This document provides an overview of load forecasting in the power system planning process. It discusses the need for load forecasting to determine generation, transmission, and distribution capacity needs. Accurate load forecasting is important to avoid excess or insufficient investment. The document outlines different load classification categories and forecasting methodologies. It also examines factors like weather that impact load forecasting and concludes that regular adjustments are needed to forecasts to account for seasonal and other usage changes.

1. WELCOME

2. LOAD FORCASTING
PRESENTED BY-
BHUPATI BHAKTIMANAS PRADHAN
(EE / 1501298212)
GUIDED BY-
Prof.SRIKANT DASH

3. CONTENTS
 Introduction
 Need of load forecasting
 Need of accurate load forecasting
 Classification of load
 Forecasting methodology
 Energy forecasting
 Commercial sale forecasting
 Residential sale forecasting
 Peak demand forecasting
 Industrial sale forecasting
 Impact of weather in load forecasting
 Conclusion
 References

4. Introduction
• Load is a general meaning either Demand or
Energy.
• Forecast refers to projected load requirements
determined using a systematic process of defining
future loads in sufficient quantitative details to
permit important system decision to be made.

5. Need of load forecasting ?
•Power system planning.
•To determine capacity of generation, transmission and
distribution system .
•The accuracy of a forecast is crucial to any electric utility,
since it dictates the timing and characteristics of major
system addition.
•Energy forecast determine the type of facilities required.
•Good forecast reflecting current and future trends,
tempered with good judgment, it is key to planning,
indeed to financial success.

6. Needof Accurate load forecasting ?
• Very low forecast results in lost in revenue from sales to utilities or
even load curtailment.
• Forecast too high can result in severe financial problems due to
excessive investment in an electric plant that is not fully utilized or
eventually operated at low capacity factor.
• Unfortunately, an accurate forecast depends on the judgment of
forecaster, and it is impossible to rely strictly on analytical
procedures to obtain an accurate forecast.

7. Classification of Load
• There are five broad categories of load :
I) Domestic load
II) Commercial Load
III) Industrial Load
IV) Agricultural Load
V) Other Load
• Commercial and agricultural loads are characterized by seasonal
variations.
• Industrial loads are considered base load that contain little weather
dependent variations.

8. Domestic Loads
• This type of load consist mainly of lights, fans, domestic
appliances such as heaters, mixers, refrigerators, air
conditioners and various motors for pumping and various
other small household appliances.
• Demand factor = 70 – 100 %
• Load Factor = 10 – 15 %

9. Commercial Load
• This type of load mainly lightning for shops and
advertisement boarding, fans, air-conditioning, heating
and other electrical appliances used in commercial
establishment such a shops, restaurants, market places ,
etc.
• Demand Factor – 90 – 100%
• Load Factor – 20 – 30%

10. Industrial Load
• These loads may be of typical power range :
• Small Scale industries – 0 – 20 kw
• Medium Scale Industries – 20 – 100 kw
• Large scale industries – 100 kw and above.
• The large scale industrial load need power over a longer
period and which
remains fairly uniform throughout the day.
• For Large scale industrial load
1. Demand Factor – 70 -80 %
2. Load Factor – 60 – 65 %
• For heavy industries
1. Demand Factor – 85 – 90 %
2. Load Factor – 70 – 80 %

11. Agricultural Load
• This type of load is required for supplying water for
irrigation by means of suitable pumps driven by electrical
motors .
• Load Factor – 15 – 25 %
• Demand Factor – 90 – 100 %

12. Other Loads
•Apart from the load mentioned above, there are other loads
such as bulk supplies, street light, traction and government
loads which have there own particular characteristics.
•The average energy consumed is equal to the power
multiplied by 8,760 and load factor.

13. Forecasting Methodology
• Load Forecasting is simply a systematic procedure for quantitative
defining future loads.
• Depending upon time period of interest, a specific forecasting
procedure may be classified as short term, intermediate or long term
technique.
• System planning is our main concern and because planning for the
addition of new generation, transmission and distribution facilities
must begin 4 – 10 years in advance of actual in-service date, we shall
be concerned with methodology of intermediate range forecast.
• Techniques may be further classified as either deterministic,
probalistic, or stochastic.

14. Energy Forecasting
• Energy forecast tend to be developed using correlation and
extrapolation primarily, tempered with sound projections of future
conditions.
• To arrive at a total energy forecast, the forecasts for residential,
commercial and industrial customers are forecasted separately and
then combined.

15. Residential Sales Forecast
 Population Method
• Residential energy requirements are dependent on:
– Residential customers
– Population
– Per capita energy consumption

16.  Synthetic Method
• Detailed look at each customer
• Major factors are:
– Saturation level of major appliances
– Average energy consumption per appliance
– Residential customers
• Forecast these factors using extrapolation.
• Multiplying the three factors gives the forecast of residential
sales.

17. Commercial sales forecast
• Commercial establishments are service oriented.
• Growth patterns are related closely to growth patterns in residential
sales.
Method 1:
• Extrapolate historical commercial sales which is frequently available.
Method 2:
• Extrapolate the ratio of commercial to residential sales into the future.
• Multiply this forecast by residential sales forecast.

18. Industrial Sales Forecast
• Industrial sales are very closely tied to the overall economy.
• Economy is unpredictable over selected periods.
• Industrial forecast is by far most difficult.
Method 1:
• Multiply forecasted production levels by forecasted energy
consumption per unit of production.
Method 2:
• Multiply forecasted number of industrial workers by forecasted energy
consumption per worker.

19. Impact of weather in load Forecasting
• Weather causes variations in domestic load, public lighting, commercial loads etc.
 Main weather variables that affect the power consumption are:
• Temperature
• Cloud cover
 First two factors affect the heating/cooling loads
• In load forecast models proper temperature ranges and
representative average temperatures which cover all regions of the
area served by the electric utility should be selected.

20. • Cloud cover is measured in terms of:
 Height of cloud cover
 Thickness
Cloud amount
Time of occurrence and duration before crossing over a population area.
• Visibility measurements are made in terms of meters/kilometers with fog
indication.
• To determine impact of weather variables on load demand, it is essential
to analyze data concerning different weather variables through the cross-
section of area served by utility and calculate weighted averages for
incorporation in the modeling.

21. CONCLUSSION
The load forecasting has both commercial and technical implications
and if not done properly, it may lead to bad planning and inefficient
operation of the electrical power systems. The accuracy of the load
forecasting is important to both the utility companies as well as the
consumers. For this reason, it may be necessary to keep on adjusting
based on seasons and other factors that may affect the way
consumers use the power. In addition, the forecast should rely on
accurate data and best forecasting practices.

22. REFERENCES
 FACTOR AFFECTING SHORT TERM LOAD FORECASTING, Muhammad Usman
Fahad and Naeem Arbab.
 LOAD FORECASTING Eugene A. Feinberg.
 LOAD FORECASTING Amanpreet Kaur.
 AN OVERVIEW OF ELECTRICITY DEMAND FORECASTING TECHNIQUES
Arunesh Kumar Singh, Ibraheem, S. Khatoon, Md. Muazzam .
 LOAD FORECASTING IN ELECTRIC UTILITY INTEGRATED RESOURCE
PLANNING, Juan Pablo Carvallo, Peter Larsen, Alan H. Sanstad, Charles A. Goldman.
 POWER SYSTEM PLANNING AND RELIABILITY, Mr. Akshay M. Kharwade.
 ELECTRIC LOAD FORECASTING,,marcelo espinoza, johan a.k. Suykens, ronnie
belmans, and bart de moor.