الفهرس 
INTRODUCTIONOnly 14 pages are availabe for public view
 |  | from | 105 |  |  |
| | | from | 105 | | |
Abstract
Large-scale control systems are frequently made up of multiple smaller units that are linked together. For these systems, it is common to use local control units that monitor and act locally. Governments around the world have set environmental targets that are spurring in high penetration of small to medium-scale decentralized generation (DG). In most nations, a decentralized energy generation system (DEG) is a relatively recent approach to the power business. The goal of DEG is to bring power sources closer to the end-user. End users are dispersed across a geographic area, so similarly decentralized can reduce transmission and distribution losses, as economic and environmental consequences.
A DEG could be beneficial to energy efficiency initiatives. Smart meters can provide additional data about energy flows, making consumers more aware of their usage. A decentralized control strategy for grid-connected and off-grid connected depends on cascaded control techniques that do not require communication, with each module making decisions based on local data. Power and voltage control are the foundations of the power system’s stability and dependability. Voltage Source Converter (VSC) technology can change its operating point reasonably quickly within its capacity limits as an advantage. So VSC can be used to help the system maintain output voltage or active power during load variations. Due to simplicity and robustness Proportional Integral (PI) controllers are suitable to achieve this.
Engineering design optimization is notoriously difficult, partially due to the problem’s complexity and non-linearity, and partially to strict design codes in engineering practice. Conventional algorithms, such as local search, are not the greatest tools for highly non-linear global optimization.
A lot of approaches for optimization were suggested in the past decade. Genetic Algorithm and particle swarm optimization (GA&PSO) are the most famous and well-known approaches.
In this thesis, Harmony Search (HS) selects automatically the controller parameters, which minimizes the predefined objective function. The result obtained is compared with the ones obtained by using (GA&PSO). Simulations are conducted using MATLAB/Simulink software. The system is tested under different operating conditions as per the following conditions: 1) the steady-state operation is on-grid connected mode. 2) System is transfer from on-grid connected to off-grid, and 3) System is exposed to three lines to earth fault in an off-grid mode.
Equilibrium Optimizer (EO) is used in this thesis. It is based on the characteristics of unimodal and multimodal functions, which benefit from high exploitation and exploration abilities. EO parameters are adjusted automatically. The results are compared with GA as the most well-studied method and Salp Swarm Algorithm (SSA) as swarm intelligence algorithm.
The impact of this thesis is twofold: First, it offers the novel concept of a decentralized energy system with cascaded modular converters which applies voltage source converter technology based on PI controller. Second, the thesis proves that improving control can be made through new optimization algorithms. These algorithms are used to find controller gains for optimum system performance.