Title:
Forecasting Electricity Consumption in Tehran City Using Data Mining Techniques
Ali Akbari Alireza Namazi Hassan Eskandari
Pooyesh University, Qom, IRAN Pooyesh University, Qom, IRAN Pooyesh University, Qom, IRAN
Abstract:
Today, electric energy plays a key role in people’s lives despite the availability of many technologies. Most equipment and devices around us are powered by electricity, yet electricity cannot be stored. On the other hand, even a short shortage of electricity may cause irreversible disruptions. To optimally distribute electricity across the country and control the customers’ consumption, electricity is transmitted to the grid management, and thereafter it is transmitted to the Electricity Distribution Company to be provided to the customers. The Electricity Distribution Company is in charge of serving the industrial and resi-dential customers. Hence, it must purchase the energy required per day from the grid management and distribute it among the customers. The purchase of the ad-equate volume of energy calls for precise examinations and forecasts, because over-purchase causes loss to the Electricity Distribution Company. Under-pur-chase, on the other hand, also results in blackouts in some parts of the city, re-sulting in customer dissatisfaction or disruptions. The present research was an attempt to use the data mining techniques and the past data to improve the preci-sion of the predicted consumption load. The results from the application of the aforementioned techniques are presented at the end of the paper.
Keyword:
Electricity consumption forecasting, Data mining, Information Sci-ence