Load forecasting plays a crucial role in the electricity sector as it aids in planning periodic operations and facility expansion. However, due to the complexity of demand patterns resulting from energy market deregulation, identifying an appropriate forecasting model for a specific electricity network can be challenging. While numerous forecasting methods have been developed, none can be universally applied to all demand patterns. This training course introduces a practical methodology that serves as a helpful guide for constructing Electric Power Load Forecasting models. The trainer shares real case studies and examples from their direct industry experience, enhancing the practicality and applicability of the training.

Course Objectives:

The objective is to enable course participants to learn how to:

Significance and implementation of Load Forecast
Accuracy vs. Sensitivity of Load Flow assessment
Data mining and information required for the analysis
Methodology
Building a benchmark model for different utilities and example from practice
Practical implementation, best practice, and continuous updates

Who Should Attend?

The course is designed for plants engineers and technicians, maintenance engineers and technicians, who are involved in the operation, planning, maintenance, protection, control, analysis, and troubleshooting/repair either working in power utilities, industrial plants and gas or oil industries (generation, transmission, and distribution of electrical power).

Course Outlines:

Significance and implementation of Load Forecast

Inexact Load Forecast leads to increased costs in supplementary application
Load Forecast as a crucial input to System Planning
Load Forecast as a basis for Energy Saving evaluation.

Accuracy vs. Sensitivity of Load Flow assessment

The Art of forecasting and planning | Strategic vs. virtual forecast; different approach | Long term forecast and impact on investment
Short term forecast or dynamic change of load impact on local Energy Market.

Data mining and information requirement for the analysis

Macro Economics for long term planning | GDP | Inflation | unemployment
| Price | indexes | national income | investment |
Microeconomics | local development | taxation system | relative price ratios | demand-supply matching | Stakeholder’s information (utilities, ministries, independent agencies, etc.) | Historical values and trends | Social and Environmental influences | New technology application – Energy efficiency and energy storage.

Methodology

General approach and differences in application

Specific requirements for LF for generation planning

Spatial forecasting for transmission and distribution planning

Econometric approach

Basic econometrics models; Statistical models | Linear regression

| Generalized linear models | Probabilistic models |

Artificial Intelligence methods | neural networks | fuzzy logic, Software application | Weather Normalization corrections, Application of sensitivity methods.

Building a benchmark model for different utilities and examples from practice

New product forecasting

New product success and error rates | New product success and failure factors | Issues to consider when developing new product forecasts | Qualitative and Quantitative methods used in new product forecasting.

Promotions forecast

Promotions forecast error rates | Manage the process for unplanned and abnormal demand | Factors, issues, and considerations in developing promotions forecasts | Cannibalization impact of promotions on-base / open stock SKUs.

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