Development of An Intelligent Forecasting System for Pakistan WAPDA using Machine Learning Techniques

Principal Investigator’s Organization (PIO):

Al-Khawarizmi Institute of Computer Science, UET Lahore

Principal Investigator (PI):

Dr. Zubair Ahmed Khan, Engr. Nisar Ahmad Bazmi, Dr. Waqar Mahmood


In this project, a software solution for load forecasting was developed, tested and is an intelligent, self learning, adaptive, decision making system that forecasts accurately. It can be utilized in short term, long term and real time energy requirements, facilitate in most economic unit commitment and in planning efficient and least cost power generation.
This software was successfully integrated into “Data Collection and Management” software system for National Transmission and Dispatch Company (NTDC) for real time generation and distribution forecasting.