• Energy Research

There are different monitoring procedures in wind farms with two main objectives: (i) to improve energy production by the capability of the national electrical network and (ii) to reduce the stooped hours due to preventive and or corrective maintenance activities. In this sense, different sensors are employed to sample in real-time the working conditions of equipment, the electrical production and the weather conditions. Despite this, just the anemometer measurement can be related to the more important errors of interruption of power regulation and anemometer errors. Both errors are related to gusty winds and contribute to more than 33% of the cost of a wind farm. The present paper reports some mathematical relations between weather and maintenance but there are no extreme values of each variable that let us predict a near failure and its corresponding loss of working hours. To achieve this, statistical analysis identifies the relation between weather variables and errors and different models are obtained. What is more, due to the difficulty and economic implications involving the implementation of complex algorithms and techniques of artificial intelligence, it is still a challenge to optimize this process. Finally, the obtained results show a particular case study that can be extrapolated to other wind farms after different case studies to adjust the model to different weather regions, and serve as a useful tool for weather maintenance.

The majority of buildings in Europe are at present naturally ventilated and do not use heating or cooling equipment throughout the summer. However, this idea is changing and as a result heating ventilation air conditioning (HVAC) related energy consumption has been rising in the recent years. On the other hand, predictions published by the intergovernmental Panel on Climate Change (IPCC) indicate an annual warming rate ranging between 0.1 and 0.4 °C. In the present study, the ISO 13790:2011 standard has been employed to analyze the effect of building design corrections over the energy saving of a real building during its mean life and under climatic change predictions. In this sense, the effect of climate change, ventilation rate and its energetic and carbon dioxide emissions implications are obtained for the next 15 years. The results obtained indicate that an increment in the air changes by natural ventilation will be more effective than changing the wall structure and, in consequence, the thermal inertia. In particular, it was obtained that an increase of natural ventilation will always reduce the energy consumption and that this consumption will be lower with time due to an increment of an average outdoor air temperature. This modification will allow reduced cooling energy peak demands during the summer season and improve indoor ambiences in mild regions and the energy efficiency.

The present study introduces a new procedure to analyze and design wind farms maintenance plans, based on analysis of variance, that can be directly implemented by the own operator. This methodology, based on a one-way analysis of variance study of weather variables and wind turbine working conditions, allows to define the exact operating range at which each of the most frequent errors in wind farms used to happen. Typically, most frequent errors, like freezing of anemometers, excessive orientation time errors, brake shoe excessive temperature, emergency stop, and asymmetric currents, appear under certain weather, temperature, and wind velocity conditions, in such a way that they can be modeled as a function of wind velocity and wind direction. In a similar way, other analyzed errors, such as starting problems and errors in current phase sequence, showed a tendency to appear under specific wind orientations.