Short Term Load Forecasting For The Electric Power System : particle swarm optimization

ISBN-13: 9786133991644 / Angielski / Miękka / 2017 / 172 str.

Ahmed Ibrahim

Opis

Solving the problem of electric power energy in Egypt using the latest and modern algorithms, particle swarm optimization that optimized the error of neural networks to get the most accurate data from the model that helps us in good planning and controlling the electric power in Egypt sector. The proposed model is used to find the accurate forecasting model of the hourly load through an application on Zagazig city - Egypt. Actual record data is used to perform the study. The data given represents the hourly load for four months, two months (July- 2011, August- 2011) in the summer season and the other two months (December- 2011, January- 2012) in the winter season.

O autorze

Electric power system load forecasting plays an important role in the energy management system (EMS), which has a great effect on the operation, controlling and planning of electric power system. A precise electric power system short-term load forecasting will lead to economic cost saving and right decisions on generating electric power.