الفهرس 
Generation Expansion Planning (GEP) Considering Renewable Energy.Only 14 pages are availabe for public view
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Abstract
Nowadays, the power system has been expanded to include several renewable technologies
which entail variability and uncertainty in the operation and planning processes of the power
system. One of the key issues in the planning process of electric power systems is generation
expansion planning (GEP) which aims at selecting the most suitable technology, size, location,
and timing for the building of additional plant capacity while taking into account economical
capabilities and technical power system constraints.
In this thesis, wind energy assessment via searching for optimal parameters estimation of the
wind speed Weibull distribution and wind power curve model are presented by several analytical
and heuristic optimization techniques. The parameters estimation and wind power curve model
are carried out based on per year real wind speed data that are collected from Zafaranah and
Shark El-Ouinate sites in Egypt.
Also, a new framework to study the GEP in a multi-stage horizon with reliability constrained
is presented to minimize the capital investment costs, salvage value cost, operation and
maintenance, and outage cost under several constraints over short and long-term planning
horizons. In this context, several modern meta-heuristic optimization algorithms are employed
and assessed which are particle swarm optimization (PSO) algorithm, crow search algorithm
(CSA), Aquila optimizer (AO) algorithm, bald eagle search (BES) and honey badger algorithm
(HBA). The system reliability is incorporated as well where the expected energy not served
(EENS), loss of load probability (LOLP), and loss of load expectation (LOLE) are estimated.
Added to that, the probabilistic production cost simulation is involved using the Equivalent
Energy Function (EEF) and Effective Load Distribution Curve (ELDC).