الفهرس 
INTRODUCTIONOnly 14 pages are availabe for public view
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Abstract
Photovoltaic (PV) systems are taking a leading role as a solar-based
renewable energy source (RES) due to their unique advantages. In the field of
Seawater desalination, this trend is increasing. The thesis presents a utility
network feeding seawater desalination plant (SWDP) in Egypt. The main
challenge in such nonlinear systems with high variability is to size the SWDP at
the suggested whole solar-powered while maintaining good dynamic
performance. Also, the thesis presents a consolidated electrical load analysis to
evaluate the optimal design of SWDP powered by a PV array system.
Additionally, an optimal maximum power point tracking controller (MPPTC)
has been developed to improve the dynamic performance of SWDP powered by
PV arrays.
A real case study represented in a utility network connected SWDP plant
implemented in Egypt is employed in this thesis to validate the efficacy of the
proposed energy management framework. The selected SWDP produces 700
m3
/day. Actual experimental data for the plant was extracted by daily readings
of water production and electricity consumption meters. After that, the attained
experimental data is imported into HOMER software program to design the
optimal components of the proposed PV system based on minimum net present
cost. The proposed power system plant consisted of a load, PV array, grid, and
DC/AC converter. Furthermore, to address the challenge of low conversion
efficiency of PV systems, MPPTCs have been studied to improve the dynamic
performance of the proposed SWDP powered by PV systems. Incremental
conductance combined with three optimization methods (particle swarm
optimization (PSO), grey wolf optimization (GWO), and Harris hawks
optimization (HHO)) is applied to evaluate the dynamic performance of the
presented SWDP with PV. The developed system was designed, modeled, and
simulated using MATLAB/SIMULINK software package. The obtained results of the three methods are promising in extracting the maximum power from the
PV system with minimum error while improving SWDP performance. The
obtained simulation and experimental results prove the effectiveness of the
proposed optimal design strategy.
Two new methods of energy management system (EMS) based on a
modified cost function are described in this thesis. HHO and Fuzzy logic (FL)-
based EMSs are implemented to achieve optimal performance of SWDP with a
minimum feed-in tariff (FiT). Technical challenges and uncertainties in the
system parameters associated with changing the price of energy from one point
at a time to another are investigated in this thesis. For example, energy prices are
higher during peak times and lower during normal times. Also, peak times vary
from day to day. The proposed EMS can handle these cases of variability and
uncertainty. The proposed EMS is realized by a two-way electrical energy
exchange (π-EEE) approach. The main concept behind the proposed π-EEE is
how and when the surplus renewable energy generated is fed into the grid, or
how batteries are charged according to minimum dynamic cost criteria and vice
versa. To conduct this study, a 700 m3
/day SWDP powered by solar energy and
utility grids was constructed in Egypt and analyzed. SWDP powered by a PV
system and utility grid in addition to a battery energy storage system (BESS) is
employed to conduct this study. The main objective of this study is the
management and coordination between energy exchange processes from solar
energy, utility grid, and BESS to provide sufficient electrical energy for SWDP
within the minimum FiT. The system has been designed and verified using
MATLAB/SIMULINK in conjunction with HOMER. The proposed HHO and
FL-based EMS are investigated in the presence of system uncertainties such as
changes in energy (Excess or shortages energy), the utility grid energy prices
(high or low) at time (normal or peak). The obtained results show that the
proposed FL and HHO-based EMS provide high dynamic performance and
precise coordination between different energy resources and BESS.