الفهرس 
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Abstract
Due to industrial growth and industries evolution such as automotive and steel industries, the demand for delivery of reliable and stable power has become significantly important. Therefore, this thesis aims at surveying the economical planning of power transmission networks, as well as specifying the most reasonable transmission lines shall be added to guarantee both high quality and low cost. Since the commonly used scientific method depends mainly on the linear programming system,this thesis focuses on applying one of the modern techniques and comparing with traditional ones. A newly proposed technique, called Integer Based Particle Swarm Optimization (IBPSO), applied to standard network which proved the accuracy and efficiency of that proposed technique. That technique also helped in attaining the convergence curve that verifies the target function. In addition, that proposed (IBPSO) has been compared with both Linear Programming and Heuristic Methods. Transmission Expansion Planning (TEP) has also been applied to a real transmission network in Egypt, in West Delta region of 66 kV transmission voltage using both methods mentioned above and submitting the best proposal for constructing a new generation plant to meet future loads expected by 2030.
Transmission Expansion Planning (TEP) has also been applied to a 500 kV Extra High Voltage Network (EHVN) in Egypt using (IBPSO) taking into account the centralization of the power demanded in 2030 at Kurimat Solar Power Plant. That is according iiito the Ministry of Electricity and Renewable Energy report in 2013/2014 after the approval of the Cabinet on 12/7/2012 which gave the green line to start the Egyptian solar plan that targeted using solar power by establishing capacities up to 3500 MW by 2027. Historical loads of the region have been obtained and analyzed over a period of time, with making future forecast for more than ten upcoming years and using the modern techniques for load forecast as well as applying computer programs and comparing with the traditional methods. Traditional methods for load forecast have been applied to West Delta Network (WDN), using three traditional methods and selecting the best one by studying some statistical tests and comparing a method of artificial intelligence which is Adaptive Neuro-Fuzzy Inference System (ANFIS) after applying all tests mentioned previously. ANFIS has also been applied after proving its advantage of the load forecast of Egypt Unified Electrical Network (UEN, 220kV) and the EHVN over a long period from 2016 till 2030 in order to make the future planning process.