Load Forecasting

1.1 Classification of Load Forecasting

Perfect calculation of both the magnitude and environmental position of electrical load over the dissimilar period of scheduling horizon is complicated in the load forecasting [2]. The calculation may be immediately for a fraction of an hour in advance for process purposes, or as a great deal as 15 years into the expectations for development purposes. Therefore, the forecast for dissimilar time perspective are significant for different operation within a usefulness company as summarized in table 1.1. The characters of these forecasts are dissimilar as well. For example, for an exacting area, it is probable to expect the next day load by means of an accurateness of just about 1-3%. However, it is not possible

The four significant factors upsetting load forecast are:

Weather Influence: Electrical load has an obvious correlation to weather. Much effort has been spent to find a viable relationship between the weather and the load so that an accurate load model could be developed. The change of the weather causes the change of consumers comfort feeling and in turn the usage of some appliances such as space heater, water heater and air conditioner. Weather-sensitive load also includes appliance of agricultural irrigation due to the need of the cultivated plants. In the areas where summer and winter have great meteorological difference, the load patterns differ greatly

The most important weather variables in load changes are –

I. Dry and wet bulb temperature

II. Dew point

III. Humidity

IV. Wind speed / Wind direction

V.

The economic situation also influences the utilization of this commodity. Economic factors, such as the degree of industrialization, price of electricity and load management policy have significant impacts on the system load growth/decline trend. With the development of modern electricity markets, the relationship between electricity price and load profile is even stronger. Although time-of use pricing and demand-side management had arrived before deregulation, the volatility of spot markets and incentives for consumers to adjust loads are potentially of a much greater magnitude. At low prices, elasticity is still negligible, but at times of extreme conditions, price-induced rationing is a much more likely scenario in a deregulated market compared to that under central planning.

(iv) Customer class: Most electric utilities serve customers of different types such as residential, commercial, and industrial. The electric usage pattern is different for customers that belong to different classes but is somewhat alike for customers within each class [11]. Therefore, most utilities distinguish load behaviour on a class-by-class basis. The fig 1.2 depicts the load behaviour in the various classes by showing the amount of peak load per customer, and the total