Load Forecasting

This course provides a comprehensive guide to Load Forecasting and Best Practice, emphasizing its role as a critical foundation for energy system planning and evaluation. The curriculum is designed to help professionals master the "art of forecasting" by balancing strategic long-term investment needs with the dynamic, short-term requirements of the energy market.

1. Significance and implementation of Load Forecast

a. Inexact Load Forecast leads to increased costs in supplementary application

b. Load Forecast as crucial input to System Planning

c. Load Forecast as a basis for Energy Saving evaluation

2. Accuracy vs. Sensitivity of Load Flow assessment

a. The Art of forecasting and planning

b. Strategic vs. virtual forecast; different approach

c. Long term forecast and impact on investment

d. Short term forecast or dynamic change of load impact on local Energy Market

3. Data mining and information requirement for the analysis

a. Macro Economics for long term planning, GDP, Inflation, unemployment, price indexes, national income, investment…

b. Micro economics, local development, taxation system, relative prices ratios, demand-supply matching,

c. Stakeholder’s information (utilities, ministries, independent agencies etc.)

d. Historical values and trends

e. Social and Environmental influences

f. New technology application – Energy efficiency and energy storage

4. Methodology

a. General approach and differences in application

i. Driving factors – Economy, Climate, Weather, Social activities, Stakeholders activities, Main specific characteristics of electrical load

ii. Analysis by graphic methods for comparison

iii. Type of load, technical parameters affecting the LF values

b. Specific requirements for LF for generation planning

c. Spatial forecasting for transmission and distribution planning

d. Econometric approach

i. Basic econometrics models; Statistical models

ii. Linear regression, Generalized linear models,

iii. Probabilistic models

iv. Artificial Intelligence methods, neural networks, fuzzy logic

v. Software application

e. Weather Normalization corrections

f. Application of sensitivity methods

5. Building a benchmark model for different utilities and examples from practice

a. Urban, Rural, Industrial, Commercial, Transportation, Special consumers

b. Spatial forecast/planning

c. Methods for large and small utilities, identify special features for local utility

d. Specific approach for short LF usually referred as to emergency or immediate requirements

6. Practical implementation, best practice and continuous updates

a. Iterative process requiring constant updates

b. Continuous improving of the forecast through application of new methods in the latest software models and refined parameters

c. Lessons learned on previous forecasts

Power Systems Engineers, Load Forecasting / Demand Planning Engineers, Data Analysts / Energy Analysts, Grid Planning Engineers, Transmission & Distribution Engineers, System Operators / Dispatch Engineers, Demand Response Specialists