Equipment Using a Predictive Health Model

Abstract—In this paper, a model-predictive control based framework is proposed for modeling and optimization of the health state of power system equipment. In the framework, a predictive health model is proposed that predicts the health state of the equipment based on its usage and maintenance actions. Based on the health state, the failure rate of the equipment can be estimated. We propose to use this predictive health model to predict the effects of different maintenance actions. The effects of maintenance actions over a future time window are evaluated by a cost function. The maintenance actions are optimized using this cost function. The proposed framework is applied in the optimization of the loading of transformers based on the thermal degradation of the paper insulation

The Electrostatic Wind Energy Converter: Electrical performance of a high voltage prototype

Wind energy is converted to electrical energy by letting the wind move charged particles against the direction of an electric field. The advantage of this type of conversion is that no rotational movement, which occurs in conventional wind turbines, is required. An electrostatic wind energy converter (EWICON) has been developed. Charged particles have been created using two spraying methods, electrohydrodynamic atomisation and high pressure monodisperse spraying. Using both methods, wind energy has been converted to electric energy and delivered to an electrical load with positive efficiency.Electrical Engineering, Mathematics and Computer Scienc

Windenergie zonder wieken

Electrical Engineering, Mathematics and Computer Scienc

UC3M Books

Contiene: Viaje a las puertas del infierno (p. 22) -- La Segunda República española (p. 23) -- El factor de impacto (p. 24

The influence of square voltage waveforms on transformer insulation break down voltage

The use of Voltage Source Converters (VSCs) in HVDC transmission and, more generally, in flexible AC transmission systems (FACTS), raises concerns over the endurance of turn/turn insulation of grid/converter interface transformers. In this paper, tests performed on oil-impregnated paper specimens are discussed. The results indicate clearly that shorter rise times and higher repetition frequencies have a strong impact on both partial discharge inception voltage and breakdown voltage. These results suggest that deeper investigation might be important to understand the long term behavior of these insulation systems

Upcoming Role of Condition Monitoring in Risk-Based Asset Management for the Power Sector

The electrical power sector is stimulated to evolve under the pressures of the energy transition, the deregulation of electricity markets and the introduction of intelligent grids. In general, engineers believe that technologies such as monitoring, control and diagnostic devices, can realize this evolvement smoothly. Unfortunately, the contributions of these emerging technologies to business strategies remain difficult to quantify in straightforward metrics. Consequently, decisions to invest on these technologies are still taken in an ad hoc manner. This is far from the risk-based approach commonly recommended for asset management (AM). The paper introduces risk-based management as a guiding principle for maintenance management. Then, the triple-level AM model (strategic, tactical and operational) as the foundation to define risk-based AM is described. Afterwards, two categories of risks, one triggered by technical stimuli and the other by non-technical stimuli are introduced. It is shown that the main challenge of managing risks with technical stimuli is to have the ability to understand the technical cause of failures, which is located at the operational level within the triple-level AM model. One method to quantitatively understand the technical cause of failures is by means of condition diagnostic and monitoring technologies. Therefore, the aim of this paper is to clarify the potential contribution of condition diagnostic and monitoring technologies to risk-based decision making for the power sector. This paper shows that, in practice, the implementation of condition diagnostic and monitoring technologies is mainly driven by purely technical asset based considerations without evaluating the contribution to, for instance, risks. This paper provides a list of aspects in which condition diagnostic and monitoring may contribute to risk evaluation with technical stimuli. The listed aspects (which are: (1) asset specific condition data, (2) timely condition data and (3) predictive condition data) can be regarded as input for the probability of failure and as influencing input for the consequence of failure, hence benefiting quantitative risk studies and AM activities (such as condition assessment/maintenance or replacement). Finally, these benefits can be evaluated afterwards in a risk-based AM planning stage, so that asset managers can justify investments on necessary technical improvements of condition monitoring systems.Electrical Sustainable EnergyElectrical Engineering, Mathematics and Computer Scienc