Power Routing: A New Paradigm for Maintenance Scheduling

Abstract

Nowadays, the necessity of efficient and reliable power systems is increasing in order to meet the strict requirements imposed by standards and regulations with minimum cost. One specific requirement is focused on the maximization of the power converters lifetime what produces a reduction in the maintenance cost. However, to overcome the related challenges is not a straight-forward task as it involves knowledge of power devices physics, smart management of electrical magnitudes and optimal maintenance planning and scheduling. It represents a multidisciplinary issue being faced in the last decade. As a first issue to be considered, it is clear that the evolution of power electronics is playing a principal role in the world in many ways:• development of environmentally friendly and economically affordable clean energy sources such as the wind and solar energy [1],• installation and enhancement of facilities to develop the robust, reliable and high quality distributed electrical grid including the smart grid paradigm with distributed energy storage systems [2]-[5],• efficient and low cost freight transportation based on electric vehicles, low-fuel consumption cargo ships and more electric aircraft [6],• personal transportation such as electric motorbikes, electric cars, robust high-speed trains, efficient subways with regenerative breaking, public electric buses, etcetera [7].The power electronic applications, that include multi-disciplinary research topics such as digital signal processing, power electronics and power systems, have actually experienced a technology disruption in the last decades [8]:1) new power semiconductor devices with high voltage/current ratings and very low power losses; 2) powerful microprocessor hardware platforms including accurate sensors and high-bandwidth data acquisition systems; 3) effective simulation and design software tools to predict the behavior of power systems.Power electronics reliability and consequently the corresponding required power systems maintenance cost is one of the major concerns of this technology [9]. An accurate estimation of the remaining useful lifetime (RUL) of a power converter is fundamental to reduce the maintenance cost [10]. Historically, the first approaches to estimate the RUL were just limited by the manufacturers guarantee. The power system operator just counted the power converter years in operation to decide when it had to be replaced by a new unit. But it is clear that the accuracy of this approach is low because the RUL highly depends on the operating conditions of the power system, usually called mission profile. For instance, factors such as the ambient temperature and the actual power that is managed by the power system highly influences the possibility of failure in any power converter component [11].

The Role of Renewable Energy System in Reshaping the Electrical Grid Scenario

“…The basic idea is to route the power arbitrarily between the parallel/series connections, according to the remaining lifetime of the components. In this way, if a good reliability model is available and the stress is estimated on-line, it is possible to optimize the maintenance scheduling [109].…”

A Novel Three-Pulse Equivalent Power Loss Profile for Simplified Thermal Estimation

“…By solving the first-order derivative of (5) expressed as (6), the time point of unique maximum and minimum junction temperature can be located accurately. It can be seen that thermal characteristics are affected by some factors, such as thermal resistance R thj , thermal time constant τ thj , the peak value of the half-sine power loss P peak , the fundamental frequency f0, and the initial temperature difference ∆Tj_in.…”

Probabilistic forecasting informed failure prognostics framework for improved RUL prediction under uncertainty: A transformer case study

“…In particular, in the area of power and energy systems, owing to the increasing advent of dynamic and stochastic energy applications, monitoring and reliability applications are rapidly departing from deterministic operation contexts [16,17]. This application context, including renewable energy systems [18] and electric vehicles [19], along with the inherent PHM modelling uncertainties, invalidates the use of deterministic lifetime models owing to the generated dynamics and sources of uncertainty that affect the operation conditions and lifetime management practices [20,21].…”