الفهرس 
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Abstract
The present day utility grids in Egypt and other countries are source-defined centralized power distribution system. The major issue with the present day grids is the outdated of the infrastructure, owing to which, the infrastructure can’t easily be expanded to meet the ever increasing power demands of the 21st century. In the next decade, power demand is expected to increase more rapidly and the current infrastructure has the capability to increase its productivity in order to meet the demand. The increase in production of electricity in the past few decades without major changes to the infrastructure has made the grid system highly unreliable. Blackout and grid failures have been common problems to be addressed, having resulted in as much as billions of dollars in losses. A solution envisioned by academia and industry is the ’’Smart Grid’’. The objective of this thesis is to develop solutions to improve the energy efficiency in electric grids. It presents the smart grid different definitions, concepts, benefits, challenges, opportunities and the ways for implementing Smart Grid (SG) and making it real in Egypt, also this thesis focuses on the Demand Side Management (DSM). DSM represents an option of SG. DSM can be defined as the implementation of policies and measures to control, regulate, and reduce energy consumption. Four techniques of DSM namely Load Shifting (LS), Peak Clipping (PC), Energy Conservation (EC) and Valley Filling (VF) are applied on a real case study to show the effectiveness of these techniques on load factor from utility point of view. A Heuristic optimization algorithm i.e., Genetic Algorithm (GA) is used for the optimization of DSM operation for maximizing the utility’s load factor. Short Term Load Forecasting (STLF) on a peak Load using Artificial Neural Network (ANN) is finally presented in this thesis. The data are obtained from Egyptian Electricity Holding Company (EEHC). The Matlab is used as a software program in thesis’s analysis.