Universiti Teknologi Malaysia Institutional Repository

Allocation and sizing of renewable energy distributed generation units in distribution networks using advanced differential evolution algorithm

Mohamed, Ahmed Hussein (2018) Allocation and sizing of renewable energy distributed generation units in distribution networks using advanced differential evolution algorithm. Masters thesis, Universiti Teknologi Malaysia, Faculty of Electrical Engineering.

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Abstract

Renewable Energy Distributed Generation unit (REDG) can be strategically placed in power systems for grid reinforcement, for reduction in on-peak operating costs, power losses. Often improvement of voltage profiles, load factors, system reliability, integrity and efficiency are resulted from properly designing in the distribution network. The design of the REDGs means the design of the position and capacity in the network. The change of position and capacity could both change the voltage and current distribution in the distribution network, thus influences the voltage and power loss. As the power output of the photovoltaic fluctuates depending on weather conditions which results in back flow of power and voltage fluctuation on the bus which causes instability of the distribution network. In this project advanced differential evolution algorithm is used to allocate and size of REDGs which contains mixed continuous and discrete parameters with limitations in order to improve the voltage profile of the distribution network. The optimal location and range of sizes of the REDGs which results in normal flow of power in the distribution network in different time of the day with power output fluctuation of photovoltaic is examined with limitation on the voltage fluctuation on the bus using MATLAB/Simulink software. Proper design of the Renewable Energy distributed generation could bring positive influence to the distribution networks.

Item Type:Thesis (Masters)
Additional Information:Thesis (Sarjana Kejuruteraan (Elektrik - Kuasa)) - Universiti Teknologi Malaysia, 2018; Supervisor : Dr. Madihah Rasid
Subjects:T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions:Electrical Engineering
ID Code:79221
Deposited By: Widya Wahid
Deposited On:14 Oct 2018 08:39
Last Modified:14 Oct 2018 08:39

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