In this paper, the most frequently used power system maintenance strategies are reviewed. Distinction is made between strategies where maintenance consists of replacement by a new (or "good as new") component and where it is represented by a less costly activity resulting in a limited improvement of the component's condition. Methods are also divided into categories where maintenance is performed at fixed intervals and where it is carried out as needed. A further distinction is made between heuristic methods and those based on mathematical models; the models themselves can be deterministic or probabilistic. From a review of present maintenance policies in electric utilities, it is concluded that maintenance at fixed intervals is the most frequently used approach, often augmented by additional corrections. Newer "as needed"-type methods, such as reliability-centered maintenance (RCM), are increasingly considered for application in North America, but methods based on mathematical models are hardly ever used or even considered. Yet only mathematical approaches where component deterioration and condition improvement by maintenance are quantitatively linked can determine the effect of maintenance on reliability. Although more complex, probabilistic models have advantages over deterministic ones: they are capable of describing actual processes more realistically, and also facilitate optimization for maximal reliability or minimal costs.

This paper introduces a method for forecasting energy prices using artificial intelligence methods, such as neural networks and fuzzy logic, and a combination of the two. The new approach is compared with some of the exiting methods. Various factors affecting the market clearing price are investigated. Results for the Ontario electricity market are presented.

Expressions for computing the external thermal resistance (T₄) of buried cables, in both the IEEE and the IEC standards, are applicable to a limited number of installation geometries. In this paper, a method for the computation of T₄ using the finite element approach is presented. With this method, a parametric study on how cable ampacity is affected by different configurations of the backfills is performed. The obtained results are compared with those of the IEC and IEEE standards (Neher-McGrath) and published extensions by El-Kady and Horrocks. Important differences can be observed for nonstandardized situations.

A survey is offered for the various maintenance methods available for operators to preserve equipment health and extend equipment life. The methods range from the simplest, "follow-the-manual" types to detailed probabilistic approaches. To get the most out of maintenance, one has to select a mathematical model where optimization is possible. Another choice, of which operators are becoming more and more aware, is to apply a maintenance policy. This article concentrates on maintenance policies and their applications. Maintenance policy is based not on a rigid schedule but on the "as needed" principle. This can be implemented with or without mathematical models

This paper presents an algorithm for the estimation of the time-dependent temperature evolution of power cables, when real-time temperature measurements of the cable surface or a point within its vicinity are available. The thermal resistivity and specific heat of the cable surroundings are varied as functions of the moisture content which is known to vary with time. Furthermore, issues related to the cooling effect during rainy weather are considered. The algorithm is based on the lumped parameters model and takes as input distributed temperature sensing measurements as well as the current and ambient temperature. The concept is verified by studying a laboratory setup of a 245 kV cable system.