The renewable energy becomes the secondlargest source of global electricity worldwide. However, the
intermittent nature of RESs (RES)causes great challenges and
severed problems regarding system security and reliability.
Combining two or more RES in hybrid renewable topologies can
overcome these problems and improve the power quality,
reliability and increasing the overall system efficiency especially
when the combined sources have a complementary nature for
each other. For example, Solar Photovoltaic and Wind energy
have a complementary nature since they can complement each
other in partial failure time and in turn, increases the reliability
of the overall system. Optimization techniques are essentially
required to optimally coordinate between the combined energy
sources, reduce the total system cost, and maximize the extracted
power and consequently increasing the total efficiency.
Therefore, this paper has a twofold aim which is conducting
comprehensive review of the optimization techniques, Software
and tools, topologies of hybrid renewable energy systems
(HRES)and then applying data mining and statistical
calculations to predict the most suitable optimization techniques
for a hybrid system composed of Solar PV, Wind Turbine, and
battery bank.
Data mining and Statistical Review of Optimization Techniques of Hybrid Renewable Energy Systems
