Page 25 - Hybrid-Renewable Energy Systems in Microgrids

10 Hybrid-Renewable Energy Systems in Microgrids

lished in Ref. [35] to get the most out of the reliability of the system and minimize the
system costs. Moreover, the influence of the tilt angle of solar panels on the incoming
wind speed is studied by the use of computational fluid dynamics (CFD) simulation.
Designing and modeling of an energy management strategy is adopted in Ref. [36]
to optimize the operational costs and self-feeding plan by means of the day-ahead
forecast data. A Modified Optimal Dispatch Strategy (MODS) is obtained in Ref. [37]
by adopting a mathematical optimization employed in General Algebraic Modeling
System (GAMS) and solved by CPLEX 12 to find the daily minimum operation cost.
Optimal design approach using a computer software tool, termed as HOMER, is used
to determine the viability of the hybrid energy system in terms of the system’s lifecycle
cost [38]. A brief summary of the optimization practices in HRES is given in Table 1.2.

Table 1.2 Summary of the optimization practices in hybrid system

Application Control Choice of Modes of Paper
schemes algorithm energy source microgrid references
Trade-off solu- A Modified Wind, PV, Grid connected [28]
tions between Particle battery
economy, Swarm Op-
reliability, and timization
pollutant emis- Algorithm
sions.
To reduce the Genetic Algo- Wind, PV, bat- Standalone [29]
total cost rithm (GA) tery, diesel
and meeting
the customer
demand com-
pletely
Total cost reduc- A hybrid Wind, PV, bat- Standalone [30]
tion, including genetic tery, diesel
the construc- algorithm
tion, operation,
maintenance,
and replace-
ment costs
To maximize the An improved Wind, PV, Grid connected [31]
long-term eco- quantum battery
nomic benefits evolution
algorithm
(IQEA)
Optimal size and Invasive Weed Wind, PV, Standalone [32]
cost of the MG Optimization battery
(IWO) and
the hybrid
IWO–PSO
algorithm
(Continued)