الفهرس 
HOSTINGCAPACITYASSESSMENTOFRENEWABLEENERGY RESOURCESOnly 14 pages are availabe for public view
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Abstract
The integration of Renewable Energy Resources (RERs) into electrical networks has several technical, economical, and environmental benefits. On the other side, excessive RERs integration may negatively affect the performance of the system and may lead to serious voltage problems, thermal overloading,..etc. These problems occur when the system exceeds its hosting
capacity (HC) limit. The HC determines the amount of RERs, integrated into the power system, above which the system performance becomes unacceptable. Accordingly, HC assessment and enhancement become an essential research target. In this thesis, various techniques are proposed to assess and enhance the HC of RERs in distribution systems. In the proposed approaches, a
correlated multi-dimension probability uncertainty model is proposed to emulate the uncertainty of PV, WT and load demand. Manta Ray Foraging Optimization (MRFO) algorithm is proposed to solve single and multi-objective frameworks in the proposed approaches. Where, the effectiveness of the proposed MRFO is approved compared with other optimization algorithms.
Firstly, this thesis proposes a stochastic approach for assessing the HC of the RERs i.e. photovoltaic (PV) and wind turbines (WTs) in distribution systems. Voltage deviation and current carrying capacity of the conductors (which represents the thermal capacity of the conductors) are considered as the performance limits (PLs). Two cases for the renewable based distributed generation units’ power factor are investigated to study the effect of the units’ power factor on the system HC.
Secondly, a bi-stage approach is proposed to enhance the HC considering RERs and load uncertainties. The first stage develops a multi-objective frame-work to adjust the system voltage profiles in a specific manner to avoid exceeding the voltage boundaries with high RERs penetration. In the second stage, two processes are employed to maximize the HC as the main objective function. In the first process, the PV and WTs are optimally allocated while in the second process, a combination of three voltage control devices is proposed. The proposed approach is tested and validated on small- and large-scale distribution systems.
Thirdly, an optimization based approach is proposed for assessing and maximizing the HC via network reconfiguration (NR) and/or soft open points (SOPs) techniques. Various cases studied are considered to evaluate the impact of the NR and SOPs on maximizing the system HC. Finally, the renewable energy HC maximization problem in distorted distribution systems is employed. An optimization based approach is proposed for maximizing the HC using single tuned filters. Over voltage, under voltage, current capacity of the lines and the total harmonic distortion are considered to be the limiting constraints. The optimal design and planning of the harmonic filters besides the optimal allocation of RERs units are determined in
the proposed approach.