Weather station

About: Weather station is a research topic. Over the lifetime, 1789 publications have been published within this topic receiving 42864 citations. The topic is also known as: meteorological station & meteorological observation post.

Potential of wind and solar energy using Weibull and hargreaves method analysis

Abstract: This paper presents an analysis of wind speed characteristics and solar radiation received in Perlis, Northern of Peninsular Malaysia. The characteristic of wind and solar is recorded per hour for a month using Davis Vantage Pro2 Weather Station. Recorded data is analyze using Weibull distribution function and Hargreaves method for wind and solar respectively. The analysis through Davis Vantage Pro2 Weather Station is then used to compare wind and solar data collected from Chuping station, Malaysian Meteorological Department. From overall of this work, the authors found that the potential of wind and solar energy through out Weibull and Hargreaves method is successfully analyzes.

Impact of Actual Weather Datasets for Calibrating White-Box Building Energy Models Base on Monitored Data

Abstract: The need to reduce energy consumption in buildings is an urgent task. Increasing the use of calibrated building energy models (BEM) could accelerate this need. The calibration process of these models is a highly under-determined problem that normally yields multiple solutions. Among the uncertainties of calibration, the weather file has a primary position. The objective of this paper is to provide a methodology for selecting the optimal weather file when an on-site weather station with local sensors is available and what is the alternative option when it is not and a mathematically evaluation has to be done with sensors from nearby stations (third-party providers). We provide a quality assessment of models based on the Coefficient of Variation of the Root Mean Square Error (CV(RMSE)) and the Square Pearson Correlation Coefficient (R2). The research was developed on a control experiment conducted by Annex 58 and a previous calibration study. This is based on the results obtained with the study case based on the data provided by their N2 house.

Prospect of Design Rainfall in Urban Area Considering Climate Change

Abstract: Recent inundation damage has frequently occurred due to heavy rainfall in urban area, because rainfall has locally occurred exceeding the capability of a flood control plan by the exiting design rainfall from the data of Seoul weather station. Accordingly the objective of this study is to predict new design rainfall in order to make a future flood control plan considering climate change. In this study, for considering spatial characteristics of rainfall in urban area, data of AWS was used and for retaining insufficient rainfall data, WGR model was estimated the application of target area. The results were compared with the observation data and consequently show reasonable results. In addition, to prepare for climate change, design rainfall was calculated by applying for various climate scenarios and the result would be used in order to establish future flood control plan.

Performance analysis of artificial and wavelet neural networks for short term wind speed prediction

Abstract: In recent years, the importance of integrating the production of wind energy into electrical energy networks has been increasing rapidly. The biggest challenge to integrate wind energy into the power grid wind power is variability and discontinuity. To deal with this situation, the best approach is to predict future values of wind power production. Wind speed estimation methods with high accuracy are an effective tool that can be used to minimize these problems. This paper presents a short-term wind speed prediction using artificial neural network (ANN) and wavelet neural network (WNN) and compares the performance of these networks. Data are collected from a weather station located in Ondokuz Mayis University in ten minute resolution for a period of one year. Wind speed predictions are presented within a period of 24-hours for 10 minute ahead. Although ANN and WNN use the same topology, the performance of the proposed prediction system based on WNN has higher than that of ANN. The root mean square error (RMSE) and the mean squared error (MSE) values have been selected as performance criteria.