Power conversion systems are dependent on the performance and reliability of static converters. However, they are subject to frequent functional and environmental strains, which can induce failures. The anticipation of these failures is difficult but important so the operation of a system can be halted before a breakdown occurs. In the case of photovoltaic (PV) power plants, the system can be simplified into two distinct blocks: the solar panels/modules and the power inverter. A breakdown in either of these blocks can cause significant downtime in the system. Nevertheless, multiple solar module failures can often be tolerated and not lead to a total breakdown of the entire array, whereas a single component failure in the inverter can lead to a collapse of the entire system. Furthermore, solar panel/module manufacturers often offer warranties of up to 20 years, while warranties for inverters rarely reach the ten-year mark [1]. As such, the overall cost of a PV inverter can increase by a factor of two or three if it undergoes one or two failures during the life of the system. Although the market competition between PV inverter manufacturers has traditionally focused on the efficiency of their product, a failure that induces a downtime of just a few days can easily negate the yield attained through a 1% efficiency improvement. Oversizing the inverter or introducing redundancy into the inverter system is one option to improve reliability; however, often, this is not economical
Vehicles of the future will store, transport and use large amounts of electrical energy. The main components of DC networks are power electronic converters. Combinations of such converters are known to be unstable in certain situations. By investigating the causes of instability and comparing current methods, a state space representation is chosen for converter modelling. The concepts of sensitivity and participation factors applied to network models are proposed to address the requirement for algorithms aimed at optimisation. Conclusions are drawn for converters under development for aircraft systems. It is possible to identify parameters responsible for instability, sensitivity to network parameters at different operating points and the safety margins available. Thanks to this method, passive elements are optimised by reducing their global weight and volume.
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