposes four modified Weibull distribution models with straightforward physical meanings specific to power system applications. Furthermore, this paper proposes a novel method to effectively evaluate different Weibull distribution models and select the suitable model(s). More importantly, if more than one suitable model exists, these models can be mathematically combined as a joint forecast model, which could provide better accuracy to forecast future asset reliability. Finally, the proposed approach was applied to a Canadian utility company for the reliability forecast of electromechanical relays and distribution poles to demonstrate its practicality and usefulness.

Residential transformer population is a critical type of asset that many electric utility companies have been attempting to manage proactively and effectively to reduce unexpected transformer failures and life loss that are often caused by overloading. Within the typical power asset portfolio, the residential transformer asset is often large in population, has the lowest reliability design, lacks transformer loading data and is susceptible to customer loading behaviors, such as adoption of distributed energy resources and electric vehicles. On the bright side, the availability of more residential service operation data along with the advancement of data analytics techniques have provided a new path to further our understanding of residential transformer overloading risk statistically. This research developed a new data-driven method that combines a transformer temperature rise and insulation life loss simulation model with clustering analysis technique. It quantitatively and statistically assesses the overloading risk of residential transformer population in one area and suggests proper risk management measures according to the assessment results. Multiple application examples for a Canadian utility company have been presented and discussed in detail to demonstrate the applicability and usefulness of the proposed method.

Declining extraction costs and process efficiencies have incented the revival of the oil and gas sector post-recession. The application of drilling rigs has been done more efficiently. These loads are very large, temporary in nature, and mobile. The drilling of each well can be done as quickly as a few hours and typically not more than a few days. These massive loads are complex to own, maintain and operate, as a result few specialized drillers share the market. Because of the requirements for variable speed and control, drilling rigs are driven by Variable Frequency Drives, which are in their clear majority of older technologies such as six-pulse thyristor bridge or SCR-driven motors. These technologies are known to impose steep ramp rates (up and down), as well as rich harmonic content and variable, typically low, power factor. Furthermore, the locations of drilling rigs are typically remote, where distribution systems, if present, are weak, which lead to large background voltage distortions when such loads are present. This paper presents measurements, simulations, and analytical assessments of the characteristics and effects of harmonics and interharmonics generated by top-drive and mud-pump VFDs in a large drilling rig operated in Alberta, Canada. Measurement results reveal very high harmonic and interharmonic generation. To further refine the impact assessment of these harmonic emissions, the harmonic Attenuation Effect of the VFDs is quantified to avoid overestimating the harmonic generation of the loads. The thermal impact of the current harmonics on the coupling transformer is also quantified.

Distributed energy resources (DERs) are a new class of disruptive technologies with rapidly increasing adoption levels due to favorable government policies and subsidies. However, these emerging technologies come with technical challenges for utilities and system operators; for instance, voltage rise issues in residential secondary distribution systems with high penetration of DERs. One of the low-cost mitigation options to alleviate the overvoltage problem is reactive power absorption. Nevertheless, secondary feeders exhibit a high R/X ratio more noticeably than primary distribution systems, requiring large amount of reactive power for voltage regulation which cannot be entirely provided by the DERs alone. It is also necessary to minimize the reactive power drawn from the primary distribution system to prevent any stress on the network and reduce extra system losses. To address these critical issues, this paper proposes a distributed reactive power management, where additional source is provided from inexpensive devices such as switchable shunt reactors. The proposed overvoltage mitigation is accompanied by analytical investigation that estimates the required reactive power to manage the voltage with user specified voltage rise tolerances. Case studies have been also conducted on real residential distribution systems subjected to severe voltage rise issues provoked by large adoption of DERs

Utility companies have widely adopted the concept of health index to describe asset health statuses and choose proper asset management actions. The existing application and research works have been focused on determining the current asset health index based on the current condition data. For long-term preventative asset management, it is highly desirable to predict asset health indices in the next few years, especially for asset classes in which the assets share similar electrical, mechanical and condition degradation characteristics. This important problem has not been sufficiently addressed. This paper proposes a sequence learning based method to predict long-term health indices for power asset classes. A comprehensive data-driven method based on sequence learning is presented and solid tests are conducted based on real utility data. The proposed method revealed superior performance with comparison to other prediction methods.