Parallel redundancy is a common approach to increase network availability. As a consequence of providing redundancy, the loading of that component changes, affecting its reliability. In this article, a holistic approach combining two models is introduced to assess both instantaneous and future effects on general failure rates in the context of competing risks and dynamic degradation. Concretely, both are designed to account for the duration of abnormal loading events. First, a per-unit-degradation method is introduced to map the different loading states onto a single normal operation sojourn time variable. Second, a time-inhomogeneous Markov chain is introduced to assess the irreversible degradation following a nondetrimental abnormal loading event. The numerical illustration shows that both models are necessary to correctly assess the effects of redundancy dependence if the underlying failure distribution has a shape parameter exceeding one.

Transmission system operators apply selective load-shedding plans to prevent system wide interruptions and black-outs due to generation and transmission adequacy issues. If the load-shedding plan is activated, the electricity supply is intentionally switched off in indicated areas for a fixed period of time. The burden of load-shedding plans thus falls on a subset of consumers, while the benefits accrue to all consumers. This results in public opposition as illustrated with the publication of the load-shedding plan in Belgium in the winter of 2014 - 2015. To improve the social acceptability of load-shedding plans, we analyzed the unfairness of load-shedding plans based on Gini-based inequality indices and studied a top-down socialized compensation scheme and bottom-up priority service contracts to indirectly reduce the unfairness. The analysis is executed for a simplified version of the Belgian load-shedding plan for the winter of 2014 - 2015.

Given the high interruption costs of industrial processes, dependent on the cause, duration, and time, accurate availability assessment of the industrial energy systems (IES) supplying those processes is crucial in order to avoid unnecessary investments or indicate necessary improvements. A method is presented to sectionalize an IES based on its radial topology and recoverability options. Additionally, this paper introduces a novel nonrenewal stochastic process able to compute the (un)availability of single-feeder sections with respect to cause, duration, and time, taking into account competing risks, general transition rates, and both minimal and perfect corrective maintenance. An accompanying solution strategy is developed, which allows decoupling of the very diverse time constants. Finally, a numerical illustration is provided validating the proposed approach against the Markov and semi-Markov processes under their respective assumptions and illustrating the possible errors when modeling the problem using the aforementioned stochastic processes.

The use of direct current (dc) power networks, either at high voltage or at medium voltage, is being increasingly seen in modern smart grids. This is due to the flexible control possible with dc and its ability to transmit and distribute power under circumstances where alternating current (ac) networks are either unable to, or less economic. This paper provides an overview of the evolution of high-voltage dc (HVDC) transmission from early Thury systems, to modern ultrahigh-voltage dc and multiterminal voltage-source converter systems. The operation of both current-source and voltage-source systems is discussed, along with modeling requirements. The paper provides a snapshot of the state of the art of HVDC with copious references to enable in-depth reading. Key developments over the last 20 years are highlighted. Issues surrounding multiterminal operation and dc protection are explained, along with drivers in economics and policy. This will inform HVDC integration into smart grids.