ABSTRACT
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.
Subject(s)
Artificial Intelligence , Climate , Energy-Generating Resources , Wind , Spain , WeatherABSTRACT
Urban microclimate patterns can play a great role for the allocation and management of cooling and heating energy sources, urban design and architecture, and urban heat island control. Therefore, the present study intends to investigate the variability of spatial and temporal entropy of the Effective Temperature index (ET) for the two basic periods (1971-2010) and the future (2011-2050) in Tehran to determine how the variability degree of the entropy values of the abovementioned bioclimatic would be, based on global warming and future climate change. ArcGIS software and geostatistical methods were used to show the Spatial and Temporal variations of the microclimate pattern in Tehran. However, due to global warming the temperature difference between the different areas of the study has declined, which is believed to reduce the abnormalities and more orderly between the data spatially and over time. It is observed that the lowest values of the Shannon entropy occurred in the last two decades, from 2030 to 2040, and the other in 2040-2050. Because, based on global warming, dominant areas have increased temperature, and the difference in temperature is reduced daily and the temperature difference between the zones of different areas is lower. The results of this study show a decrease in the coefficient of the Shannon entropy of effective temperature for future decades in Tehran. This can be due to the reduction of temperature differences between different regions. However, based on the urban-climate perspective, there is no positive view of this process. Because reducing the urban temperature difference means reducing the local pressure difference as well as reducing local winds. This is a factor that can effective, though limited, in the movement of stagnant urban air and reduction of thermal budget and thermal stress of the city.
ABSTRACT
BACKGROUND: Galicia, in northwest Spain, experiences warm summers and winters. However, the higher relative humidity that prevails the whole year through and the location of the summer hot points are related to real weather heat stroke in the hottest season. However, Planet Global Heating was recently analyzed for the climate in Galicia. Climate change was found to be able to trigger effects that involve a new situation with new potential regions of risk. In this paper, 50 weather stations were selected to sample the weather conditions in this humid region, over the last 10 years. From these results, new regions with a potential for heat stroke risk in the next 20 years were identified using the humidex index. RESULTS: Results reveal that during the last 10 years, the winter season presents more comfortable conditions, whereas the summer season presents the highest humidex value. Further, the higher relative humidity throughout the whole year reveals that the humidex index clearly depends upon the outdoor temperature. CONCLUSIONS: Global Planet Heating shows a definite effect on the outdoor comfort conditions reaching unbearable degrees in the really hottest zones. Therefore, this effect will clearly influence tourism and risk prevention strategies in these areas.
ABSTRACT
BACKGROUND: Today, the International Energy Agency is working under good practice guides that integrate appropriate and cost effective technologies. In this paper a new procedure to define building energy consumption in accordance with the ISO 13790 standard was performed and tested based on real data from a Spanish region. RESULTS: Results showed that the effect of air changes on building energy consumption can be defined using the Weibull peak function model. Furthermore, the effect of climate change on building energy consumption under several different air changes was nearly nil during the summer season. CONCLUSIONS: The procedure obtained could be the much sought-after solution to the problem stated by researchers in the past and future research works relating to this new methodology could help us define the optimal improvement in real buildings to reduce energy consumption, and its related carbon dioxide emissions, at minimal economical cost.
