Introduction and Objective
The weather has been one of the important factors affecting the construction, safe and stable running of the power system.
An automatic weather station (AWS) is a device for meteorological observation above ground. It can observe spatial environmental factors accurately, such as solar radiation, wind speed, wind direction, rainfall, air pressure, air temperature, and relative humidity.
With the help of AWS data reading, we can forecast electricity load. In a power grid, as we move to the higher levels of load hierarchy, the aggregated load covers a larger geographic region. Therefore, the point readings of a single weather station may not sufficiently explain the load variations over a vast area. Typically, multiple weather stations are inside or around the service territory, which leaves the Load forecasters with the question of how to best utilize the weather data collected from different Stations. Although a forecasting model may use multiple temperature profiles simultaneously, most Load forecasting models in the literature use a single weather profile to predict the load.
Components of Electrical Power utility
It measures the gas flow that is in turbulent flow conditions.
It is used to measure the mean velocity, and the hot wire type is used when the turbulence characteristics are to be measured, such as transverse measurement in a cross-section.
It can measure even the pressure, direction, and velocity of wind along with the speed.
Pilots, long-range shooters, and sky drivers mainly prefer it.
It also indicates the change in the pattern of weather and is thus suitable for meteorologists and climatologists.
It can measure the airflow in heating systems, air conditioners, ventilation units, etc.
Temperature Sensor: Temperature Sensor measures atmospheric temperature.
Hygrometer – Measures relative humidity using a percentage measure of water vapor in the air.
Barometer – Measures atmospheric pressure to predict precipitation
Rain Gauge – Measures liquid precipitation using an open container. They usually empty automatically and measure the amount of rainfall over a given time interval.
Electric load profiles of residential and commercial customers have shown a significant correlation between weather and load.
Weather data plays a major source of information to predict future demand.
Weather properties such as temperature and relative humidity are provided by the weather stations located in a service zone. Because some service territories are large, some utilities rely on multiple weather stations.
Combining multiple weather profiles helps the forecasting model explain more variations of the load spread.
Weather plays an important role in the field of the rail network. Through Ice monitoring and prediction sensors, we can observe the overhead contact wire.